Balázs Györffy

Semmelweis University, Budapeŝto, Budapest, Hungary

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Publications (48)186.21 Total impact

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    ABSTRACT: Exogenous glutamine is an important source of energy and molecular building blocks for many tumors. There is a renewed interest in therapeutically targeting glutamine metabolism due to the recent discovery of two novel glutaminase inhibitors. To quantify the dysregulation of the glutamate-glutamine equilibrium in breast cancer, metabolomics analysis of 270 clinical breast cancer and 97 normal breast samples was carried out using gas chromatography combined with time-of-flight mass spectrometry. Positive correlation between glutamate and glutamine in normal breast tissues switched to negative correlation between glutamate and glutamine in breast cancer tissues. Compared to the level of glutamate/glutamine in normal tissues, we found 56% of the ER+ tumor tissues and 88% of the ER- tumor tissues glutamate-enriched. The glutamate/glutamine ratio (GGR) significantly correlated with ER status (p=8.0E-09) and with tumor grade (p=3.3E-05). Higher levels of GGR were associated with prolonged overall survival in univariate analysis (HR=0.77, p=0.027) and in multivariate analysis (HR=0.73, p=0.038). GGR levels were reflected in an unsupervised clustering of metabolomics profiles. In a supervised analysis of metabolomics data and of genome-wide expression data, replacement of GGR by metabolite surrogate markers was feasible, while replacement of GGR by RNA markers had a limited accuracy. Functional analysis of the gene expression data showed negative correlation between glutamate enrichment and activation of peroxisome proliferator-activated receptor (PPAR) pathway. Our findings may have important implications for patient stratification related to utilization of glutaminase inhibitors. © 2014 Wiley Periodicals, Inc.
    International Journal of Cancer 08/2014; · 6.20 Impact Factor
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    ABSTRACT: Prognosis for patients with estrogen-receptor (ER)-negative basal breast cancer is poor, and chemotherapy is currently the best therapeutic option. We have generated a compound-mutant mouse model combining the activation of β-catenin and HGF (Wnt-Met signaling), which produced rapidly growing basal mammary gland tumors. We identified the chemokine system CXCL12/CXCR4 as a crucial driver of Wnt-Met tumors, given that compound-mutant mice also deficient in the CXCR4 gene were tumor resistant. Wnt-Met activation rapidly expanded a population of cancer-propagating cells, in which the two signaling systems control different functions, self-renewal and differentiation. Molecular therapy targeting Wnt, Met, and CXCR4 in mice significantly delayed tumor development. The expression of a Wnt-Met 322 gene signature was found to be predictive of poor survival of human patients with ER-negative breast cancers. Thus, targeting CXCR4 and its upstream activators, Wnt and Met, might provide an efficient strategy for breast cancer treatment.
    Cell Reports 11/2013; · 7.20 Impact Factor
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    ABSTRACT: Analysis of genome-wide data is often carried out using standard methods such as differential expression analysis, clustering analysis and heatmaps. Beyond that, differential correlation analysis was suggested to identify changes in the correlation patterns between disease states. The detection of differential correlation is a demanding task, as the number of entries in the gene-by-gene correlation matrix is large. Currently, there is no gold standard for the detection of differential correlation and statistical validation. We developed two untargeted algorithms (DCloc and DCglob) that identify differential correlation patterns by comparing the local or global topology of correlation networks. Construction of networks from correlation structures requires fixing of a correlation threshold. Instead of a single cutoff, the algorithms systematically investigate a series of correlation thresholds and permit to detect different kinds of correlation changes at the same level of significance: strong changes of a few genes and moderate changes of many genes. Comparing the correlation structure of 208 ER- breast carcinomas and 208 ER+ breast carcinomas, DCloc detected 770 differentially correlated genes with a FDR of 12.8%, while DCglob detected 630 differentially correlated genes with a FDR of 12.1%. In two-fold cross-validation, the reproducibility of the list of the top 5% differentially correlated genes in 140 ERtumors and in 140 ER+ tumors was 49% for DCloc and 33% for DCglob. We developed two correlation network topology based algorithms for the detection of differential correlations in different disease states. Clusters of differentially correlated genes could be interpreted biologically and included the marker genes hydroxyprostaglandin dehydrogenase (PGDH) and acyl-CoA synthetase medium chain 1 (ACSM1) of invasive apocrine carcinomas that were differentially correlated, but not differentially expressed. Using random subsampling and cross-validation, DCloc and DCglob were shown to identify specific and reproducible lists of differentially correlated genes.
    BMC Systems Biology 08/2013; 7(1):78. · 2.98 Impact Factor
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    ABSTRACT: BUBR1 (budding uninhibited by benzimidazole-related 1) represents the component of a controlling complex in mitosis. Defects in mitotic control complex result in chromosomal instability and, as a result, disturb the mitotic process. This study was aimed at examining the prognostic value linked to the expression of BUBR1 in a group of patients with breast cancer. We analyzed the expression of BUBR1 in 98 stage II breast cancer patients with a median follow-up of 15 years. Immunohistochemical reactions were performed using monoclonal antibodies against BUBR1. We also studied the prognostic value of BUBR1 mRNA expression using the Kaplan-Meier (KM) plotter, which assessed the effect of 22,277 genes on survival in 2422 breast cancer patients. A background database was established using gene expression data and survival information on 2422 patients downloaded from the Gene Expression Omnibus (GEO; Affymetrix HGU133A and HGU133+2 microarrays). The median relapse-free survival was 6.43 years. Univariate and multivariate analyses showed that higher expression of BUBR1 was typical for cases of shorter overall survival, disease-free time, and disease-specific survival. KM plotter analysis showed that elevated BUBR1 mRNA expression had a negative impact on patients’ relapse-free, distant metastases–free, and overall survival. Elevated BUBR1 expression was associated with poor survival in early stage breast cancer patients.
    Journal of Histochemistry and Cytochemistry 02/2013; · 2.26 Impact Factor
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    ABSTRACT: S100P - low molecular weight acidic protein has been shown to be involved in processes of proliferation, survival, angiogenesis, multidrug resistance and metastasis in various human malignancies. In breast cancer, S100P expression is associated with immortalization of neoplastic cells and aggressive tumour behaviour, indicating that this protein may have adverse prognostic value. We analyzed nuclear and cytoplasmic expression of S100P in 85 stage II breast cancer patients with a median follow up of 17 years. Immunohistochemical reactions were performed on paraffin sections of primary tumours, using monoclonal antibodies against S100P. We also studied prognostic value of S100P mRNA expression using the KM plotter which assessed the effect of 22,277 genes on survival in 2422 breast cancer patients. Moreover, the relationship was examined between expression of S100P in cells of four breast cancer cell lines and their sensitivity to the 11 most frequently applied cytotoxic drugs. Univariate and multivariate analyses showed that higher expression of nuclear S100P (S100Pn) was typical for cases of a shorter overall survival and disease-free time. KM plotter analysis showed that elevated S100P expression was specific for cases of a relapse-free survival and distant metastases-free survival. No relationship could be documented between expression of S100P and sensitivity of breast cancer cells to cytostatic drugs. We demonstrated that a high S100Pn expression level was associated with poor survival in early stage breast cancer patients. Since preliminary data indicated that expression of S100P was up-regulated by activation of glucocorticoid receptor and several agents manifested potential to activate or inhibit S100P promoter activity, this protein might become a therapy target and warrants further studies with respect to its prognostic, predictive and potentially therapeutic value.
    Histology and histopathology 01/2013; · 2.28 Impact Factor
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    01/2013;
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    ABSTRACT: Integrating gene expression data with secondary data such as pathway or protein-protein interaction data has been proposed as a promising approach for improved outcome prediction of cancer patients. Methods employing this approach usually aggregate the expression of genes into new composite features, while the secondary data guide this aggregation. Previous studies were limited to few data sets with a small number of patients. Moreover, each study used different data and evaluation procedures. This makes it difficult to objectively assess the gain in classification performance. Here we introduce the Amsterdam Classification Evaluation Suite (ACES). ACES is a Python package to objectively evaluate classification and feature-selection methods and contains methods for pooling and normalizing Affymetrix microarrays from different studies. It is simple to use and therefore facilitates the comparison of new approaches to best-in-class approaches. In addition to the methods described in our earlier study (Staiger et al., 2012), we have included two prominent prognostic gene signatures specific for breast cancer outcome, one more composite feature selection method and two network-based gene ranking methods. Employing the evaluation pipeline we show that current composite-feature classification methods do not outperform simple single-genes classifiers in predicting outcome in breast cancer. Furthermore, we find that also the stability of features across different data sets is not higher for composite features. Most stunningly, we observe that prediction performances are not affected when extracting features from randomized PPI networks.
    Frontiers in Genetics 01/2013; 4:289.
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    ABSTRACT: Changes in energy metabolism of the cells are common to many kinds of tumors and are considered a hallmark of cancer. Gas chromatography followed by time-of-flight mass spectrometry (GC-TOFMS) is a well-suited technique to investigate the small molecules in the central metabolic pathways. However, the metabolic changes between invasive carcinoma and normal breast tissues were not investigated in a large cohort of breast cancer samples so far. A cohort of 271 breast cancer and 98 normal tissue samples was investigated using GC-TOFMS-based metabolomics. A total number of 468 metabolite peaks could be detected; out of these 368 (79%) were significantly changed between cancer and normal tissues (p<0.05 in training and validation set). Furthermore, 13 tumor and 7 normal tissue markers were identified that separated cancer from normal tissues with a sensitivity and a specificity of >80%. Two-metabolite classifiers, constructed as ratios of the tumor and normal tissues markers, separated cancer from normal tissues with high sensitivity and specificity. Specifically, the cytidine-5-monophosphate / pentadecanoic acid metabolic ratio was the most significant discriminator between cancer and normal tissues and allowed detection of cancer with a sensitivity of 94.8% and a specificity of 93.9%. For the first time, a comprehensive metabolic map of breast cancer was constructed by GC-TOF analysis of a large cohort of breast cancer and normal tissues. Furthermore, our results demonstrate that spectrometry-based approaches have the potential to contribute to the analysis of biopsies or clinical tissue samples complementary to histopathology.
    BMC Genomics 07/2012; 13:334. · 4.40 Impact Factor
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    ABSTRACT: Degradation of the extracellular matrix and basement membrane is a critical step in tumor progression. Matrix metalloproteinase 2 (MMP-2) and tissue inhibitor of metalloproteinase 2 (TIMP 2) act in a coordinated manner to form an integrated system involved in ovarian cancer (OC) progression. In this study, the authors describe the expression of TIMP-2 detected by immunohistochemistry in 6 OC cell lines and in 43 malignant epithelial ovarian tumors (in tumor and stromal compartments) in sections originating from primary laparotomies. No significant correlations between overall and progression-free survival and TIMP-2 expression in tumor compartment were observed. The analysis demonstrated a significant association between enhanced stromal expression of TIMP-2 and better clinical response to cisplatin- and paclitaxel-based chemotherapy. Increased expression of TIMP-2 in the stromal compartment and simultaneous overexpression in both stromal and tumor compartments strongly correlated with increased survival. No significant correlations were found in vitro between resistance to cisplatin, paclitaxel, or topotecan and the expression of TIMP-2 in the OC cell lines, suggesting stromal influences on tumor chemoresistance in the physiological environment. This study supports the concept of TIMP-2 expression in the stromal compartment of OC as a promising marker of prognosis and response to cisplatin- and paclitaxel-based chemotherapy in OC patients.
    Journal of Histochemistry and Cytochemistry 04/2012; 60(7):491-501. · 2.26 Impact Factor
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    ABSTRACT: Nuclear expression of ABCC2 can be specific for lower differentiated cells and stem cells. The study aimed at examination of ABCC2 expression in breast cancers. The immunohistochemical analyses were performed on 70 samples of breast cancer. We have also studied prognostic value of the ABCC2 mRNA expression using the KM plotter which assessed the effect of 22,277 genes on survival in 1809 breast cancer patients. Immunohistochemical studies demonstrated that ABCC2 expression may be manifested in nuclear envelope of neoplastic cells (ABCC2n) as well as in their cell membrane and cytoplasm (ABCC2c). The univariate and multivariate analyses showed that higher expression of ABCC2n and ABCC2c was typical for cases of a shorter overall survival time. Higher ABBC2n expression was also typical for cases of a shorter disease-free survival and a shorter progression-free time. The KM plotter analysis of the prognostic value of ABCC2 mRNA expression showed that elevated ABCC2 expression was specific for cases of a shorter relapse-free survival only in the estrogen receptor-negative subgroup. The study demonstrated hat breast cancers manifest ABCC2 expression and that it is linked to a less favourable prognosis. Our results suggested that immunohistochemical tests represent a reliable way to detect prognostic value of ABCC2 expression, allowing to demonstrate differences related to subcellular localization of the protein. Cases with nuclear expression of ABCC2 manifested a more aggressive clinical course, which might reflect a less advanced differentiation of neplastic cells, resistance to the applied cytostatic drugs and tamoxifen.
    Pathology & Oncology Research 10/2011; 18(2):331-42. · 1.56 Impact Factor
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    ABSTRACT: Transcriptomic analysis of global gene expression in ovarian carcinoma can identify dysregulated genes capable to serve as molecular markers for histology subtypes and survival. The aim of our study was to validate previous candidate signatures in an independent setting and to identify single genes capable to serve as biomarkers for ovarian cancer progression. As several datasets are available in the GEO today, we were able to perform a true meta-analysis. First, 829 samples (11 datasets) were downloaded, and the predictive power of 16 previously published gene sets was assessed. Of these, eight were capable to discriminate histology subtypes, and none was capable to predict survival. To overcome the differences in previous studies, we used the 829 samples to identify new predictors. Then, we collected 64 ovarian cancer samples (median relapse-free survival 24.5 months) and performed TaqMan Real Time Polimerase Chain Reaction (RT-PCR) analysis for the best 40 genes associated with histology subtypes and survival. Over 90% of subtype-associated genes were confirmed. Overall survival was effectively predicted by hormone receptors (PGR and ESR2) and by TSPAN8. Relapse-free survival was predicted by MAPT and SNCG. In summary, we successfully validated several gene sets in a meta-analysis in large datasets of ovarian samples. Additionally, several individual genes identified were validated in a clinical cohort.
    International Journal of Cancer 08/2011; 131(1):95-105. · 6.20 Impact Factor
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    ABSTRACT: Estrogen receptor beta (ERβ) belongs to a large family of nuclear receptors. Recent studies have suggested that ERβ in contrast to ERα might act as a tumour suppressor in ovarian cancer (OVCA). Expression of ERβ was detected by immunocytochemistry in 11 OVCA cell lines and by immunohistochemistry in 43 (41 FIGO stage III) OVCA specimens prepared before chemotherapy and 30 specimens from the same group after chemotherapy. Cisplatin sensitivity in the 11 cell lines was also analysed. No significant correlations between cisplatin-sensitivity and expression of ERβ was found in the cell lines. In the cases which responded well to chemotherapy (complete response) ERβ expression at preliminary laparotomy (PL) was significantly higher (p = 0.0004) than in those with progressive disease. Kaplan-Meier analysis revealed that the patients with higher ERβ expression (>30% of cells) at PL had an increased overall survival time and progression-free time (p = 0.00161 and p = 0.03255, respectively) than the patients with lower ERβ expression. Significantly shorter overall survival time characterized the cases with lower immunoreactivity score of ERβ expression at secondary cytoreduction (SCR) (p = 0.00346). The loss of ERβ expression in ovarian tumours may be a feature of malignant transformation.
    Anticancer research 02/2011; 31(2):711-8. · 1.71 Impact Factor
  • Balazs Györffy, Reinhold Schäfer
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    ABSTRACT: The small GTP-binding proteins HRAS, KRAS and NRAS belong to a family of oncoproteins associated with many types of human cancer. Signal transduction processes initiated at receptor tyrosine kinases converge on RAS proteins which serve as molecular switches linking upstream signals with the transcriptional machinery. RAS proteins interact with a number of effector proteins that in turn activate the Raf/MEK/ERK pathway, the PI3K/PKB/Akt pathway, the RalGDS/Ral pathway and other downstream pathways. Mutations in RAS lock the protein in its active form. Chronic activation of the KRAS isoform is the basis for resistance toward antibody therapies targeting receptor tyrosine kinases, as an upstream stimulus through growth factor receptor-mediated activation is no longer required. However, the complexity of the RAS signaling system necessitates the search for additional activating mechanisms as well as biomarkers associated with pathway activation. During recent years, several RAS pathway-related gene signatures were identified, mostly by microarray-based gene expression profiling of normal versus RAS-transformed cells. The signatures can serve as a source of common biomarkers indicating functionally relevant downstream effects of the RAS signaling system. In searching for new markers, we compared the gene expression signatures compiled in 24 independent studies. We analyzed differentially regulated genes recovered in microarray studies on human specimens to discriminate paired normal and tumor tissues. Although the overlap between individual studies was low, this meta-analysis revealed Kruppel-like factor 5 (KLF5), the CD44 antigen and members of the epidermal growth factor (EGR)-family as common downstream effectors of RAS.
    Current cancer drug targets 12/2010; 10(8):858-68. · 5.13 Impact Factor
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    ABSTRACT: We investigated the differential expression of Dicer and Drosha, as well as that of microRNA (miRNA), in adjacent normal and tumour samples of patients with gastric cancer. The expression of Dicer and Drosha was studied by immunohistochemistry in 332 gastric cancers and correlated with clinico-pathological patient characteristics. Differential expression of miRNAs was studied using the Invitrogen NCode(™) Multi-Species miRNA Microarray Probe Set containing 857 mammalian probes in a test set of six primary gastric cancers (three with and three without lymph node metastases). Differential expression was validated by RT-PCR on an independent validation set of 20 patients with gastric cancer. Dicer and Drosha were differentially expressed in non-neoplastic and neoplastic gastric tissue. The expression of Drosha correlated with local tumour growth and was a significant independent prognosticator of patient survival. Twenty miRNAs were up- and two down-regulated in gastric carcinoma compared with non-neoplastic tissue. Six of these miRNAs separated node-positive from node-negative gastric cancers, ie miR-103, miR-21, miR-145, miR-106b, miR-146a, and miR-148a. Five miRNAs expressed differentially in node-positive cancers had conserved binding sites for mRNAs differentially expressed in the same set of tumour samples. Gastric cancer shows a complex derangement of the miRNA-ome, including Dicer and Drosha. These changes correlate independently with patient prognosis and probably influence local tumour growth and nodal spread.
    The Journal of Pathology 11/2010; 222(3):310-9. · 7.59 Impact Factor
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    ABSTRACT: Functional studies have demonstrated that nuclear factor (NF)-kappaB promotes tumour progression in ovarian cancer cells. However, surprisingly little is known of the expression of effectors of the NF-kappaB pathway in human ovarian cancer in vivo. Immunohistochemistry and in situ hybridization revealed that in a cohort of 85 primary ovarian carcinomas, total p65 expression was inversely correlated to nuclear and cytoplasmic phospho-IkappaBalpha (P = 0.002 and P = 0.05, respectively), and IkappaBalpha mRNA expression (P = 0.032). In contrast, phospho-p65 expression was paralleled by the expression of nuclear (P = 0.027) and cytoplasmic phospho-IkappaBalpha (P = 0.01). Total p65 expression was an adverse prognostic factor for overall survival (P = 0.018). In contrast, total IkappaBalpha and phosphorylated nuclear and cytoplasmic IkappaBalpha expression were favourable prognostic markers (P = 0.001, P = 0.031, P = 0.001, respectively). Cytoplasmic phospho-IkappaBalpha expression remained a significant prognostic factor on multivariate analysis (P = 0.010). In cultured, stimulated OVCAR-3 ovarian cancer cells the cytoplasmic retranslocation of p65 was delayed by inhibition of the nuclear membrane transporter chromosomal region maintenance/exportin1 protein (CRM1). A positive association of p65 and CRM1 expression was demonstrated in ovarian cancer tissue (P < 0.0001). Total and phosphorylated IkappaBalpha protein expression might serve as markers for NF-kappaB activation in human ovarian carcinoma. Cytoplasmic localization of p65 may be related to deregulated nucleocytoplasmic transport in carcinomas overexpressing CRM1.
    Histopathology 05/2010; 56(6):727-39. · 2.86 Impact Factor
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    ABSTRACT: Validating prognostic or predictive candidate genes in appropriately powered breast cancer cohorts are of utmost interest. Our aim was to develop an online tool to draw survival plots, which can be used to assess the relevance of the expression levels of various genes on the clinical outcome both in untreated and treated breast cancer patients. A background database was established using gene expression data and survival information of 1,809 patients downloaded from GEO (Affymetrix HGU133A and HGU133+2 microarrays). The median relapse free survival is 6.43 years, 968/1,231 patients are estrogen-receptor (ER) positive, and 190/1,369 are lymph-node positive. After quality control and normalization only probes present on both Affymetrix platforms were retained (n = 22,277). In order to analyze the prognostic value of a particular gene, the cohorts are divided into two groups according to the median (or upper/lower quartile) expression of the gene. The two groups can be compared in terms of relapse free survival, overall survival, and distant metastasis free survival. A survival curve is displayed, and the hazard ratio with 95% confidence intervals and logrank P value are calculated and displayed. Additionally, three subgroups of patients can be assessed: systematically untreated patients, endocrine-treated ER positive patients, and patients with a distribution of clinical characteristics representative of those seen in general clinical practice in the US. Web address: www.kmplot.com . We used this integrative data analysis tool to confirm the prognostic power of the proliferation-related genes TOP2A and TOP2B, MKI67, CCND2, CCND3, CCNDE2, as well as CDKN1A, and TK2. We also validated the capability of microarrays to determine estrogen receptor status in 1,231 patients. The tool is highly valuable for the preliminary assessment of biomarkers, especially for research groups with limited bioinformatic resources.
    Breast Cancer Research and Treatment 12/2009; 123(3):725-31. · 4.47 Impact Factor
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    ABSTRACT: To date individual markers have failed to correctly predict resistance against anticancer agents in breast cancer. We used gene expression patterns attributable to chemotherapy-resistant cells to detect potential new biomarkers related to anthracycline resistance. One of the genes, PSMB7, was selected for further functional studies and clinical validation. We contrasted the expression profiles of four pairs of different human tumour cell lines and of their counterparts resistant to doxorubicin. Observed overexpression of PSMB7 in resistant cell lines was validated by immunohistochemistry. To examine its function in chemoresistance, we silenced the gene by RNA interference (RNAi) in doxorubicin-resistant MCF-7 breast cancer cells, then cell vitality was measured after doxorubicin treatment. Microarray gene expression from GEO raw microarray samples with available progression-free survival data was downloaded, and expression of PSMB7 was used for grouping samples. After doxorubicin treatment, 79.8+/-13.3% of resistant cells survived. Silencing of PSMB7 in resistant cells decreased survival to 31.8+/-6.4% (P>0.001). A similar effect was observed after paclitaxel treatment. In 1592 microarray samples, the patients with high PSMB7 expression had a significantly shorter survival than the patients with low expression (P<0.001). Our findings suggest that high PSMB7 expression is an unfavourable prognostic marker in breast cancer.
    British Journal of Cancer 12/2009; 102(2):361-8. · 5.08 Impact Factor
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    ABSTRACT: Ovarian carcinoma has the highest mortality rate among gynaecological malignancies. In this project, we investigated the hypothesis that molecular markers are able to predict outcome of ovarian cancer independently of classical clinical predictors, and that these molecular markers can be validated using independent data sets. We applied a semi-supervised method for prediction of patient survival. Microarrays from a cohort of 80 ovarian carcinomas (TOC cohort) were used for the development of a predictive model, which was then evaluated in an entirely independent cohort of 118 carcinomas (Duke cohort). A 300-gene ovarian prognostic index (OPI) was generated and validated in a leave-one-out approach in the TOC cohort (Kaplan-Meier analysis, p = 0.0087). In a second validation step, the prognostic power of the OPI was confirmed in an independent data set (Duke cohort, p = 0.0063). In multivariate analysis, the OPI was independent of the post-operative residual tumour, the main clinico-pathological prognostic parameter with an adjusted hazard ratio of 6.4 (TOC cohort, CI 1.8-23.5, p = 0.0049) and 1.9 (Duke cohort, CI 1.2-3.0, p = 0.0068). We constructed a combined score of molecular data (OPI) and clinical parameters (residual tumour), which was able to define patient groups with highly significant differences in survival. The integrated analysis of gene expression data as well as residual tumour can be used for optimized assessment of the prognosis of platinum-taxol-treated ovarian cancer. As traditional treatment options are limited, this analysis may be able to optimize clinical management and to identify those patients who would be candidates for new therapeutic strategies.
    The Journal of Pathology 03/2009; 218(2):273-80. · 7.59 Impact Factor
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    Balazs Györffy, Reinhold Schäfer
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    ABSTRACT: The transcriptome of breast cancers have been extensively screened with microarrays and large sets of genes associated with clinical features have been established. The aim of this study was to validate original gene sets on a large cohort of raw breast cancer microarray data with known clinical follow-up. We recovered 20 publications and matched them to Affymetrix HGU133A annotations. Raw Affymetrix HGU133A microarray data were extracted from GEO and MAS5 normalized. For classifying patients using the selected gene sets, we applied prediction analysis of microarrays and constructed Kaplan-Meier plots. A new classification including all patients was generated using supervised principal components analysis. Seven studies including 1,470 patients were downloaded from GEO. Notably, we uncovered 641 microarrays representing 251 individual tumor specimens among them, which were repeatedly described under independent GEO identifiers. We excluded all redundant data and used the remaining 1,079 samples. Eight of the 20 gene sets were able to predict response at a significance of P < 0.05. The discrimination of good and poor prognosis groups exclusively relying on gene expression data resulted in high significance (P = 1.8E-12). A model including genes fitted by both gene expression and clinical covariates (lymph node status and grade) contains 44 genes and can predict response at P = 9.5E-7. The outcome provides a ranking of the gene lists regarding applicability on an independent dataset. We established a consensus predictor combining the available clinical and gene expression data. The database comprising expression profiles of 1,079 breast cancers can be used to classify individual patients.
    Breast Cancer Research and Treatment 01/2009; 118(3):433-41. · 4.47 Impact Factor
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    ABSTRACT: Head and neck cancers are treated by a combination of surgery, radiotherapy and/or chemotherapy. The clinical success of cisplatin-based chemotherapy, mostly in combination with 5-FU or a taxane, is however limited by multifactorial intrinsic or acquired resistance. So far, known genes involved in cisplatin resistance do not sufficiently allow the prediction of cancer chemosensitivity. Thus, the purpose of this study was to search for further genes involved in cisplatin resistance by differential gene expression analysis of the parental tongue cancer cell line Cal27 and its 10-fold more resistant sub-cell line Cal27cis, which was obtained by treating Cal27 with increasing concentrations of cisplatin. As found by the suppression subtractive hybridization, expression of DKK1, an inhibitor of canonical WNT signaling, was decreased in Cal27cis. Microarray analysis, qPCR and ELISA confirmed the approximately 2-fold difference in expression. Cisplatin treatment and serum starvation increased by 2-fold the secretion of DKK1 in Cal27 and Cal27cis, thus rendering DKK1-levels significantly different in both cell lines under basal and stress conditions. Recombinant overexpression of DKK1 in Cal27 and Cal27cis resulted in clonal cell lines, which were both 2.2- to 3-fold more sensitive toward cisplatin in cell viability (MTT) and in proliferation (BrdU) assays. In conclusion, acquired (10-fold) resistance of Cal27 against cisplatin is associated with decreased DKK1 expression and could partially be reversed by DKK1 overexpression, thus suggesting DKK1 and the WNT signaling pathway as a marker and target for cisplatin chemosensitivity.
    International Journal of Cancer 12/2008; 123(9):2013-9. · 6.20 Impact Factor

Publication Stats

695 Citations
186.21 Total Impact Points

Institutions

  • 2003–2013
    • Semmelweis University
      • • Second Department of Internal Medicine
      • • First Department of Paediatrics
      Budapeŝto, Budapest, Hungary
  • 2011–2012
    • Wroclaw Medical University
      • Department of Pathomorphology
      Wrocław, Lower Silesian Voivodeship, Poland
  • 2006–2009
    • Charité Universitätsmedizin Berlin
      • Institute of Pathology
      Berlin, Land Berlin, Germany
  • 2007
    • Hungarian Academy of Sciences
      Budapeŝto, Budapest, Hungary
  • 2005
    • Humboldt-Universität zu Berlin
      Berlín, Berlin, Germany
  • 2004
    • Szent László Hospital, Budapest
      Budapeŝto, Budapest, Hungary