Balázs Gyorffy

University of Bradford, Bradford, ENG, United Kingdom

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Publications (30)68.54 Total impact

  • Zsofia Penzvalto, Pawel Surowiak, Balazs Gyorffy
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    ABSTRACT: Epithelial ovarian cancer (EOC) is the most deadly tumor of the female reproductive system. Despite improvements in understanding the biology of EOC, therapeutic strategies still depend on surgery and combination of taxane and platinum agents. Here, we provide a summary of clinically tested biomarkers potentially useful to predict drug response. Resistance against platinum derivatives can result from lower drug concentrations, alterations in the target molecule and changes in the cellular signal transduction pathways. Taxane resistance can develop due to decreased intracellular drug concentration, alterations in microtubuli structure and changes in the cellular response including ERBB2 (epidermal growth factor receptor 2). A few key genes have been suggested as biomarkers for hormonal therapy. Currently, the only targeted therapy agent approved for ovarian cancer is the VEGF (vascular endothelial growth factor) inhibitor bevacizumab. Response to bevacizumab is correlated with VEGF-A levels and hypertension. The primary problems in identifying reliable biomarkers for EOC are the usage of different clinical endpoints, multivariate analysis for a panel of clinical parameters and the lack of published comprehensive clinical information of patients enrolled in these studies. The future lies in adding targeted agents to the taxane/platinum gold standard and in a more detailed stratification of patients into sub-cohorts enabling a more effective therapy. In conclusion, a large-scale coordinated effort is needed for the robust validation of the numerous biomarker candidates available in EOC therapy.
    Current cancer drug targets 03/2014; · 5.13 Impact Factor
  • Zsuzsanna Mihály, Balázs Gyõrffy
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    ABSTRACT: In the last decade, the targeted therapy of breast cancer became part of routine clinical protocols all over the globe. Options in today's targeted therapy include hormonal therapy and the modulation of the EGFR/HER-pathway. Of the four HER receptors, HER2 is the target of currently used treatment strategies. HER2 activates multiple intracellular pathways via RAS, RAF and PI3K. We give a comprehensive summary of approved monoclonal antibodies and tyrosine kinase inhibitors acting over HER2, including trastuzumab, lapatinib and pertuzumab. We elaborate on their mechanism of action and on clinical trials behind their approval. Agents in third phase clinical studies (neratinib, afatinib) are also described. We give a brief overview of agents currently in phase I and phase II studies; these are acting over the PI3K pathway, over IGFR1 and over HSP90. Furthermore, currently validated negative biomarkers (markers predicting lack of response) in clinical use are also summarized. Finally, the major bottlenecks of clinical application including tumor heterogeneity and the high diversity of clinical studies are discussed. For a breakthrough we will need to identify new positive biomarkers of therapy response.
    Magyar Onkológia 10/2013; 57(3):147-156.
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    ABSTRACT: Malignant melanoma biologically can be divided into non-metastatic and metastatic forms which cannot be predicted precisely using classical clinicopathological parameters, therefore studies on novel genetic or protein markers are abundant in the literature. These studies did not result in clinically useful markers because mostly ignored the results of studies on the genetic basis of metastatic potential of malignant melanoma. Accordingly, the list of promising novel markers is short (BCL2, CDK2, MART-1, OPN). Similar to other solid malignancies, introduction of targeted therapy into clinical practice of melanoma turned the attention toward the genetic basis of resistance to chemo- and targeted therapies. These novel data could lead to the development of molecular diagnostics which can help in designing more effective therapeutic strategies of malignant melanoma.
    Magyar Onkológia 06/2013; 57(2):79-83.
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    ABSTRACT: The estrogen receptor (ER)α drives growth in two-thirds of all breast cancers. Several targeted therapies, collectively termed endocrine therapy, impinge on estrogen-induced ERα activation to block tumor growth. However, half of ERα-positive breast cancers are tolerant or acquire resistance to endocrine therapy. We demonstrate that genome-wide reprogramming of the chromatin landscape, defined by epigenomic maps for regulatory elements or transcriptional activation and chromatin openness, underlies resistance to endocrine therapy. This annotation reveals endocrine therapy-response specific regulatory networks where NOTCH pathway is overactivated in resistant breast cancer cells, whereas classical ERα signaling is epigenetically disengaged. Blocking NOTCH signaling abrogates growth of resistant breast cancer cells. Its activation state in primary breast tumors is a prognostic factor of resistance in endocrine treated patients. Overall, our work demonstrates that chromatin landscape reprogramming underlies changes in regulatory networks driving endocrine therapy resistance in breast cancer.
    Proceedings of the National Academy of Sciences 04/2013; · 9.81 Impact Factor
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    ABSTRACT: Conventional chemotherapy not only kills tumor cells but also changes gene expression in treatment-damaged tissues, inducing production of multiple tumor-supporting secreted factors. This secretory phenotype was found here to be mediated in part by a damage-inducible cell-cycle inhibitor p21 (CDKN1A). We developed small-molecule compounds that inhibit damage-induced transcription downstream of p21. These compounds were identified as selective inhibitors of a transcription-regulating kinase CDK8 and its isoform CDK19. Remarkably, p21 was found to bind to CDK8 and stimulate its kinase activity. p21 and CDK8 also cooperate in the formation of internucleolar bodies, where both proteins accumulate. A CDK8 inhibitor suppresses damage-induced tumor-promoting paracrine activities of tumor cells and normal fibroblasts and reverses the increase in tumor engraftment and serum mitogenic activity in mice pretreated with a chemotherapeutic drug. The inhibitor also increases the efficacy of chemotherapy against xenografts formed by tumor cell/fibroblast mixtures. Microarray data analysis revealed striking correlations between CDK8 expression and poor survival in breast and ovarian cancers. CDK8 inhibition offers a promising approach to increasing the efficacy of cancer chemotherapy.
    Proceedings of the National Academy of Sciences 08/2012; 109(34):13799-804. · 9.81 Impact Factor
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    ABSTRACT: Chemotherapy and immunotherapy failed to deliver decisive results in the systemic treatment of metastatic renal cell carcinoma. Agents representing the current standards operate on members of the RAS signal transduction pathway. Sunitinib (targeting vascular endothelial growth factor), temsirolimus (an inhibitor of the mammalian target of rapamycin - mTOR) and pazopanib (a multi-targeted receptor tyrosine kinase inhibitor) are used in the first line of recurrent disease. A combination of bevacizumab (inhibition of angiogenesis) plus interferon α is also first-line therapy. Second line options include everolimus (another mTOR inhibitor) as well as tyrosine kinase inhibitors for patients who previously received cytokine. We review the results of clinical investigations focusing on survival benefit for these agents. Additionally, trials focusing on new agents, including the kinase inhibitors axitinib, tivozanib, dovitinib and cediranib and monoclonal antibodies including velociximab are also discussed. In addition to published outcomes we also include follow-up and interim results of ongoing clinical trials. In summary, we give a comprehensive overview of current advances in the systemic treatment of metastatic renal cell carcinoma.
    Current cancer drug targets 04/2012; 12(7):857-72. · 5.13 Impact Factor
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    ABSTRACT: The validation of prognostic biomarkers in large independent patient cohorts is a major bottleneck in ovarian cancer research. We implemented an online tool to assess the prognostic value of the expression levels of all microarray-quantified genes in ovarian cancer patients. First, a database was set up using gene expression data and survival information of 1287 ovarian cancer patients downloaded from Gene Expression Omnibus and The Cancer Genome Atlas (Affymetrix HG-U133A, HG-U133A 2.0, and HG-U133 Plus 2.0 microarrays). After quality control and normalization, only probes present on all three Affymetrix platforms were retained (n=22,277). To analyze the prognostic value of the selected gene, we divided the patients into two groups according to various quantile expressions of the gene. These groups were then compared using progression-free survival (n=1090) or overall survival (n=1287). A Kaplan-Meier survival plot was generated and significance was computed. The tool can be accessed online at www.kmplot.com/ovar. We used this integrative data analysis tool to validate the prognostic power of 37 biomarkers identified in the literature. Of these, CA125 (MUC16; P=3.7×10(-5), hazard ratio (HR)=1.4), CDKN1B (P=5.4×10(-5), HR=1.4), KLK6 (P=0.002, HR=0.79), IFNG (P=0.004, HR=0.81), P16 (P=0.02, HR=0.66), and BIRC5 (P=0.00017, HR=0.75) were associated with survival. The combination of several probe sets can further increase prediction efficiency. In summary, we developed a global online biomarker validation platform that mines all available microarray data to assess the prognostic power of 22,277 genes in 1287 ovarian cancer patients. We specifically used this tool to evaluate the effect of 37 previously published biomarkers on ovarian cancer prognosis.
    Endocrine Related Cancer 01/2012; 19(2):197-208. · 5.26 Impact Factor
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    ABSTRACT: Developing chemotherapy resistant cell lines can help to identify markers of resistance. Instead of using a panel of highly heterogeneous cell lines, we assumed that truly robust and convergent pattern of resistance can be identified in multiple parallel engineered derivatives of only a few parental cell lines. Parallel cell populations were initiated for two breast cancer cell lines (MDA-MB-231 and MCF-7) and these were treated independently for 18 months with doxorubicin or paclitaxel. IC50 values against 4 chemotherapy agents were determined to measure cross-resistance. Chromosomal instability and karyotypic changes were determined by cytogenetics. TaqMan RT-PCR measurements were performed for resistance-candidate genes. Pgp activity was measured by FACS. All together 16 doxorubicin- and 13 paclitaxel-treated cell lines were developed showing 2-46 fold and 3-28 fold increase in resistance, respectively. The RT-PCR and FACS analyses confirmed changes in tubulin isofom composition, TOP2A and MVP expression and activity of transport pumps (ABCB1, ABCG2). Cytogenetics showed less chromosomes but more structural aberrations in the resistant cells. We surpassed previous studies by parallel developing a massive number of cell lines to investigate chemoresistance. While the heterogeneity caused evolution of multiple resistant clones with different resistance characteristics, the activation of only a few mechanisms were sufficient in one cell line to achieve resistance.
    PLoS ONE 01/2012; 7(2):e30804. · 3.53 Impact Factor
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    ABSTRACT: Interpretation of gene expression microarrays requires a mapping from probe set to gene. On many Affymetrix gene expression microarrays, a given gene may be detected by multiple probe sets, which may deliver inconsistent or even contradictory measurements. Therefore, obtaining an unambiguous expression estimate of a pre-specified gene can be a nontrivial but essential task. We developed scoring methods to assess each probe set for specificity, splice isoform coverage, and robustness against transcript degradation. We used these scores to select a single representative probe set for each gene, thus creating a simple one-to-one mapping between gene and probe set. To test this method, we evaluated concordance between protein measurements and gene expression values, and between sets of genes whose expression is known to be correlated. For both test cases, we identified genes that were nominally detected by multiple probe sets, and we found that the probe set chosen by our method showed stronger concordance. This method provides a simple, unambiguous mapping to allow assessment of the expression levels of specific genes of interest.
    BMC Bioinformatics 12/2011; 12:474. · 3.02 Impact Factor
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    ABSTRACT: The elevated expression of claudins (CLDN) and E-cadherin (CDH-1) was found to correlate with poor prognostic features. Our aim was to perform a comprehensive analysis to assess their potential to predict prognosis in breast cancer. The expression of CLDN-1, -3-5, -7, -8, -10, -15, -18, and E-cadherin at the mRNA level was evaluated in correlation with survival in datasets containing expression measurements of 1809 breast cancer patients. The breast cancer tissues of 197 patients were evaluated with tissue microarray technique and immunohistochemical method for CLDN-1-5, -7, and E-cadherin protein expression. An additional validation set of 387 patients was used to test the accuracy of the resulting prognostic score. Based on the bioinformatic screening of publicly-available datasets, the metagene of CLDN-3, -4, -7, and E-cadherin was shown to have the most powerful predictive power in the survival analyses. An immunohistochemical protein profile consisting of CLDN-2, -4, and E-cadherin was able to predict outcome in the most effective manner in the training set. Combining the overlapping members of the above two methods resulted in the claudin-4 and E-cadherin score (CURIO), which was able to accurately predict relapse-free survival in the validation cohort (P = 0.029). The multivariate analysis, including clinicopathological variables and the CURIO, showed that the latter kept its predictive power (P = 0.040). Furthermore, the CURIO was able to further refine prognosis, separating good versus poor prognosis subgroups in luminal A, luminal B, and triple-negative breast cancer intrinsic subtypes. In breast cancer, the CURIO provides additional prognostic information besides the routinely utilized diagnostic approaches and factors.
    Cancer Science 08/2011; 102(12):2248-54. · 3.48 Impact Factor
  • European Journal of Cancer - EUR J CANCER. 01/2011; 47.
  • European Journal of Cancer - EUR J CANCER. 01/2011; 47.
  • Zsuzsanna Mihály, Balázs Gyorffy
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    ABSTRACT: In the past ten years the development of next generation sequencing technologies brought a new era in the field of quick and efficient DNA sequencing. In our study we give an overview of the methodological achievements from Sanger's chain-termination sequencing in 1975 to those allowing real-time DNA sequencing today. Sequencing methods that utilize clonal amplicons for parallel multistrand sequencing comprise the basics of currently available next generation sequencing techniques. Nowadays next generation sequencing is mainly used for basic research in functional genomics, providing quintessential information in the meta-analyses of data from signal transduction pathways, onthologies, proteomics and metabolomics. Although next generation sequencing is yet sparsely used in clinical practice, cardiology, oncology and epidemiology already show an immense need for the additional knowledge obtained by this new technology. The main barrier of its spread is the lack of standardization of analysis evaluation methods, which obscure objective assessment of the results.
    Orvosi Hetilap 01/2011; 152(2):55-62.
  • József Tímár, Balázs Gyorffy, Erzsébet Rásó
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    ABSTRACT: It was expected that with the advent of genomics, oncology may defeat the deadliest forms of cancer including malignant melanoma, but the past years have indicated that this is not the case. Despite the stunning success of genomics in defining markers or gene signatures for breast cancer prognosis and predicting therapies, there is virtually no progression in malignant melanoma. This is happening when experimental oncology or metastasis research is using several rodent and human melanoma models, when our knowledge on the metastatic cascade is actually derived from these models. Our critical analysis of these studies revealed several factors which might be responsible for this failure. First, it is evident, that these studies must be based on rigorous sample collection and basic pathological considerations, where divergent histological types of melanoma cannot be analysed universally. Secondly, without following basic consideration of metastasis biology, the majority of these studies were rarely based on primary tumors but frequently on various types of regional metastases. Third, successful expression profiling studies on other tumors such as breast cancer, provided evidences that the homogeneity of the patient cohort at least by clinicopathological stage is a critical element when defining prognostic signatures. Four studies attempted to define the prognostic signature of skin melanoma but only one based the study on the primary tumor resulting in heterogenous signatures with a minimal overlap (MCM3 and NFKBIZ). Four study attempted to define the invasiveness-signature in the primary tumor based on thickness or growth pattern discrimination identifying a 9-gene overlap which proved to be different from the prognostic signatures. On the other hand, seven studies analyzed various types of metastatic tissues (rarely visceral-, mostly cutaneous or lymphatic metastases) to define the metastasis-signatures, again with minimal overlap (AQP3, LGALS7 and SFN). Using seven GEO-based melanoma datasets we have performed a meta-analysis of the metastasis-gene signatures using normalization protocols. This analysis identified a 350-gene signature, the core of which was a 17-gene signature characterizing locoregional metastases where the individual components occurred in 3 studies: several members of this signature were extensively studied before in context of melanoma metastasis including WNT5A, EGFR, BCL2A1 and OPN. These data suggest that only efficient inter-disciplinary collaboration throughout genomic analysis of human skin melanoma could lead to major advances in defining relevant gene-sets appropriate for clinical prognostication or revealing basic molecular pathways of melanoma progression.
    Clinical and Experimental Metastasis 02/2010; 27(6):371-87. · 3.46 Impact Factor
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    ABSTRACT: The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding of molecular mechanisms driving resistance to anti-angiogenesis agents, the current limitations of laboratory and clinical trial strategies and how the PREDICT consortium will endeavor to identify a new generation of predictive biomarkers.
    Genome Medicine 01/2010; 2(8):53. · 4.94 Impact Factor
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    ABSTRACT: Patient tailored therapy will serve the fundamentals of future cancer treatment. For this it will be imperative to characterize the tumor and to acquire precise predictive and prognostic information. We can achieve this by using not only monogenic (like ER, PR, HER-2, Ki-67) but also multigene assays, which can provide answers to several diagnostic questions simultaneously. We present a summary of currently available RT-PCR and microarray based multigene tests including MammaPrint, Oncotype DX, BLN Assay, Theros Breast Cancer Index SM, MapQuant DX, ARUP Breast Bioclassifier, Celera Metastatic Score, eXagen BCtm, Invasive Gene Signature, Wound Response Indicator and Mammostrat. Two of these (Oncotype DX and MammaPrint) are already incorporated in several diagnostic protocols. However, multiple unsolved issues deteriorate the value of these tests: generally the validation is poor, the gene sets do not confirm each other, the associated costs are high and the necessary bioinformatics is highly complex.
    Magyar Onkológia 12/2009; 53(4):351-9.
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    ABSTRACT: Several preprocessing algorithms for Affymetrix gene expression microarrays have been developed, and their performance on spike-in data sets has been evaluated previously. However, a comprehensive comparison of preprocessing algorithms on samples taken under research conditions has not been performed. We used TaqMan RT-PCR arrays as a reference to evaluate the accuracy of expression values from Affymetrix microarrays in two experimental data sets: one comprising 84 genes in 36 colon biopsies, and the other comprising 75 genes in 29 cancer cell lines. We evaluated consistency using the Pearson correlation between measurements obtained on the two platforms. Also, we introduce the log-ratio discrepancy as a more relevant measure of discordance between gene expression platforms. Of nine preprocessing algorithms tested, PLIER+16 produced expression values that were most consistent with RT-PCR measurements, although the difference in performance between most of the algorithms was not statistically significant. Our results support the choice of PLIER+16 for the preprocessing of clinical Affymetrix microarray data. However, other algorithms performed similarly and are probably also good choices.
    PLoS ONE 02/2009; 4(5):e5645. · 3.53 Impact Factor
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    ABSTRACT: Chronic Helicobacter pylori infection affects approximately half of the world, leads to chronic gastritis and peptic ulceration, and is linked to gastric carcinoma. Our aims were to compare the gene expression profile (GEP) of H. pylori-positive and H. pylori-negative gastric erosions and adjacent mucosa to explain the possible role and response to H. pylori infection and to get erosion-related mRNA expression patterns. Total RNA was extracted, amplified, and biotinylated from gastric biopsies of patients with H. pylori-positive and H. pylori-negative antrum erosions (ER) (8/8) and adjacent macroscopically normal mucosae (8/8). The GEP was evaluated using HGU133plus2.0 microarrays. Two independent normalizations (MAS5.0, RMA), PAM feature selection, hierarchical cluster analysis, and discriminant analysis were done. The expression of 14 genes was also measured by real-time-polymerase chain reaction. VCAM-1 and CXCL13 immunohistochemistry (IHC) was done. In H. pylori infection, significant overexpression of MHC class II antigen-presenting genes, interleukin-7 receptor, ubiquitin-D, CXCR4, lactoferrin immune response-related genes, CXCL-2 and -13, CCL18 chemokine ligand, and VCAM-1 genes were established. In erosive gastritis, increased proliferation (MET) and transport (UCP2, SCFD1, KPNA4) were found, while genes associated with adhesion (SIGLEC11), transcription regulation (ESRRG), and electron and ion transport (ACADM, CLIC6) were down-regulated. Discriminant analysis successfully classified all samples into four groups (HP+ER-, HP+ER+, HP-ER+, HP-ER-) using a reduced gene set (20). Significant overexpression of VCAM-1 and CXC13 protein was detected by IHC in HP+ samples (p < .05). Whole genomic microarray analysis yielded new H. pylori infection and erosion-related gene expression changes. Discriminative genes can be used in mRNA-based diagnostic classification of gastric biopsies.
    Helicobacter 05/2008; 13(2):112-26. · 3.51 Impact Factor
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    ABSTRACT: RNA interference is a type of posttranscriptional gene silencing, when short RNA molecules suppress the function of RNAs and block gene expression. Double-stranded RNAs or short interfering RNAs injected into cells activate the RNA-induced silencing complex which degrades the target messenger RNA. The short RNAs produced inside the cell are called micro RNAs. These form a hairpin and then have the same function as double-stranded RNAs. RNA interference is an evolutionary important mechanism having a role in the protection against transposon and viral infection and regulate gene expression. While a number of studies demonstrate the in vivo applicability of RNAi, the first potential clinical trials are arising. So far it has been used to treat viral infections, inhibit macula degeneration, decrease the level of cholesterol in blood, treat cancer and neurodegenerative diseases. However, its application is hampered by ineffective bioinformatics algorithms unable to design effective short interfering RNAs, by low delivery efficiency and by the limited use to temporary antagonist gene silencing. The most important advantage of its application is the exceptional specificity resulting minimal side-effects. For this reason therapies based on RNA interference can be expected to spread in the near future.
    Orvosi Hetilap 12/2007; 148(47):2235-40.
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    ABSTRACT: Discrimination and classification of colorectal diseases (adenoma, colorectal cancer, inflammatory bowel disease) using biopsy samples and expression microarrays, has not been solved yet, nevertheless, it can contribute to the understanding of the colonic diseases. Total ribonucleic acid was extracted, amplified and biotinylated from frozen colonic biopsies of 15 patients with colorectal cancer, 15 with adenoma, 14 with inflammatory bowel disease and 8 normal controls. Genome-wide gene expression profile was evaluated by Human Genome U133 Plus 2.0 microarrays. Two independent methods were used for data normalization and "Prediction Analysis of Microarrays" was performed for feature selection. Leave one-out stepwise discriminant analysis was performed. The expression results were verified by real-time polymerase chain reaction. Top validated genes included CD44 antigen, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; collagen IValpha1, lipocalin-2, calumenin, aquaporin-8 genes in colorectal cancer; and lipocalin-2, ubiquitin D and interferon induced transmembrane protein 2 genes in inflammatory bowel disease. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes. The expression of 94% of the 52 genes measured by Taqman real-time polymerase chain reaction correlated with the results obtained using Affymetrix microarrays at a significance of p < 0.05. We successfully performed whole genomic microarray analysis to identify discriminative signatures using routine biopsy samples. The results set up data warehouse which can be further mined.
    Orvosi Hetilap 11/2007; 148(44):2067-79.

Publication Stats

207 Citations
68.54 Total Impact Points

Institutions

  • 2012
    • University of Bradford
      • Institute of Cancer Therapeutics
      Bradford, ENG, United Kingdom
  • 2008–2012
    • Hungarian Academy of Sciences
      Budapeŝto, Budapest, Hungary
  • 2006–2012
    • Semmelweis University
      • First Department of Internal Medicine
      Budapeŝto, Budapest, Hungary