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Khalique L, Ayhan A, Weale ME, Jacobs IJ, Ramus SJ, Gayther SA.. Genetic intra-tumour heterogeneity in epithelial ovarian cancer and its implications for molecular diagnosis of tumours. J Pathol 211: 286-295
Abstract
Genetic analysis of solid tumours using DNA or cDNA expression microarrays may enable individualized treatment based on the profiles of genetic changes that are identified from each patient. This could result in better response to adjuvant chemotherapy and, consequently, improved clinical outcome. So far, most research studies that have tested the efficacy of such an approach have sampled only single areas of neoplastic tissue from tumours; this assumes that the genetic profile within solid tumours is homogeneous throughout. The aim of this study was to evaluate the extent of genetic intra-tumour heterogeneity (ITH) within a series of epithelial ovarian cancers. Several different regions (five to eight regions) of tumour tissue from 16 grade 3, serous epithelial ovarian cancers were analysed for genetic alterations using a combination of microsatellite analysis and single nucleotide polymorphism (SNP) analysis, in order to establish the extent of ITH. Maximum parsimony tree analysis was applied to the genetic data from each tumour to evaluate the clonal relationship between different regions within tumours. Extensive ITH was identified within all ovarian cancers using both microsatellite and SNP analysis. Evolutionary analysis of microsatellite data suggested that the origin of all tumours was monoclonal, but that subsequent clonal divergence created mixed populations of genetically distinct cells within the tumour. SNP analysis suggested that ITH was not restricted to random genetic changes, but affected genes that have an important functional role in ovarian cancer development. The frequent occurrence of ITH within epithelial ovarian cancers may have implications for the interpretation of genetic data generated from emerging technologies such as DNA and mRNA expression microarrays, and their use in the clinical management of patients with ovarian cancer. The basis of genetic ITH and the possible implications for molecular approaches to clinical diagnosis of ovarian cancers may apply to other tumour types.
... Manual segmentation and image analysis was performed on 463 metastatic tumor sites from 84 patients. In the MSKCC cohort the median number of tumor sites was 7 (interquartile range 5-9) and 4 (interquartile range [3][4] in the TCIA patients. Sub-regions were produced within each tumor site by grouping voxels with similar Haralick texture using the Kernel K-means method. ...
... High grade serous ovarian carcinoma (HGSOC) is the deadliest gynecologic malignancy 2 with overall survival remaining unchanged over the last 20 years [1]. Although HGSOC 3 shows marked sensitivity to platinum-based chemotherapy [2], the majority of cases recur 4 and become progressively resistant to subsequent treatment regimes [3]. Acquisition of 5 resistance may be related to specific mutational processes that drive genomic 6 heterogeneity [4,5] and clonal evolution [6,7]. ...
... Although HGSOC 3 shows marked sensitivity to platinum-based chemotherapy [2], the majority of cases recur 4 and become progressively resistant to subsequent treatment regimes [3]. Acquisition of 5 resistance may be related to specific mutational processes that drive genomic 6 heterogeneity [4,5] and clonal evolution [6,7]. HGSOC exhibits marked intra-site and 7 inter-site genetic heterogeneity across metastatic sites in the peritoneal cavity [5][6][7] with 8 altered immunological infiltrates and tumor microenvironments [8]. ...
Background
High grade serous ovarian carcinoma shows marked intra-tumoral heterogeneity which is associated with decreased survival and resistance to platinum-based chemotherapy. Pre-treatment quantification of spatial tumor heterogeneity by multiple tissue sampling is not clinically feasible. Using standard-of-care CT imaging to non-invasively quantify heterogeneity could have high clinical utility and would be highly cost-effective. Texture analysis measures local variations in computed tomography (CT) image intensity. Haralick texture methods are typically used to capture the heterogeneity of entire lesions; however, this neglects the possible presence of texture habitats within the lesion, and the differences between metastatic sites. The primary aim of this study was to develop texture analysis of intra-site and inter-site spatial heterogeneity from standard-of-care CT images and to correlate these measures with clinical and genomic features in patients with HGSOC.
Methods and findings
We analyzed the data from a retrospective cohort of 84 patients with HGSOC consisting of 46 patients from Memorial Sloan Kettering Cancer Center (MSKCC) and 38 non-MSKCC cases selected from The Cancer Imaging Archive (TCIA). Inclusion criteria consisted of FIGO stage II–IV HGSOC, attempted primary cytoreductive surgery, intravenous contrast-enhanced CT of abdomen and pelvis performed prior to surgery and availability of molecular tumor data analysed as per the Cancer Genome Atlas (TCGA) Research Network ovarian cancer project. Manual segmentation and image analysis was performed on 463 metastatic tumor sites from 84 patients. In the MSKCC cohort the median number of tumor sites was 7 (interquartile range 5–9) and 4 (interquartile range 3–4) in the TCIA patients. Sub-regions were produced within each tumor site by grouping voxels with similar Haralick texture using the Kernel K-means method. We derived statistical measures of intra- and inter-site tumor heterogeneity (IISTH) including cluster sites entropy (cSE), cluster sites standard deviation (cluDev) and cluster sites dissimilarity (cluDiss) from sub-regions identified within and between individual tumor sites. Unsupervised clustering was used to group patient IISTH measures into low, medium, high, and ultra-high heterogeneity clusters from each cohort.
The IISTH measure cluDiss was an independent predictor of progression-free survival (PFS) in multivariable analysis in both datasets (MSKCC hazard ratio [HR] 1.04, 95% CI 1.01–1.06, P = 0.002; TCIA HR 1.05, 95% CI 1.00–1.10, P = 0.049). Low and medium IISTH clusters were associated with longer PFS in multivariable analysis (MSKCC HR 2.94, 90% CI 1.29–6.70, P = 0.009, TCIA HR 5.94, 95% CI 1.05–33.6, P = 0.044). IISTH measures were robust to differences in the CT imaging systems. Average Haralick textures contrast (TCIA HR 1.08, 95% CI 1.01–1.10, P = 0.019) and homogeneity (TCIA HR 1.09, 95% CI 1.02–1.16, P = 0.008) were associated with PFS in mutivariate analysis only in the TCIA dataset. All other average Haralick textures and total tumor volume were not associated with PFS in either dataset.
Conclusions
Texture measures of intra- and inter-site tumor heterogeneity from standard of care CT images are correlated with shorter PFS in HGSOC patients. These quantitative methods are independent of the CT imaging system and can thus be applied in clinical practice. The methodology proposed here enables the non-invasive quantification of intra-tumoral heterogeneity and disease stratification for future experimental medicine studies and clinical trials, particularly in cases where total tumour volume and averaged textures have low predictive power.
Author summary
Why was this study done?
Tumor heterogeneity is a feature of many solid malignancies including ovarian cancer.
Recent genomic research suggests that intra-site tumor heterogeneity (heterogeneity within a single tumor site) and inter-site tumor heterogeneity (heterogeneity between different metastatic sites in the same patient) correlate with clinical outcome in HGSOC.
What did the researchers do and find?
We developed quantitative and non-invasive image-analysis based measures for predicting outcome in HGSOC patients by combining image-based information from within and between multiple tumor sites.
Using datasets from two sources, we demonstrate that these image-based tumor heterogeneity measures predict progression free survival in patients with HGSOC.
What do these findings mean?
Non-invasive measures of CT image heterogeneity may predict outcomes in HGSOC patients.
Wider application of these CT image heterogeneity measures could prove useful for stratifying patients to different therapies given that total tumour volume and averaged textures have low predictive power.
... By reconstructing their evolutionary history a monoclonal origin was suggested with no evidence of two or more ancestral lines. Common alterations included deletions on chromosomes 13 and 17, where BRCA1/2 and p53 genes are also located [41]. Employing similar methods, a subsequent study was conducted by the same group and focused on the relationship between primary and metastatic lesions. ...
... The advent of high throughput technologies demonstrated the existence of a common ancestor and revealed the scale of intratumor heterogeneity [41]. Analyzing the relationships between different metastatic samples of the same patient, there were no cases in which all metastatic samples of a patient were identical. ...
Ovarian cancer is composed of a complex system of cells best described by features such as clonal evolution, spatial and temporal genetic heterogeneity, and development of drug resistance, thus making it the most lethal gynecologic cancer. Seminal work on cancer as an evolutionary process has a long history; however, recent cost-effective large-scale molecular profiling has started to provide novel insights coupled with the development of mathematical algorithms. In the current review, we have systematically searched for articles that focused on the clonal evolution of ovarian cancer to offer the whole landscape of research that has been done and highlight future research avenues given its characteristic features and connections to evolutionary biology.
... Molecular genetic analysis in ovarian cancer of tumour tissue has assumed that the sample reflects the DNA expression profile of the entire tumour [195]. However cancer cells within a tumour can exhibit different gene expression patterns known as intratumoural heterogeneity (ITH) [196]. ...
... However cancer cells within a tumour can exhibit different gene expression patterns known as intratumoural heterogeneity (ITH) [196]. ITH has been shown to exist in epithelial ovarian cancer, which has implications for the reliability of tumour testing; Khalique et al suggested that in order to obtain a true representation of the genetic profile of ovarian cancer, multiple samples of tissue from the tumour would require analysis [195]. Due to a laboratory error, one participant did in fact have tumour testing using two distinct tumour tissues; testing was undertaken in both tumour tissue from IDS in 2012 and metastatic tissue from laparotomy and resection of a pararectal mass in 2018. ...
Background With the advent of targeted therapies in ovarian cancer (OC), there is an impetus to identify patients with a BRCA1/2 mutation. Germline testing has already been integrated into the oncology setting using a mainstreamed model (MGT). Tumour testing is now available to detect the presence of somatic BRCA1/2 mutations. Aim To explore the introduction of mainstreamed BRCA1/2 tumour testing (MTT) in OC, focusing on clinical outcomes and patient experience. Methods A case study approach, using different research methods, was taken to gain an in depth understanding of the case (MTT) within its context. Results A service evaluation of the current state of MGT at UCLH found that in the 122 patients who were tested over 12 months, germline BRCA1/2 mutation prevalence was 14.8%. Developing the MTT pathway was feasible but challenging; delays were related to retrieval and review of archived tumour tissue. First-line MTT was provided for fifty patients; one somatic and eight germline mutations were identified. More than half this sample (52.6%) required follow-up germline testing. A prospective study using validated measures found no change in distress or quality of life scores before, during and after MTT. Patients reported low decisional conflict scores and no decision regret over MTT. After results disclosure patients with a genetic alteration had significantly more testing-related distress. Qualitative interviews revealed MTT was a brief, transient experience in the context of facing OC. Genetic misconception was common, with patients incorrectly attributing a hereditary component to tumour testing. Primary motivations for testing were related to clarifying genetic risk information for family, rather than personal benefit for treatment options. Conclusion A more streamlined process of providing MTT is needed. While MTT appears to have little psychosocial impact, poor understanding of the distinction between germline and somatic mutations indicates the need for improved communication and information provision in OC.
... Within individual tumors, significant differences in the molecular and phenotypic profiles may arise from tumor cell-intrinsic or extrinsic factors. Genomics has provided the most extensive insights to date about tumor-intrinsic variations, with sequencing studies revealing a large extent of clinically-relevant intra-tumor heterogeneity [1][2][3]. Thus, next generation sequencing of multiple tumor types identifying the association between increased clonal heterogeneity and higher pathological stage and/or worse prognosis [4]. Moreover, genetic heterogeneity has also been identified across patients, and the incidence of clinically actionable mutations differs significantly between tumors arising from different tissue or cell types, amongst patients with the same class of tumor, and between matched primary and metastatic tumors within the same patient [5][6][7][8]. ...
... As well as differences in immune infiltration and interaction of immune cell types, there are multiple tumor cell intrinsic factors, such as the secretome, receptor-ligand profile, and neoantigen repertoire, which can drive immunological heterogeneity ( Figure 1). (1), which determines whether the local tumor microenvironment (TME) will support or suppress anti-tumor immune cells; the variable expression of neoantigens (2) and ligands (3), which facilitate interaction with various immune cell types; and the secretion of soluble factors (4) (which may also be produced by the immune cells themselves) that may promote or restrain the action of nearby immune cells. Immune cell contributions to heterogeneity (bottom right) include: the type and density of infiltrating versus excluded immune cells (5); modulatory interactions between co-localised immune cell types (6); the balance of activating versus inhibitory receptors (7); effector cell distribution between the invasive margin (IM) and central tumor (CT) (8); and the overall balance between pro-and anti-tumor effectors (9). ...
Metastatic tumors are the primary cause of cancer-related mortality. In recent years, interest in the immunologic control of malignancy has helped establish escape from immunosurveillance as a critical requirement for incipient metastases. Our improved understanding of the immune system’s interactions with cancer cells has led to major therapeutic advances but has also unraveled a previously unsuspected level of complexity. This review will discuss the vast spatial and functional heterogeneity in the tumor-infiltrating immune system, with particular focus on natural killer (NK) cells, as well as the impact of tumor cell-specific factors, such as secretome composition, receptor–ligand repertoire, and neoantigen diversity, which can further drive immunological heterogeneity. We emphasize how tumor and immunological heterogeneity may undermine the efficacy of T-cell directed immunotherapies and explore the potential of NK cells to be harnessed to circumvent these limitations.
... 19,31 The presence of different cell populations within a tumor with specific genomic, genetic and/or epigenetic characteristics has been demonstrated in numerous tumor types, including solid tumors and hematologic malignancies. 19 Indeed, intra-tumor heterogeneity has been observed among gynecological cancers, particularly in high-grade serous ovarian carcinomas, 27,[32][33][34] although this issue has not been studied in endometrial cancer so far. Therefore, a better understanding of the genetic heterogeneity underlying the biological and phenotypic evolution of endometrial is crucial to understand the clinical behavior of this disease. ...
... The fact that intra-tumor heterogeneity may be represented in uterine aspirates is probably related to the nature of such samples, consisting of cells from many different parts of the uterine cavity, which could provide a more representative picture of the entire tumor specimen than samples from a specific tumor region. Similar results were observed in ovarian carcinomas where intra-tumor genetic heterogeneity was evident when solid tumor biopsies were compared, [32][33][34] but not when different ascites from the same patient were compared. 41 In this case, ascites could represent the entire cavity in a similar way that uterine aspirates do in uterine cancers, capturing all the genetic mutations and representing the heterogeneity found in the solid tumor biopsies. ...
Endometrial cancer is the most common cancer of the female genital tract in developed countries. Although the majority of endometrial cancers are diagnosed at early stages and the 5-year overall survival is around 80%, early detection of these tumors is crucial to improve the survival of patients given that the advanced tumors are associated with a poor outcome. Furthermore, correct assessment of the pre-clinical diagnosis is decisive to guide the surgical treatment and management of the patient. In this sense, the potential of targeted genetic sequencing of uterine aspirates has been assessed as a pre-operative tool to obtain reliable information regarding the mutational profile of a given tumor, even in samples that are not histologically classifiable. A total of 83 paired samples were sequenced (uterine aspirates and hysterectomy specimens), including 62 endometrioid and non-endometrioid tumors, 10 cases of atypical hyperplasia and 11 non-cancerous endometrial disorders. Even though diagnosing endometrial cancer based exclusively on genetic alterations is currently unfeasible, mutations were mainly found in uterine aspirates from malignant disorders, suggesting its potential in the near future for supporting the standard histologic diagnosis. Moreover, this approach provides the first evidence of the high intra-tumor genetic heterogeneity associated with endometrial cancer, evident when multiple regions of tumors are analyzed from an individual hysterectomy. Notably, the genetic analysis of uterine aspirates captures this heterogeneity, solving the potential problem of incomplete genetic characterization when a single tumor biopsy is analyzed.Modern Pathology advance online publication, 2 September 2016; doi:10.1038/modpathol.2016.143.
... Intra-tumour genetic heterogeneity in cancer has been investigated for almost half a century [1,2], and recent advances in genomic technology have demonstrated diverse genetic changes within a single epithelial cancer [3][4][5][6][7][8][9][10][11][12][13][14]. Multiple sampling of primary and metastatic sites in breast, pancreas, and renal carcinoma has catalogued genetic divergence and shown that metastases from the same site can show organ-specific phylogenetic branches [5][6][7][8]12]. ...
... The typical clinical presentation of HGSOC is with extensive abdominal disease, involving multiple implantation sites throughout the abdomen. Intra-tumour heterogeneity may contribute to acquired resistance in HGSOC [3,4,[28][29][30], but quantitation of the degree of heterogeneity and its relationship to changes in the course of treatment or the development of resistance is unknown. ...
The major clinical challenge in the treatment of high-grade serous ovarian cancer (HGSOC) is the development of progressive resistance to platinum-based chemotherapy. The objective of this study was to determine whether intra-tumour genetic heterogeneity resulting from clonal evolution and the emergence of subclonal tumour populations in HGSOC was associated with the development of resistant disease.
Evolutionary inference and phylogenetic quantification of heterogeneity was performed using the MEDICC algorithm on high-resolution whole genome copy number profiles and selected genome-wide sequencing of 135 spatially and temporally separated samples from 14 patients with HGSOC who received platinum-based chemotherapy. Samples were obtained from the clinical CTCR-OV03/04 studies, and patients were enrolled between 20 July 2007 and 22 October 2009. Median follow-up of the cohort was 31 mo (interquartile range 22-46 mo), censored after 26 October 2013. Outcome measures were overall survival (OS) and progression-free survival (PFS). There were marked differences in the degree of clonal expansion (CE) between patients (median 0.74, interquartile range 0.66-1.15), and dichotimization by median CE showed worse survival in CE-high cases (PFS 12.7 versus 10.1 mo, p = 0.009; OS 42.6 versus 23.5 mo, p = 0.003). Bootstrap analysis with resampling showed that the 95% confidence intervals for the hazard ratios for PFS and OS in the CE-high group were greater than 1.0. These data support a relationship between heterogeneity and survival but do not precisely determine its effect size. Relapsed tissue was available for two patients in the CE-high group, and phylogenetic analysis showed that the prevalent clonal population at clinical recurrence arose from early divergence events. A subclonal population marked by a NF1 deletion showed a progressive increase in tumour allele fraction during chemotherapy.
This study demonstrates that quantitative measures of intra-tumour heterogeneity may have predictive value for survival after chemotherapy treatment in HGSOC. Subclonal tumour populations are present in pre-treatment biopsies in HGSOC and can undergo expansion during chemotherapy, causing clinical relapse.
... Intratumoral heterogeneity has been proven to lead to initial efficacy and subsequent resistance to chemotherapy, as well as the failure of most targeted drug interventions. [2] Clarifying the degree of intratumoral heterogeneity will improve patient stratification and enhance clinical outcomes, which is more conducive to exploring the guiding factors of intratumoral heterogeneity. Inhibition therapy for these driving factors is a highly promising approach, which utilizes intratumoral genetic heterogeneity to improve clinical efficacy of cancer targeted therapy. ...
Intratumoral heterogeneity has been a hot topic of cancer research in recent years, which has become a part of resolving cancer metastasis, recurrence and drug resistance. Intratumoral heterogeneity shows that cells undergo different division and proliferation during the process of tumor development, and their genomic cells exist in the process of tumor development. Protein and epigenetic changes can lead to differences in proliferation, migration and invasion, sensitivity and pharmacological prognosis of tumor cells, promote sustainable development and development of cancer cells, produce greater adaptability, and lead to metastasis, recurrence and drug resistance of malignant tumors. In recent years, the molecular mechanism and clinical application of intratumoral heterogeneity have captivated widespread attention from researchers. In the era of precision medicine, oncologists attempt to improve the clinical efficacy of targeted tumor therapy via intratumoral heterogeneity. In this article, recent advances in the study of intratumoral heterogeneity, molecular mechanism of intratumoral heterogeneity, systematic evolution and quantification and clinical significance of tumor heterogeneity were reviewed.
... Additionally, low levels of cancer cell death are encouraging from the point of view of potentially maintaining a greater degree of intra-tumoural heterogeneity, now understood to be present in many tumour types and a likely driver of recurrence in patients not reflected by studies in cell lines [25][26][27]. ...
Purpose
This 3D in vitro cancer model for propagation of patient-derived cells, using a synthetic self-assembling peptide gel, allows the formation of a fully characterised, tailorable tumour microenvironment. Unlike many existing 3D cancer models, the peptide gel is inert, apart from molecules and motifs deliberately added or produced by cells within the model.
Methods
Breast cancer patient-derived xenografts (PDXs) were disaggregated and embedded in a peptide hydrogel. Growth was monitored by microscopic examination and at intervals, cells were extracted from the gels and passaged on into fresh gels. Passaged cells were assessed by qPCR and immunostaining techniques for the retention of characteristic markers.
Results
Breast cancer PDXs were shown to be capable of expansion over four or more passages in the peptide gel. Contaminating mouse cells were found to be rapidly removed by successive passages. The resulting human cells were shown to be compatible with a range of common assays useful for assessing survival, growth and maintenance of heterogeneity.
Conclusions
Based on these findings, the hydrogel has the potential to provide an effective and practical breast cancer model for the passage of PDXs which will have the added benefits of being relatively cheap, fully-defined and free from the use of animals or animal products. Encapsulated cells will require further validation to confirm the maintenance of cell heterogeneity, genotypes and phenotypes across passage, but with further development, including the addition of bespoke cell and matrix components of the tumour microenvironment, there is clear potential to model other cancer types.
... In addition, this research and methodology could be expanded to assay the connection between genetic changes in cell signaling pathways and cellular responses to external cues and stimuli. The continuation of this research could lead to powerful advances in diagnostics, 164 prognostics, 141 as well as therapeutics. 140,141 The scRNA-seq can be combined with ML and other sequencing techniques to research cell heterogeneity. ...
... Molecular pathology studies of primary high-grade serous ovarian carcinomas found that, despite histologically uniform morphology, there is a high degree of intratumor and interpatient heterogeneity in these cancers [45]. Studies found an underlying branching process into different molecular tumor areas in the primary tumor and the independent adaptation of tumor lesions to the respective environment at different sites, while maintaining the morphological subtype [46,47]. ...
Simple Summary
Recurrent ovarian-cancer patients face low 5-year survival rates despite chemotherapy. Oncologists may choose from a variety of guideline-recommended second-line therapeutic options without knowing which one works best. Thus, therapy alterations and adjustments are often required. We analyzed the response that 30 tumor lesions had to certain treatments in our patient-derived ovarian-cancer spheroid model. In addition, we characterized samples by immunohistochemical staining for new druggable molecular targets. Our results might help in tailoring future therapies for individual patients with recurrent ovarian cancer.
Abstract
Recurrent ovarian-cancer patients face low 5-year survival rates despite chemotherapy. A variety of guideline-recommended second-line therapies are available, but they frequently result in trial-and-error treatment. Alterations and adjustments are common in the treatment of recurrent ovarian cancer. The drug response of 30 lesions obtained from 22 relapsed ovarian cancer patients to different chemotherapeutic and molecular agents was analyzed with the patient-derived ovarian-cancer spheroid model. The profile of druggable biomarkers was immunohistochemically assessed. The second-line combination therapy of carboplatin with gemcitabine was significantly superior to the combination of carboplatin with PEGylated liposomal doxorubicin (p < 0.0001) or paclitaxel (p = 0.0007). Except for treosulfan, all nonplatinum treatments tested showed a lesser effect on tumor spheroids compared to that of platinum-based therapies. Treosulfan showed the highest efficacy of all nonplatinum agents, with significant advantage over vinorelbine (p < 0.0001) and topotecan (p < 0.0001), the next best agents. The comparative testing of a variety of treatment options in the ovarian-cancer spheroid model resulted in the identification of more effective regimens for 30% of patients compared to guideline-recommended therapies. Recurrent cancers obtained from different patients revealed profound interpatient heterogeneity in the expression pattern of druggable protein biomarkers. In contrast, different lesions obtained from the same patient revealed a similar drug response and biomarker expression profile. Biological heterogeneity observed in recurrent ovarian cancers might explain the strong differences in the clinical drug response of these patients. Preclinical drug testing and biomarker profiling in the ovarian-cancer spheroid model might help in optimizing treatment management for individual patients.
... HGSOC is known to be associated with high rates of genomic instability and TP53 mutations [34]. The intratumoral genetic heterogeneity of HGSOC was revealed by loss of heterozygosity and comparative genomic hybridization, leading to implications for the molecular diagnosis of ovarian cancer [35][36][37][38][39]. In addition, recent studies using scRNA-seq analysis have further revealed high-resolution views of the molecular environment of individual cells and distinct cell subtypes that characterize the intratumoral heterogeneity of ovarian cancer tissues [40][41][42][43][44]. scRNA-seq data from multiple ovarian cancer ascites provided gene expression profiles of individual cells, identified the immune and stromal cells, and characterized their interactions and contributions to cancer pathogenesis and resistance to chemotherapy [45,46]. ...
Precision oncology involves an innovative personalized treatment strategy for each cancer patient that provides strategies and options for cancer treatment. Currently, personalized cancer medicine is primarily based on molecular matching. Next-generation sequencing and related technologies, such as single-cell whole-transcriptome sequencing, enable the accurate elucidation of the genetic landscape in individual cancer patients and consequently provide clinical benefits. Furthermore, advances in cancer organoid models that represent genetic variations and mutations in individual cancer patients have direct and important clinical implications in precision oncology. This review aimed to discuss recent advances, clinical potential, and limitations of genomic profiling and the use of organoids in breast and ovarian cancer. We also discuss the integration of genomic profiling and organoid models for applications in cancer precision medicine.
... Although HGSOC shows marked sensitivity to initial platinum-based chemotherapy [3], most patients recur and become progressively resistant to subsequent treatments [4]. Acquisition of resistance may be related to specific mutational processes that drive genomic heterogeneity [5,6] and clonal evolution [7,8]. HGSOC exhibits marked intra-site and inter-site genomic heterogeneity across metastatic sites in the peritoneal cavity [6][7][8] with altered immunological infiltrates and a tumor micro-environment (TME) [9]. ...
Simple Summary
Clinical responses to the initial treatment of high grade serous ovarian cancer (HGSOC) vary greatly. Widespread intra-site and inter-site genomic heterogeneity presents significant challenges for the development of predictive biomarkers based on pre-treatment sampling of select individual tumors. Non-invasive stratification of patients with HGSOC by risk of outcome could facilitate a higher level of intervention for those with the highest risk of a poor outcome. We developed and validated a machine learning-based integrated marker of HGSOC outcomes to standard chemotherapy that combines a previously developed intra-site and inter-site CT radiomics measure called cluster dissimilarity (cluDiss) with clinical and genomic measures using two retrospective cohorts of internal and external institution datasets. Our approach was more accurate than conventional clinical and average radiomics measures for prognosticating progression-free survival and platinum resistance.
Abstract
Purpose: Develop an integrated intra-site and inter-site radiomics-clinical-genomic marker of high grade serous ovarian cancer (HGSOC) outcomes and explore the biological basis of radiomics with respect to molecular signaling pathways and the tumor microenvironment (TME). Method: Seventy-five stage III-IV HGSOC patients from internal (N = 40) and external factors via the Cancer Imaging Archive (TCGA) (N = 35) with pre-operative contrast enhanced CT, attempted primary cytoreduction, at least two disease sites, and molecular analysis performed within TCGA were retrospectively analyzed. An intra-site and inter-site radiomics (cluDiss) measure was combined with clinical-genomic variables (iRCG) and compared against conventional (volume and number of sites) and average radiomics (N = 75) for prognosticating progression-free survival (PFS) and platinum resistance. Correlation with molecular signaling and TME derived using a single sample gene set enrichment that was measured. Results: The iRCG model had the best platinum resistance classification accuracy (AUROC of 0.78 [95% CI 0.77 to 0.80]). CluDiss was associated with PFS (HR 1.03 [95% CI: 1.01 to 1.05], p = 0.002), negatively correlated with Wnt signaling, and positively to immune TME. Conclusions: CluDiss and the iRCG prognosticated HGSOC outcomes better than conventional and average radiomic measures and could better stratify patient outcomes if validated on larger multi-center trials.
... The advances in the NGS and in other 'omics' studies have revealed the intrinsic complexity within the OC subtypes and within an individual patient with OC [78e87]. First, studies based on loss of heterozygosity data by microsatellite and single-nucleotide polymorphism analyses demonstrated widespread ITH in primary ovarian tumours, suggesting a monoclonal origin [78]. This process was also found between metastatic lesions, being clonally related with the primary tumour [79]. ...
Background and purpose
Ovarian cancer (OC) is the deadliest gynaecologic cancer characterised by a high heterogeneity not only at the clinical point of view but also at the molecular level. This review focuses on the new insights about the OC molecular classification.
Materials and methods
We performed a bibliographic search for different indexed articles focused on the new molecular classification of OC. All of them have been published in PubMed and included information about the most frequent molecular alterations in OC confirmed by omics approaches. In addition, we have extracted information about the role of liquid biopsy in the OC diagnosis and prognosis.
Results
New molecular insights into OC have allowed novel clinical entities to be defined. Among OC, high-grade serous ovarian carcinoma (HGSOC) which is the most common OC is characterised by omics approaches, mutations in TP53 and in other genes involved in the homologous recombination repair, especially BRCA1/2. Recent studies in HGSOC have allowed a new molecular classification in subgroups according to their mutational, transcriptional, methylation and copy number variation signatures with a real impact in the characterisation of new therapeutic targets for OC to be defined. Furthermore, despite the intrinsic intra-tumour heterogeneity, the advances in next generation sequencing (NGS) analyses of ascetic liquid from OC have opened new ways for its characterisation and treatment.
Conclusions
The advances in genomic approaches have been used for the identification of new molecular profiling techniques which define OC subgroups and has supposed advances in the diagnosis and in the personalised treatment of OC.
... Deletions were assumed to be heterozygous if the copy number as estimated by both CNVkit and CLImAT was 1. It is possible that these deletions are homozygous deletions in a subclone of the tumour but as we expect that these events are early events 63 we believe that it is more likely that they are true heterozygotes so have . CC-BY 4.0 International license (which was not certified by peer review) is the author/funder. ...
Around half of high grade serous ovarian carcinomas (HGSOC) show homologous recombination repair deficiency (HRD), often caused by germline or somatic single nucleotide variant (SNV) mutations or small indels disrupting BRCA1/2. We have uniformly processed the largest collection of whole genome sequencing (WGS) data from HGSOC samples to date (N=205), comprehensively characterising the somatic mutational landscape, and expression at the BRCA1/2 loci. We discover that large structural variants (SV) are a frequent but unappreciated source of BRCA1/2 disruption in these tumours. Somatic structural variation at these loci is dominated by multi-megabase deletions that span the entirety of BRCA1 (median = 4.9Mb) or BRCA2 (median = 6.2Mb), independently affecting a substantial proportion of patients (16%) in addition to those affected by damaging germline or somatic short variants, within the BRCA1/2 coding sequences (24%). In common with previous studies, we show that the presence of damaging somatic SNVs or short indels in BRCA1 (OR=10, 95% CI 1.8-103, p=0.002, adj p=0.027 and BRCA2 (OR=17, 95% CI 2.1-816), p=0.002, adj.p=0.021) was found to influence HRD. For the first time we also study the compound effect of SV and SNV or short indel mutations at both loci, demonstrating that SVs often contribute to compound deficiencies involving SNVs or indels, with large somatic deletions contributing to these compound deficiencies in 15/205 (7%) of samples. Notably the strongest risk of HRD (OR=19 (2.4-896), p=6.6x10-3, adj P=8.5x10-3) is generated by combined large deletions at BRCA1 and BRCA2 in the absence of SNVs or indels, affecting 3% of patients. Overall, we show that HRD is a complex phenotype in HGSOC tumours, affected by the patterns of shorter variants such as SNVs and indels, SVs, methylation and expression seen at multiple loci, and we construct a successful (ROC AUC = 0.75) predictive model of HRD using such variables. In addition, HRD impacts patient survival when conferred by mechanisms other than through the well-understood short variants at BRCA1/2, currently exploited in the clinic. These results alter our understanding of the mutational landscape at the BRCA1/2 loci in highly rearranged tumours, and increase the number of patients predicted to benefit from therapies exploiting HRD in tumours such as PARP inhibition.
... Previous studies [38][39][40] have demonstrated heterogeneity among OCs. The aim of the present study was to compare overall CNVs and LOH across the entire genome using the limiting dilution method [41] to isolate and establish heterogeneous subclones of ovarian cancer tissues and cell lines. ...
Ovarian cancer (OC) metastasis presents major hurdles that must be overcome to improve patient outcomes. Recent studies have demonstrated copy number variations (CNVs) frequently contribute to alterations in oncogenic drivers. The present study used a CytoScan HD Array to analyse CNVs and loss of heterozygosity (LOH) in the entire genomes of 6 OC patients and human OC cell lines to determine the genetic target events leading to the distinct invasive/migratory capacities of OC. The results showed that LOH at Xq11.1 and Xp21.1 and gains at 8q21.13 were novel, specific CNVs. Ovarian cancer-related CNVs were then screened by bioinformatics analysis. In addition, transcription factors-target gene interactions were predicted with information from PASTAA analysis. As a result, six genes (i.e., GAB2, AKT1, EGFR, COL6A3, UGT1A1 and UGT1A8) were identified as strong candidates by integrating the above data with gene expression and clinical outcome data. In the transcriptional regulatory network, 4 known cancer-related transcription factors (TFs) interacted with 6 CNV-driven genes. The protein/DNA arrays revealed 3 of these 4 TFs as potential candidate gene-related transcription factors in OC. We then demonstrated that these six genes can serve as potential biomarkers for OC. Further studies are required to elucidate the pathogenesis of OC.
... Type II (high-grade) EOC has a poor prognosis, yet it is sensitive to chemotherapy (9). The evaluation of ovarian cancer grade currently relies solely on clinicopathological parameters; a molecular standard for diagnosis is yet to be established (10). Therefore, identifying effective biomarkers associated with the EOC grade is of clinical significance for developing effective therapeutic strategies for patients with EOC, and may contribute to the prediction of prognosis. ...
Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy that threatens the health of females. Previous studies have demonstrated that the survival outcomes of patients with different EOC grades varied. Therefore, the EOC grade is considered to serve as a distinctive prognostic factor. To date, the evaluation of ovarian cancer grade relies on pathological examination and a quantitative index for diagnosis is lacking. Furthermore, the dysregulation of genes has been demonstrated to exert pivotal functions in the carcinogenesis of EOCs. Therefore, the identification of effective biomarkers associated with EOC grade is of importance for the development of therapeutic regimens, and also contributes to the prediction of EOC prognosis. Microarrays have been increasingly applied for the identification of potential molecular biomarkers for numerous diseases including EOC. In the present study, four public microarray datasets (GSE26193, GSE63885, GSE30161 and GSE9891) were analyzed. A total of 6,103 upregulated probes corresponding to 5,766 genes, and 4,004 downregulated probes corresponding to 3,707 genes were identified in the GSE26193, GSE63885 and GSE30161 datasets. ALK and LTK ligand 2 was the most downregulated gene associated with the tumor grade, while CCCTC-binding factor like (CTCFL), EGF like domain multiple 6, radical S-adenosyl methionine domain containing 2 and SAM and HD domain containing deoxynucleoside triphosphate triphosphohydrolase 1 were the most upregulated genes associated with EOC grade. The GSE9891 dataset was added for further analysis. Only one probe (1552368_at) encoding for CTCFL was identified to be consistently upregulated in the four examined datasets. Immunohistochemical analysis was used to detect the expression of CTCFL between low- and high-grade EOC tissues and revealed that the EOC grade was closely associated with CTCFL level. This was corroborated via the reverse transcription-quantitative polymerase chain reaction. Taken together, the results of the present study suggested that CTCFL is upregulated in high-grade epithelial ovarian cancer.
... Tumor metastasis, drug resistance and recurrence are the major causes of a poor prognosis in patients [2,3]. Within a single tumor, cancer cells display various heterogeneous features, including different biological characteristics, gene expression levels, and differentiation statuses; this phenomenon is referred to as intratumoral heterogeneity (ITH) [4][5][6]. ITH appears to be related to tumor metastasis, therapeutic resistance and recurrence, which lead to treatment failure in many human malignant tumors [7][8][9][10][11]. ...
Background:
To explore the role of lysophosphatidic acid receptor 1 (LPAR1) and its correlation with the PI3K/AKT pathway in the development of intratumoral heterogeneity (ITH) in human ovarian serous cystadenocarcinoma (OSC).
Methods:
Immunohistochemical staining was performed to detect LPAR1 expression in matched primary and recurrent lesions from the same patients. Cell models of ITH were established using the limiting dilution methodology and Transwell invasion/migration assays. LPAR1 expression in the ITH cell models was silenced or upregulated with lentiviral particles, and the biological characteristics were evaluated using various in vitro and in vivo assessments of cell function. The levels of phosphorylated PI3K/AKT (p-PI3K/p-AKT) in LPAR1 knockdown and LPAR1-overexpressing cells were detected.
Results:
The H-scores for LPAR1 staining in the lymphatic metastatic and recurrent lesions were noticeably higher than in the primary tumor lesions from the same patients (P = 0.024/0.031). High LPAR1 expression was associated with worse progression-free survival and overall survival (P = 0.017/0.039). Biological functions in vitro, including invasion, migration, and proliferation, and tumor formation in vivo were decreased in the LPAR1-silenced cells (all P < 0.05). These cellular functions were significantly increased in the LPAR1-overexpressing cells in vitro and in vivo (all P < 0.05). The levels of p-PI3K and p-AKT were significantly decreased in the LPAR1 knockdown cells and significantly increased in the LPAR1-overexpressing cells (all P < 0.05).
Conclusions:
Higher levels of the LPAR1 protein were associated with a poor prognosis. LPAR1 plays essential roles in the invasion, migration, and proliferation of heterogeneous subsets of OSC cell lines and the development of ITH of OSC, possibly by modulating the activity of the PI3K/AKT signaling pathway.
... As a result, pre-existing drug-resistant sub clones in the initial cell population survive the treatment, leading to chemotherapeutic resistance (Burrel and Swanton, 2014). Evidence for tumour heterogeneity comes from histological observations (Komaki et al., 2006), transcript expression (Bachtiary et al., 2006), single nucleotide polymorphisms (Khalique et al., 2007) and large-scale genomic analysis of tumour sections to identify tumour sub populations (Navin et al., 2010). Such population-based bulk sequencing analyses provide major insights into cancer genomics, but often fail to provide the insights at the cellular resolution that is crucial for understanding the tumour recurrence mechanisms after anti-cancer treatments (Wills and Mead, 2015). ...
... As a result, pre-existing drug-resistant sub clones in the initial cell population survive the treatment, leading to chemotherapeutic resistance (Burrel and Swanton, 2014). Evidence for tumour heterogeneity comes from histological observations (Komaki et al., 2006), transcript expression (Bachtiary et al., 2006), single nucleotide polymorphisms (Khalique et al., 2007) and large-scale genomic analysis of tumour sections to identify tumour sub populations (Navin et al., 2010). Such population-based bulk sequencing analyses provide major insights into cancer genomics, but often fail to provide the insights at the cellular resolution that is crucial for understanding the tumour recurrence mechanisms after anti-cancer treatments (Wills and Mead, 2015). ...
... It is well established that tumors harbor intra-as well as intertumor genomic heterogeneity from off-branching metastatic deposits [109][110][111][112][113]. In principle, ctDNA is released from tumor cells present at all sites (Figure 1). ...
Circulating tumor DNA (ctDNA) consists of cell-free DNA (cfDNA) fragments that are released from tumor cells into the bloodstream. ctDNA harbors cancer-specific genetic and epigenetic alterations that allow its detection and quantification using a variety of emerging techniques. The promise of convenient non-invasive access to the complex and dynamic molecular features of cancer through peripheral blood has galvanized translational researchers around this topic with compelling routes to clinical implementation, particularly in the post-treatment surveillance setting. Although analysis methods must contend with the small quantities of ctDNA present in most patients and the relative over-abundance of background cfDNA derived from normal tissues, recent technical innovations have led to dramatic improvements in the sensitivity of ctDNA detection. As a result, ever more studies are investigating the clinical utility of ctDNA for applications in (1) treatment response assessment, (2) identification of emerging resistance mechanisms, (3) minimal residual disease detection, and (4) characterization of clonal heterogeneity and selection. In this review, we describe the detection methods currently used in clinical studies to assess low fractions of ctDNA, as well as their utility in the applications previously described. Finally, we address current limitations that have hampered the clinical implementation of ctDNA analysis for post-treatment surveillance and propose steps that could be made to address them.
... However, if the DNA is damaged or not copied correctly, the new damaged cells will either die or start to proliferate in an uncontrolled manner, creating a signalling of oncogenes that act by mimicking growth signalling (Hanahan & Weinberg, 2000), eventually leading to an abnormal mass of tissues from cells that differ in clinically important phenotypic features (Marusyk et al., 2012). More precisely, tumour formation is a result of clonal expansion driven by somatic mutation, developed by a single precursor (monoclonal) that undergoes genetic and biological changes (Khalique et al., 2007;Nowell, 1976). This transformation of normal cells to cancer cells is a multistep process described via 544 V. BITSOUNI ET AL. sub-populations have been shown to be distinct not only in their adhesion capabilities but also in their motility and metastatic potential (Marusyk & Polyak, 2010). ...
Cells adhere to each other and to the extracellular matrix (ECM) through protein molecules on the surface of the cells. The breaking and forming of adhesive bonds, a process critical in cancer invasion and metastasis, can be influenced by the mutation of cancer cells. In this paper, we develop a nonlocal mathematical model describing cancer cell invasion and movement as a result of integrin-controlled cell-cell adhesion and cell-matrix adhesion, for two cancer cell populations with different levels of mutation. The partial differential equations for cell dynamics are coupled with ordinary differential equations describing the ECM degradation and the production and decay of integrins. We use this model to investigate the role of cancer mutation on the possibility of cancer clonal competition with alternating dominance, or even competitive exclusion (phenomena observed experimentally). We discuss different possible cell aggregation patterns, as well as travelling wave patterns. In regard to the travelling waves, we investigate the effect of cancer mutation rate on the speed of cancer invasion.
... Some study groups have evaluated ITH on a molecular level in EOC. Khalique et al. [59] analyzed several regions of tumor tissue from 16 patients with HGSC, and then used microsattellite analysis and single-nucleotide polymorphism analysis to evaluate the extent of ITH and identify the clonal relationship between these regions. Although the tumors exhibited similar morphology, all cases showed a high degree of ITH between patients and between samples. ...
Ovarian cancer encompasses a collection of neoplasms with distinct clinicopathological and molecular features and prognosis. Despite there being a variety of ovarian cancer subtypes, these are treated as a single disease. Tremendous efforts have been made to characterize these subtypes and identify tumoral pathways and potential biomarkers for therapeutic strategies. As in other cancer types, tumor heterogeneity appears to be very high across subtypes and within a single tumor, representing a major cause of treatment failure. We describe the morphological and molecular heterogeneity among ovarian cancers and discuss recent advances in our understanding of intratumor heterogeneity.
... Experimental studies 33,41 have shown that tumours consist of heterogeneous populations of cells, which are the result of genetic instability. Intra-tumour heterogeneity appears in almost all phenotypic cell features: from cell morphology, to gene expression, motility, proliferation, immunogenicity and metastatic potential. ...
In this paper, we develop a non-local mathematical model describing cancer cell invasion and movement as a result of integrin-controlled cell–cell adhesion and cell–matrix adhesion, and transforming growth factor-beta (TGF-β) effect on cell proliferation and adhesion, for two cancer cell populations with different levels of mutation. The model consists of partial integro-differential equations describing the dynamics of two cancer cell populations, coupled with ordinary differential equations describing the extracellular matrix (ECM) degradation and the production and decay of integrins, and with a parabolic PDE governing the evolution of TGF-β concentration. We prove the global existence of weak solutions to the model. We then use our model to explore numerically the role of TGF-β in cell aggregation and movement.
... Tumour heterogeneity within a single tumour site (intratumour heterogeneity) or between different metastatic sites in the same patient (inter-site heterogeneity) is a feature of many solid malignancies, and preliminary evidence linking tumour heterogeneity and outcomes in ovarian cancer is emerging [5,6]. A robust imaging-based method to quantify non-invasively heterogeneity within and among separate tumour sites in the same patient could improve our ability to select effective therapies and curtail treatment resistance. ...
PurposeTo evaluate the associations between clinical outcomes and radiomics-derived inter-site spatial heterogeneity metrics across multiple metastatic lesions on CT in patients with high-grade serous ovarian cancer (HGSOC). MethodsIRB-approved retrospective study of 38 HGSOC patients. All sites of suspected HGSOC involvement on preoperative CT were manually segmented. Gray-level correlation matrix-based textures were computed from each tumour site, and grouped into five clusters using a Gaussian Mixture Model. Pairwise inter-site similarities were computed, generating an inter-site similarity matrix (ISM). Inter-site texture heterogeneity metrics were computed from the ISM and compared to clinical outcomes. ResultsOf the 12 inter-site texture heterogeneity metrics evaluated, those capturing the differences in texture similarities across sites were associated with shorter overall survival (inter-site similarity entropy, similarity level cluster shade, and inter-site similarity level cluster prominence; p ≤ 0.05) and incomplete surgical resection (similarity level cluster shade, inter-site similarity level cluster prominence and inter-site cluster variance; p ≤ 0.05). Neither the total number of disease sites per patient nor the overall tumour volume per patient was associated with overall survival. Amplification of 19q12 involving cyclin E1 gene (CCNE1) predominantly occurred in patients with more heterogeneous inter-site textures. Conclusion
Quantitative metrics non-invasively capturing spatial inter-site heterogeneity may predict outcomes in patients with HGSOC. Key Points• Calculating inter-site texture-based heterogeneity metrics was feasible• Metrics capturing texture similarities across HGSOC sites were associated with overall survival• Heterogeneity metrics were also associated with incomplete surgical resection of HGSOC.
... Studies performed by others [30][31][32] and in our lab [33][34][35] have demonstrated that there is heterogeneity among ovarian cancers. We used the limiting-dilution method to isolate and establish heterogeneous subclones of the ovarian cancer cell lines A2780 and SKOV3 [22]. ...
Ovarian cancer has the worst prognosis of any gynecological malignancy, and generally presents with metastasis at advanced stages. Copy number variation (CNV) frequently contributes to the alteration of oncogenic drivers. In this study, we sought to identify genetic targets in heterogeneous clones from human ovarian cancers cells. We used array-based technology to systematically assess all the genes with CNVs in cell models clonally expanded from A2780 and SKOV3 ovarian cancer cell lines with distinct highly and minimally invasive/migratory capacities. We found that copy number alterations differed between matched highly and minimally invasive/migratory subclones, differentially affecting specific functional processes including immune response processes, DNA damage repair, cell cycle and cell proliferation. We also identified seven genes as strong candidates, including DDB1, ERCC1, ERCC2, PRPF19, BCAT1, CDKN1B and MARK4, by integrating the above data with gene expression and clinical outcome data. Thus, by determining the molecular signatures of heterogeneous invasive/migratory ovarian cancer cells, we identified genes that could be specifically targeted for the treatment and prognosis of advanced ovarian cancers.
... We performed micro-satellite analysis to objectively detect LOH as described previously [16]. We amplified patient tumor and blood DNA for two markers within BRCA1 (D17S855 and D17S1322) and four markers around BRCA2 (D13S290, D13S260, D13S1698, and D13S171). ...
Background: Most $\textit{BRCA1}$ or $\textit{BRCA2}$ mutation carriers have inherited a single (heterozygous) mutation. Transheterozygotes (TH) who have inherited deleterious mutations in both $\textit{BRCA1}$ and $\textit{BRCA2}$ are rare, and the consequences of transheterozygosity are poorly understood. Methods: From 32,295 female $\textit{BRCA1/2}$ mutation carriers, we identified 93 TH (0.3 %). "Cases" were defined as TH, and "controls" were single mutations at $\textit{BRCA1}$ (SH1) or $\textit{BRCA2}$ (SH2). Matched SH1 "controls" carried a BRCA1 mutation found in the TH "case". Matched SH2 "controls" carried a BRCA2 mutation found in the TH "case". After matching the TH carriers with SH1 or SH2, 91 TH were matched to 9316 SH1, and 89 TH were matched to 3370 SH2. Results: The majority of TH (45.2 %) involved the three common Jewish mutations. TH were more likely than SH1 and SH2 women to have been ever diagnosed with breast cancer (BC; $p$ = 0.002). TH were more likely to be diagnosed with ovarian cancer (OC) than SH2 ($p$ = 0.017), but not SH1. Age at BC diagnosis was the same in TH vs. SH1 ($p$ = 0.231), but was on average 4.5 years younger in TH than in SH2 ($p$ < 0.001). BC in TH was more likely to be estrogen receptor (ER) positive ($p$ = 0.010) or progesterone receptor (PR) positive ($p$ = 0.013) than in SH1, but less likely to be ER positive ($p$ < 0.001) or PR positive ($p$ = 0.012) than SH2. Among 15 tumors from TH patients, there was no clear pattern of loss of heterozygosity (LOH) for $\textit{BRCA1}$ or $\textit{BRCA2}$ in either BC or OC. Conclusions: Our observations suggest that clinical TH phenotypes resemble SH1. However, TH breast tumor marker characteristics are phenotypically intermediate to SH1 and SH2.
... We performed micro-satellite analysis to objectively detect LOH as described previously [16]. We amplified patient tumor and blood DNA for two markers within BRCA1 (D17S855 and D17S1322) and four markers around BRCA2 (D13S290, D13S260, D13S1698, and D13S171). ...
Background
Most BRCA1 or BRCA2 mutation carriers have inherited a single (heterozygous) mutation. Transheterozygotes (TH) who have inherited deleterious mutations in both BRCA1 and BRCA2 are rare, and the consequences of transheterozygosity are poorly understood. Methods
From 32,295 female BRCA1/2 mutation carriers, we identified 93 TH (0.3 %). “Cases” were defined as TH, and “controls” were single mutations at BRCA1 (SH1) or BRCA2 (SH2). Matched SH1 “controls” carried a BRCA1 mutation found in the TH “case”. Matched SH2 “controls” carried a BRCA2 mutation found in the TH “case”. After matching the TH carriers with SH1 or SH2, 91 TH were matched to 9316 SH1, and 89 TH were matched to 3370 SH2. ResultsThe majority of TH (45.2 %) involved the three common Jewish mutations. TH were more likely than SH1 and SH2 women to have been ever diagnosed with breast cancer (BC; p = 0.002). TH were more likely to be diagnosed with ovarian cancer (OC) than SH2 (p = 0.017), but not SH1. Age at BC diagnosis was the same in TH vs. SH1 (p = 0.231), but was on average 4.5 years younger in TH than in SH2 (p < 0.001). BC in TH was more likely to be estrogen receptor (ER) positive (p = 0.010) or progesterone receptor (PR) positive (p = 0.013) than in SH1, but less likely to be ER positive (p < 0.001) or PR positive (p = 0.012) than SH2. Among 15 tumors from TH patients, there was no clear pattern of loss of heterozygosity (LOH) for BRCA1 or BRCA2 in either BC or OC. Conclusions
Our observations suggest that clinical TH phenotypes resemble SH1. However, TH breast tumor marker characteristics are phenotypically intermediate to SH1 and SH2.
... (59) There was considerable genetic heterogeneity observed between patients and between samples collected from the same patient, manifested as chromosome deletion, microsatellite instability and single nucleotide polymorphism (SNP) variation. (60) It is now evident that tumor cells within the ascites are also heterogeneous at both cellular and molecular levels, (55) but its contribution to the tumor heterogeneity and ovarian cancer prognosis need to be studied further. Cancer was previously viewed as a heterogeneous disease, caused not only by tumor cell themselves containing aberrant mutations but also by microenvironment constituents. ...
The ascites of cancer is a unique tumor-microenvironment, providing a physical structure for the accumulation of cellular and acellular components. Ascites is initiated and maintained by physical and biological factors resulting from underlying disease and forms an ecosystem that contributes to disease progression. It has been demonstrated that the cellular contents and the molecular signatures of ascites change continuously, during the course of a disease. Over the last decade, increasing attention has been given to the characterization of components of ascites and their role in the progression of ovarian cancer, the most malignant gynecologic cancer in women. This review will discuss the role of ascites in disease progression, in terms of modulating cancer cell behavior and contributing to tumor heterogeneity from molecular levels to clinical implication in ovarian cancer. This article is protected by copyright. All rights reserved.
... When the TMA technology was first published in 1998 (Kononen et al. 1998), the small diameter of the tissue spots (0.6 mm) prompted concerns regarding the representativity of the TMA cores (Camp et al. 2000;Gancberg et al. 2002;Rimm et al. 2001). Tumor heterogeneity is a consequence of genetic instability and molecular evolution, and genetic differences have been found between different cells of the same tumor (Khalique et al. 2007), between invasive and noninvasive parts (Sauter and Mihatsch 1998;Simon et al. 1998;Robanus-Maandag et al. 2003), between primary tumors and metastases (Cho et al. 2008), or between multifocal tumors from the same organ (Simon et al. 2001a). Consequently, many researchers recommended the use of larger core diameters, or the inclusion of more than one tissue spot per tumor to increase the degree of representativity (Camp et al. 2000;Engellau et al. 2001;Fernebro et al. 2002;Hoos et al. 2001aHoos et al. , b, 2002Kristiansen et al. 2008;Zhang et al. 2003). ...
Array-comparative genomic hybridisation (array-CGH) and single nucleotide polymorphism array hybridisation (SNP-array) enable genome-wide detection of copy number alterations (CNA). These techniques outperform conventional chromosomal karyotyping in relation to detection of CNAs. The discovery of previously cryptic alterations associated with constitutional or acquired cytogenetic changes with DNA copy number gains or losses quickly led to the identification of novel syndromes or previously unseen tumour-related changes. Array platforms are often targeted to pathognomonic regions to detect well-characterised unbalanced chromosomal rearrangements. Platforms with genome-wide coverage detect additional CNA representing normal genomic variation (copy number variation: CNV) or variation with yet unknown significance. The use of SNP-array facilitating the detection of segmental uniparental disomies might be advantageous compared to classical array-CGH approaches. However, none of the array platforms permit the detection of balanced genomic rearrangements such as translocation, inversion or insertions or some polyploidies. The use of array platforms in cytogenetic testing quickly became a routine diagnostic tool and will replace conventional cytogenetic testing in many instances. In addition, these techniques have the potential to identify genomic changes relevant for the establishment of prognostic stratification of different neoplastic conditions. © 2012 Springer-Verlag Berlin Heidelberg. All rights are reserved.
... Hypoxic conditions created by the growing mass then induce expression of large sets of genes (e.g., hypoxia inducible factor (HIF) and its downstream effectors) that allows the tumor to revert to a more primitive phenotype and acquire aerobic glycolysis to lower local pH and disrupt the surrounding stromal tissues [15]. This primitive phenotype also accelerates genetic mutations to reach dysregulated proliferation and leads to tumor genetic heterogeneity [3,4]. ...
... Conversely, other studies have shown a high degree of intra-tumor heterogeneity, which would allow clonal evolution and the successive tumor progression and resistance to chemotherapy [15,16]. In fact, intra-tumor heterogeneity has been shown to be intrinsic to primary tumor and not just a result of chemotherapy treatment [14,17]. ...
Background
High grade serous ovarian cancer is characterised by high initial response to chemotherapy but poor outcome in the long term due to acquired resistance. One of the main genetic features of this disease is TP53 mutation. The majority of TP53 mutated tumors harbor missense mutations in this gene, correlated with p53 accumulation. TP53 null tumors constitute a specific subgroup characterised by nonsense, frameshift or splice-site mutations associated to complete absence of p53 expression. Different studies show that this kind of tumors may have a worse prognosis than other TP53 mutated HGSC.
Methods
In this study, we sought to characterise the intra-tumor heterogeneity of a TP53 null HGSC consisting of six primary tumor samples, two intra-pelvic and four extra-pelvic recurrences using exome sequencing and comparative genome hybridisation.
Results
Significant heterogeneity was found among the different tumor samples, both at the mutational and copy number levels. Exome sequencing identified 102 variants, of which only 42 were common to all three samples; whereas 7 of the 18 copy number changes found by CGH analysis were presented in all samples. Sanger validation of 20 variants found by exome sequencing in additional regions of the primary tumor and the recurrence allowed us to establish a sequence of the tumor clonal evolution, identifying those populations that most likely gave rise to recurrences and genes potentially involved in this process, like GPNMB and TFDP1. Using functional annotation and network analysis, we identified those biological functions most significantly altered in this tumor. Remarkably, unexpected functions such as microtubule-based movement and lipid metabolism emerged as important for tumor development and progression, suggesting its potential interest as therapeutic targets.
Conclusions
Altogether, our results shed light on the clonal evolution of the distinct tumor regions identifying the most aggressive subpopulations and at least some of the genes that may be implicated in its progression and recurrence, and highlights the importance of considering intra-tumor heterogeneity when carrying out genetic and genomic studies, especially when these are aimed to diagnostic procedures or to uncover possible therapeutic strategies.
Electronic supplementary material
The online version of this article (doi:10.1186/s12885-015-1952-z) contains supplementary material, which is available to authorized users.
... Clonal evolution generated by genetic instability and genetic drift is not a new concept [28]. Evidence of intratumor heterogeneity and branched evolutionary growth has been revealed in solid tumors via both tissue sections and multiregion sequencing [29][30][31][32]. Kreso et al., followed the repopulation dynamics of 150 single lentivirus-marked lineages from ten human CRCs through serial xenograft passages in mice using DNA copy number profiling, sequencing and lentiviral lineage tracking. ...
Background:
This retrospective study aims to investigate the activity of retreatment with anti-EGFR-based therapies in order to explore the concept of clonal evolution by evaluating the impact of prior activity and intervening time interval.
Methods:
Eighty-nine KRAS exon 2-wild-type metastatic colorectal patients were retreated on phase I/II clinical trials containing anti-EGFR therapies after progressing on prior cetuximab or panitumumab. Response on prior anti-EGFR therapy was defined retrospectively per physician-records as response or stable disease ≥6 months. Multivariable statistical methods included a multiple logistic regression model for response, and Cox proportional hazards model for progression-free survival.
Results:
Retreatment anti-EGFR agents were cetuximab (n = 76) or cetuximab plus erlotinib (n = 13). The median interval time between prior and retreatment regimens was 4.57 months (range: 0.46-58.7). Patients who responded to the prior cetuximab or panitumumab were more likely to obtain clinical benefit to the retreatment compared to the non-responders in both univariate (p = 0.007) and multivariate analyses (OR: 3.38, 95 % CI: 1.27, 9.31, p = 0.019). The clinical benefit rate on retreatment also showed a marginally significant association with interval time between the two anti-EGFR based therapies (p = 0.053). Median progression-free survival on retreatment was increased in prior responders (4.9 months, 95 % CI: 3.6, 6.2) compared to prior non-responders (2.5 months, 95 % CI, 1.58, 3.42) in univariate (p = 0.064) and multivariate analysis (HR: 0.70, 95 % CI: 0.43-1.15, p = 0.156).
Conclusion:
Our data lends support to the concept of clonal evolution, though the clinical impact appears less robust than previously reported. Further work to determine which patients benefit from retreatment post progression is needed.
... Accumulating evidence in the literature [16,17] and from our previous studies [18,19] has demonstrated that tumor heterogeneity exists in EOC. In this study, using limiting dilution methodology and routine culture conditions, 45 subclones were isolated and established from the A2780 cell line, and 40 subclones were acquired from the SKOV3 cell line. ...
To explore the genetic and molecular events that control subclones exhibiting distinct invasive/migratory capacities derived from human epithelial ovarian cancer (EOC) cell line A2780 and SKOV3.
Single-cell subclones were isolated and established that were derived from the SKOV3 and A2780 cell lines through limiting dilution methodology. Transwell insert assays and MTT assays were performed to screen and identify the subclones exhibiting the highest and the lowest invasive/migratory capacities, and the selected subclones were renamed as A-H (A2780 high), A-L (A2780 low), S-H (SKOV3 high), and S-L (SKOV3 low). Their biological characteristics were evaluated. RNA-Seq was conducted on the targeted subclones.
Compared with their corresponding counterparts, A-H/S-H cells exhibited significantly higher invasive/migratory capacities (P < 0.001 and = 0.001, respectively). A-H/S-H cells displayed a clear reduction in doubling time (P = 0.004 and 0.001, respectively), and a significant increase in the percentage of cells in S phase (P = 0.004 and 0.022, respectively). Additionally, the apoptotic rates of A-H/S-H cells were significantly lower than those of A-L/S-L cells (P = 0.002 and 0.026, respectively). At both mRNA and protein levels, caspase-3 and caspase-7 expression were reduced but Bcl-2 expression was increased in A-H/S-H cells. The TrkB (anoikis-related) and Beclin1 (autophagy-related) levels were consistently high and low, respectively, in both A-H/S-H cells. Resistance to chemotherapy in vitro and higher capacities on tumor formation in vivo was presented in both A-H/S-H cells. PI3K/AKT/mTOR pathway components, PIK3CA, PIK3CD, AKT3, ECM1, GPCR, mTOR and PRKCB were increased but that the Nur77 and PTEN were decreased in A-H/S-H cells, identified by RNA-Seq and consistently confirmed by RT-PCR and Western blot analyses.
Heterogeneous cell subpopulations exhibiting distinct invasive and migratory capacities co-exist within the SKOV3 and A2780 cell lines. PI3K/AKT/mTOR pathway activation is associated with higher invasive and migratory capacities in subpopulations of human ovarian cancer cell lines. Inhibiting this pathway may be useful for the chemoprevention or treatment of EOC.
... In a study published in 2007, multiple specimens were microdissected from paraffinembedded tumors obtained from 22 patient samples and compared using microsatellite and single nucleotide polymorphism (SNP) analysis. Although all tumors were HGSOC and thus morphologically similar, there was considerable genetic heterogeneity observed between patients and between samples collected from the same patient, manifested as chromosome deletions (particularly chromosomes 13 and 17), microsatellite instability, and SNP variation (38). ...
Heterogeneity has emerged as a key feature of ovarian cancer between different ovarian cancer subtypes; within single ovarian cancer subtypes; and within individual patient tumors. At the genomic level, with the advent of ultra-deep sequencing technologies alongside RNA-Seq, epigenomics, and proteomics, the complexity surrounding heterogeneity has deepened. Here, we summarize the emerging understanding of heterogeneity in cancer as a whole and the key discoveries in this area relating to ovarian cancer. We explore the therapeutic limitations and possibilities posed by heterogeneity and how these will influence the future of ovarian cancer treatment and research.
... method of mutation ana lysis), protein (detected by the method of immunohistochemical ana lysis) and macroscopic level in a wide range of tumors, such as breast cancer [6][7][8][9][10][11][12][13][14], CRC [15][16][17][18][19][20][21][22][23][24][25], NSCLC [26,27], prostate cancer [28][29][30][31][32], ovarian cancer [33][34][35][36][37][38][39][40][41], pancreatic cancer [42,43], gastric cancer [44][45][46][47], brain cancer [48][49][50][51][52][53] and renal clear cell carcinoma [54]. In recent years, many stud ies have focused on the heterogeneity found in primary tumors and corresponding metastases with the consideration that evaluation of meta static rather than primary sites could be of clini cal relevance. ...
Interpatient variability in response to anticancer drugs is associated with different clinical outcomes, which is partially owing to the individual differences among patients. Many investigators have hoped that tumor heterogeneity would help to reveal the underlying mechanism of interpatient variability in response to anticancer therapy. Numerous studies have demonstrated the presence of intratumor heterogeneity and the heterogeneity in primary tumors and corresponding metastases in a wide range of tumors at different levels and have indicated that the heterogeneity might make sense as a potential determinant of anticancer therapy response. This article discusses tumor heterogeneity, focusing on the heterogeneity in primary tumors and corresponding metastases as well as the effect on anticancer therapy response. Furthermore, an idea of tumor-site-based personalized cancer therapy for patients with metastatic malignancies was hypothesized, and a strategy using a patient-derived tumor tissue xenograft model to realize this idea is also proposed in this article.
Ovarian cancers encompass a group of neoplasms originating from germinal tissues and exhibiting distinct clinical, pathological, and molecular features. Among these, epithelial ovarian cancers (EOCs) are the most prevalent, comprising five distinct tumor histotypes. Notably, high-grade serous ovarian cancers (HGSOCs) represent the majority, accounting for over 70% of EOC cases. Due to their silent and asymptomatic behavior, HGSOCs are generally diagnosed in advanced stages with an evolved and complex genomic state, characterized by high intratumor heterogeneity (ITH) due to chromosomal instability that distinguishes HGSOCs. Histologically, these cancers exhibit significant morphological diversity both within and between tumors. The histologic patterns associated with solid, endometrioid, and transitional (SET) and classic subtypes of HGSOCs offer prognostic insights and may indicate specific molecular profiles. The evolution of HGSOC from primary to metastasis is typically characterized by clonal ITH, involving shared or divergent mutations in neoplastic sub-clones within primary and metastatic sites. Disease progression and therapy resistance are also influenced by non-clonal ITH, related to interactions with the tumor microenvironment and further genomic changes. Notably, significant alterations occur in nonmalignant cells, including cancer-associated fibroblast and immune cells, during tumor progression. This review provides an overview of the complex nature of HGSOC, encompassing its various aspects of intratumor heterogeneity, histological patterns, and its dynamic evolution during progression and therapy resistance.
Objective
A novel classification system of high-grade serous ovarian carcinoma based on gross morphology observed at pre-treatment laparoscopy was recently defined. The purpose of this study was to identify radiographic features unique to each morphologic subtype.
Methods
This retrospective study included 109 patients with high-grade serous ovarian cancer who underwent pre-operative computed tomography (CT) scanning and laparoscopic assessment of disease burden between 1 April 2013 and 5 August 2015. Gross morphologic subtype had been previously assigned by laparoscopy. Two radiologists independently reviewed CT images for each patient, categorized disease at eight anatomic sites, and assessed for radiographic characteristics of interest: large infiltrative plaques, mass-like metastases, enhancing peritoneal lining, architectural distortion, fat stranding, calcifications, and lymph node involvement. Demographic and clinical information was summarized with descriptive statistics and compared using Student's t-tests, χ² tests, or Fisher exact tests as appropriate; kappa statistics were used to assess inter-reader agreement.
Results
Certain radiographic features were found to be associated with gross morphologic subtype. Large infiltrative plaques were more common in type 1 disease (88.7% (47/53) vs 71.4% (25/35), p=0.04), while mass-like metastases were more often present in type 2 disease (48.6% (17/35) vs 22.6% (12/53), p=0.01). Additionally, radiographic presence of disease at the falciform ligament was more common in type 1 morphology (33.9% (19/56) vs 13.2% (5/38), p=0.02).
Conclusion
Morphologic subtypes of high-grade serous ovarian cancer were associated with specific CT findings, including the presence of large infiltrative plaques, mass-like metastases, and falciform ligament involvement.
A new interdisciplinary approach based on medical imaging phenotypes, gene expression patterns, and clinical parameters, referred to as radiogenomics, has recently been developed for biomarker identification and clinical risk stratification in oncology, including for the assessment of ovarian cancer. Some radiological phenotypes (implant distribution, lymphadenopathy, and texture-derived features) are related to specific genetic landscapes (BRCA, BRAF, SULF1, the Classification of Ovarian Cancer), and integrated models can improve the efficiency for predicting clinical outcomes. The establishment of databases in medical images and gene expression profile with large sample size and the improvement of artificial intelligence algorithm will further promote the application of radiogenomics in ovarian cancer.
Epithelial ovarian cancers (EOCs) are sensitive to chemotherapy but will ultimately relapse and develop drug resistance. The origin of EOC recurrence has been elusive due to intra-tumor heterogeneity. Here we performed single-cell RNA sequencing (scRNA-seq) in 13,369 cells from primary, untreated peritoneal metastasis, and relapse tumors. We used time-resolved analysis to chart the developmental sequence of cells from the metastatic tumors, then traced the earliest replanting cells back to the primary tumors. We discovered seven distinct subpopulations in primary tumors where the CYR61⁺ “stress” subpopulation was identified as the relapse-initiators. Furthermore, a subpopulation of RGS5⁺ cancer-associated fibroblasts (CAFs) was found to strongly support tumor metastasis. The combined CYR61/RGS5 expression scores significantly correlated with the relapse-free-survival of EOC patients and can be used as predictors of EOC recurrence. Our study provides insights into the mechanism of EOC recurrence and presents CYR61⁺ relapse-initiating cells as potential therapeutic targets to prevent EOC relapse.
The three most common malignancies in gynecological oncology are cervical cancer, endometrial cancer, and ovarian cancer. Studies related to treatment response and prognosis of these cancers have mainly examined magnetic resonance (MR) imaging factors, which include tumor size, diffusion-weighted image (DWI), and perfusion image, followed by positron emission tomography/computed tomography (PET/CT) and CT images. To study cervical cancer, imaging modalities and factors have been combined variously with clinical factors, and DWI and derived apparent diffusion coefficient (ADC) values playing important roles. Because endometrial cancer diagnosed at an early stage exhibits favorable overall survival, many studies have specifically examined relations with clinical factors such as stage, histology, depth of myometrial invasion, lymphovascular invasion, and lymph node (LN) metastasis. Ovarian cancer is diagnosed at a high stage with tumor spread in the abdomen and thoracic cavity. Then PET/CT is more emphasized than MRI for the evaluation of treatment response. The latest analytic methods using radiogenomics and texture analysis are also applied to evaluate cervical cancer and ovarian cancer.
Overall survival rates for women with advanced epithelial ovarian cancer (ovarian carcinoma) have remained unchanged over the past three decades, and fewer than 40% of patients remain alive at 5 years after diagnosis. High-grade serous ovarian carcinoma (HGSOC) accounts for the majority of these cases. Mortality for HGSOC has not been altered by the use of complex cytotoxic chemotherapy combinations, and the lack of progress in improving outcomes reflects its unique biology and extreme genomic complexity. Here, we review key approaches to diagnosis and stratification of HGSOC that are now needed to advance treatment options for patients. The most important clinical questions for the pathologist remain how to unequivocally classify the different histotypes of ovarian carcinoma and which additional genomic data may identify individuals with high risk of response or relapse. This section will concentrate on recent molecular insights that are likely to be highly relevant to clinical care over the next 5 years.
Purpose To evaluate interradiologist agreement on assessments of computed tomography (CT) imaging features of high-grade serous ovarian cancer (HGSOC), to assess their associations with time-to-disease progression (TTP) and HGSOC transcriptomic profiles (Classification of Ovarian Cancer [CLOVAR]), and to develop an imaging-based risk score system to predict TTP and CLOVAR profiles. Materials and Methods This study was a multireader, multi-institutional, institutional review board-approved, HIPAA-compliant retrospective analysis of 92 patients with HGSOC (median age, 61 years) with abdominopelvic CT before primary cytoreductive surgery available through the Cancer Imaging Archive. Eight radiologists from the Cancer Genome Atlas Ovarian Cancer Imaging Research Group developed and independently recorded the following CT features: characteristics of primary ovarian mass(es), presence of definable mesenteric implants and infiltration, presence of other implants, presence and distribution of peritoneal spread, presence and size of pleural effusions and ascites, lymphadenopathy, and distant metastases. Interobserver agreement for CT features was assessed, as were univariate and multivariate associations with TTP and CLOVAR mesenchymal profile (worst prognosis). Results Interobserver agreement for some features was strong (eg, α = .78 for pleural effusion and ascites) but was lower for others (eg, α = .08 for intraparenchymal splenic metastases). Presence of peritoneal disease in the right upper quadrant (P = .0003), supradiaphragmatic lymphadenopathy (P = .0004), more peritoneal disease sites (P = .0006), and nonvisualization of a discrete ovarian mass (P = .0037) were associated with shorter TTP. More peritoneal disease sites (P = .0025) and presence of pouch of Douglas implants (P = .0045) were associated with CLOVAR mesenchymal profile. Combinations of imaging features contained predictive signal for TTP (concordance index = 0.658; P = .0006) and CLOVAR profile (mean squared deviation = 1.776; P = .0043). Conclusion These results provide some evidence of the clinical and biologic validity of these image features. Interobserver agreement is strong for some features, but could be improved for others. (©) RSNA, 2017 Online supplemental material is available for this article.
Ovarian cancer is the most deadly of gynecological malignancies. Lineage analyses have suggested broadly classifying ovarian cancers into two types: Type I, which includes low grade cancers with intact TP53, and Type II, which comprises high grade cancers with defective TP53. If detected in early stages, surgical resection of ovarian tumors results in a high rate of long-term survival; however, most ovarian cancers are detected at advanced stages. The standard first line treatment for advanced stage ovarian cancer is maximal surgical cytoreduction followed by platinum-based combination chemotherapy. Although the overall prognosis for less aggressive Type I ovarian cancers is better, their response to chemotherapy is generally weaker than that of the Type II ovarian cancers. Despite an initially favorable response of optimally debulked Type II ovarian cancers to platinum-based chemotherapy, the rate of recurrence is high, making the long-term survival rate quite poor. The dynamics of the response of high grade ovarian cancers platinum suggest that the tumors are phenotypically heterogeneous, and that a subpopulation of tumor cells is relatively resistant to chemotherapy. The resistant tumor cell population persists after chemotherapy in a state of dormancy, with recurrent tumors arising upon transformation of the dormant cells back to malignant growth. This chapter will consider how lineage, histological subtype, and grade influence the differential responses of ovarian cancers to platinum-based chemotherapy. In addition, mechanisms contributing ovarian cancer resistance to platinum drugs and to tumor cell entry into and exit from dormancy will be discussed.
Recent advances in high-throughput genomic technologies have deepened our understanding of the molecular underpinnings and cell of origin of gynecologic malignancies. Genomic studies of uterine and ovarian cancers have the potential to refine the current classification of these most common gynecologic malignancies and promise the identification of novel prognostic parameters and novel therapeutic targets. Molecular genomic advances could finally alter the so far dismal outcome of patients with advanced epithelial ovarian carcinomas. This chapter reviews key approaches to diagnosis and stratification of epithelial ovarian carcinomas that are now needed to advance the field.
Introduction: Epithelial ovarian cancer is recognized to be heterogeneous but is currently treated with a single treatment strategy. Successful patient stratification of emerging chemotherapy agents is dependent upon the availability of reliable biomarkers indicative of the entire tumor.
Aim: The aim of this study was to evaluate intertumor and intratumor heterogeneity within a series of epithelial ovarian cancer using homologous recombination (HR) DNA repair status.
Methods: Primary cultures generated from ascites and solid tumor from multiple intra-abdominal sites were characterized by their morphology and expression of protein markers. Results were compared with Formalin fixed paraffin embedded tissue pathology.
Homologous recombination function was determined by quantification of nuclear Rad51 foci. Growth inhibition (sulforhodamine B) assays were used to calculate the GI50 for cisplatin and rucaparib.
Results: Ascites with matched solid tumor were cultured from 25 patients.
Concordance in functional HR status between ascites and solid tumor subcultures was seen in only 13 (52%) of 25 patients. Heterogeneity in HR status was seen even in patients with homogeneous histological subtype. Homologous recombination defective cultures were significantly more sensitive to cisplatin and rucaparib.
Additionally, intertumor and intratumor heterogeneity was seen between the expression of epithelial and ovarian markers (EpCAM, cytokeratin, CA125, MOC-31, and vimentin). There was no relationship between heterogeneity of HR functional status and antigen expression.
Conclusions: Intertumor and intratumor functional HR heterogeneity exists that cannot be detected using histological classification. This has implications for biomarker-directed treatment.
The population of cells that make up a cancer are manifestly heterogeneous at the genetic, epigenetic, and phenotypic levels. In this mini-review, we summarise the extent of intra-tumour heterogeneity (ITH) across human malignancies, review the mechanisms that are responsible for generating and maintaining ITH, and discuss the ramifications and opportunities that ITH presents for cancer prognostication and treatment.
Advances in the identification of genes and proteins that are connected to human disease have resulted in an enormously increased need for validation studies including large sets of clinically well-defined tissue samples in order to translate basic molecular findings into clinically useful applications. The tissue microarray (TMA) technology combines hundreds of minute tissue samples on a single microscopic slide and overcomes the bottleneck of traditional large section tissue analysis. The array format facilitates linking of pathological and clinical data to the molecular results obtained from TMA studies. Consequently, tissue microarrays have become a standard tool for modern high-throughput tissue analysis. Current techniques and applications of the TMA technology in cancer research are discussed. © 2012 Springer-Verlag Berlin Heidelberg. All rights are reserved.
In cancer research and personalized medicine, new tissue culture models are needed to better predict the response of patients to therapies. With a concern for the small volume of tissue typically obtained through a biopsy, we describe a method to reproducibly section live tumor tissue to submillimeter sizes. These micro-dissected tissues (MDTs) share with spheroids the advantages of being easily manipulated on-chip and kept alive for periods extending over one week, while being biologically relevant for numerous assays. At dimensions below ~420 μm in diameter, as suggested by a simple metabolite transport model and confirmed experimentally, continuous perfusion is not required to keep samples alive, considerably simplifying the technical challenges. For the long-term culture of MDTs, we describe a simple microfluidic platform that can reliably trap samples in a low shear stress environment. We report the analysis of MDT viability for eight different types of tissues (four mouse xenografts derived from human cancer cell lines, three from ovarian and prostate cancer patients, and one from a patient with benign prostatic hyperplasia) analyzed by both confocal microscopy and flow cytometry over an 8-day incubation period. Finally, we provide a proof of principle for chemosensitivity testing of human tissue from a cancer patient performed using the described MDT chip method. This technology has the potential to improve treatment success rates by identifying potential responders earlier during the course of treatment and providing opportunities for direct drug testing on patient tissues in early drug development stages.
The study of phenotypic and genetic intratumor heterogeneity in glioblastoma is attracting a lot of attention. Recent studies have demonstrated that transcriptional profiling analysis can help interpret the complexity of this disease. Previously proposed molecular classifiers have been recently challenged due to the unexpected degree of intratumor heterogeneity that has been described spatially and at single-cell level. Different computational methods have been employed to analyze this huge amount of data, but new experimental designs including multisampling from individual patients and single-cell experiments require new specific approaches. In light of these results, there is hope that integration of genetic, phenotypic and transcriptional data coupled with functional experiments might help define new therapeutic strategies and classify patients according to key pathways and molecular targets that can be further investigated to develop personalized and combinatorial treatment strategies.
Cytoreductive surgery is the cornerstone of ovarian cancer (OVCA) treatment. Detractors of initial maximal surgical effort argue that aggressive tumor biology will dictate survival, not the surgical effort. We investigated the role of biology in achieving optimal cytoreduction in serous OVCA using microarray gene expression analysis.
For the initial model, we used a gene expression signature from a microarray expression analysis of 124 women with serous OVCA, defining optimal cytoreduction as removal of all disease greater than 1 cm (with 64 women having optimal and 60 suboptimal cytoreduction). We then applied this model to 2 independent data sets: the Australian Ovarian Cancer Study (AOCS; 190 samples) and The Cancer Genome Atlas (TCGA; 468 samples). We performed a second analysis, defining optimal cytoreduction as removal of all disease to microscopic residual, using data from AOCS to create the gene signature and validating results in TCGA data set.
Of the 12,718 genes included in the initial analysis, 58 predicted accuracy of cytoreductive surgery 69% of the time (P = 0.005). The performance of this classifier, measured by the area under the receiver operating characteristic curve, was 73%. When applied to TCGA and AOCS, accuracy was 56% (P = 0.16) and 62% (P = 0.01), respectively, with performance at 57% and 65%, respectively. In the second analysis, 220 genes predicted accuracy of cytoreductive surgery in the AOCS set 74% of the time, with performance of 73%. When these results were validated in TCGA set, accuracy was 57% (P = 0.31) and performance was at 62%.
Gene expression data, used as a proxy of tumor biology, do not predict accurately nor consistently the ability to perform optimal cytoreductive surgery. Other factors, including surgical effort, may also explain part of the model. Additional studies integrating more biological and clinical data may improve the prediction model.
Loss of heterozygosity (LOH) affects a number of chromosome regions in ovarian cancer, pointing to the possible involvement of tumour‐suppressor genes in ovarian tumorigenesis. We performed comparative analysis of allelic loss at 6 frequently affected chromosome regions in a panel of 53 benign, borderline and malignant ovarian tumours. Precursor lesions could provide evidence that an accumulation of genetic events is required for normal ovarian epithelium to generate malignant tumours. LOH on chromosome 1p was relatively common in benign, borderline and malignant tumours, while at 11p and 7q it was observed not only in invasive but also in borderline tumours. Moreover, 17q and 18q were affected mainly in advanced malignant tumours and revealed a high frequency of clonal intratumoral heterogeneity. We encountered different spectra of genetic alterations in primary tumours and their metastasis, which may be the results of intratumoral heterogeneity leading to dissemination in only some sub‐clones. Int. J. Cancer 82:822–826, 1999. © 1999 Wiley‐Liss, Inc.
Understanding of the nature of tumor heterogeneity has undergone change in the last 5 years. From early attempts to demonstrate tumor subpopulations, we have progressed to studying their biological significance. It is clear that our first ideas about tumor heterogeneity were too simple. As isolation of tumor subpopulations became more routine, the phenotypic differences between them have come to seem less important. We began as tumor taxonomists seeking to classify the characteristics and origin of different neoplastic populations and now are developmental biologists studying their ontogeny, structure, interactions, and collective behavior. In this maturing view, a particular isolated tumor subpopulation is unimportant except as a reminder of the diversity of the cell society from which it came. Recognition of tumor heterogeneity is essential to any theory of neoplastic development, as well as to experimental design and clinical treatment. Tumor societies are highly adapted for survival. They survive natural and artificial (therapeutic) selection through heterogeneity by producing new variants to 'outflank' it and by utilizing subpopulation interactions to counteract its destructive influence. Goldie and Coldman have analyzed the therapeutic implications of variant production, showing that early and combined therapy is required to defeat its protective effects. Cellular interaction also offers opportunity for intervention. Having recognized their complexity, we must now learn to annihilate tumor societies.
Detection of loss of heterozygosity (LOH) and DNA flow cytometry (FCM) were used to trace the origin of bilateral ovarian cancer from 16 patients. From each tumour the DNA index (DI) and LOH patterns for chromosomes 1, 3, 6, 11, 17, 18, 22 and X were determined with 36 microsatellite markers. Formalin-fixed, paraffin-embedded as well as frozen specimens were used. Flow cytometric cell sorting was used to enrich tumour cells for polymerase chain reaction (PCR)-driven LOH analysis. Analysis of the LOH data showed that in 12 of the 16 cases concordance was observed for all informative markers, namely retention of heterozygosity (ROH) or loss of identical alleles in both tumour samples. In four cases discordant LOH patterns were observed. In two cases the discordant LOH was found for one of the chromosomes tested while other LOH patterns clearly indicated a unifocal origin. This suggests limited clonal divergence. In the other two cases all LOH patterns were discordant, most likely indicating an independent origin. The number of chromosomes showing LOH ranged from 0 to 6. Comparison of DNA FCM and the LOH data showed that the latter technique has a higher sensitivity for the detection of a unifocal origin. In 14/16 cases evidence was found for a unifocal origin, while in two cases clonal divergence was found at LOH level and in two other cases clonal divergence at DNA ploidy level. In 12 cases the complete observed allelotype had developed before the formation of metastases, including the two cases showing a large DNA ploidy difference.
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Loss of heterozygosity (LOH) and replication error (RER) are important phenomena in tumor development, with diagnostic and prognostic relevance. Therefore, screening for LOH and RER is a desirable first step in the molecular analysis of tumors. We used semiautomated procedures based on multicolor fluorescently labeled microsatellite markers and an automated sequencer for PCR amplification, electrophoresis of PCR products, and allele detection with a set of 16 microsatellites in 56 colorectal tumors. We improved existing software for computer-assisted assessment of LOH and RER. A comparison of these results with those of a conventional, radioactive technique and visual interpretation shows a high degree of correlation between the two methods. The detection rates of LOH and RER are similar to those reported previously. The main advantages of the semiautomated fluorescence-based typing are in the objective, observer-unrelated, easy, and rapid computer-based scoring, and the resulting quantitative assessment of RER.
No abstract available.
Epithelial ovarian cancer is the leading cause of death from gynecologic cancer, in part because of the lack of effective early detection methods. Although alterations of several genes, such as c-erb-B2, c-myc, and p53, have been identified in a significant fraction of ovarian cancers, none of these mutations are diagnostic of malignancy or predictive of tumor behavior over time. Here, we used oligonucleotide microarrays with probe sets complementary to >6,000 human genes to identify genes whose expression correlated with epithelial ovarian cancer. We extended current microarray technology by simultaneously hybridizing ovarian RNA samples in a highly parallel manner to a single glass wafer containing 49 individual oligonucleotide arrays separated by gaskets within a custom-built chamber (termed "array-of-arrays"). Hierarchical clustering of the expression data revealed distinct groups of samples. Normal tissues were readily distinguished from tumor tissues, and tumors could be further subdivided into major groupings that correlated both to histological and clinical observations, as well as cell type-specific gene expression. A metric was devised to identify genes whose expression could be considered ideal for molecular determination of epithelial ovarian malignancies. The list of genes generated by this method was highly enriched for known markers of several epithelial malignancies, including ovarian cancer. This study demonstrates the rapidity with which large amounts of expression data can be generated. The results highlight important molecular features of human ovarian cancer and identify new genes as candidate molecular markers.
Multiple endocrine neoplasia type 1 (MEN1) is an inherited syndrome with multiple tumors of the endocrine pancreas, the parathyroid, the pituitary, and other tissues. The MEN1 gene at 11q13 is homozygously mutated in the majority of MEN1 tumors. Here we present a genome-wide loss of heterozygosity (LOH) screening of 23 pancreatic lesions, one duodenal tumor, and one thymic carcinoid from 13 MEN1 patients. Multiple allelic deletions were found. Fractional allelic loss varied from 6-75%, mean 31%. All pancreatic tumors displayed LOH on chromosome 11, whereas the frequency of losses for chromosomes 3, 6, 8, 10, 18, and 21 was over 30%. Different lesions from individual patients had discrepant patterns of LOH. Intratumoral heterogeneity was revealed, with chromosome 6 and 11 deletions in most tumor cells, whereas other chromosomal loci were deleted in portions of the analyzed tumor. Chromosome 6 deletions were mainly found in lesions from patients with malignant features. Fractional allelic loss did not correlate to malignancy or to tumor size. Our findings indicate that MEN1 pancreatic tumors fail to maintain DNA integrity and demonstrate signs of chromosomal instability.
A better understanding of the molecular circuitry in normal ovarian tissues and in ovarian cancer will likely provide new targets for diagnosis and therapy. Recently, much has been learned about the genes expressed in ovarian cancer through studies with cDNA arrays and serial analysis of gene expression. However, these methods do not allow highly quantitative analysis of gene expression on a large number of specimens. Here, we have used quantitative real-time RT-PCR in a panel of 39 microdissected ovarian carcinomas of various subtypes to systematically analyze the expression of 13 genes, many of which were previously identified as up-regulated in a subset of ovarian cancers by serial analyses of gene expression. The genes analyzed are glutathione peroxidase 3 (GPX3), apolipoprotein J/clusterin, insulin-like growth factor-binding protein 2, epithelial cell adhesion molecule/GA733-2, Kop protease inhibitor, matrix gla protein, tissue inhibitor of metalloproteinase 3, folate receptor 1, S100A2, signal transducer and activator of transcription 1, secretory leukocyte protease inhibitor, apolipoprotein E, and ceruloplasmin. All of the genes were found overexpressed, some at extremely high levels, in the vast majority of ovarian carcinomas irrespective of the subtype. Interestingly, GPX3 was found at much higher levels in tumors with clear cell histology and may represent a biomarker for this subtype. Some of the genes studied here may thus represent targets for early detection ovarian cancer. The gene expression patterns were not associated with age at diagnosis, stage, or K-ras mutation status in ovarian cancer. We find that several genes are coordinately regulated in ovarian cancer, likely representing the fact that many genes are activated as part of common signaling pathways or that extensive cross-talk exists between several pathways in ovarian cancer. A statistical analysis shows that genes commonly up-regulated in ovarian cancer may result from the aberrant activation of a limited number of pathways, providing promising targets for novel therapeutic strategies.
Tumour heterogeneity and clonal evolution at the genetic level may explain the development of malignant or resistant disease during clinical progression of neuroblastoma (NB). In this report we use 1p allelic analysis and DNA ploidy to evaluate clonal heterogeneity and clonal selection in vivo. We studied a total of 69 tumours from 29 patients with NB. To evaluate tumour heterogeneity and clonal evolution in vivo we used a panel of polymorphic allelic markers mapping to chromosome 1. 33 tumours from 12 patients (group 1) were obtained from different sites during the same surgery or at sequential surgeries without intervening chemotherapy to evaluate genetic heterogeneity. Paired samples from 10 patients (group 2) were used to evaluate clonal selection before and after chemotherapy. In 6 cases paired tumours and derived cell lines were studied. Analysis of DNA ploidy changes by karyotype, FISH and flow cytometry was performed in 15 tumours from 6 multiply recurred local-regional (LR) NB patients. Allelotype study revealed that 66% (8/12) of group 1 samples were heterogeneous, with distinct allelic patterns in tumour samples separated by time or location. In group 2 allelic patterns were different in post-chemotherapy specimens in 60% (6/10). DNA ploidy analysis showed that pre-chemotherapy samples contained 2 distinct ploidy clones, one diploid and one triploid, whereas all post-chemotherapy tumor samples were 100% diploid. These findings suggest that NB exhibits a high degree of clonal heterogeneity and clonal evolution occurs during the course of therapy and clinical progression.
In the United States, ovarian cancer is the fourth most common cause of cancer-related deaths among women. The most important prognostic factor for this cancer is tumor stage, or extent of disease at diagnosis. Although women with low-stage tumors have a relatively good prognosis, most women diagnosed with late-stage disease eventually succumb to their cancer. In an attempt to understand early events in ovarian carcinogenesis, and to explore steps in its progression, we have applied multiple molecular genetic techniques to the analysis of 21 early-stage (stage I/II) and 17 advanced-stage (stage III/IV) ovarian tumors. These techniques included expression profiling with cDNA microarrays containing approximately 18,000 expressed sequences, and comparative genomic hybridization to address the chromosomal locations of copy number gains as well as losses. Results from the analysis indicate that early-stage ovarian cancers exhibit profound alterations in gene expression, many of which are similar to those identified in late-stage tumors. However, differences observed at the genomic level suggest differences between the early- and late-stage tumors and provide support for a progression model for ovarian cancer development.
Classification of human tumors according to their primary anatomical site of origin is fundamental for the optimal treatment of patients with cancer. Here we describe the use of large-scale RNA profiling and supervised machine learning algorithms to construct a first-generation molecular classification scheme for carcinomas of the prostate, breast, lung, ovary, colorectum, kidney, liver, pancreas, bladder/ureter, and gastroesophagus, which collectively account for approximately 70% of all cancer-related deaths in the United States. The classification scheme was based on identifying gene subsets whose expression typifies each cancer class, and we quantified the extent to which these genes are characteristic of a specific tumor type by accurately and confidently predicting the anatomical site of tumor origin for 90% of 175 carcinomas, including 9 of 12 metastatic lesions. The predictor gene subsets include those whose expression is typical of specific types of normal epithelial differentiation, as well as other genes whose expression is elevated in cancer. This study demonstrates the feasibility of predicting the tissue origin of a carcinoma in the context of multiple cancer classes.
To identify novel tumor suppressor genes involved in ovarian carcinogenesis, we generated four down-regulated suppression subtraction cDNA libraries from two early-stage (stage I/II) and two late-stage (stage III) primary ovarian tumors, each subtracted against cDNAs derived from normal ovarian epithelial cell brushings. Approximately 600-700 distinct clones were sequenced from each library. Comparison of down-regulated clones obtained from early- and late-stage tumors revealed genes that were unique to each library which suggested tumor-specific differences. We found 45 down-regulated genes that were common in all four libraries. We also identified several genes, the role of which in tumor development has yet to be elucidated, in addition to several under expressed genes, the potential role of which in carcinogenesis has been described previously (Bagnoli et al., Oncogene, 19: 4754-4763, 2000; Yu et al., Proc. Natl. Acad. Sci. USA, 96: 214-219, 1999; Mok et al., Oncogene, 12: 1895-1901, 1996). The differential expression of a subset of these genes was confirmed by semiquantitative reverse transcription-PCR using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as control in a panel of 15 stage I and 15 stage III tumors of mixed histological subtypes. Chromosomal sorting of library sequences revealed that several of the genes mapped to known regions of deletion in ovarian cancer. Loss of heterozygosity (LOH) analysis revealed multiple genomic regions with a high frequency of loss in both early- and late-stage tumors. To determine whether loss of expression of some of the genes corresponds to loss of an allele by LOH, we used a microsatellite marker for one of the novel genes on 8q and have shown that loss of expression of this novel gene correlates with loss of an allele by LOH. In conclusion, our analysis has identified down-regulated genes, which map to known as well as novel regions of deletions and may represent potential candidate tumor suppressor genes involved in ovarian cancer.
Analysis of ovarian carcinomas has shown that karyotypes are often highly abnormal and cannot be identified with certainty by conventional cytogenetic methods. In this study, 17 tumors derived from 13 patients were analyzed by a combination of spectral karyotyping (SKY), comparative genomic hybridization (CGH), and expression microarrays. Within the study group, a total of 396 chromosomal rearrangements could be identified by SKY and CGH analysis. When the distribution of aberrations was normalized with respect to relative genomic length, chromosomes 3, 8, 11, 17, and 21 had the highest frequencies. Parallel microarray expression studies of 1718 human cDNAs were used to analyze expression profiles and to determine whether correlating gene expression with chromosomal rearrangement would identify smaller subsets of differentially expressed genes. Within the entire set of samples, microarray expression analysis grouped together poorly differentiated tumors irrespective of histological subtype. For three patients, a comparison between genomic alterations and gene expression pattern was performed on samples of primary and metastatic tumors. Their common origin was demonstrated by the close relationship of both the SKY and CGH karyotypes and the observed profiles of gene expression. In agreement with the pattern of genomic imbalance observed for chromosome 3 in ovarian cancer, the relative expression profile with respect to a normal ovary exhibited a contiguous pattern of reduced expression of genes mapping to the 3p25.5-3p21.31 and increased expression of genes from 3q13.33-3q28. This study demonstrates that SKY, CGH, and microarray analysis can in combination identify significantly smaller subsets of differentially expressed genes for future studies.
Germline mutations in BRCA1 and BRCA2 are responsible for 5%-10% of epithelial ovarian cancers, but the molecular pathways affected by these mutations are unknown. We used complementary DNA (cDNA) microarrays to compare gene expression patterns in ovarian cancers associated with BRCA1 or BRCA2 mutations with gene expression patterns in sporadic epithelial ovarian cancers and to identify patterns common to both hereditary and sporadic tumors.
Tumor samples from 61 patients with pathologically confirmed epithelial ovarian adenocarcinoma with matched clinicopathologic features were studied, including 18 with BRCA1 founder mutations, 16 with BRCA2 founder mutations, and 27 without either founder mutation (termed sporadic cancers). The cDNA microarrays contained 7651 sequence-verified features. Gene expression data were analyzed with a modified two-sided F test, with P<.0001 considered statistically significant. The expression level of six genes was also studied with reverse transcription-polymerase chain reaction.
The greatest contrast in gene expression was observed between tumors with BRCA1 mutations and those with BRCA2 mutations; 110 genes showed statistically significantly different expression levels (P<.0001). This group of genes could segregate sporadic tumors into two subgroups, "BRCA1-like" and "BRCA2-like," suggesting that BRCA1-related and BRCA2-related pathways are also involved in sporadic ovarian cancers. Fifty-three genes were differentially expressed between tumors with BRCA1 mutations and sporadic tumors; six of the 53 mapped to Xp11.23 and were expressed at higher levels in tumors with BRCA1 mutations than in sporadic tumors. Compared with the immortalized ovarian surface epithelial cells used as reference, several interferon-inducible genes were overexpressed in the majority of tumors with a BRCA mutation and in sporadic tumors.
Mutations in BRCA1 and BRCA2 may lead to carcinogenesis through distinct molecular pathways that also appear to be involved in sporadic cancers. Sporadic carcinogenic pathways may result from epigenetic aberrations of BRCA1 and BRCA2 or their downstream effectors.
Metaphase comparative genomic hybridization was used to analyze the spectrum of genetic alterations in 141 epithelial ovarian cancers from BRCA1 and BRCA2 mutation carriers, individuals with familial non-BRCA1/2 epithelial ovarian cancer, and women with nonfamilial epithelial ovarian cancer. Multiple genetic alterations were identified in almost all tumors. The high frequency with which some alterations were identified suggests the location of genes that are commonly altered during ovarian tumor development. In multiple chromosome regions, there were significant differences in alteration frequency between the four tumor types suggesting that BRCA1/2 mutation status and a family history of ovarian cancer influences the somatic genetic pathway of ovarian cancer progression. These findings were supported by hierarchical cluster analysis, which identified genetic events that tend to occur together during tumorigenesis and several alterations that were specific to tumors of a particular type. In addition, some genetic alterations were strongly associated with differences in tumor differentiation and disease stage. Taken together, these data provide molecular genetic evidence to support previous findings from histopathological studies, which suggest that clinical features of ovarian and breast tumors differ with respect to BRCA1/2 mutation status and/or cancer family history.
Ovarian cancer (OC) is often asymptomatic at the initial stage. When diagnosed, up to 75% of the patients present grade III or IV tumors with metastasis in nearby organs of the abdomen. Genetic imbalance is abundant in OC, and allelic loss (AL) of specific chromosomal regions is considered an early event. To establish association between genetic markers for early diagnosis/prognosis of OC, our target was to define narrow specific regions of AL. We analyzed 65 ovarian carcinomas by using 19 microsatellite markers located in three different chromosomes. First, a 7.6-Mb region containing the estrogen receptor (ESR1) and the tumor suppressor gene LATS1 was analyzed. Several chromosomal breakpoints flanking ESR1 affecting the region harboring LATS1 were found. Second, we found chromosomal breakpoints on 13q13.1 approximately q13.3 that defined two narrow regions flanking the BRCA2 locus. Third, our ovarian tumors exhibited a very high frequency of AL on 16q and chromosomal breakpoints defining two narrow regions within 16q22.2 approximately q24.3. In this article, we report three new polymorphic microsatellite markers and strong evidence of AL of narrow well-defined regions in hot spots on 6q, 13q, and 16q in ovarian tumors.
We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A comparison of the gene expression patterns in the ovarian cancers to published data of gene expression in breast cancers revealed a large number of differentially expressed genes. We identified a group of 62 genes that correctly classified all 125 breast and ovarian cancer specimens. Among the best discriminators more highly expressed in the ovarian carcinomas were PAX8 (paired box gene 8), mesothelin, and ephrin-B1 (EFNB1). Although estrogen receptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estrogen receptor in breast cancers, including GATA-3, LIV-1, and X-box binding protein 1, did not show a similar pattern of coexpression in the ovarian cancers.
Ovarian cancer has the highest mortality rate of gynaecological cancers. This is partly due to the lack of effective screening markers. Here, we used oligonucleotide microarrays complementary to approximately 12 000 genes to establish a gene-expression microarray (GEM) profile for normal ovarian tissue, as compared to stage III ovarian serous adenocarcinoma and omental metastases from the same individuals. We found that the GEM profiles of the primary and secondary tumours from the same individuals were essentially alike, reflecting the fact that these tumours had already metastasised and acquired the metastatic phenotype. We have identified a novel biomarker, mammaglobin-2 (MGB2), which is highly expressed specific to ovarian cancer. MGB2, in combination with other putative markers identified here, could have the potential for screening.
Purpose: Epithelial ovarian cancer (EOC) is characterized by early peritoneal involvement ultimately contributing to morbidity and mortality. To study the role of the peritoneum in fostering tumor invasion, we analyzed differences between the transcriptional repertoires of peritoneal tissue lacking detectable cancer in patients with EOC versus benign gynecologic disease.
Experimental Design: Specimens were collected at laparotomy from patients with benign disease (b) or malignant (m) ovarian pathology and comprised primary ovarian tumors, paired bilateral specimens from adjacent peritoneum and attached stroma (PE), subjacent stroma (ST), peritoneal washes, ascites, and peripheral blood mononuclear cells. Specimens were immediately frozen. RNA was amplified by in vitro transcription and cohybridized with reference RNA to a custom-made 17.5k cDNA microarray.
Results: Principal component analysis and unsupervised clustering did not segregate specimens from patients with benign or malignant pathology. Class comparison identified differences between benign and malignant PE and ST specimens deemed significant by permutation test (P = 0.027 and 0.012, respectively). A two-tailed Student's t test identified 402 (bPE versus mPE) and 663 (mST versus bST) genes differentially expressed at a significance level of P2 ≤ 0.005 when all available paired samples from each patient were analyzed. The same comparison using one sample per patient reduced the pool of differentially expressed genes but retained permutation test significance for bST versus mST (P = 0.031) and borderline significance for bPE versus mPE (P = 0.056) differences.
Conclusions: The presence of EOC may foster peritoneal implantation and growth of cancer cells by inducing factors that may represent molecular targets for disease control.
The major obstacle preventing effective treatment of melanoma is the biological heterogeneity of tumor cells. This study was performed to determine clonal genetic heterogeneity within primary melanoma and the evolution of these heterogeneous sub‐clones during disease progression. DNA samples were obtained from 44 morphologically distinct areas identified within 10 primary tumors and from 15 metastases in the same patients. Loss of heterozygosity (LOH) analyses were performed using 17 microsatellite markers that mapped to chromosomes 6q, 9p, 10q and 18q, the most frequently deleted in melanoma. Of 10 primary tumors, 8 were revealed to have intratumoral genetic heterogeneity in terms of LOH of the 4 chromosome arms examined, 7 containing at least 2 different sub‐clones harboring LOH of different chromosome areas, while the remaining one tumor showed prominent intratumoral genetic heterogeneity consisting of at least 6 genetically distinct sub‐clones. LOH of 6q was detected only in a sub‐set of multiple microdissected samples in most of the primary tumors, but was most frequently detected in metastases, suggesting that loss of this chromosome arm occurred late and played an important part in metastatic progression. Comparison of LOH between sub‐clones within primary tumors and within metastases showed the divergence of metastatic clones from dominant populations within the primary tumor in 5 patients, whereas in the remaining three patients parent sub‐clones were not identified, or constituted only a minor sub‐population within the primary tumors. These results, showing considerable genetic heterogeneity in sporadic melanoma, have profound implications for the choice of future therapeutic strategies. Int. J. Cancer 85:492–497, 2000. © 2000 Wiley‐Liss, Inc.
The molecular events leading to the development and progression of ovarian carcinoma are not completely understood. We performed a large-scale survey for the identification of differentially expressed genes between ovarian carcinoma and normal ovarian tissue by using cDNA microarray analysis. We utilized 512 member human novel putative oncogene and tumor suppressor gene cDNA microarrays to study the differences in gene expression between ovarian carcinoma and normal ovarian tissues. Some differentially expressed genes have been further confirmed by immunohistochemical analysis. A total of 39 differentially expressed genes were identified, of which 16 and 23 were specifically expressed in ovarian cancer and normal ovarian tissue, respectively. The comparison of average signal of differentially expressed genes exhibited at least a twofold difference in expression. The differentially expressed genes may be related to the carcinogenesis and progression of the malignant growth. The use of cDNA microarrays allows simultaneous monitor of the expression of many genes, thereby it speeds up the identification of differentially expressed genes. It is essential for further exploration of the mechanisms of the disease.
Loss of heterozygosity (LOH) affects a number of chromosome regions in ovarian cancer, pointing to the possible involvement of tumour-suppressor genes in ovarian tumorigenesis. We performed comparative analysis of allelic loss at 6 frequently affected chromosome regions in a panel of 53 benign, borderline and malignant ovarian tumours. Precursor lesions could provide evidence that an accumulation of genetic events is required for normal ovarian epithelium to generate malignant tumours. LOH on chromosome 1p was relatively common in benign, borderline and malignant tumours, while at 11p and 7q it was observed not only in invasive but also in borderline tumours. Moreover, 17q and 18q were affected mainly in advanced malignant tumours and revealed a high frequency of clonal intratumoral heterogeneity. We encountered different spectra of genetic alterations in primary tumours and their metastasis, which may be the results of intratumoral heterogeneity leading to dissemination in only some sub-clones. Int. J. Cancer 82:822–826, 1999.
Objective: To identify gene expression patterns that characterize advanced stage serous ovarian cancers by using microarray expression analysis.
Tumor specimens from 78 epithelial ovarian cancer patients were examined for loss of heterozygosity (LOH) at 11 microsatellite markers at chromosomes 3p14.2, 6q27, 8p12, 11p15.5, 11q23.1–q24, 16q24.3, and 17p13.1, to evaluate the involvement, possible clustering, and prognostic significance of these lesions in the progression of the disease. The LOH analysis was performed on polymerase chain reaction (PCR)-amplified DNA from sections of paraffin-embedded tumor and normal tissue pairs. In addition to primary tumors, specimens of metastatic tissues were studied from 19 patients. In the combined results from primary and metastatic tumors, LOH frequencies varied between 31% (6q27) and 69% (17p13.1). Only LOH at chromosomal regions 3p14.2 (D3S1300), 11p15.5 (D11S1318), 11q23.3–q24 (D11S1340 and D11S912), 16q24.3 (D16S476 and D16S3028), and 17p13.1 (D17S938) was associated with an adverse disease course. Our results indicate that LOH at 17p13.1 occurs independently from the other chromosomal sites studied, and is an early event in ovarian tumorigenesis. The LOH at 16q24.3, 11q23.3/q24, and 11p15.5 seems to occur later. The LOH at 11p15.5 and 11q23.3 was associated with reduced cancer-specific survival time; therefore, the studied markers could be located close to genes with influence on patient survival. Of the studied chromosomal regions, the most important tumor suppressor genes involved in the evolution of ovarian cancer appear to be located on chromosomes 11, 16, and 17. The genetic heterogeneity observed in primary and metastatic specimens demonstrates that there are multiple pathways involved in the progression of ovarian cancer.
Loss of heterozygosity (LOH) affects a number of chromosome regions in ovarian cancer, pointing to the possible involvement of tumour-suppressor genes in ovarian tumorigenesis. We performed comparative analysis of allelic loss at 6 frequently affected chromosome regions in a panel of 53 benign, borderline and malignant ovarian tumours. Precursor lesions could provide evidence that an accumulation of genetic events is required for normal ovarian epithelium to generate malignant tumours. LOH on chromosome 1p was relatively common in benign, borderline and malignant tumours, while at 11p and 7q it was observed not only in invasive but also in borderline tumours. Moreover, 17q and 18q were affected mainly in advanced malignant tumours and revealed a high frequency of clonal intratumoral heterogeneity. We encountered different spectra of genetic alterations in primary tumours and their metastasis, which may be the results of intratumoral heterogeneity leading to dissemination in only some sub-clones. Int. J. Cancer 82:822–826, 1999. © 1999 Wiley-Liss, Inc.
BACKGROUNDA multiple sampling study was performed on 124 specimens of renal cell carcinomas to analyze the consistency and reliability of DNA measurements. The authors investigated intratumoral DNA heterogeneity and its role as a adverse prognostic factor for disease progression.METHODSDNA content was analyzed by flow cytometry on three different samples of the same tumor. The Cronbach α coefficient was used to assess the reliability and a Cox proportional hazards model was used to test the effect of DNA ploidy heterogeneity on time of disease progression.RESULTSThe agreement among the DNA ploidy samples was high. The number of aneuploid findings increased significantly with the number of samples analyzed. The presence of non-diploid cell populations was a significant adverse predictive value for disease progression. However, the authors were unable to demonstrate that intratumoral heterogeneity DNA content had any influence on the biological behavior of the tumor.CONCLUSIONS
Determination of DNA ploidy based on single samples may be inaccurate. Spatial variation in DNA ploidy is a feature of renal cell carcinoma; however, its biologic significance remains to be demonstrated. Cancer 1999;86:664–71. © 1999 American Cancer Society.
Comparative hybridization of cDNA arrays is a powerful tool for the measurement of differences in gene expression between two or more tissues. We optimized this technique and employed it to discover genes with potential for the diagnosis of ovarian cancer. This cancer is rarely identified in time for a good prognosis after diagnosis. An array of 21 500 unknown ovarian cDNAs was hybridized with labeled first-strand cDNA from 10 ovarian tumors and six normal tissues. One hundred and thirty-four clones are overexpressed in at least five of the 10 tumors. These cDNAs were sequenced and compared to public sequence databases. One of these, the gene HE4, was found to be expressed primarily in some ovarian cancers, and is thus a potential marker of ovarian carcinoma.
Chromosomal deletions, associated with the loss of normal function of tumour suppressor genes, have been identified in a variety of both familial and sporadic human cancers. Although the molecular pathology of ovarian cancer is not understood, several studies have reported deletions in chromosome 17 in ovarian tumours. We have used 13 restriction site polymorphic, microsatellite, and variable number tandem repeat markers to make a detailed analysis of chromosome 17 deletions in 12 benign and 19 malignant ovarian tumours. Two benign and 11 malignant tumours were informative for at least one marker on each arm of the chromosome. Loss of heterozygosity (LOH) was detected in both arms (by all informative markers) in 5 malignant tumours from four women (three with the disease at FIGO stage Ia). In a further bilateral ovarian tumour a partial LOH affecting 17q22-q25 was present in one ovary only. By contrast to a number of previous studies, none of the 19 malignant and 12 benign tumours showed ERBB2 (17q12-22) amplification. The data presented show that the loss of a whole copy of chromosome 17 is a frequent and relatively early event in the development of some ovarian cancers. This suggests the possible involvement of multiple chromosome 17 loci in the pathogenesis of ovarian cancer. Equally plausible is that the loss of a whole chromosome copy could be the product of chromosomal instabilities induced by loss of the normal allele of tumour suppressors, such as TP53, located on this chromosome.
Tumor heterogeneity can be measured by quantifying variance of nuclear characteristics by image analysis. Heterogeneity of cell nuclear features correlated with increased local progression in prostate cancer. In the present study, the influence of tumor heterogeneity on prostate-specific antigen (PSA) recurrence after radical retropubic prostatectomy was analyzed and tumor heterogeneity was compared in patients with and without neoadjuvant hormonal therapy.
Retrospectively, radical prostatectomy material of 44 patients without and 12 patients with neoadjuvant hormonal treatment with a postoperative follow-up of at least 4 years was studied. Each prostatectomy specimen was systematically embedded in paraffin, and each tumor area within the prostate was marked and analyzed by an image analysis system for 32 nuclear features comprising nuclear shape, size, DNA content, and chromatin pattern. Several clinical features were available: preoperative serum PSA, hemoglobin concentration, Karnofsky score, tumor stage, and Gleason score.
Increased tumor heterogeneity, as expressed by differences in karyometric values between tumor areas in nuclear shape and chromatin pattern within the tumor, was significantly correlated with earlier PSA recurrence rate. As compared with nonpretreated patients, hormonally pretreated specimens showed smaller and less heterogeneous tumors. In particular, chromatin pattern heterogeneity was decreased in patients who underwent preoperative hormonal treatment compared with patients who were not pretreated. However, decreased heterogeneity was accompanied by a higher percentage of aneuploid areas per tumor in the pretreated patients. Cox regression analysis showed that karyometric determination of nuclear shape heterogeneity in combination with preoperative PSA level could predict time to PSA recurrence after radical prostatectomy in patients without hormonal pretreatment.
Increase in karyometric tumor heterogeneity in nuclear shape and chromatin pattern was correlated with a shorter PSA recurrence-free interval after radical prostatectomy. Preoperative PSA and karyometric tumor heterogeneity were the best predictors of PSA recurrence in a multivariate analysis. Intratumoral heterogeneity was decreased in patients with prostate cancer who underwent neoadjuvant hormonal therapy.
To evaluate the potential cytogenetic heterogeneity in breast carcinoma, several small cell groups (each consisting of 20 to 50 cells) were investigated within paraffin sections. By laser-microdissection, three to seven cell groups were taken per case. The DNA was amplified by degenerate oligonucleotide primed PCR (DOP-PCR), and the samples were analyzed by CGH for chromosomal gains and losses. Two ductal invasive breast carcinomas, one of them with two lymphnode metastases, were investigated. To compare the results from the small samples, CGH was also performed on DNA isolated from the tumorous regions of three to five serial sections (10(7) to 10(6) cells). The aberrations observed in the microdissected tumor samples were multiple and involved up to 14 different chromosomal or subchromosomal regions. The most frequent changes were gains on chromosomes 12q (14/20) and 20q (16/20), and loss on 13q (12/20). Some aberrations have rarely been detected (e.g., loss on 2p, gain on 8q). Comparing chromosomal imbalances in primary tumors and lymph node metastases, more consistent changes were found between the primary tumor and its corresponding metastases than between both primary tumors. The laser-microdissected samples in general showed more chromosomal aberrations than DNA isolated from several tumor sections. Our CGH results were confirmed by fluorescence in situ hybridization (FISH) for the chromosomal regions of centromere 1 and 20, and 20q13. In addition, microsatellite analyses on 31 samples confirmed our CGH findings for selected chromosome regions 2p and 11q. It can be concluded that there is a distinct intratumoral heterogeneity in primary breast tumors as well as in the corresponding lymph node metastases. The combination of microdissection and CGH enabled us to detect cytogenetic aberrations from important clones which are missed when analyzing DNA extracted from large cell numbers.
We analyzed regional heterogeneity of DNA content and of proliferative capacity. DNA-diploid as well as DNA-non-diploid tumour cell populations both were found to be present in 13% of the cases. The average coefficient of variation (CV) of DI appeared to be 2%. The CV's of G1PF, LI, and SPF, were 4%, 20%, and 25%, respectively. The CV's of Ts and for Tpot appeared to be 17% and 30%, respectively. The ratio of the intratumoural variability to the intertumoural variability, was lowest for DI. Intraobserver variability was evaluated. The correlation coefficient (CC) for LI and DI was 0.99 and 0.98, respectively, and for relative movement (RM) was 0.71. We concluded that for DI of head and neck tumours both representativity and reproducibility were better when compared with those for SPF, LI, G1PF, Ts, and Tpot.
Comparative hybridization of cDNA arrays is a powerful tool for the measurement of differences in gene expression between two or more tissues. We optimized this technique and employed it to discover genes with potential for the diagnosis of ovarian cancer. This cancer is rarely identified in time for a good prognosis after diagnosis. An array of 21,500 unknown ovarian cDNAs was hybridized with labeled first-strand cDNA from 10 ovarian tumors and six normal tissues. One hundred and thirty-four clones are overexpressed in at least five of the 10 tumors. These cDNAs were sequenced and compared to public sequence databases. One of these, the gene HE4, was found to be expressed primarily in some ovarian cancers, and is thus a potential marker of ovarian carcinoma.
The major obstacle preventing effective treatment of melanoma is the biological heterogeneity of tumor cells. This study was performed to determine clonal genetic heterogeneity within primary melanoma and the evolution of these heterogeneous sub-clones during disease progression. DNA samples were obtained from 44 morphologically distinct areas identified within 10 primary tumors and from 15 metastases in the same patients. Loss of heterozygosity (LOH) analyses were performed using 17 microsatellite markers that mapped to chromosomes 6q, 9p, 10q and 18q, the most frequently deleted in melanoma. Of 10 primary tumors, 8 were revealed to have intratumoral genetic heterogeneity in terms of LOH of the 4 chromosome arms examined, 7 containing at least 2 different sub-clones harboring LOH of different chromosome areas, while the remaining one tumor showed prominent intratumoral genetic heterogeneity consisting of at least 6 genetically distinct sub-clones. LOH of 6q was detected only in a sub-set of multiple microdissected samples in most of the primary tumors, but was most frequently detected in metastases, suggesting that loss of this chromosome arm occurred late and played an important part in metastatic progression. Comparison of LOH between sub-clones within primary tumors and within metastases showed the divergence of metastatic clones from dominant populations within the primary tumor in 5 patients, whereas in the remaining three patients parent sub-clones were not identified, or constituted only a minor sub-population within the primary tumors. These results, showing considerable genetic heterogeneity in sporadic melanoma, have profound implications for the choice of future therapeutic strategies.
One of the unique features of advanced hepatocellular carcinoma (HCC) is the morphological heterogeneity in a single tumor nodule. In order to investigate the intratumoral genomic heterogeneity of HCC, we performed Restriction Landmark Genomic Scanning (RLGS), which allows genomic DNAs to be surveyed at approximately 2000 landmark sites in a single 2-dimensional gel electrophoresis.
RLGS profiles of two regions from a single HCC nodule in six patients were compared with non-tumorous liver tissue. Four HCCs consisting of moderately-differentiated cells were separated into several small parts by thin fibrous septa, but not encapsulated. DNA samples were obtained from both parts of these so-called "nodule-in-nodule" HCC. Two HCCs consisting of well-differentiated cells which did not have a definite partition appeared pathologically homogeneous, and two independent regions of the HCC were used for the analysis.
All six HCCs demonstrated different RLGS profiles (in total about 160 different spots) from the corresponding non-tumorous liver, and the number of different spots was greater in the 4 moderately-differentiated nodule-in-nodule HCCs (39-68 spots) than in the 2 well-differentiated homogeneous HCCs (6 and 3 spots). RLGS profiles of the two parts were different to each other in all 4 nodule-in-nodule HCCs. On the other hand, two other homogeneous HCCs showed the same RLGS profiles in the two regions.
Thus, intratumoral genomic heterogeneity was demonstrated in the advanced HCC samples, and the genomic alterations may relate to the progression of HCC.
The purpose of this study was to elucidate the relationship between intratumoral regional heterogeneity in DNA ploidy and chromosomal instability (CIN) in primary gastric adenocarcinomas. In 45 sporadic gastric adenocarcinomas, we measured DNA ploidy and numerical aberrations for chromosomes 7, 11, 17, and 18 by laser scanning cytometry and fluorescence in situ hybridization, respectively, in small tissue specimens taken from 2 to 6 (on the average 4) different portions of the same tumor. A total of 231 specimens including 45 normal control specimens were examined. All 98 tumor specimens with DNA aneuploidy (DNA index > or = 1.2) showed large intercellular variations in chromosome copy number, indicating CIN. In contrast, 85 tumor specimens with (near) diploidy (1.0 < or = DNA index < 1.2) exhibited much small intercellular variations in chromosome copy number as compared with aneuploid specimens (P < 0.0001). The relationship between DNA ploidy and intercellular variation in chromosome copy number was true for tumors consisting of a mixture of (near) diploid and aneuploid subpopulations. These data indicate that DNA aneuploidy is associated with CIN but that (near) diploidy is not. Intratumoral regional DNA ploidy heterogeneity was conspicuous in 33 (92%) of 36 tumors with regions of DNA aneuploidy, and all aneuploid specimens showed great intercellular variation in chromosome copy number. Diploid regions were predominant in early stage cancers (intramucosal and submucosal cancers), and five of eight early cancers contained only diploid population. In contrast, all tumors without (near) diploid regions were advanced cancers. These observations suggest that CIN is a necessary prerequisite for developing intratumoral DNA ploidy heterogeneity with DNA aneuploidy.
To identify genes involved in the development or progression of ovarian cancer, we analyzed gene expression profiles of nine ovarian tumors using a DNA microarray consisting of 9121 genes. Comparison of expression patterns between carcinomas and the corresponding normal ovarian tissues enabled us to identify 55 genes that were commonly up-regulated and 48 genes that were down-regulated in the cancer specimens. When the five serous adenocarcinomas were analyzed separately from the four mucinous adenocarcinomas, we identified 115 genes that were expressed differently between the two types of tumor. Investigation of these genes should help to disclose the molecular mechanism(s) of ovarian carcinogenesis and define molecular separation of the two most common histological types of ovarian cancer.
Tumor specimens from 78 epithelial ovarian cancer patients were examined for loss of heterozygosity (LOH) at 11 microsatellite markers at chromosomes 3p14.2, 6q27, 8p12, 11p15.5, 11q23.1-q24, 16q24.3, and 17p13.1, to evaluate the involvement, possible clustering, and prognostic significance of these lesions in the progression of the disease. The LOH analysis was performed on polymerase chain reaction (PCR)-amplified DNA from sections of paraffin-embedded tumor and normal tissue pairs. In addition to primary tumors, specimens of metastatic tissues were studied from 19 patients. In the combined results from primary and metastatic tumors, LOH frequencies varied between 31% (6q27) and 69% (17p13.1). Only LOH at chromosomal regions 3p14.2 (D3S1300), 11p15.5 (D11S1318), 11q23.3-q24 (D11S1340 and D11S912), 16q24.3 (D16S476 and D16S3028), and 17p13.1 (D17S938) was associated with an adverse disease course. Our results indicate that LOH at 17p13.1 occurs independently from the other chromosomal sites studied, and is an early event in ovarian tumorigenesis. The LOH at 16q24.3, 11q23.3/q24, and 11p15.5 seems to occur later. The LOH at 11p15.5 and 11q23.3 was associated with reduced cancer-specific survival time; therefore, the studied markers could be located close to genes with influence on patient survival. Of the studied chromosomal regions, the most important tumor suppressor genes involved in the evolution of ovarian cancer appear to be located on chromosomes 11, 16, and 17. The genetic heterogeneity observed in primary and metastatic specimens demonstrates that there are multiple pathways involved in the progression of ovarian cancer.
The majority of ovarian tumors arise from the transformation of the ovarian surface epithelial cells, a single layer of cells surrounding the ovary. To identify genes that may contribute to the malignant phenotype of ovarian cancers, cDNA representational difference analysis was used to compare expressed genes in primary cultures of normal human ovarian surface epithelium (HOSE) and ovarian tumor-derived epithelial cells from the Cedars-Sinai Ovarian Cancer (CSOC) repository. A total of 255 differentially expressed genes were identified, of which 160 and 95 were specifically expressed in HOSE and CSOC cells, respectively. Using cDNA array hybridization, the expression profiles of the genes identified by cDNA-representational difference analysis were examined in an additional 5 HOSE and 10 CSOC lines. The comparison of average signal of each gene revealed 44 HOSE-specific and 16 CSOC-specific genes that exhibited at least a 2.5-fold difference in expression. A large number of genes identified in this study encode membrane-associated or secreted proteins and, hence, may be useful as targets in the development of serum-based diagnostic markers for ovarian cancer. Very few genes associated with protein synthesis or metabolism were identified in this study, reflecting the lack of observable differences in phenotypic or growth characteristics between HOSE and CSOC cells. Northern blot analysis on a subset of these genes demonstrated comparable levels of gene expression as observed in the cDNA array hybridization.
The molecular events leading to the development and progression of serous ovarian carcinoma are not completely understood. We performed a large scale survey for the identification of differentially expressed genes in serous ovarian carcinoma by using cDNA array analysis. Differences in gene expression between serous adenocarcinoma and benign serous adenoma, and between advanced and/or moderately or poorly differentiated and local, highly differentiated serous adenocarcinoma were assessed. The most striking difference between adenocarcinoma and benign adenoma was upregulation of RHOGDI2 in the carcinomas irrespective of the clinical tumor stage. Other changes in carcinoma were upregulation of MET and Ne-dlg, and downregulation of HGFAC, desmin, and PDGFA. The most prominent differences between advanced and local adenocarcinoma were upregulation of COL3A1, CFGR, and MET in advanced carcinoma, and downregulation of HGFAC, FZD3, and BFL1 in the same tumors. In conclusion, significant differences were found in the gene expression between benign and malignant serous ovarian tumors, and between local, highly differentiated and advanced and/or moderately or poorly differentiated serous adenocarcinomas. The differentially expressed genes may be related to the carcinogenesis and progression of the malignant growth.
Molecular classification of tumors based on their gene expression profiles promises to significantly refine diagnosis and management of cancer patients. The establishment of organ-specific gene expression patterns represents a crucial first step in the clinical application of the molecular approach. Here, we report on the gene expression profiles of 154 primary adenocarcinomas of the lung, colon, and ovary. Using high-density oligonucleotide arrays with 7129 gene probe sets, comprehensive gene expression profiles of 57 lung, 51 colon, and 46 ovary adenocarcinomas were generated and subjected to principle component analysis and to a cross-validated prediction analysis using nearest neighbor classification. These statistical analyses resulted in the classification of 152 of 154 of the adenocarcinomas in an organ-specific manner and identified genes expressed in a putative tissue-specific manner for each tumor type. Furthermore, two tumors were identified, one in the colon group and another in the ovarian group, that did not conform to their respective organ-specific cohorts. Investigation of these outlier tumors by immunohistochemical profiling revealed the ovarian tumor was consistent with a metastatic adenocarcinoma of colonic origin and the colonic tumor was a pleomorphic mesenchymal tumor, probably a leiomyosarcoma, rather than an epithelial tumor. Our results demonstrate the ability of gene expression profiles to classify tumors and suggest that determination of organ-specific gene expression profiles will play a significant role in a wide variety of clinical settings, including molecular diagnosis and classification.
In 10 cases of Barrett adenocarcinoma, samples from 8 tumor areas (including superficial and deep from peripheral and central areas) and a regional lymph node metastasis were studied for amplification of c-myc, c-erbB-2, and EGFR. We analyzed loss of heterozygosity (LOH) at 3 loci (APC, MCC, and RB) and 2 anonymous microsatellite markers (D4S1652 and D18S474). We detected c-myc in variable fractions of tissue samples from 3 of 9 tumors; EGFR was amplified in 2 specimens from 1 tumor. One tumor demonstrated amplification of c-erbB-2 in all areas. LOH at the D4S1652, MCC, RB, APC, and D18S474 loci was found in 75% (3/4), 57% (4/7), 50% (4/8), 11% (1/9), and 0% (0/10) of informative cases, respectively. LOH generally was restricted to variable subpopulations of tumor cells within individual tumors. There was no obvious association of certain genetic alterations with topographically distinct tumor regions; however, superficial areas showed more frequent genetic alterations than areas from the deeply invading front. More aberrations were detected in the periphery than in the center. Barrett adenocarcinoma is characterized by marked intratumoral genetic heterogeneity, which must be considered when evaluating genetic alterations as indicators of response to therapy and prognosis.
Ovarian cancer is a major cause of cancer death in women. Unfortunately, the molecular pathways underlying ovarian cancer progression are poorly understood, making the development of novel diagnostic and therapeutic strategies difficult. On the basis of our previous observations obtained from serial analysis of gene expression, we have constructed a specialized cDNA array for the study of ovarian cancer. Small, specialized arrays have several practical advantages and can reveal information that is lost in the "noise" generated by irrelevant genes present in larger arrays. The array, which we named Ovachip, contains 516 cDNAs chosen from our serial analysis of gene expression and cDNA array studies for their relevance to ovarian cancer. The gene expression patterns revealed with the Ovachip are highly reproducible and extremely consistent among the different ovarian specimens tested. This array was extremely sensitive at differentiating ovarian cancer from colon cancer based on expression profiles. The Ovachip revealed clusters of coordinately expressed genes in ovarian cancer. One such cluster, the IGF2 cluster, is particularly striking and includes the insulin-like growth factor II, the cisplatin resistance-associated protein, the checkpoint suppressor 1, the cyclin-dependent kinase 6, and a protein tyrosine phosphatase receptor. We also identified a cluster of down-regulated genes that included the cyclin-dependent kinase 7 and cyclin H. Thus, the Ovachip allowed us to identify previously unidentified clusters of differentially expressed genes that may provide new paradigms for molecular pathways important in ovarian malignancies. Because of the relevance of the arrayed genes, the Ovachip may become a powerful tool for investigators in the field of ovarian cancer and may facilitate progress in understanding the etiology of this disease and in its clinical management.
We analysed the mRNA levels corresponding to 12,600 transcripts in primary cultures of ovarian epithelial cells derived from nine normal ovaries and 21 epithelial ovarian carcinoma. The class distinction and hierarchical clustering of expression data revealed a clear distinction in gene expression between normal and carcinoma-derived ovarian epithelial cells. Comparison of expression levels revealed 111 genes with mean expression values of >2.5-fold higher in carcinoma cells. Similarly, 62 genes were expressed at >2.5-fold higher levels in normal ovarian epithelial cells. For a few selected genes, we demonstrate that the pattern of differential expression observed in cultured epithelial cells is present in the normal ovaries and epithelial ovarian carcinoma. Use of cultured epithelial cells represents a novel strategy to study gene expression in a cell-type specific manner.
In epithelial ovarian cancer, tumor grade is an independent prognosticator whose molecular determinants remain unknown. We investigated patterns of gene expression in well- and poorly differentiated serous papillary ovarian and peritoneal carcinomas with cDNA microarrays. A 6500-feature cDNA microarray was used for comparison of the molecular profiles of eight grade III and four grade I stage III serous papillary adenocarcinomas. With a modified F-test in conjunction with random permutations, 99 genes whose expression was significantly different between grade I and grade III tumors were identified (P < 0.01). A disproportionate number of these differentially expressed genes were located on the chromosomal regions 20q13 and all exhibited higher expression in grade III tumors. Interphase fluorescent in situ hybridization demonstrated 20q13 amplification in two of the four grade III and none of the three grade I tumors available for evaluation. Several centrosome-related genes also showed higher expression in grade III tumors. We propose a model in which tumor differentiation is inversely correlated with the overexpression of several oncogenes located on 20q13, a common amplicon in ovarian and numerous other cancers. Dysregulation of centrosome function is one potential mechanistic link between genetic/epigenetic changes and the poorly differentiated phenotype in ovarian cancer.
To identify gene expression patterns that characterize advanced stage serous ovarian cancers by using microarray expression analysis.
Using genome-wide expression analysis, we compared a series of 31 advanced stage (III or IV) serous ovarian cancers from patients who survived either less than 2 years or more than 7 years with three normal ovarian epithelial samples. Array findings were validated by analysis of expression of the insulin-like growth factor binding protein 2 (IGFBP2) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) genes using quantitative real-time polymerase chain reaction (QRT-PCR).
Hierarchical clustering identified patterns of gene expression that distinguished cancer from normal ovarian epithelium. We also identified gene expression patterns that distinguish cancers on the basis of patient survival. These genes include many that are associated with immune function. Expression of IGFBP2 and TRAIL genes measured by array and QRT-PCR analysis demonstrated correlation coefficients of 0.63 and 0.78, respectively.
Global expression analysis can identify expression patterns and individual genes that contribute to ovarian cancer development and outcome. Many of the genes that determine ovarian cancer survival are associated with the immune response, suggesting that immune function influences ovarian cancer virulence. With the generation of newer arrays with more transcripts, larger studies are possible to fully characterize genetic signatures that predict survival that may ultimately be used to guide therapeutic decision-making.
Advanced-stage epithelial ovarian cancer has a poor prognosis with long-term survival in less than 30% of patients. When the disease is detected in stage I, more than 90% of patients can be cured by conventional therapy. Screening for early-stage disease with individual serum tumor markers, such as CA125, is limited by the fact that no single marker is up-regulated and shed in adequate amounts by all ovarian cancers. Consequently, use of multiple markers in combination might detect a larger fraction of early-stage ovarian cancers.
To identify potential candidates for novel markers, we have used Affymetrix human genome arrays (U95 series) to analyze differences in gene expression of 41,441 known genes and expressed sequence tags between five pools of normal ovarian surface epithelial cells (OSE) and 42 epithelial ovarian cancers of different stages, grades, and histotypes. Recursive descent partition analysis (RDPA) was performed with 102 probe sets representing 86 genes that were up-regulated at least 3-fold in epithelial ovarian cancers when compared with normal OSE. In addition, a panel of 11 genes known to encode potential tumor markers [mucin 1, transmembrane (MUC1), mucin 16 (CA125), mesothelin, WAP four-disulfide core domain 2 (HE4), kallikrein 6, kallikrein 10, matrix metalloproteinase 2, prostasin, osteopontin, tetranectin, and inhibin] were similarly analyzed.
The 3-fold up-regulated genes were examined and four genes [Notch homologue 3 (NOTCH3), E2F transcription factor 3 (E2F3), GTPase activating protein (RACGAP1), and hematological and neurological expressed 1 (HN1)] distinguished all tumor samples from normal OSE. The 3-fold up-regulated genes were analyzed using RDPA, and the combination of elevated claudin 3 (CLDN3) and elevated vascular endothelial growth factor (VEGF) distinguished the cancers from normal OSE. The 11 known markers were analyzed using RDPA, and a combination of HE4, CA125, and MUC1 expression could distinguish tumor from normal specimens. Expression at the mRNA level in the candidate markers was examined via semiquantitative reverse transcription-PCR and was found to correlate well with the array data. Immunohistochemistry was performed to identify expression of the genes at the protein level in 158 ovarian cancers of different histotypes. A combination of CLDN3, CA125, and MUC1 stained 157 (99.4%) of 158 cancers, and all of the tumors were detected with a combination of CLDN3, CA125, MUC1, and VEGF.
Our data are consistent with the possibility that a limited number of markers in combination might identify >99% of epithelial ovarian cancers despite the heterogeneity of the disease.