Article

A Comprehensive Human Gastric Cancer Organoid Biobank Captures Tumor Subtype Heterogeneity and Enables Therapeutic Screening

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Abstract

Gastric cancer displays marked molecular heterogeneity with aggressive behavior and treatment resistance. Therefore, good in vitro models that encompass unique subtypes are urgently needed for precision medicine development. Here, we have established a primary gastric cancer organoid (GCO) biobank that comprises normal, dysplastic, cancer, and lymph node metastases (n = 63) from 34 patients, including detailed whole-exome and transcriptome analysis. The cohort encompasses most known molecular subtypes (including EBV, MSI, intestinal/CIN, and diffuse/GS, with CLDN18-ARHGAP6 or CTNND1-ARHGAP26 fusions or RHOA mutations), capturing regional heterogeneity and subclonal architecture, while their morphology, transcriptome, and genomic profiles remain closely similar to in vivo tumors, even after long-term culture. Large-scale drug screening revealed sensitivity to unexpected drugs that were recently approved or in clinical trials, including Napabucasin, Abemaciclib, and the ATR inhibitor VE-822. Overall, this new GCO biobank, with linked genomic data, provides a useful resource for studying both cancer cell biology and precision cancer therapy.

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... [15][16][17] The establishments of tumour organoids have been reported for the most common types of cancers, including prostate cancer, colorectal cancer, pancreatic cancer, liver cancer, breast cancer, bladder cancer, gastric cancer, ovarian cancer and endometrial cancer. [18][19][20][21][22][23][24][25][26] Two recent studies reported the establishment of RCC organoid lines from clinical samples, but these organoid lines have not been extensively characterized. 27,28 Another study recently developed a protocol for the culture of childhood kidney cancer organoids and established the first paediatric cancer organoid biobank. ...
... Scale bar, 50 μm noggin, N-acetyl-l-cysteine, A83-01, SB202190; fibroblast growth factor (FGF) 10, epidermal growth factor (EGF) and Y-27632. 21,22,24,31 To improve the success rate of RCC organoid derivation, we tested the effect of these niche factors on the formation of RCC organoids. Each niche factor was individually omitted from the culture medium, as shown in Figure 1B. ...
... Previous reports demonstrate that tumour organoids derived from patients correlate with patients' responses. 24,47,48 Next, we will perform co-clinical trials to test whether in vitro patient-derived RCC organoids' responses recapitulate patients' responses to the corresponding treatments in vivo. ...
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Background: Kidney cancer is one of the most common solid tumors. The advancement of human kidney cancer research and treatment has been hindered by a lack of research models that faithfully recapitulate the diversity of the disease. Methods: We established an effective three-dimensional culture system for generating kidney cancer organoids from clinical renal cell carcinoma samples. Renal cell carcinoma (RCC) organoids were characterized by H&E staining, immunofluorescence, whole-exome sequencing, RNA sequencing and single-cell RNA sequencing. The use of RCC organoids in personalized cancer therapy was assessed by testing their responses to treatment drugs and chimeric antigen receptor T cells. Results: Using this organoid culture system, 33 kidney cancer organoid lines from common kidney cancer subtypes, including clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (pRCC), and chromophobe renal cell carcinoma (chRCC), were generated. RCC organoids preserved the histological architectures, mutational landscapes, and transcriptional profile of the parental tumor tissues. Single-cell RNA-sequencing revealed inter- and intra-tumoral heterogeneity in RCC organoids. RCC organoids allowed for in vitro drug screening and provided a tool for assessing the efficacy of chimeric antigen receptor T cells. Conclusions: Patient-derived RCC organoids are valuable pre-clinical models for academic research and personalized medicine.
... Although spherical cancer models are useful, they fail to fully recapitulate the real conditions of a tumor in a living organism; thus, organoids have arisen as a promising near-physiological model in cancer research due to their potential to represent the tumor microenvironment at the level of individual patients, which makes this technology a great tool in the personalized medicine approach. Cancer organoids or tumoroids have been successfully established from both ASCs and PSCs, including for the prostate [164], breast [165,166], pancreas [167][168][169], liver [170,171], ovary [172], esophagus [173,174], colon [82,175], stomach [176] and fallopian tubes [177]. ...
... Intratumor heterogeneity is represented by tumor cells that harbor single unstable genomes that might contribute to therapy resistance and cancer progression [34]. Patient-derived organoids (PDOs) from different regions of the same tumor retain the heterogeneous genetic composition [166,173,176]; however, they need to be characterized in-depth before experimental procedures due to the possible different sensitivities of tumor subclones to the same treatment and the acquisition of novel mutational signatures over time. Surprisingly, tumor organoid growth does not surpass that of normal organoids; consequently, epithelial cells from the remaining healthy tissue of a biopsy can overgrow tumoral cells. ...
... Huang et al. established the conditions to generate primary human PDAC tumor organoid growth with matching of greater than 80% of the characteristics of the original tumors and identified changes in SOX9 location related to mutant TP53 expression in tumor organoids and differences in EZH2 among patients, which was frequently upregulated in patients with pancreatic cancer [169]. Regarding stomach cancer, Yan et al. established a gastric cancer organoid biobank containing 7 normal and 46 gastric cancer organoid lines from different tumor regions and lymph node metastasis samples from 34 patients, with detailed wholeexome and transcriptome analyses [176]. Organoids were cocultured along with stromal cells to more closely resemble the tumor microenvironment. ...
Article
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In nature, cells reside in tissues subject to complex cell–cell interactions, signals from extracellular molecules and niche soluble and mechanical signaling. These microenvironment interactions are responsible for cellular phenotypes and functions, especially in normal settings. However, in 2D cultures, where interactions are limited to the horizontal plane, cells are exposed uniformly to factors or drugs; therefore, this model does not reconstitute the interactions of a natural microenvironment. 3D culture systems more closely resemble the architectural and functional properties of in vivo tissues. In these 3D cultures, the cells are exposed to different concentrations of nutrients, growth factors, oxygen or cytotoxic agents depending on their localization and communication. The 3D architecture also differentially alters the physiological, biochemical, and biomechanical properties that can affect cell growth, cell survival, differentiation and morphogenesis, cell migration and EMT properties, mechanical responses and therapy resistance. This latter point may, in part, explain the failure of current therapies and affect drug discovery research. Organoids are a promising 3D culture system between 2D cultures and in vivo models that allow the manipulation of signaling pathways and genome editing of cells in a body-like environment but lack the many disadvantages of a living system. In this review, we will focus on the role of stem cells in the establishment of organoids and the possible therapeutic applications of this model, especially in the field of cancer research.
... These PDOs can then be used for numerous downstream translational applications, such as drug screening for novel therapeutics, study of TME heterogeneity, and used in precision oncology to predict therapeutic responses. As with the PDX platform, PDOs can consistently recapitulate in vivo tumor genotypes, phenotypes, and histopathological heterogeneity [31][32][33][34][35][36][37][38][39][40], thereby providing clinically relevant tissue for ex vivo modeling. One major advantage of PDOs over the PDX platform is the shorter time needed for initial PDO growth (days to weeks rather than months), which can be critical when predicting treatment responses in patients with advanced cancers who have limited lifespans. ...
... This suggests their use as personalized platforms to measure responses against chemotherapies or targeted agents. Indeed, human organoid biobanks have been established from multiple types of cancers and subsequently utilized in high-throughput drug screens to discover novel cancer therapeutics [31,32,35,37,[42][43][44]. Additionally, a multitude of studies have attempted to correlate ex vivo PDO responses with clinical efficacy of chemotherapies or targeted agents in a variety of cancer types, including advanced colorectal [45][46][47], rectal [43,48,49], stomach [32,37,50], pancreatic [35,51,52], ovarian [53][54][55][56], esophageal [57], breast [31,52], bladder [39], liver [58], prostate [59], and mesothelioma [60]. ...
... This suggests their use as personalized platforms to measure responses against chemotherapies or targeted agents. Indeed, human organoid biobanks have been established from multiple types of cancers and subsequently utilized in high-throughput drug screens to discover novel cancer therapeutics [31,32,35,37,[42][43][44]. Additionally, a multitude of studies have attempted to correlate ex vivo PDO responses with clinical efficacy of chemotherapies or targeted agents in a variety of cancer types, including advanced colorectal [45][46][47], rectal [43,48,49], stomach [32,37,50], pancreatic [35,51,52], ovarian [53][54][55][56], esophageal [57], breast [31,52], bladder [39], liver [58], prostate [59], and mesothelioma [60]. Several recent reviews have thoroughly summarized these clinical correlation studies [41,61,62] and attempted to analyze the level of evidence supporting the use of PDOs in clinical decision-making. ...
Article
Cancer immunotherapies, particularly immune checkpoint inhibitors, are rapidly becoming standard-of-care for many cancers. The ascendance of immune checkpoint inhibitor treatment and limitations in the accurate prediction of clinical response thereof have provided significant impetus to develop preclinical models that can guide therapeutic intervention. Traditional organoid culture methods that exclusively grow tumor epithelium as patient-derived organoids are under investigation as a personalized platform for drug discovery and for predicting clinical efficacy of chemotherapies and targeted agents. Recently, the patient-derived tumor organoid platform has evolved to contain more complex stromal and immune compartments needed to assess immunotherapeutic efficacy. We review the different methodologies for developing a more holistic patient-derived tumor organoid platform and for modeling the native immune tumor microenvironment.
... The ordinary organoid culture, in which dissociated cells and sticky ECM hydrogel are mixed and dispensed and a culture medium is added, is more difficult and time-consuming than the culture of 2D monolayer cells. The liquid handling robotic systems can culture large amounts of PDCO with smaller efforts and can minimize inter-and intra-personal variability, enabling drug screening with high reproducibility [66][67][68]. Furthermore, large-scale drug response data analysis can be automated by measuring image data, such as changes in the organoid size or morphologic characteristics of PDCO after drug treatment [69][70][71]. ...
... The factors determining the success rate of PDCO culture have not yet been fully elucidated. Tumor cellularity of the resected primary tumor tissue, culture medium composition, normal epithelial cell contamination, and limited tumor microenvironments have been suggested as causes [68,90,98,99]. ...
Article
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The cancer burden is rapidly increasing in most countries, and thus, new anticancer drugs for effective cancer therapy must be developed. Cancer model systems that recapitulate the biological processes of human cancers are one of the cores of the drug development process. PDCO has emerged as a unique model that preserves the genetic, physiological, and histologic characteristics of original cancer, including inter- and intratumoral heterogeneities. Due to these advantages, the PCDO model is increasingly investigated for anticancer drug screening and efficacy testing, preclinical patient stratification, and precision medicine for selecting the most effective anticancer therapy for patients. Here, we review the prospects and limitations of PDCO compared to the conventional cancer models. With advances in culture success rates, co-culture systems with the tumor microenvironment, organoid-on-a-chip technology, and automation technology, PDCO will become the most promising model to develop anticancer drugs and precision medicine.
... Gastric cancer is a common malignancy worldwide with marked molecular heterogeneity and is the second leading cause of cancer-related deaths [65,66]. Many studies have reported the successful generation of GCOs [12,26,[67][68][69][70][71][72][73][74][75][76][77][78][79][80]. Seidlitz T documented the feasibility of establishing a gastric cancer organoid biobank from human gastric or esophagogastric adenocarcinoma and mouse gastric cancer tissues [26]. ...
... In addition, a mutational spectrum was revealed among these tumoroids using whole-genome sequencing that was consistent with the previously reported genomic stable (GS) subtype, microsatellite instable (MSI) subtype, and chromosomal instable (CIN) subtype of gastric cancer [26]. In another study, gastric tumoroids, including the subtypes of EBV, MSI, CIN, and GS, as well as CLDN18-ARHGAP6 or CTNND1-ARHGAP26 fusions or mutations in RHOA, also faithfully recapitulated architectural and regional heterogeneity, as well as the morphology and transcriptomic and genomic profiles, even after long-term culture [68]. ...
Article
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Cancer is a top-ranked life-threatening disease with intratumor heterogeneity. Tumor heterogeneity is associated with metastasis, relapse, and therapy resistance. These factors contribute to treatment failure and an unfavorable prognosis. Personalized tumor models faithfully capturing the tumor heterogeneity of individual patients are urgently needed for precision medicine. Advances in stem cell culture have given rise to powerful organoid technology for the generation of in vitro three-dimensional tissues that have been shown to more accurately recapitulate the structures, specific functions, molecular characteristics, genomic alterations, expression profiles, and tumor microenvironment of primary tumors. Tumoroids in vitro serve as an important component of the pipeline for the discovery of potential therapeutic targets and the identification of novel compounds. In this review, we will summarize recent advances in tumoroid cultures as an excellent tool for accurate cancer modeling. Additionally, vascularization and immune microenvironment modeling based on organoid technology will also be described. Furthermore, we will summarize the great potential of tumor organoids in predicting the therapeutic response, investigating resistance-related mechanisms, optimizing treatment strategies, and exploring potential therapies. In addition, the bottlenecks and challenges of current tumoroids will also be discussed in this review.
... Organoid isolation from human primary tumors and metastases 5,8 has enabled the establishment of living biobanks 6,7,9 . Notably, patient-derived organoids have been shown to represent their origin's molecular features and morphology [6][7][8]10 , enabling functional experiments such as drug testing ex vivo 7,9,[11][12][13][14][15][16] . As a consequence, organoids are an attractive model system, as they combine the modeling capacity of patient-derived xenografts with the scalability of adherent in vitro cell lines. ...
... Tumor organoids are still far away from being a predictive tool for clinical decision making, as recent clinical studies have failed to show a clear benefit of organoid-based treatment allocation or consistant predictive value 16,45,46 . However, previous studies have successfully used patient-derived organoids to perform small-and medium-scale drug testing using ATP based cell viability readouts and have described clinically relevant predictive molecular features 7,[9][10][11][12][13][14][15][47][48][49] . Additionally, imaging studies with organoids have been used to characterize developmental processes such as the self-organization of intestinal cells 25,50 or the morphological response to individual drugs 24,51 . ...
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Patient-derived organoids resemble the biology of tissues and tumors, enabling ex vivo modeling of human diseases. They have heterogeneous morphologies with unclear biological causes and relationship to treatment response. Here, we use high-throughput, image-based profiling to quantify phenotypes of over 5 million individual colorectal cancer organoids after treatment with >500 small molecules. Integration of data using multi-omics modeling identifies axes of morphological variation across organoids: Organoid size is linked to IGF1 receptor signaling, and cystic vs. solid organoid architecture is associated with LGR5 + stemness. Treatment-induced organoid morphology reflects organoid viability, drug mechanism of action, and is biologically interpretable. Inhibition of MEK leads to cystic reorganization of organoids and increases expression of LGR5, while inhibition of mTOR induces IGF1 receptor signaling. In conclusion, we identify shared axes of variation for colorectal cancer organoid morphology, their underlying biological mechanisms, and pharmacological interventions with the ability to move organoids along them. The heterogeneity underlying cancer organoid phenotypes is not yet well understood. Here, the authors develop an imaging analysis assay for high throughput phenotypic screening of colorectal organoids that allows to define specific morphological changes that occur following different drug treatments.
... In addition, Nanki et al. 178 generated a biobank consisting of 37 patientderived organoid lines, including rare genome-stable tumors. Furthermore, Yan et al. 179 established a large and unique biobank, covering nearly all molecular subtypes and subtype-specific mutational profiles, including organoids carrying EBV, RHOA mutations, CLDN18-ARHGAP6 fusion and CTNND1-ARHGAP26 fusion, all of which had been rarely described in cell lines or organoids so far. Importantly, although most newly diagnosed gastric cancer patients have advanced or metastatic disease, this biobank collected organoids from four stage I and one pre-invasive lesion, as well as from different regions of the tumor. ...
... PDOs from gastric cancer were sensitive to unexpected drugs that were recently approved or in clinical trials, including Napabucasin, Abemaciclib, and the ataxia telangiectasia and Rad3-related protein (ATR) inhibitor VE-822, indicating that gastric cancer organoids have the ability to recapitulate the similar response from clinical trials and can be used for in vitro drug screening. 179 Trastuzumab was identified to effectively treat gastric cancer organoids with abnormally amplified and mutated ERBB2, producing an accumulative therapeutic effect by combining with 5-FU treatment. 177 Lapatinib inhibited MAPK and PI3K/AKT signaling downstream of EGFR/ERBB2 in ERBB2amplified PDOs and induced apoptosis of organoids. ...
Cancer represents a leading cause of death, despite the rapid progress of cancer research, leading to urgent need for accurate preclinical model to further study of tumor mechanism and accelerate translational applications. Cancer cell lines cannot fully recapitulate tumors of different patients due to the lack of tumor complexity and specification, while the high technical difficulty, long time, and substantial cost of patient-derived xenograft model makes it unable to be used extensively for all types of tumors and large-scale drug screening. Patient-derived organoids can be established rapidly with a high success rate from many tumors, and precisely replicate the key histopathological, genetic, and phenotypic features, as well as therapeutic response of patient tumor. Therefore, they are extensively used in cancer basic research, biobanking, disease modeling and precision medicine. The combinations of cancer organoids with other advanced technologies, such as 3D bio-printing, organ-on-a-chip, and CRISPR-Cas9, contributes to the more complete replication of complex tumor microenvironment and tumorigenesis. In this review, we discuss the various methods of the establishment and the application of patient-derived organoids in diverse tumors as well as the limitations and future prospects of these models. Further advances of tumor organoids are expected to bridge the huge gap between bench and bedside and provide the unprecedented opportunities to advance cancer research.
... The development of tumor organoid culture has allowed the application of PDTOs to test and predict drug responses in the context of precision cancer treatment. Currently, tumor organoid biobanks have been established from various types of cancer, including breast (17), lung (22,23), colorectum (24)(25)(26)(27)(28), stomach (29)(30)(31), liver (32,33), pancreas (34), ovary (35,36), prostate (37), and brain (38). Although these epithelial-only PDTOs are generally available, their lack of immune and other nonimmune components of the TIME impedes immunotherapy assessment, such as checkpoint inhibition blockade and adaptive T-cell therapy. ...
Article
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Cancer immunotherapy has revolutionized the field of cancer treatment in recent years. However, not all patients receiving cancer immunotherapy exhibit durable responses, and reliable, high-throughput testing platforms are urgently needed to guide personalized cancer immunotherapy. The ability of patient-derived tumor organoids to recapitulate pivotal features of original cancer tissues makes them useful as a preclinical model for cancer research and precision medicine. Nevertheless, many challenges exist in the translation of tumor organoid research to clinical decision making. Herein we discuss the applications of patient-derived tumor organoid models and the advances and potential of using complex immune-organoid systems as testing platforms to facilitate precision cancer immunotherapy. In addition, we highlight intriguing applications of tumor organoids with novel multi-omics in preclinical cancer research, highlighting genetic editing, proteomics, and liquid biopsy.
... Moreover, altered expression among cell lines due to the extended culture in non-physiological media should be considered. For future study, organoids derived from tumor tissues might be the perfect model to investigate the different role of PYCR1 in different GC subtypes, because organoids have the same genetic characteristic as the primary tumors and stable phenotype in long-term in-vitro culture [35,36]. Taken together, the available evidence from breast cancer and our results suggested that rewiring of proline metabolism catalyzed by PYCR1 may be cancer-subtype specific. ...
Article
Background & aims Pyrroline-5-carboxylate reductase 1 (PYCR1) upregulation contributes to the progression of gastric cancer (GC) and indicates poor survival. However, PYCR1 expression profile in GC subtypes and the mechanism behind its upregulation are not well-studied. Methods PYCR1 expression profiles in GC subtypes and different stages of gastric carcinogenesis were assessed in different GC cohorts. Genetic alterations and epigenetic modulation in PYCR1 regulation were further investigated using bioinformatics analysis and in vitro experiments. Results PYCR1 expression was significantly higher in intestinal-type GC and associated molecular subtypes in TCGA and ACRG GC cohorts. During the cascade of intestinal-type GC, PYCR1 was continuously increased from normal gastric tissues through to atrophic gastritis, to intraepithelial neoplasia, and to GC. Copy number alterations in PYCR1 were associated with PYCR1 transcript expression. One CpG island was observed in PYCR1 promoter region, and the hypomethylation occurred at this region could contribute to PYCR1 transcriptional activation in GC. Besides, H3K27ac combination was found in PYCR1 promoter, and acetyltransferase p300 induced H3K27ac could promote PYCR1 expression in GC. Conclusions PYCR1 expression varies across GC subtypes, with intestinal-type GC and associated molecular subtypes having the highest expression. Hypomethylation at CpG sites and p300-induced H3K27ac modification within PYCR1 promoter could contribute to maintaining PYCR1 overexpression in GC. These results provide us with a new insight into epigenetic modulation in mitochondrial proline metabolism.
... The establishment of cancer organoids has had a significant impact on the cancer research field by providing a patient-specific three-dimensional (3D) model designed to better represent the tumour than conventional two-dimensional cell cultures [10][11][12][13][14][15][16]. However, cancer organoids only represent the epithelial compartment of the tumour, limiting their utility in several fields of cancer research, including immunotherapy. ...
Article
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Background Immunotherapy with immune checkpoint inhibitors (ICIs) is being explored to improve cholangiocarcinoma (CCA) therapy. However, it remains difficult to predict which ICI will be effective for individual patients. Therefore, the aim of this study is to develop a co-culture method with patient-derived CCA organoids and immune cells, which could represent anti-cancer immunity in vitro. Methods CCA organoids were co-cultured with peripheral blood mononuclear cells or T cells. Flow cytometry, time-lapse confocal imaging for apoptosis, and quantification of cytokeratin 19 fragment (CYFRA) release were applied to analyse organoid and immune cell behaviour. CCA organoids were also cultured in immune cell-conditioned media to analyse the effect of soluble factors. Results The co-culture system demonstrated an effective anti-tumour organoid immune response by a decrease in live organoid cells and an increase in apoptosis and CYFRA release. Interpatient heterogeneity was observed. The cytotoxic effects could be mediated by direct cell–cell contact and by release of soluble factors, although soluble factors only decreased viability in one organoid line. Conclusions In this proof-of-concept study, a novel CCA organoid and immune cell co-culture method was established. This can be the first step towards personalised immunotherapy for CCA by predicting which ICIs are most effective for individual patients.
... Recently, patient-derived organoids (PDOs), which are miniature, three-dimensional (3D), self-organized tissue culture models derived from primary patient tumor stem cells, have emerged as alternative tools [21][22][23]. PDOs closely recapitulate the genotypic, phenotypic, histological and malignant features of the corresponding primary tumors [24][25][26]. Compared with PDXs, PDOs have the advantages of rapid construction, high success rate, and Graphical Abstract high-throughput capacity [27,28], all of which may help further accelerate the process of providing guidance for the rational and individualized use of anticancer therapeutic agents. ...
Article
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Background Gastric cancer (GC) is a highly heterogeneous disease with many different histological and molecular subtypes. Due to their reduced systemic adverse effects, nanoformulation agents have attracted increasing attention for use in the treatment of GC patients in the clinic. To improve therapeutic outcomes, it is vitally necessary to provide individual medication references and guidance for use of these nanoformulations, and patient-derived organoids (PDOs) are promising models through which to achieve this goal. Results Using an improved enzymatic digestion process, we succeeded in constructing GC PDOs from surgically resected tumor tissues and endoscopic biopsies from GC patients; these PDOs closely recapitulated the histopathological and genomic features of the corresponding primary tumors. Next, we chose two representative paclitaxel (PTX) nanoformulations for comparative study and found that liposomal PTX outperformed albumin-bound PTX in killing GC PDOs at both the transcriptome and cellular levels. Our results further showed that the different distributions of liposomal PTX and albumin-bound PTX in PDOs played an essential role in the distinct mechanisms through which they kill PDOs. Finally, we constructed patient-derived xenografts model in which we verified the above distinct therapeutic outcomes via an intratumoral administration route. Conclusions This study demonstrates that GC PDOs are reliable tools for predicting nanoformulation efficacy. Graphical Abstract
... While clearly representing milestones in the field, these studies did not reveal the relationship between GC subtypes and chemotherapy. More recent molecular subtyping studies have indeed established a correlation with the clinical characteristics (26)(27)(28). For example, Oh et al. identified two subtypes based on genomic data of GC: mesenchymal phenotype (MP) and epithelial phenotype (EP), which are linked to distinct patterns of molecular alterations, disease progression, and prognosis (29). ...
Article
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Gastric cancer (GC) is one of the most common malignant tumors with a high mortality rate worldwide and lacks effective methods for prognosis prediction. Postoperative adjuvant chemotherapy is the first-line treatment for advanced gastric cancer, but only a subgroup of patients benefits from it. Here, we used 833 formalin-fixed, paraffin-embedded resected tumor samples from patients with TNM stage II/III GC and established a proteomic subtyping workflow using 100 deep-learned features. Two proteomic subtypes (S-I and S-II) with overall survival differences were identified. S-I has a better survival rate and is sensitive to chemotherapy. Patients in the S-I who received adjuvant chemotherapy had a significant improvement in the 5-year overall survival rate compared with patients who received surgery alone (65.3% vs 52.6%; log-rank P = 0.014), but no improvement was observed in the S-II (54% vs 51%; log-rank P = 0.96). These results were verified in an independent validation set. Furthermore, we also evaluated the superiority and scalability of the deep learning-based workflow in cancer molecular subtyping, exhibiting its great utility and potential in prognosis prediction and therapeutic decision-making.
... Emerging evidence suggests that the prognosis of gastric cancer is not only associated with tumor indicators, but also related to systemic inflammation, patient's condition, and nutritional status (22)(23)(24). Nowadays, due to the heterogeneity and comprehensiveness of gastric cancer, even if the same TNM is staged through the AJCC TNM staging system, the prognosis of patients may be different and vary greatly (25). As a result, it is necessary to develop an accurate prognostic risk stratification system to predict treatment outcomes. ...
Article
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Objective This study is aimed to determine the potential prognostic significance of nutritional risk index (NRI) in patients with stage III gastric cancer. Methods A total of 202 patients with stage III gastric cancer were enrolled in this study. NRI was an index based on ideal body weight, present body weight, and serum albumin levels. All patients were divided into two groups by receiver operating characteristic curve: low NRI group (NRI<99) and high NRI group (NRI≥99). The relationship between NRI and clinicopathologic characteristics was evaluated by Chi-square test. The clinical survival outcome was analyzed by Kaplan-Meier method and compared using log-rank test. The univariate and multivariate analyses were used to detect the potential prognostic factors. A nomogram for individualized assessment of disease-free survival (DFS) and overall survival (OS). The calibration curve was used to evaluate the performance of the nomogram for predicted and the actual probability of survival time. The decision curve analysis was performed to assess the clinical utility of the nomogram by quantifying the net benefits at different threshold probabilities. Results The results indicated that NRI had prognostic significance by optimal cutoff value of 99. With regard to clinicopathologic characteristics, NRI showed significant relationship with age, weight, body mass index, total protein, albumin, albumin/globulin, prealbumin, glucose, white blood cell, neutrophils, lymphocyte, hemoglobin, red blood cell, hematocrit, total lymph nodes, and human epidermal growth factor receptor 2 (P<0.05). Through the univariate and multivariate analyses, NRI, total lymph nodes, and tumor size were identified as the independent factor to predict the DFS and OS. The nomogram was used to predict the 1-, 3-, and 5-year survival probabilities, and the calibration curve showed that the prediction line matched the reference line well for 1-, 3-, and 5-year DFS and OS. Furthermore, the decision curve analysis also showed that the nomogram model yielded the best net benefit across the range of threshold probability for 1-, 3-, 5-year DFS and OS. Conclusions NRI is described as the potential prognostic factor for patients with stage III gastric cancer and is used to predict the survival and prognosis.
... PDTXs accurately retain the heterogeneity of human tumors, but in contrast to PDTXs, PDOs can be cultured for a long time, expanded, and finally cryopreserved. The establishment of large organoid biobanks has been made possible by the propagation of tumor biopsies in vitro, that these tumor biobanks preserve the mutational diversity and histological properties of native human tumors (30)(31)(32). Here, we discuss the various organoid culture strategies for the modeling of TIME and the applications of complex PDOs in testing cancer immunotherapeutics and personalized cancer immunotherapy. ...
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Cancer immunotherapy is exploited for the treatment of disease by modulating the immune system. Since the conventional in vivo animal and 2D in vitro models insufficiently recapitulate the complex tumor immune microenvironment (TIME) of the original tumor. In addition, due to the involvement of the immune system in cancer immunotherapy, more physiomimetic cancer models, such as patient-derived organoids (PDOs), are required to evaluate the efficacy of immunotherapy agents. On the other hand, the dynamic interactions between the neoplastic cells and non-neoplastic host components in the TIME can promote carcinogenesis, tumor metastasis, cancer progression, and drug resistance of cancer cells. Indeed, tumor organoid models can properly recapitulate the TIME by preserving endogenous stromal components including various immune cells, or by adding exogenous immune cells, cancer-associated fibroblasts (CAFs), vasculature, and other components. Therefore, organoid culture platforms could model immunotherapy responses and facilitate the immunotherapy preclinical testing. Here, we discuss the various organoid culture approaches for the modeling of TIME and the applications of complex tumor organoids in testing cancer immunotherapeutics and personalized cancer immunotherapy.
... Another benefit of 3D organoid culture is the fact that they can be isolated from both normal and diseased donors. Since organoid cultures maintain the traits of the original tissue, organoids derived from tissues of clinical cases can recapitulate the pathology of disease (133)(134)(135)(136). Therefore, patient-derived organoids are very useful natural models for studying pathophysiology of the disease (135,136) and establishing disease-specific living biobanks for large scale genetic analyses such as in cases of neoplasia (137)(138)(139)(140). Patient-derived organoid models also present great potential for precision medicine such as preclinical drug efficacy testing and pharmacodynamics studies (141,142). ...
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Animal organoid models derived from farm and companion animals have great potential to contribute to human health as a One Health initiative, which recognize a close inter-relationship among humans, animals and their shared environment and adopt multi-and trans-disciplinary approaches to optimize health outcomes. With recent advances in organoid technology, studies on farm and companion animal organoids have gained more attention in various fields including veterinary medicine, translational medicine and biomedical research. Not only is this because three-dimensional organoids possess unique characteristics from traditional two-dimensional cell cultures including their self-organizing and self-renewing properties and high structural and functional similarities to the originating tissue, but also because relative to conventional genetically modified or artificially induced murine models, companion animal organoids can provide an excellent model for spontaneously occurring diseases which resemble human diseases. These features of companion animal organoids offer a paradigm-shifting approach in biomedical research and improve translatability of in vitro studies to subsequent in vivo studies with spontaneously diseased animals while reducing the use of conventional animal models prior to human clinical trials. Farm animal organoids also could play an important role in investigations of the pathophysiology of zoonotic and reproductive diseases by contributing to public health and improving agricultural production. Here, we discuss a brief history of organoids and the most recent updates on farm and companion animal organoids, followed by discussion on their potential in public health, food security, and comparative medicine as One Health initiatives. We highlight recent evolution in the culturing of organoids and their integration with organ-on-a-chip systems to overcome current limitations in in vitro studies. We envision multidisciplinary work integrating organoid culture and organ-on-a-chip technology can contribute to improving both human and animal health.
... We then exploited their antitumor function in vivo by tumoroid xenograft mouse models. As with tumoroids, patient-derived xenograft (PDX) mouse models are also described to be able to recapitulate the intra-and inter- (31). Therefore, we combined both promising armaments (21) to confirm the feasibility of TIL or PBL therapy. ...
Article
Background: Tumor-derived organoid, namely tumoroid, can realistically retain the clinicopathologic features of original tumors even after long-term in vitro expansion. Here we develop this production methodology derived from hepatocellular carcinoma primary samples and generate a platform to evaluate the tumoricidal efficacy of autologous adoptive cell transfer including tumor infiltrating lymphocytes and peripheral blood lymphocytes. Methods: Haematoxylin and eosin together with immunohistochemistry staining were employed to ascertain the morphologic and histological features of tumoroids and original tumors. Tumor killing ability of T cells was detected by lactate dehydrogenase assay and propidium iodide staining. In tumoroid xenograft mouse model, tumor volumes were measured and T cell functions were examined by flow cytometry technique. Results: Four tumoroids with characteristics of poor differentiation and mild fibrosis were successfully established from fourteen hepatocellular carcinoma samples. More robust antitumor potential and hyper-functional phenotype of all four tumor infiltrating lymphocytes were observed compared to matched peripheral blood lymphocytes in coculture system. In tumoroid xenograft mouse models, however, only one patient-derived tumor infiltrating lymphocytes with the highest antitumor activity can bestow efficient tumor eradication. Conclusions: Hepatocellular carcinoma tumoroid-based models could represent invaluable resources for evaluating the tumoricidal efficacy of autologous adoptive cell transfer. Tumor infiltrating lymphocytes should be a promising and yet-to-be-developed regimen to treat hepatocellular carcinoma.
... One of the important obstacles for slowing progression of the development for GCa therapeutics is the lacking of theranostic marker. 4,15 One previous study has shown that ~20% of GCa patients overly express CYP19A1 (cytochrome P450 family 19 subfamily A member 1; also known as aromatase, Ar). 16 Because Ar acts, in terms of biochemical function, as a metabolic enzyme to convert testosterone into estradiol, 17 aromatase inhibitors have been developed and implemented as treatments for estrogen receptor (ESR)-positive breast cancer patients. ...
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Introduction: Gastric cancer (GCa) is a malignancy with few effective treatments. Ursolic acid (UA), a bioactive triterpenoid enriched in Hedyotis diffusa Willd, known to suppress GCa without identified target. CYP19A1 (cytochrome P450 family 19A1; also known as aromatase, Ar) was correlated to GCa prognosis. Relatedly, Ar silencers, which halt the expression of Ar exhibited anti-GCa effects in experimental models, are currently being investigated. Method: The docking simulation score of UA was compared with Ar inhibitors, e.g., letrozole, exemestane, in Ar protein crystallization. Hedyotis diffusa Willd ethanol extract, UA, or 5-fluracil were applied onto AGS, SC-M1, MKN45 GCa cells for cancer inhibition tests. Immunoblot for measuring gene expressions upon drug treatments, or gene knockdown/overexpression. Treatments were also applied in a MKN45 implantation tumor model. A web-based GCa cohort for Ar expression association with prognosis was performed. Result: The ethanol extracts of Hedyotis diffusa Willd, enrich with UA, exhibited cytotoxic activity against GCa cells. Molecular docking simulations with the 3D Ar structure revealed an excellent fitting score for UA. UA increase cytotoxic, and suppressed colony, in addition to its Ar silencing capacity. Moreover, UA synergistically facilitated 5-FU, (a standard GCa treatment) regimen in vitro. Consistent with those results, adding estradiol did not reverse the cancer-suppressing effects of UA, which confirmed UA acts as an Ar silencer. Furthermore, UA exhibited tumor-suppressing index (TSI) score of 90% over a 6-week treatment term when used for single dosing in xenograft tumor model. In the clinical setting, Ar expression was found to be higher in GCa tumors than normal parental tissue from the TCGA (The Cancer Genome Atlas) cohort, while high Ar expression associated with poor prognosis. Together, the results indicate UA could be used to treat GCa by silencing Ar expression in GCa. Hedyotis diffusa Willd ethanol extract could be an functional food supplements.
... In a translational perspective, it is important to underline that these observations were not only reproduced, but also more evident in CRC organoids, a tridimensional tumor model that resembles several characteristics of human solid tumors (50)(51)(52). In particular, the data of the present study demonstrated an earlier transcriptional reprogramming in response to hypoxia in organoids compared to monolayer cells, since their growth within a 3D matrix already promotes the formation of spontaneous hypoxic area which characterize solid tumors (37). ...
Article
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Metabolic rewiring fuels rapid cancer cell proliferation by promoting adjustments in energetic resources, and increasing glucose uptake and its conversion into lactate, even in the presence of oxygen. Furthermore, solid tumors often contain hypoxic areas and can rapidly adapt to low oxygen conditions by activating hypoxia inducible factor (HIF)‑1α and several downstream pathways, thus sustaining cell survival and metabolic reprogramming. Since TNF receptor‑associated protein 1 (TRAP1) is a HSP90 molecular chaperone upregulated in several human malignancies and is involved in cancer cell adaptation to unfavorable environments and metabolic reprogramming, in the present study, its role was investigated in the adaptive response to hypoxia in human colorectal cancer (CRC) cells and organoids. In the present study, glucose uptake, lactate production and the expression of key metabolic genes were evaluated in TRAP1‑silenced CRC cell models under conditions of hypoxia/normoxia. Whole genome gene expression profiling was performed in TRAP1‑silenced HCT116 cells exposed to hypoxia to establish the role of TRAP1 in adaptive responses to oxygen deprivation. The results revealed that TRAP1 was involved in regulating hypoxia‑induced HIF‑1α stabilization and glycolytic metabolism and that glucose transporter 1 expression, glucose uptake and lactate production were partially impaired in TRAP1‑silenced CRC cells under hypoxic conditions. At the transcriptional level, the gene expression reprogramming of cancer cells driven by HIF‑1α was partially inhibited in TRAP1‑silenced CRC cells and organoids exposed to hypoxia. Moreover, Gene Set Enrichment Analysis of TRAP1‑silenced HCT116 cells exposed to hypoxia demonstrated that TRAP1 was involved in the regulation of ribosome biogenesis and this occurred with the inhibition of the mTOR pathway. Therefore, as demonstrated herein, TRAP1 is a key factor in maintaining HIF‑1α‑induced genetic/metabolic program under hypoxic conditions and may represent a promising target for novel metabolic therapies.
... As such, a growing body of evidence shows clear correlation between organoid in vitro responses to long-term clinical responses of individual patient donors. Currently, these evaluations have been mostly performed on patients diagnosed with gastrointestinal cancer [50][51][52], colorectal cancer [53][54][55][56][57][58], breast cancer [59,60], pancreatic cancer [57,59,61], ovarian cancer [62,63] and esophageal adenocarcinoma [64]. PDO conceptualization for personalized treatment is lagging for CNS tumors and needs further validation. ...
Article
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Glioblastoma remains the most malignant and intrinsically resistant brain tumour in adults. Despite intensive research over the past few decades, through which numerous potentially druggable targets have been identified, virtually all clinical trials of the past 20 years have failed to improve the outcome for the vast majority of GBM patients. The observation that small subgroups of patients displayed a therapeutic response across several unsuccessful clinical trials suggests that the GBM patient population probably consists of multiple subgroups that probably all require a distinct therapeutic approach. Due to extensive inter- and intratumoral heterogeneity, assigning the right therapy to each patient remains a major challenge. Classically, bulk genetic profiling would be used to identify suitable therapies, although the success of this approach remains limited due to tumor heterogeneity and the absence of direct relationships between mutations and therapy responses in GBM. An attractive novel strategy aims at implementing methods for functional precision oncology, which refers to the evaluation of treatment efficacies and vulnerabilities of (ex vivo) living tumor cells in a highly personalized way. Such approaches are currently being implemented for other cancer types by providing rapid, translatable information to guide patient-tailored therapeutic selections. In this review, we discuss the current state of the art of transforming technologies, tools and challenges for functional precision oncology and how these could improve therapy selection for GBM patients.
... In comparison, patient-derived organoids (PDOs) offer a lower cost and higher throughput model for clinical applications (Jenkins et al., 2018;Neal et al., 2018;Yuki et al., 2020). With large-scale biobanks of breast (Sachs et al., 2018), colorectal (Sato et al., 2011;van de Wetering et al., 2015), ovarian (Kopper et al., 2019), pancreatic (Driehuis et al., 2019b), brain (Jacob et al., 2020), kidney (Calandrini et al., 2020), head and neck (Driehuis et al., 2019a), and gastric cancers (Seidlitz et al., 2021;Yan et al., 2018), PDO have been shown to capture patient diversity. Additionally, broad-based drug screens have reproduced known associations between genetic mutations and sensitivity to targeted therapies (Gao et al., 2014;Skardal et al., 2015). ...
Article
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Patient-derived xenografts (PDXs) and patient-derived organoids (PDOs) have been shown to model clinical response to cancer therapy. However, it remains challenging to use these models to guide timely clinical decisions for cancer patients. Here, we used droplet emulsion microfluidics with temperature control and dead-volume minimization to rapidly generate thousands of micro-organospheres (MOSs) from low-volume patient tissues, which serve as an ideal patient-derived model for clinical precision oncology. A clinical study of recently diagnosed metastatic colorectal cancer (CRC) patients using an MOS-based precision oncology pipeline reliably assessed tumor drug response within 14 days, a timeline suitable for guiding treatment decisions in the clinic. Furthermore, MOSs capture original stromal cells and allow T cell penetration, providing a clinical assay for testing immuno-oncology (IO) therapies such as PD-1 blockade, bispecific antibodies, and T cell therapies on patient tumors.
... Most of the translational applications of organoids have been focused on protocols to generate organoids from different tissues [81]. Organoid biobanks are being established from tumor tissues and healthy tissues [82][83][84], which can be propagated and studied in the laboratory for HTS-based drug discovery. ...
Article
3D cell cultures are being utilized for drug discovery and development. However, there are still challenges to implementing them generally in quantitative high-throughput screening (HTS) due to the complexity of the 3D architecture, the time- and labor-consuming process, and the lack of compatibility with traditional screening protocols. Therefore, there is a great need for the integration of microfabrication techniques, automation systems, and high-throughput analytical tools that reveal the pharmacological and toxicological effects of therapeutics using 3D cultures. We first review the current advances in 3D culture models and discuss their key challenges in HTS. Last, we review recent progress and breakthroughs in the automation and high-throughput imaging of 3D culture models, which can be integrated with machine-learning (ML) tools to aid quantitative HTS for drug discovery and development.
... With the advent of tumor organoid culture, patient-derived tumor organoids (PDTOs) have become popular tools to study molecular tumorigenesis, understand tumor heterogenity, predict drug responses, immunotherapy, and precision cancer therapy. At the moment, several tumor organoid biobanks have been developed catering to a variety of cancer types, including lung [31], breast [32], gut [33], and brain [34], liver [35], colorectal [36], pancreas [37], prostate [38], and ovary [39]. The role of tumor immune microenvironments (TIME) is significant in improving cancer immunotherapies, and PDTOs have started playing a crucial role in modeling the tumor-immune landscape. ...
Chapter
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Organoids are 3D miniature tissue mimics and have been effectively used for various purposes, including disease modeling, various drug screening, mechanism of pathogenesis, stem cell research, and tumor immunology. Organoids are as varied as the body's tissues and organs and have enormous economic potential. They can open new ways to tailored therapy and precision medicine. In clinical investigations, patient-derived organoids have been used to predict patient responses to therapeutic regimens and perhaps improve cancer treatment outcomes. Recent developments in stem cell research and genomic technologies have led to breakthrough innovations in organoid bioengineering, large-scale manufacturing, biobanking, and commercial-ization. This chapter reviews the notion of organoid biobanking, companies involved and the commercialization aspect, and ethical considerations.
... Ten years ago, cancer genomics was welcomed as a powerful tool to grasp tumor heterogeneity and propose personalized treatment233 . Today, organoids join the toolbox of personalized medicine, as they can serve as screening platform to assess numerous drugs on patient-derived cancer organoids, simultaneously modeling the response of the patient to multiple therapeutic strategies, and accelerating the time to identify the best treatment to propose[234][235][236] .Overall, 3D cell culture, and especially organoids, have clearly demonstrated that they have advantages over flat culture, on which we can capitalize: better survival, better differentiation profile, possibility to produce complex architecture, more relevant cell shape and mechano-responses237 . Some are already asking if it is time to start transitioning to 3D cell culture? ...
Thesis
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Modern day ethics and laws call for more safety and use of fewer animals in biomedical research. It became crucial to develop novel in vitro devices of higher relevance. Since the end of the twentieth century, several systems have been proposed by researchers in attempts to palliate the shortcomings of current systems. Notably, organs-on-chip systems are specifically tailored to recapitulate tissue functions in a manner that remains easily accessible for the experimenter. Despite the significant improvements that were brought during the last century to in vitro cell and tissue culture systems, the field of bioengineering is still young and much progress remains to be done. The work presented here details the development of an organ-on-chip that includes a biocompatible and actuatable hydrogel membrane, with controlled physico-chemical properties. Such chip is relevant when hosting barrier tissues, which are composed of several cell types, disposed on each side of a barrier, as well as within its bulk, and are often submitted to mechanical stimuli. During this PhD, several objectives have been attained. Notably, we: - Designed and produced an organ-on-chip including a biocompatible and actuatable hydrogel layer, as well as a microfluidic system allowing the independent control of both flow and actuation. - Characterized the deformation of the hydrogel layer. - Cultured intestinal cells within the chip, which formed a three dimensionally structure epithelium, and characterized its apparent permeability to molecules of varying sizes
... Gastric cancer is considered as one of the most deadly cancers, ranked as the third leading cause of cancer-associated deaths worldwide (Chen et al., 2014). Exploring the heterogeneity within the tumor can help to deeply understand the microenvironment of gastric cancer (Yan et al., 2018). Recently, it has been validated that CNVs (deletion, insertion or SNPs) in genes are one of the important factors affecting cellular functions (Nakamura, 2009). ...
Article
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Gastric cancer (GC) is a highly fatal and common malignancy of the digestive system. Recent therapeutic advancements have significantly improved the clinical outcomes in GC, but due to the unavailability of suitable molecular targets, a large number of patients do not respond to the immune checkpoint inhibitors (ICI) therapy. To identify and validate potential therapeutic and prognostic targets of gastric cancer, we used the “inferCNV” R package for analyzing single-cell sequencing data (GSE112302) of GC and normal epithelial cells. First, by using LASSO, we screened genes that were highly correlated with copy number variations (CNVs). Therefrom, five gene signature (CPVL, DDC, GRTP1, ONECUT2, and PRSS21) was selected by cross-validating the prognosis and risk management with the GC RNA-seq data obtained from GEO and TCGA. Moreover, the correlation analyses between CNVs of these genes and immune cell infiltration in gastric cancer identified CPVL as a potential prognostic marker. Finally, CPVL showed high expression in gastric cancer samples and cell lines, then siRNA-mediated silencing of CPVL expression in gastric cancer cells showed significant proliferation arrest in MGC803 cells. Here, we conclude that CNVs are key regulators of the immune cells infiltration in gastric TME as well as cancer development, and CPVL could potentially be used as a prognostic and therapeutic marker in gastric cancer.
... Patient-derived organoids have contributed to successful drug screenings, showing concordance with matched patient tumors [39,40]. Until now, only a few reports of primary NSCLC organoids for drug screening have been published. ...
Article
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Despite major research and clinical efforts, lung cancer remains the leading cause of cancer-related death. While the delivery of conformal radiotherapy and image guidance of stereotactic body radiotherapy (SBRT) have revolutionized the treatment of early-stage non-small-cell lung cancer (NSCLC), additional research is needed to elucidate underlying mechanisms of resistance and identify novel therapeutic combinations. Clinical progress relies on the successful translation of pre-clinical work, which so far has not always yielded expected results. Improved clinical modelling involves characterizing the preclinical models and selecting appropriate experimental designs that faithfully mimic precise clinical scenarios. Here, we review the current role of SBRT and the scope of pre-clinical armamentarium at our disposal to improve successful clinical translation of pre-clinical research in the radiation oncology of NSCLC.
... Additionally, BME hydrogels do not provide a stiffness comparable with most solid tumors, even at the highest protein concentration available, and do not reflect a physiological molecular organization, since it does not include a 3D-organized basement membrane. Indeed, clinical assays based on tumoroids embedded in BME do not provide an acceptable clinical prediction so far, for most drug treatments as observed by several authors [30][31][32][33][34]. For example, a study based on 12 patient-derived organoids was consistent with clinical evolution when treated with irinotecan, a DNA topoisomerase inhibitor. ...
Article
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The recent trend in 3D cell modeling has fostered the emergence of a wide range of models, addressing very distinct goals ranging from the fundamental exploration of cell–cell interactions to preclinical assays for personalized medicine. It is clear that no single model will recapitulate the complexity and dynamics of in vivo situations. The key is to define the critical points, achieve a specific goal and design a model where they can be validated. In this report, we focused on cancer progression. We describe our model which is designed to emulate breast carcinoma progression during the invasive phase. We chose to provide topological clues to the target cells by growing them on microsupports, favoring a polarized epithelial organization before they are embedded in a 3D matrix. We then watched for cell organization and differentiation for these models, adding stroma cells then immune cells to follow and quantify cell responses to drug treatment, including quantifying cell death and viability, as well as morphogenic and invasive properties. We used model cell lines including Comma Dβ, MCF7 and MCF10A mammary epithelial cells as well as primary breast cancer cells from patient-derived xenografts (PDX). We found that fibroblasts impacted cell response to Docetaxel and Palbociclib. We also found that NK92 immune cells could target breast cancer cells within the 3D configuration, providing quantitative monitoring of cell cytotoxicity. We also tested several sources for the extracellular matrix and selected a hyaluronan-based matrix as a promising alternative to mouse tumor basement membrane extracts for primary human cancer cells. Overall, we validated a new 3D model designed for breast cancer for preclinical use in personalized medicine.
... Since then, various types of tissuespecific organoids have been reported, such as liver (Takebe et al., 2013), kidney (Taguchi et al., 2014), brain (Lancaster and Knoblich, 2014a), pancreas (Boj et al., 2015), and lung (Dye et al., 2015) organoids. Using these organoids, a variety of human diseases have been modeled in vitro, including infectious diseases (Lamers et al., 2020;Qiao et al., 2020), genetic diseases (Ramli et al., 2020;Schwank et al., 2013), and cancers (Bian et al., 2018;Shi et al., 2020;Yan et al., 2018). These disease models facilitate human disease mechanistic studies and preclinical drug development. ...
Article
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Organoids are considered a game-changing paradigm of research models for human physiology and disease, which provides unsurpassed opportunities across disciplines in basic medical research, drug development, and personalized medicine. Here, we made a deep investigation for global patents of organoid technologies in the past decade using bibliometric analysis for the first time. We have identified a total of 672 patents related to organoid technology. The number of annual patent applications exhibits an overall upward growth trend over the past decade, especially entering an exponential growth since 2015. Notably, 76.64% of patents are related to the construction of organoid models. Liver, brain, and intestinal models take up the first three places in the physiological models, while tumor models account for 76.30% of the total patents for disease models. Furthermore, drug screening is the most preferred application, revealing the great commercial value of organoid technologies in precision medicine and preclinical drug screening.
... Yan et al. 96 have constructed a GC organoid biobank comprising normal, dysplastic, cancer, and lymph node metastases (n = 63) from 34 patients. The success rate of normal organoids was more than 90%, and that of GC organoids exceeded 50%. ...
Article
Biobanks bridge the gap between basic and translational research. Traditional cancer biobanks typically contain normal and tumor tissues, and matched blood. However, biospecimens in traditional biobanks are usually nonrenewable. In recent years, increased interest has focused on establishing living biobanks, including organoid biobanks, for the collection and storage of viable and functional tissues for long periods of time. The organoid model is based on a 3D in vitro cell culture system, is highly similar to primary tissues and organs in vivo, and can recapitulate the phenotypic and genetic characteristics of target organs. Publications on cancer organoids have recently increased, and many types of cancer organoids have been used for modeling cancer processes, as well as for drug discovery and screening. On the basis of the current research status, more exploration of cancer organoids through technical advancements is required to improve reproducibility and scalability. Moreover, given the natural characteristics of organoids, greater attention must be paid to ethical considerations. Here, we summarize recent advances in cancer organoid biobanking research, encompassing rectal, gastric, pancreatic, breast, and glioblastoma cancers. Living cancer biobanks that contain cancerous tissues and matched organoids with different genetic backgrounds, subtypes, and individualized characteristics will eventually contribute to the understanding of cancer and ultimately facilitate the development of innovative treatments.
... This is possible using biobanks of PDOs conserved under long term culture [77], though some tissues still pose challenges in achieving this maintainability [78]. One such biobank has been established in gastric cancer, accounting for wide molecular diversity across normal, dysplastic, cancerous, and metastatic tissue [79]. Similar long term and genetically heterogenous PDO libraries have been described in colorectal [80], breast [35], and bladder tissue [81]. ...
Article
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The field of cancer research is famous for its incremental steps in improving therapy. The consistent but slow rate of improvement is greatly due to its meticulous use of consistent cancer biology models. However, as we enter an era of increasingly personalized cancer care, including chemo and radiotherapy, our cancer models must be equally able to be applied to all individuals. Patient-derived organoid (PDO) and organ-in-chip (OIC) models based on the micro-physiological bioengineered platform have already been considered key components for preclinical and translational studies. Accounting for patient variability is one of the greatest challenges in the crossover from preclinical development to clinical trials and patient derived organoids may offer a steppingstone between the two. In this review, we highlight how incorporating PDO’s and OIC’s into the development of cancer therapy promises to increase the efficiency of our therapeutics.
... Also, Yan et al., developed a human gastric cancer organoid biobank that comprises normal, dysplastic, cancer, and lymph node metastases, including detailed whole-exome and transcription analysis. The developed biobank organoid system from patient-derived tissues was tested for different drugs similar to the respective patients, and the results were promising as the tumor response of the patient and the cancer organoid have shown the same response [192]. It is evident that organoid cultures have the potential to predict in vivo drug response. ...
Article
Organoid, a 3D structure derived from various cell sources including progenitor and differentiated cells that self-organize through cell-cell and cell-matrix interactions to recapitulate the tissue/organ-specific architecture and function in vitro. The advancement of stem cell culture and the development of hydrogel-based extracellular matrices (ECM) have made it possible to derive self-assembled 3D tissue constructs like organoids. The ability to mimic the actual physiological conditions is the main advantage of organoids, reducing the excessive use of animal models and variability between animal models and humans. However, the complex microenvironment and complex cellular structure of organoids cannot be easily developed only using traditional cell biology. Therefore, several bioengineering approaches, including microfluidics, bioreactors, 3D bioprinting, and organoids-on-a-chip techniques, are extensively used to generate more physiologically relevant organoids. In this review, apart from organoid formation and self-assembly basics, the available bioengineering technologies are extensively discussed as solutions for traditional cell biology-oriented problems in organoid cultures. Also, the natural and synthetic hydrogel systems used in organoid cultures are discussed when necessary to highlight the significance of the stem cell microenvironment. The selected organoid models and their therapeutic applications in drug discovery and disease modeling are also presented.
... Furthermore, it has been reported that GC patientderived organoids (PDOs), three-dimensional cell clusters cultivated from gastric cancer stem cells and spontaneously organized into organ-like or tissue-like structures (Ohta et al. 2006;;Vlachogiannis et al. 2018), can retain tumor characteristics and maintain tumor mutational properties for a long time (Ohta and Sitkovsky 2001;Yan et al. (2018); Method of the Year Organoids 2018). Thus, we used GC organoids to coculture with activated PBMCs indirectly to mimic the GC immune microenvironment. ...
Article
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Purpose Nicotinamide adenine dinucleotide (NAD+) is closely related to the pathogenesis of tumors. However, the effect of NAD+ metabolism of gastric cancer (GC) cells on immune cells remains unexplained. We targeted nicotinamide phosphoribosyltransferase (NAMPT), a rate-limiting enzyme in the NAD+ synthesis salvage pathway, to observe its effect in the immune microenvironment. Methods NAMPT of GC cell lines was inhibited by using the small molecule inhibitor (FK866) and short hairpin RNA (shRNA). CCK-8 test and flow cytometry were performed to detect cell viability and apoptosis. Immunofluorescence was used to observe changes in mitochondrial membrane potential (MMP).The transfected GC cells (AGS) and patient-derived organoids (PDOs) were cocultured with activated PBMCs, followed by flow cytometric analysis (FCA) for cytokines and inhibitory marker. The level of NAD and ATP of GC cells (AGS & MKN45) was tested combined with NMN and CD39 inhibitor. Results Targeting NAD+ by FK866 obviously reduced MMP, which ultimately inhibited proliferation and increased the apoptosis of GC cells. NAMPT silencing reduced intracellular NAD and ATP,further decreased extracellular adenosine. Meawhile, the cytokines of CD8+T cells were significantly increased after cocultured with transfected AGS, and the expression of PD-1 was distinctly decreased. NMN reversed the effect of shNAMPT and enhanced the immunosuppression. Consistent results were obtained by coculturing PBMCs with PDOs. Conclusion Restraining the function of NAMPT resulted in the functional improvement of effector CD8+ T cells by decreasing extracellular adenosine levels and inducing apoptosis of GC cells simultaneously. Therefore, this study demonstrates that NAMPT can be an effective target for gastric cancer immunotherapy.
... Representative targeted therapies for GC include trastuzumab, a monoclonal antibody that targets HER2, and ramucirumab, which targets VEFG-2. Targeted therapies aimed at EGFR, HGFR, and VEGFR are currently under development [3]; however, their therapeutic effects in GC may be different from patient to patient owing to the molecular heterogeneity of GC [4]. Therefore, it is important to identify factors that can predict poor prognosis in order to facilitate individual treatment choice [5]. ...
Article
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Gastric cancer (GC) has the highest occurrence and fourth-highest mortality rate of all cancers in Korea. Although survival rates are improving with the development of diagnosis and treatment methods, the five-year survival rate for stage 4 GC in Korea remains <10%. Therefore, it is important to identify candidate prognostic factors for predicting poor prognosis. PRNP is a gene encoding the prion protein PrP, which has been noted for its role in the nervous system and is known to be upregulated in various cancers and associated with both cell proliferation and metastasis. However, the value of PRNP as a prognostic factor for Korean GC patients remains unclear. Here, we analyzed the relationship between PRNP expression and survival in three independent datasets for Korean patients with GC as well as the TCGA-STAD dataset. Survival analysis indicates that high levels of PRNP expression are associated with poor overall survival of patients with GC. Gene set enrichment analysis showed that PRNP is associated with epithelial mesenchymal transition and Hedgehog signaling. In addition, proliferation of GC cell lines was inhibited after siRNA-mediated knockdown of PRNP. In conclusion, our study suggests a potential role for PRNP as a candidate prognostic factor for patients with GC.
... Even though the current routine use of a comprehensive treatment plan based on surgery is supplemented by chemotherapy and immune-targeted therapy, the 5-years survival rate of patients with advanced GC is still only approximately 30% (Montagnani et al., 2018). In recent years, an increasing number of studies have suggested that this phenomenon may be related to the inhibition of tumour cell programmed death and tumour microenvironment (TME)-mediated immune heterogeneity (Yan et al., 2018;Tang et al., 2020). Therefore, in-depth analysis of the genes and immune microenvironment characteristics of tumour cell programmed death is the key to identifying different patient subgroups, understanding the potential pathogenesis of GC, exploring precise therapeutic targets and predicting the effect of immunotherapy. ...
Article
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As a new programmed death mode, pyroptosis plays an indispensable role in gastric cancer (GC) and has strong immunotherapy potential, but the specific pathogenic mechanism and antitumor function remain unclear. We comprehensively analysed the overall changes of pyroptosis-related genes (PRGs) at the genomic and epigenetic levels in 886 GC patients. We identified two molecular subtypes by consensus unsupervised clustering analysis. Then, we calculated the risk score and constructed the risk model for predicting prognostic and selected nine PRGs related genes (IL18RAP, CTLA4, SLC2A3, IL1A, KRT7,PEG10, IGFBP2, GPA33, and DES) through LASSO and COX regression analyses in the training cohorts and were verified in the test cohorts. Consequently, a highly accurate nomogram for improving the clinical applicability of the risk score was constructed. Besides, we found that multi-layer PRGs alterations were correlated with patient clinicopathological features, prognosis, immune infiltration and TME characteristics. The low risk group mainly characterized by increased microsatellite hyperinstability, tumour mutational burden and immune infiltration. The group had lower stromal cell content, higher immune cell content and lower tumour purity. Moreover, risk score was positively correlated with T regulatory cells, M1 and M2 macrophages. In addition, the risk score was significantly associated with the cancer stem cell index and chemotherapeutic drug sensitivity. This study revealed the genomic, transcriptional and TME multiomics features of PRGs and deeply explored the potential role of pyroptosis in the TME, clinicopathological features and prognosis in GC. This study provides a new immune strategy and prediction model for clinical treatment and prognosis evaluation.
... Yan et al. established a primary gastric cancer organoid (GCO) biobank that comprised normal, dysplastic, cancer, and lymph node metastases (n = 63) from 34 patients, which also included detailed whole-exome and transcriptome analysis. They also tested and identified sensitivity of GC to some therapeutic agents in the clinical phase of development, which opened up new therapeutic opportunities (Yan et al., 2018). The innovative application of induced pluripotent stem cell (iPSC) technology and organoid technology to genetic neurometabolic diseases and for evaluation of individualized drug toxicity are conducive to elucidating new pathologic and therapeutic strategies for human diseases, which provides a platform for large-scale drug screening for personalized treatment of cancer. ...
Article
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The rapid development of medical technology and widespread application of immunosuppressive drugs have improved the success rate of organ transplantation significantly. However, the use of immunosuppressive agents increases the frequency of malignancy greatly. With the prospect of “precision medicine” for tumors and development of next-generation sequencing technology, more attention has been paid to the application of high-throughput sequencing technology in clinical oncology research, which is mainly applied to the early diagnosis of tumors and analysis of tumor-related genes. All generations of cancers carry somatic mutations, meanwhile, significant differences were observed in mutational signatures across tumors. Systematic sequencing of cancer genomes from patients after organ transplantation can reveal DNA damage and repair processes in exposed cancer cells and their precursors. In this review, we summarize the application of high-throughput sequencing and organoids in the field of organ transplantation, the mutational patterns of cancer genomes, and propose a new research strategy for understanding the mechanism of cancer following organ transplantation.
... The large-scale public database, such as the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), presented the transcriptome profiles of numerous cancers. The access and analysis of this large-scale database allowed us to have an overall view of the genetic landscape, identify new biomarkers, screen therapeutic strategies and predict prognosis of these cancers (Yan et al., 2018;Zhou et al., 2019;Wang et al., 2021). ...
Article
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Skin cutaneous melanoma (SKCM, hereafter referred to as melanoma) is the most lethal skin cancer with increasing incidence. Regulated cell death plays an important role in tumorigenesis and serves as an important target for almost all treatment strategies. Cuproptosis is the most recently identified copper-dependent regulated cell death form that relies on mitochondria respiration. However, its role in tumorigenesis remains unknown. The correlation of cuproptosis-related genes with tumor prognosis is far to be understood, either. In the present study, we explored the correlation between cuproptosis-related genes with the prognosis of melanoma by accessing and analyzing a public database and found 11 out 12 genes were upregulated in melanoma tissues and three genes (LIPT1, PDHA1, and SLC31A1) have predictive value for the prognosis. The subgroup of melanoma patients with higher cuproptosis-related gene expression showed longer overall survival than those with lower gene expression. We chose LIPT1 for further exploration. LIPT1 expression was increased in melanoma biopsies and was an independent favorable prognostic indicator for melanoma patients. Moreover, LIPT1 expression was positively correlated with PD-L1 expression and negatively associated with Treg cell infiltration. The melanoma patients with higher LIPT1 expression showed longer overall survival than those with lower LIPT1 expression after receiving immunotherapy, indicating the prognostic predictive value of LIPT1. Finally, a pan-cancer analysis indicated that LIPT1 was differentially expressed in diverse cancers as compared to normal tissues and correlated with the expression of multiple immune checkpoints, especially PD-L1. It could serve as a favorable prognosis indicator in some cancer types. In conclusion, our study demonstrated the prognostic value of cuproptosis-related genes, especially LIPT1, in melanoma, and revealed the correlation between LIPT1 expression and immune infiltration in melanoma, thus providing new clues on the prognostic assessment of melanoma patients and providing a new target for the immunotherapy of melanoma.
... The symptoms of gastric lymphoma and gastric cancer are very similar, with abdominal pain, abdominal distension, and abdominal mass being the most common. In addition, some patients do not have abnormal symptoms in the early stage and can only be detected in the physical examination, which largely depends on gastroscopy [4,5]. Although gastric cancer and gastric lymphoma are similar in pathology, it is easy to cause confusion, which brings great difficulties to the actual identification. ...
Article
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To analyze the application value of CT-enhanced scanning based on artificial intelligence algorithm in the diagnosis of gastric cancer and gastric lymphoma, the CT images of 80 patients with Borrmann type IV gastric cancer or primary gastric lymphoma diagnosed by endoscopic pathology were retrospectively collected. Meanwhile, a lymph node recognition algorithm based on OTSU threshold segmentation was proposed for CT image processing. The results showed that the missed diagnosis rate of suspected lymph nodes and the missed lymph node detection rate of this algorithm were substantially lower than those of other algorithms ( P < 0.05 ). The probability of gastric wall motility disappearance, perigastric fat infiltration, and type A enhancement pattern in the Borrmann type IV gastric cancer group was higher than that in the gastric lymphoma group, with remarkable differences ( P < 0.05 ). There was no remarkable difference between the Borrmann type IV gastric cancer group and the gastric lymphoma group in the probability of swollen lymph nodes under the renal hilum ( P > 0.05 ). In addition, 5the sensitivity (83.17%), specificity (95.52%), and accuracy (93.08%) of the combined detection of the three CT signs (stomach wall motility, perigastric fat infiltration, and enhancement mode) were substantially improved compared with those of a single sign ( P < 0.05 ). To sum up, the lymph node recognition algorithm based on OTSU threshold segmentation had better performance in detecting gastric lymph nodes than traditional algorithms. The CT image characteristics of gastric wall motility, perigastric fat infiltration, and enhancement pattern based on artificial intelligence algorithms were effective indicators for distinguishing gastric cancer and gastric lymphoma.
... The advantage and rapid progress of next-generation sequencing, such as whole-exome sequencing (WES), has made it possible to comprehensively characterize the disease mechanisms and altered genes in multiple cancers (Ally et al., 2017;Yan et al., 2018;Nanki et al., 2020). This approach allows the identification of novel molecular markers and the definition of underlying biological mechanisms, thus facilitating the stratification and characterization of cancers (Cortés-Ciriano et al., 2022). ...
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Hepatocellular carcinoma (HCC) is a prevalent malignancy cancer worldwide with a poor prognosis. Hepatic resection is indicated as a potentially curative option for HCC patients in the early stage. However, due to multiple nodules, it leads to clinical challenges for surgical management. Approximately 41%–75% of HCC cases are multifocal at initial diagnosis, which may arise from multicentric occurrence (MO-HCC) or intrahepatic metastasis (IM-HCC) pattern with significantly different clinical outcomes. Effectively differentiating the two mechanisms is crucial to prioritize the allocation of surgery for multifocal HCC. In this study, we collected a multifocal hepatocellular carcinoma cohort of 17 patients with a total of 34 samples. We performed whole-exome sequencing and staining of pathological HE sections for each lesion. Reconstruction of the clonal evolutionary pattern using genome mutations showed that the intrahepatic metastogenesis pattern had a poorer survival performance than independent origins, with variants in the TP53, ARID1A, and higher CNV variants occurring more significantly in the metastatic pattern. Cross-modality analysis with pathology showed that molecular classification results were consistent with pathology results in 70.6% of patients, and we found that pathology results could further complement the classification for undefined patterns of occurrence. Based on these results, we propose a model to differentiate the pattern of multifocal hepatocellular carcinoma based on the pathological results and genome mutations information, which can provide guidelines for diagnosing and treating multifocal hepatocellular carcinoma.
... As estimated, the 5-year survival rate is <20% (Cavatorta et al., 2018). GC exhibits distinct molecular heterogeneity with aggressive behaviors as well as therapy resistance (Yan et al., 2018). The conventional system for predicting survival outcomes, like histological grade and tumor staging, is of difficulty to cover the clinical diversity of GC (Shao et al., 2016). ...
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Objective: Ferroptosis is a type of iron-dependent necrosis related to cancer. Nevertheless, the features of ferroptosis in gastric cancer (GC) remain poorly understood. This study conducted a systematic analysis of ferroptosis regulators in GC. Methods: We gathered five GC cohorts, namely, TCGA-STAD, GSE84437, GSE62254, GSE26901, and GSE15459. Unsupervised clustering analysis was adopted to cluster GC patients into different ferroptosis subtypes based on ferroptosis regulators. Immune cell infiltration and hallmark pathway activity were estimated via ssGSEA. The ferroptosis index was developed with the PCA computational method. Response to chemotherapy agents and small molecular compounds was inferred via GDSC, CTRP, and PRISM projects. Two anti-PD-1 therapy cohorts were gathered and the potential of FPI in predicting immune response was assessed. Results: Expression profiles, genetic mutations, DNA methylation, prognostic implications, and drug sensitivity of ferroptosis regulators were characterized in GC. Three ferroptosis subtypes were clustered with distinct prognosis, hallmark pathway activity, and tumor-infiltrating immune cells. Ferroptosis levels were quantified based on the expression of prognostic ferroptosis-related signatures. The significant relationships between FPI and clinicopathological characteristics were observed. Furthermore, high FPI was in relation to poor prognosis, inflamed tumor microenvironment (TME) as well as high sensitivity to chemotherapy agents (docetaxel and cisplatin), and CTRP- and PRISM-derived compounds. Also, FPI acted as a promising predictor of immune response. Conclusion: Collectively, our findings identified a novel ferroptosis-based subtype classification of GC, and revealed the potential of ferroptosis in forming TME diversity and complexity, and guiding individualized treatment.
Chapter
The scenario of proteogenomics is rapidly evolving and novel technologies are enabling comprehensive molecular exploration down to single cells. Likewise, digital (immuno-)assays are revolutionizing the field of biomarker detection and have reached the grade for population-level screenings with single-molecule sensitivity. Nonetheless, cost- and time-effective, high-throughput targeted phospho-proteomics at a preclinical stage still relies on ad hoc microarray platforms, such as the Reverse-Phase Protein microArrays (RPPA). Although this technique requires specific knowledge and equipment and different laboratories worldwide have implemented alternative methodological strategies, the application of RPPA to biomarker discovery has proven successful on diverse types of samples, including tissues and biological fluids as well as nanovesicles and in vitro cultured lines. Among these, cancer stem(-like) cells (CSC) represent an ideal experimental model system for preclinical discovery and definition of novel drug targets. The present methodological article provides the basic knowledge and steps on how to deploy an RPPA analysis with specific reference to an ideal experimental setup of drug testing on CSC.
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Organoids are in vitro simplified and miniature microcosms of internal organs, which have aroused great interest in tissue development, multiple disease models, clinical diagnosis, as well as high-throughput drug screening and personalized medicine and so on. The success of physiology-related organoid culture has greatly advanced the translational medicine research in the field of cancer treatment, which was once troubled by the inconsistency between two-dimensional (2D) cell culture and in vivo studies. Especially in recent years, the success rate of establish an organoid has been greatly improved, and the types of organoids have been gradually enriched. Moreover, the utilizing of some the cutting-edge technologies, including gene editing technology such as CRISPR-Cas9, the scope of application of organoid is broadened. In this review, we discuss the latest progress and applications of organoids, and also outline the potential challenges of organoids for future improvement.
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Objective Cell-cell (CC) and cell-matrix (CM) adhesions are essential for epithelial cell survival, yet dissociation-induced apoptosis is frequently circumvented in malignant cells. Design We explored CC and CM dependence in 58 gastric cancer (GC) organoids by withdrawing either ROCK inhibitor, matrix or both to evaluate their tumorigenic potential in terms of apoptosis resistance, correlation with oncogenic driver mutations and clinical behaviour. We performed mechanistic studies to determine the role of diffuse-type GC drivers: ARHGAP fusions, RHOA and CDH1, in modulating CC (CCi) or CM (CMi) adhesion independence. Results 97% of the tumour organoids were CMi, 66% were CCi and 52% were resistant to double withdrawal (CCi/CMi), while normal organoids were neither CMi nor CCi. Clinically, the CCi/CMi phenotype was associated with an infiltrative tumour edge and advanced tumour stage. Moreover, the CCi/CMi transcriptome signature was associated with poor patient survival when applied to three public GC datasets. CCi/CMi and CCi phenotypes were enriched in diffuse-type GC organoids, especially in those with oncogenic driver perturbation of RHO signalling via RHOA mutation or ARHGAP fusions. Inducible knockout of ARHGAP fusions in CCi/CMi tumour organoids led to resensitisation to CC/CM dissociation-induced apoptosis, upregulation of focal adhesion and tight junction genes, partial reversion to a more normal cystic phenotype and inhibited xenograft formation. Normal gastric organoids engineered with CDH1 or RHOA mutations became CMi or CCi, respectively. Conclusions The CCi/CMi phenotype has a critical role in malignant transformation and tumour progression, offering new mechanistic information on RHO-ROCK pathway inhibition that contributes to GC pathogenicity.
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Cancer organoids are three-dimensional mini-organ analogues derived from cancer tissues and have been proposed as models capable of simulating the structure and function of human organs and tissues in vitro. We sought to establish gastric cancer patient-derived organoids (PDOs) from tissues obtained by endoscopic biopsies. Gastric cancer-PDOs were successfully established and cultured from cancer tissues with gastric adenocarcinoma by endoscopic biopsies. To confirm that gastric cancer-PDOs were derived from cancer tissue, the consistency of the original cancer tissue was assessed by histopathological examination. As a result, it was confirmed that the shape and internal structure of gastric cancer-PDO were derived from the original gastric cancer cells, and the tumor specificity of gastric cancer-PDO was confirmed through Periodic acid-Schiff (PAS) and polyclonal carcinoembryonic antigen antibody staining. These results demonstrate that gastric cancer-PDO models show the characteristics of primary tumors and have potential for drug screening and providing a personalized medicine platform.
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Cancer organoids, a three‐dimensional (3D) culture system of cancer cells derived from tumor tissues, recapitulate physiological structure of the parental tumor. Different tumor organoids have been established for a variety of tumor types, such as colorectal, liver, stomach, pancreatic and brain tumors. Some tumor organoid biobanks are built to screen and discover novel antitumor drug targets. Moreover, patients‐derived tumor organoids (PDOs) could predict treatment response to chemoradiotherapy, targeted therapy and immunotherapy to provide guidance for personalized cancer therapy. In this review, we provide an updated overview of tumor organoid development, summarize general approach to establish tumor organoids, and discuss the application of anti‐cancer drug screening based on tumor organoid and its application in personalized therapy. We also outline the opportunities and challenges for organoids to guide precision medicine.
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Organoids are three-dimensional (3D) miniature structures cultured in vitro produced from either human pluripotent stem cells (hPSCs) or adult stem cells (AdSCs) derived from healthy individuals or patients that recapitulate the cellular heterogeneity, structure, and functions of human organs. The advent of human 3D organoid systems is now possible to allow remarkably detailed observation of stem cell morphogens, maintenance and differentiation resemble primary tissues, enhancing the potential to study both human physiology and developmental stage. As they are similar to their original organs and carry human genetic information, organoids derived from patient hold great promise for biomedical research and preclinical drug testing and is currently used for personalized, regenerative medicine, gene repair and transplantation therapy. In recent decades, researchers have succeeded in generating various types of organoids mimicking in vivo organs. Herein, we provide an update on current in vitro differentiation technologies of brain, retinal, kidney, liver, lung, gastrointestinal, cardiac, vascularized and multi-lineage organoids, discuss the differences between PSC- and AdSC-derived organoids, summarize the potential applications of stem cell-derived organoids systems in the laboratory and clinic, and outline the current challenges for the application of organoids, which would deepen the understanding of mechanisms of human development and enhance further utility of organoids in basic research and clinical studies.
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In this chapter we consider the particular preservation storage procedures applied to a range of cell types used to produce cell-based medicines. Specifically, it deals with the scientific considerations for preserving each cell type and the kinds of cryopreservation protocols used to successfully preserve these different cell types. The cell types addressed include both those commonly in current use for patient treatment, such as whole blood and hematopoietic stem cells and also examples of new cell-based medicines including tissue progenitor cells (MSCs), (The use of the term Mesenchymal Stem Cell (MSC) has been hotly debated in the literature as it actually applies to several different cell types. The term “tissue specific progenitor cells” has been proposed as a more accurate term (Robey 2017) and where the abbreviation “MSC” appears elsewhere in this chapter it can be assumed this is a reference to Mesenchymal Stromal cells or the more generic term for this group of cell types Tissue-Specific Progenitor Cells (TSPCs).) tissue engineered constructs, CAR-T cells and pluripotent stem cells. However, the chapter does not consider the preservation and storage of organs or cells and tissues used in reproductive medicine. A second part of the chapter addresses best practice in meeting regulatory requirements for preservation and storage of both unfrozen and cryopreserved materials, including core requirements for the design of storage facilities. Also considered is best practice for packaging and shipment of cell-based medicines and their reception at the clinic and control within the hospital environment under pharmacy rules. The authors have used examples of regulatory documents primarily from the European Union and the USA, but also include reference to key international standards and WHO guidance.
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We are entering an era of medicine where increasingly sophisticated data will be obtained from patients to determine proper diagnosis, predict outcomes and direct therapies. We predict that the most valuable data will be produced by systems that are highly dynamic in both time and space. Three-dimensional (3D) organoids are poised to be such a highly valuable system for a variety of gastrointestinal (GI) diseases. In the lab, organoids have emerged as powerful systems to model molecular and cellular processes orchestrating natural and pathophysiological human tissue formation in remarkable detail. Preclinical studies have impressively demonstrated that these organs-in-a-dish can be used to model immunological, neoplastic, metabolic or infectious GI disorders by taking advantage of patient-derived material. Technological breakthroughs now allow to study cellular communication and molecular mechanisms of interorgan cross-talk in health and disease including communication along for example, the gut–brain axis or gut–liver axis. Despite considerable success in culturing classical 3D organoids from various parts of the GI tract, some challenges remain to develop these systems to best help patients. Novel platforms such as organ-on-a-chip, engineered biomimetic systems including engineered organoids, micromanufacturing, bioprinting and enhanced rigour and reproducibility will open improved avenues for tissue engineering, as well as regenerative and personalised medicine. This review will highlight some of the established methods and also some exciting novel perspectives on organoids in the fields of gastroenterology. At present, this field is poised to move forward and impact many currently intractable GI diseases in the form of novel diagnostics and therapeutics.
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Patient-derived tumour organoids (PDOs) have revolutionised our understanding of cancer biology and the applications of personalised therapies. These advancements are principally ascribed to the ability of PDOs to consistently recapitulate and maintain the genomic, proteomic and morphological characteristics of parental tumours. Given these characteristics, PDOs (and their extended biobanks) are a representative preclinical model eminently suited to translate relevant scientific findings into personalized therapies rapidly. Here, we summarise recent advancements in PDOs from the perspective of cancer biology and clinical applications, focusing on the current challenges and opportunities of reconstructing and standardising more sophisticated PDO models. Statement of Significance Patient-derived tumour organoids (PDOs), three-dimensional (3D) self-assembled organotypic structures, have revolutionised our understanding of cancer biology and the applications of personalised therapies. These advancements are principally ascribed to the ability of PDOs to consistently recapitulate and maintain the genomic, proteomic and morphological characteristics of parental tumours. Given these characteristics, PDOs (and their extended biobanks) are a representative preclinical model eminently suited to translate relevant scientific findings into personalized therapies rapidly.
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Analysing multiple cancer samples from an individual patient can provide insight into the way the disease evolves. Monitoring the expansion and contraction of distinct clones helps to reveal the mutations that initiate the disease and those that drive progression. Existing approaches for clonal tracking from sequencing data typically require the user to combine multiple tools that are not purpose-built for this task. Furthermore, most methods require a matched normal (non-tumour) sample, which limits the scope of application. We developed SuperFreq, a cancer exome sequencing analysis pipeline that integrates identification of somatic single nucleotide variants (SNVs) and copy number alterations (CNAs) and clonal tracking for both. SuperFreq does not require a matched normal and instead relies on unrelated controls. When analysing multiple samples from a single patient, SuperFreq cross checks variant calls to improve clonal tracking, which helps to separate somatic from germline variants, and to resolve overlapping CNA calls. To demonstrate our software we analysed 304 cancer-normal exome samples across 33 cancer types in The Cancer Genome Atlas (TCGA) and evaluated the quality of the SNV and CNA calls. We simulated clonal evolution through in silico mixing of cancer and normal samples in known proportion. We found that SuperFreq identified 93% of clones with a cellular fraction of at least 50% and mutations were assigned to the correct clone with high recall and precision. In addition, SuperFreq maintained a similar level of performance for most aspects of the analysis when run without a matched normal. SuperFreq is highly versatile and can be applied in many different experimental settings for the analysis of exomes and other capture libraries. We demonstrate an application of SuperFreq to leukaemia patients with diagnosis and relapse samples. SuperFreq is implemented in R and available on github at https://github.com/ChristofferFlensburg/SuperFreq .
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Patient-derived organoids (PDOs) have recently emerged as robust preclinical models; however, their potential to predict clinical outcomes in patients has remained unclear. We report on a living biobank of PDOs from metastatic, heavily pretreated colorectal and gastroesophageal cancer patients recruited in phase 1/2 clinical trials. Phenotypic and genotypic profiling of PDOs showed a high degree of similarity to the original patient tumors. Molecular profiling of tumor organoids was matched to drug-screening results, suggesting that PDOs could complement existing approaches in defining cancer vulnerabilities and improving treatment responses. We compared responses to anticancer agents ex vivo in organoids and PDO-based orthotopic mouse tumor xenograft models with the responses of the patients in clinical trials. Our data suggest that PDOs can recapitulate patient responses in the clinic and could be implemented in personalized medicine programs.
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Identifying genetic biomarkers of synthetic lethal drug sensitivity effects provides one approach to the development of targeted cancer therapies. Mutations in ARID1A represent one of the most common molecular alterations in human cancer, but therapeutic approaches that target these defects are not yet clinically available. We demonstrate that defects in ARID1A sensitize tumour cells to clinical inhibitors of the DNA damage checkpoint kinase, ATR, both in vitro and in vivo. Mechanistically, ARID1A deficiency results in topoisomerase 2A and cell cycle defects, which cause an increased reliance on ATR checkpoint activity. In ARID1A mutant tumour cells, inhibition of ATR triggers premature mitotic entry, genomic instability and apoptosis. The data presented here provide the pre-clinical and mechanistic rationale for assessing ARID1A defects as a biomarker of single-agent ATR inhibitor response and represents a novel synthetic lethal approach to targeting tumour cells.
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COSMIC, the Catalogue of Somatic Mutations in Cancer (http://cancer.sanger.ac.uk) is a high-resolution resource for exploring targets and trends in the genetics of human cancer. Currently the broadest database of mutations in cancer, the information in COSMIC is curated by expert scientists, primarily by scrutinizing large numbers of scientific publications. Over 4 million coding mutations are described in v78 (September 2016), combining genome-wide sequencing results from 28 366 tumours with complete manual curation of 23 489 individual publications focused on 186 key genes and 286 key fusion pairs across all cancers. Molecular profiling of large tumour numbers has also allowed the annotation of more than 13 million non-coding mutations, 18 029 gene fusions, 187 429 genome rearrangements, 1 271 436 abnormal copy number segments, 9 175 462 abnormal expression variants and 7 879 142 differentially methylated CpG dinucleotides. COSMIC now details the genetics of drug resistance, novel somatic gene mutations which allow a tumour to evade therapeutic cancer drugs. Focusing initially on highly characterized drugs and genes, COSMIC v78 contains wide resistance mutation profiles across 20 drugs, detailing the recurrence of 301 unique resistance alleles across 1934 drug-resistant tumours. All information from the COSMIC database is available freely on the COSMIC website.
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Drug sensitivity testing utilizing preclinical disease models such as cancer cell lines is an important and widely used tool for drug development. Importantly, when combined with molecular data such as gene copy number variation or somatic coding mutations, associations between drug sensitivity and molecular data can be used to develop markers to guide patient therapies. The use of organoids as a preclinical cancer model has become possible following recent work demonstrating that organoid cultures can be derived from patient tumors with a high rate of success. A genetic analysis of colon cancer organoids found that these models encompassed the majority of the somatic variants present within the tumor from which it was derived, and capture much of the genetic diversity of colon cancer observed in patients. Importantly, the systematic sensitivity testing of organoid cultures to anticancer drugs identified clinical gene–drug interactions, suggestive of their potential as preclinical models for testing anticancer drug sensitivity. In this chapter, we describe how to perform medium/high-throughput drug sensitivity screens using 3D organoid cell cultures.
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Genome rearrangements, a hallmark of cancer, can result in gene fusions with oncogenic properties. Using DNA paired-end-tag (DNA-PET) whole-genome sequencing, we analyzed 15 gastric cancers (GCs) from Southeast Asians. Rearrangements were enriched in open chromatin and shaped by chromatin structure. We identified seven rearrangement hot spots and 136 gene fusions. In three out of 100 GC cases, we found recurrent fusions between CLDN18, a tight junction gene, and ARHGAP26, a gene encoding a RHOA inhibitor. Epithelial cell lines expressing CLDN18-ARHGAP26 displayed a dramatic loss of epithelial phenotype and long protrusions indicative of epithelial-mesenchymal transition (EMT). Fusion-positive cell lines showed impaired barrier properties, reduced cell-cell and cell-extracellular matrix adhesion, retarded wound healing, and inhibition of RHOA. Gain of invasion was seen in cancer cell lines expressing the fusion. Thus, CLDN18-ARHGAP26 mediates epithelial disintegration, possibly leading to stomach H(+) leakage, and the fusion might contribute to invasiveness once a cell is transformed. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
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Background & aims: We previously established long-term, 3-dimensional culture of organoids from mouse tissues (intestine, stomach, pancreas, and liver) and human intestine and pancreas. Here we describe conditions required for long-term 3-dimensional culture of human gastric stem cells. The technology can be applied to study the epithelial response to infection with Helicobacter pylori. Methods: We generated organoids from surgical samples of human gastric corpus. Culture conditions were developed based on those for the mouse gastric and human intestinal systems. We used microinjection to infect the organoids with H pylori. Epithelial responses were measured using microarray and quantitative polymerase chain reaction analyses. Results: Human gastric cells were expanded indefinitely in 3-dimensional cultures. We cultured cells from healthy gastric tissues, single-sorted stem cells, or tumor tissues. Organoids maintained many characteristics of their respective tissues based on their histology, expression of markers, and euploidy. Organoids from healthy tissue expressed markers of 4 lineages of the stomach and self-organized into gland and pit domains. They could be directed to specifically express either lineages of the gastric gland, or the gastric pit, by addition of nicotinamide and withdrawal of WNT. Although gastric pit lineages had only marginal reactions to bacterial infection, gastric gland lineages mounted a strong inflammatory response. Conclusions: We developed a system to culture human gastric organoids. This system can be used to study H pylori infection and other gastric pathologies.
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Motivation: Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results: To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. Availability and implementation: STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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Objective: Gastric adenocarcinoma (gastric cancer, GC) is a major cause of global cancer mortality. Identifying molecular programmes contributing to GC patient survival may improve our understanding of GC pathogenesis, highlight new prognostic factors and reveal novel therapeutic targets. The authors aimed to produce a comprehensive inventory of gene expression programmes expressed in primary GCs, and to identify those expression programmes significantly associated with patient survival. Design: Using a network-modelling approach, the authors performed a large-scale meta-analysis of GC transcriptome data integrating 940 gastric transcriptomes from multiple independent patient cohorts. The authors analysed a training set of 428 GCs and 163 non-malignant gastric samples, and a validation set of 288 GCs and 61 non-malignant gastric samples. Results: The authors identified 178 gene expression programmes ('modules') expressed in primary GCs, which were associated with distinct biological processes, chromosomal location patterns, cis-regulatory motifs and clinicopathological parameters. Expression of a transforming growth factor β (TGF-β) signalling associated 'super-module' of stroma-related genes consistently predicted patient survival in multiple GC validation cohorts. The proportion of intra-tumoural stroma, quantified by morphometry in tissue sections from gastrectomy specimens, was also significantly associated with stromal super-module expression and GC patient survival. Conclusion: Stromal gene expression predicts GC patient survival in multiple independent cohorts, and may be closely related to the intra-tumoural stroma proportion, a specific morphological GC phenotype. These findings suggest that therapeutic approaches targeting the GC stroma may merit evaluation.
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We describe a computational method that infers tumor purity and malignant cell ploidy directly from analysis of somatic DNA alterations. The method, named ABSOLUTE, can detect subclonal heterogeneity and somatic homozygosity, and it can calculate statistical sensitivity for detection of specific aberrations. We used ABSOLUTE to analyze exome sequencing data from 214 ovarian carcinoma tumor-normal pairs. This analysis identified both pervasive subclonal somatic point-mutations and a small subset of predominantly clonal and homozygous mutations, which were overrepresented in the tumor suppressor genes TP53 and NF1 and in a candidate tumor suppressor gene CDK12. We also used ABSOLUTE to infer absolute allelic copy-number profiles from 3,155 diverse cancer specimens, revealing that genome-doubling events are common in human cancer, likely occur in cells that are already aneuploid, and influence pathways of tumor progression (for example, with recessive inactivation of NF1 being less common after genome doubling). ABSOLUTE will facilitate the design of clinical sequencing studies and studies of cancer genome evolution and intra-tumor heterogeneity.
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Gastric cancer is a heterogeneous disease with multiple environmental etiologies and alternative pathways of carcinogenesis. Beyond mutations in TP53, alterations in other genes or pathways account for only small subsets of the disease. We performed exome sequencing of 22 gastric cancer samples and identified previously unreported mutated genes and pathway alterations; in particular, we found genes involved in chromatin modification to be commonly mutated. A downstream validation study confirmed frequent inactivating mutations or protein deficiency of ARID1A, which encodes a member of the SWI-SNF chromatin remodeling family, in 83% of gastric cancers with microsatellite instability (MSI), 73% of those with Epstein-Barr virus (EBV) infection and 11% of those that were not infected with EBV and microsatellite stable (MSS). The mutation spectrum for ARID1A differs between molecular subtypes of gastric cancer, and mutation prevalence is negatively associated with mutations in TP53. Clinically, ARID1A alterations were associated with better prognosis in a stage-independent manner. These results reveal the genomic landscape, and highlight the importance of chromatin remodeling, in the molecular taxonomy of gastric cancer.
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Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (∼4×) 1000 Genomes Project datasets.
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High-throughput sequencing platforms are generating massive amounts of genetic variation data for diverse genomes, but it remains a challenge to pinpoint a small subset of functionally important variants. To fill these unmet needs, we developed the ANNOVAR tool to annotate single nucleotide variants (SNVs) and insertions/deletions, such as examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1000 Genomes Project and dbSNP. ANNOVAR can utilize annotation databases from the UCSC Genome Browser or any annotation data set conforming to Generic Feature Format version 3 (GFF3). We also illustrate a ‘variants reduction’ protocol on 4.7 million SNVs and indels from a human genome, including two causal mutations for Miller syndrome, a rare recessive disease. Through a stepwise procedure, we excluded variants that are unlikely to be causal, and identified 20 candidate genes including the causal gene. Using a desktop computer, ANNOVAR requires ∼4 min to perform gene-based annotation and ∼15 min to perform variants reduction on 4.7 million variants, making it practical to handle hundreds of human genomes in a day. ANNOVAR is freely available at http://www.openbioinformatics.org/annovar/.
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Gastric cancer is the world's second most common cause of cancer death. We analyzed gene expression patterns in 90 primary gastric cancers, 14 metastatic gastric cancers, and 22 nonneoplastic gastric tissues, using cDNA microarrays representing approximately 30,300 genes. Gastric cancers were distinguished from nonneoplastic gastric tissues by characteristic differences in their gene expression patterns. We found a diversity of gene expression patterns in gastric cancer, reflecting variation in intrinsic properties of tumor and normal cells and variation in the cellular composition of these complex tissues. We identified several genes whose expression levels were significantly correlated with patient survival. The variations in gene expression patterns among cancers in different patients suggest differences in pathogenetic pathways and potential therapeutic strategies.
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Epstein-Barr virus (EBV) was discovered 40 years ago from examining electron micrographs of cells cultured from Burkitt's lymphoma, a childhood tumour that is common in sub-Saharan Africa, where its unusual geographical distribution - which matches that of holoendemic malaria -indicated a viral aetiology. However, far from showing a restricted distribution, EBV - a gamma-herpesvirus - was found to be widespread in all human populations and to persist in the vast majority of individuals as a lifelong, asymptomatic infection of the B-lymphocyte pool. Despite such ubiquity, the link between EBV and 'endemic' Burkitt's lymphoma proved consistent and became the first of an unexpectedly wide range of associations discovered between this virus and tumours.
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The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available¹. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens².
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The recent advances in in vitro 3D culture technologies, such as organoids, have opened new avenues for the development of novel, more physiological human cancer models. Such preclinical models are essential for more efficient translation of basic cancer research into novel treatment regimens for patients with cancer. Wild-type organoids can be grown from embryonic and adult stem cells and display self-organizing capacities, phenocopying essential aspects of the organs they are derived from. Genetic modification of organoids allows disease modelling in a setting that approaches the physiological environment. Additionally, organoids can be grown with high efficiency from patient-derived healthy and tumour tissues, potentially enabling patient-specific drug testing and the development of individualized treatment regimens. In this Review, we evaluate tumour organoid protocols and how they can be utilized as an alternative model for cancer research.
Article
Objective: Serrated polyps (hyperplastic polyps, sessile or traditional serrated adenomas), which can arise in a sporadic or polyposis setting, predispose to colorectal cancer (CRC), especially those with microsatellite instability (MSI) due to MLH1 promoter methylation (MLH1(me+)). We investigate genetic alterations in the serrated polyposis pathway. Design: We used a combination of exome sequencing and target gene Sanger sequencing to study serrated polyposis families, sporadic serrated polyps and CRCs, with validation by analysis of The Cancer Genome Atlas (TCGA) cohort, followed by organoid-based functional studies. Results: In one out of four serrated polyposis families, we identified a germline RNF43 mutation that displayed autosomal dominant cosegregation with the serrated polyposis phenotype, along with second-hit inactivation through loss of heterozygosity or somatic mutations in all serrated polyps (16), adenomas (5) and cancer (1) examined, as well as coincidental BRAF mutation in 62.5% of the serrated polyps. Concurrently, somatic RNF43 mutations were identified in 34% of sporadic sessile/traditional serrated adenomas, but 0% of hyperplastic polyps (p=0.013). Lastly, in MSI CRCs, we found significantly more frequent RNF43 mutations in the MLH1(me+) (85%) versus MLH1(me-) (33.3%) group (p<0.001). These findings were validated in the TCGA MSI CRCs (p=0.005), which further delineated a significant differential involvement of three Wnt pathway genes between these two groups (RNF43 in MLH1(me+); APC and CTNNB1 in MLH1(me-)); and identified significant co-occurrence of BRAF and RNF43 mutations in the MSI (p<0.001), microsatellite stable (MSS) (p=0.002) and MLH1(me+) MSI CRCs (p=0.042). Functionally, organoid culture of serrated adenoma or mouse colon with CRISPR-induced RNF43 mutations had reduced dependency on R-spondin1. Conclusions: These results illustrate the importance of RNF43, along with BRAF mutation in the serrated neoplasia pathway (both the sporadic and familial forms), inform genetic diagnosis protocol and raise therapeutic opportunities through Wnt inhibition in different stages of evolution of serrated polyps.
Article
The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs.
Article
The latent expression pattern of Epstein-Barr Virus (EBV) genes in nasopharyngeal carcinoma (NPC) has been extensively investigated, and the expression of several lytic genes in NPC has been reported. However, comprehensive information through EBV transcriptome analysis in NPC is limited. We performed paired-end RNA-seq to systematically and comprehensively characterize the expression of EBV genes in NPC tissue and C666-1 NPC cell line, which consistently carries EBV. In addition to the transcripts restricted to type II latency infection, the type III latency EBNA3s genes and a substantial number of lytic genes, such as BZLF1, BRLF1, and BMRF1, were detected through RNA-seq and were further verified in C666-1 cells and NPC tissue through realtime PCR.We also performed clustering analysis to classify NPC patient groups in terms of EBV gene expression, which presented two subtypes of NPC samples. Results revealed interesting patterns of EBV gene expression in NPC patients. This clustering was correlated with many signaling pathways, such as those related to heterotrimeric G-protein signaling, inflammation mediated by chemokine and cytokine signaling, ribosomes, protein metabolism, influenza infection, and ECM-receptor interaction. Our combined findings suggested that the expression of EBV genes in NPC is restricted not only to type II latency genes but also to type III latency and lytic genes. This study provided further insights into the potential role of EBV in the development of NPC.
Article
In Rspondin-based 3D cultures, Lgr5 stem cells from multiple organs form ever-expanding epithelial organoids that retain their tissue identity. We report the establishment of tumor organoid cultures from 20 consecutive colorectal carcinoma (CRC) patients. For most, organoids were also generated from adjacent normal tissue. Organoids closely recapitulate several properties of the original tumor. The spectrum of genetic changes within the "living biobank" agrees well with previous large-scale mutational analyses of CRC. Gene expression analysis indicates that the major CRC molecular subtypes are represented. Tumor organoids are amenable to high-throughput drug screens allowing detection of gene-drug associations. As an example, a single organoid culture was exquisitely sensitive to Wnt secretion (porcupine) inhibitors and carried a mutation in the negative Wnt feedback regulator RNF43, rather than in APC. Organoid technology may fill the gap between cancer genetics and patient trials, complement cell-line- and xenograft-based drug studies, and allow personalized therapy design. PAPERCLIP. Copyright © 2015 Elsevier Inc. All rights reserved.
Article
Gastric cancer, a leading cause of cancer-related deaths, is a heterogeneous disease. We aim to establish clinically relevant molecular subtypes that would encompass this heterogeneity and provide useful clinical information. We use gene expression data to describe four molecular subtypes linked to distinct patterns of molecular alterations, disease progression and prognosis. The mesenchymal-like type includes diffuse-subtype tumors with the worst prognosis, the tendency to occur at an earlier age and the highest recurrence frequency (63%) of the four subtypes. Microsatellite-unstable tumors are hyper-mutated intestinal-subtype tumors occurring in the antrum; these have the best overall prognosis and the lowest frequency of recurrence (22%) of the four subtypes. The tumor protein 53 (TP53)-active and TP53-inactive types include patients with intermediate prognosis and recurrence rates (with respect to the other two subtypes), with the TP53-active group showing better prognosis. We describe key molecular alterations in each of the four subtypes using targeted sequencing and genome-wide copy number microarrays. We validate these subtypes in independent cohorts in order to provide a consistent and unified framework for further clinical and preclinical translational research.
Article
Gastric cancer is a heterogeneous disease with diverse molecular and histological subtypes. We performed whole-genome sequencing in 100 tumor-normal pairs, along with DNA copy number, gene expression and methylation profiling, for integrative genomic analysis. We found subtype-specific genetic and epigenetic perturbations and unique mutational signatures. We identified previously known (TP53, ARID1A and CDH1) and new (MUC6, CTNNA2, GLI3, RNF43 and others) significantly mutated driver genes. Specifically, we found RHOA mutations in 14.3% of diffuse-type tumors but not in intestinal-type tumors (P < 0.001). The mutations clustered in recurrent hotspots affecting functional domains and caused defective RHOA signaling, promoting escape from anoikis in organoid cultures. The top perturbed pathways in gastric cancer included adherens junction and focal adhesion, in which RHOA and other mutated genes we identified participate as key players. These findings illustrate a multidimensional and comprehensive genomic landscape that highlights the molecular complexity of gastric cancer and provides a road map to facilitate genome-guided personalized therapy.
Article
Unlabelled: Cancer is a genetic disease with frequent somatic DNA alterations. Studying recurrent copy number aberrations (CNAs) in human cancers would enable the elucidation of disease mechanisms and the prioritization of candidate oncogenic drivers with causal roles in oncogenesis. We have comprehensively and systematically characterized CNAs and the accompanying gene expression changes in tumors and matched nontumor liver tissues from 286 hepatocellular carcinoma (HCC) patients. Our analysis identified 29 recurrently amplified and 22 recurrently deleted regions with a high level of copy number changes. These regions harbor established oncogenes and tumor suppressors, including CCND1 (cyclin D1), MET (hepatocyte growth factor receptor), CDKN2A (cyclin-dependent kinase inhibitor 2A) and CDKN2B (cyclin-dependent kinase inhibitor 2B), as well as many other genes not previously reported to be involved in liver carcinogenesis. Pathway analysis of cis-acting genes in the amplification and deletion peaks implicates alterations of core cancer pathways, including cell-cycle, p53 signaling, phosphoinositide 3-kinase signaling, mitogen-activated protein kinase signaling, Wnt signaling, and transforming growth factor beta signaling, in a large proportion of HCC patients. We further credentialed two candidate driver genes (BCL9 and MTDH) from the recurrent focal amplification peaks and showed that they play a significant role in HCC growth and survival. Conclusion: We have demonstrated that characterizing the CNA landscape in HCC will facilitate the understanding of disease mechanisms and the identification of oncogenic drivers that may serve as potential therapeutic targets for the treatment of this devastating disease.
Article
Whole genome and exome sequencing of matched tumor-normal sample pairs is becoming routine in cancer research. The consequent increased demand for somatic variant analysis of paired samples requires methods specialized to model this problem so as to sensitively call variants at any practical level of tumor impurity. We describe Strelka, a method for somatic SNV and small indel detection from sequencing data of matched tumor-normal samples. The method uses a novel Bayesian approach which represents continuous allele frequencies for both tumor and normal samples, while leveraging the expected genotype structure of the normal. This is achieved by representing the normal sample as a mixture of germline variation with noise, and representing the tumor sample as a mixture of the normal sample with somatic variation. A natural consequence of the model structure is that sensitivity can be maintained at high tumor impurity without requiring purity estimates. We demonstrate that the method has superior accuracy and sensitivity on impure samples compared with approaches based on either diploid genotype likelihoods or general allele-frequency tests. The Strelka workflow source code is available at ftp://strelka@ftp.illumina.com/. csaunders@illumina.com
Article
The ability to successfully cryopreserve neural cells would represent an important advance with benefits to neural tissue engineering, neural transplantation, and neuroscience research. We have examined key factors responsible for damage to rat embryonic neural cells during cryopreservation using a two-step temperature profile, with an emphasis on the effects of cooling rate and plunge temperature. Our results indicate that the initial addition of 8% dimethyl sulfoxide (DMSO) and seeding of extracellular ice do not significantly decrease viable cell yield. However, subsequent freezing resulted in significant cell losses for all profile parameter combinations examined. A maximum post-thaw survival of 56% (compared to unfrozen controls) was observed after cooling at 2°C/min to -80°C followed by direct immersion in liquid nitrogen. Single-step removal of DMSO after thawing was associated with an additional 40-70% loss of viable cells, and the number of viable cells was further reduced by approximately 70% after 2 days of cell culture (resulting in a net viable cell yield of 9.6±0.4%). Nonetheless, the cryopreserved neurons that did survive displayed a normal morphology, including formation of neurites. Trends in neuronal viability conformed with predictions of existing theoretical models of cell freezing, with reduced survival for rapid cooling rates or high plunge temperatures (attributable to intracellular ice formation), and decreasing viability with increasing profile duration (consistent with the known effects of cell dehydration at suboptimal cooling rates). These observations suggest that neural cells are good candidates for further refinement of freezing profile design using a physics-based approach to parameter optimization.
Article
Epstein-Barr virus (EBV) may be a cofactor in the development of different malignancies, including several types of carcinomas. In this study, we investigated the presence of EBV in human breast cancers. We used tissues from 100 consecutive primary invasive breast carcinomas, as well as 30 healthy tissues adjacent to a subset of the tumors. DNA was amplified by use of the polymerase chain reaction (PCR), with the primers covering three different regions of the EBV genome. Southern blot analysis was performed by use of a labeled EBV BamHI W restriction fragment as the probe. Infected cells were identified by means of immunohistochemical staining, using monoclonal antibodies directed against the EBV nuclear protein EBNA-1. We were able to detect the EBV genome by PCR in 51% of the tumors, whereas, in 90% of the cases studied, the virus was not detected in healthy tissue adjacent to the tumor (P<.001). The presence of the EBV genome in breast tumors was confirmed by Southern blot analysis. The observed EBNA-1 expression was restricted to a fraction (5%-30%) of tumor epithelial cells. Moreover, no immunohistochemical staining was observed in tumors that were negative for EBV by PCR. EBV was detected more frequently in breast tumors that were hormone-receptor negative (P =.01) and those of high histologic grade (P =.03). EBV detection in primary tumors varied by nodal status (P =.01), largely because of the difference between subjects with more than three lymph nodes versus less than or equal to three lymph nodes involved (72% versus 44%). Our results demonstrated the presence of the EBV genome in a large subset of breast cancers. The virus was restricted to tumor cells and was more frequently associated with the most aggressive tumors. EBV may be a cofactor in the development of some breast cancers.
Article
Open source software encourages innovation by allowing users to extend the functionality of existing applications. Treeview is a popular application for the visualization of microarray data, but is closed-source and platform-specific, which limits both its current utility and suitability as a platform for further development. Java Treeview is an open-source, cross-platform rewrite that handles very large datasets well, and supports extensions to the file format that allow the results of additional analysis to be visualized and compared. The combination of a general file format and open source makes Java Treeview an attractive choice for solving a class of visualization problems. An applet version is also available that can be used on any website with no special server-side setup. Availability: http://jtreeview.sourceforge.net under GPL.
Comprehensive molecular characterization of gastric adenocarcinoma
Cancer Genome Atlas Research Network (2014). Comprehensive molecular characterization of gastric adenocarcinoma. Nature 513, 202-209.
organoids/mL, equivalent to around 480-640 organoids per well), with error bars representing ±SD. See Mendeley Dataset 15 for all other drugs
organoids/mL, equivalent to around 480-640 organoids per well), with error bars representing ±SD. See Mendeley Dataset 15 for all other drugs.
Each data point is the 1-AUC for a drug used to treat that organoid. Drugs with an IC 50 below the patient steady-state plasma concentration (Css) in two biological runs are highlighted and labeled according to the legend in each graph
Representative scatterplots of 1-AUC values from two biological replicates (two different passages) of the drug screening data. Each data point is the 1-AUC for a drug used to treat that organoid. Drugs with an IC 50 below the patient steady-state plasma concentration (Css) in two biological runs are highlighted and labeled according to the legend in each graph. See Mendeley Dataset 16 for the full set.
The subclonal architecture of metastatic breast cancer: results from a prospective community-based rapid autopsy program
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  • Z L Teo
  • C Lefevre
  • C Flensburg
  • F Caramia
  • K Alsop
  • M Mansour
  • P A Francis
  • H A Thorne
  • M J Silva
Savas, P., Teo, Z.L., Lefevre, C., Flensburg, C., Caramia, F., Alsop, K., Mansour, M., Francis, P.A., Thorne, H.A., Silva, M.J., et al. (2016). The subclonal architecture of metastatic breast cancer: results from a prospective community-based rapid autopsy program ''CASCADE''. PLoS Med. 13, e1002204. Seidlitz, T., Merker, S.R., Rothe, A., Zakrzewski, F., von Neubeck, C., Gr€ utzmann, K., Sommer, U., Schweitzer, C., Schö lch, S., Uhlemann, H., et al. (2018). Human gastric cancer modelling using organoids. Gut. Published online April 27, 2018. https://doi.org/10.1136/gutjnl-2017-314549.