Project description:Background: Validated markers to predict outcome in rectal cancer patients treated with multimodal therapy remain elusive. Identifying molecular profiles for disease prognosis would be required for the design of clinical trials aimed at optimizing risk-adapted therapies. We have therefore used whole genome expression profiling of tumors of a large cohort of patients enrolled in the multicenter trials of the German Rectal Cancer Study Group (GRCSG) to identify molecular profiles for individualized therapy. Methods: We prospectively collected pretherapeutic biopsies from patients (n=300) treated according to the GRCSG trial guidelines from seven different German surgical departments using rigid quality controls. These samples were profiled by global gene expression analysis and a classifier developed to predict postoperative lymph node status and Disease Free Survival (DFS). The performance of the classifier was validated with an independent, prospectively collected set of samples. Findings: The final training and test set included 198 patients. Analyzes for postoperative nodal status and DFS revealed 69 and 674 differentially regulated genes, respectively. Depending on the classifier the accuracy to predict lymph node status ranged from 64% to 69% with negative predictive values between 72% and 74%. Stratification according to DFS resulted in a good (n=99), bad (n=96) and a small very bad prognosis group (n=3). Based on linear discriminant analysis the classifier for positive lymph node status was validated in 47 independent patients and revealed an accuracy of 72% and a positive predictive value of 100%. Thereby, prediction based on molecular profiling is superior to prediction based on conventional clinical markers. Interpretation: Whole genome expression analysis of pretherapeutical biopsies resulted in a molecular classifier of disease prognosis. This classifier was successfully validated. The high positive predictive value for post therapeutic lymph node status allows identification of patients requiring alternative or intensified treatment protocols. These data are currently validated for their clinical applicability and should be taken as basis for future molecular driven clinical trials to develop risk-adapted treatments.

Project description:The incorporation of chemoradiation prior to resection of the tumour has revolutionized the management of locally advanced rectal cancer. However, a large proportion of these patients are resistant to preoperative treatment schedule. We recently reported that c-Myc gene expression correlates negatively with this resistance in patients with rectal cancer. In this study, we carried out integrated analysis of miRNA and mRNA expression profiling in 45 pre-treatment rectal tumour. Further, expression of miRNAs and c-Myc, and their relationship with clinicopathological factors and patient survival was analysed. As a result, we found that 12 miRNAs were differentially expressed between responder and non-responder rectal cancer patients. Functional classification revealed an association between differentially expressed miRNAs and c-Myc. Subsequent quantitative real-time PCR results showed that both, miRNA-148 and miRNA-375 levels were significantly lower in responder compared to non-responder patients. Notably, the higher level of miRNA-375 was significantly negatively correlated with c-Myc. These results suggest that miRNA-375 and its targeted c-Myc play an important role as predictive biomarker of response to neoadjuvant treatment in patients with locally advanced rectal cancer, but still not suitable for prognosis. Pre-treatment biopsies of 22 patients with LARC were prospectively collected and freshly frozen according to an institutional board-approved protocol. Tumour response was assessed in surgical specimens by pathological examination based on the semi-quantitative tumour regression grading (TRG) system described by Mandard in 1994[36]: TRG1 and TRG2 scores were considered responders, whereas TRG3, TRG4, and TRG5 were classified as non-responders. The inclusion criteria were: histologically proven rectal tumour at a clinical stage UICC II-III (cT3-4/and or N positive), following endorectal ultrasound and/or MRI scan. Patients were excluded if they had the tumour located above 13 cm from the anal verge by rigid rectoscopy, synchronic colonic cancer assessed by colonoscopy, distant metastases by 18FDG PET-CT scan, and suspicion of hereditary colorectal cancer. All patients subsequently received a total dose of 50.4Gy of radiation (28 fractions of 1.8Gy) associated with capecitabine (oral form of 5-FU) with or without oxaliplatine, according to our Hospital Clinical Practice Guidelines. Standardized Surgery was performed, including total mesorectal excision, following an interval of 8-10 weeks after completion of CT/RT.

Project description:Purpose: Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Most of these patients are treated with platinum-based chemotherapies, but there is no biomarker model to guide their responses to these therapeutic agents. We have developed and independently tested our novel multivariate molecular predictors for forecasting patients' responses to individual drugs on a cohort of 58 ovarian cancer patients. Experimental Design: We adapted and applied the previously-published COXEN algorithm to develop molecular predictors for therapeutic responses of patients' tumors based on expression signatures derived from the NCI-60 in vitro drug activities and genomic expression data. Genome-wide candidate biomarkers were first triaged by examining expression patterns of frozen and formalin-fixed paraffin embedded (FFPE) tissue samples. We then identify initial drug sensitivity biomarkers for carboplatin and paclitaxel, respectively. These biomarkers were further narrowed by examining concordant expression patterns between cell lines and a historical set of ovarian cancer patients. Multivariate predictors were obtained from the NCI-60 cell lines and refined using historical patient cohorts. To independent validate these molecular predictors, we performed genome-wide profiling on FFPE samples of 58 ovarian cancer patients obtained prior to adjuvant chemotherapy. Results: Carboplatin predictor significantly stratified platinum sensitive and resistant patients (p = 0.019) with sensitivity = 93%, specificity = 33%, PPV = 65%, and NPV = 78%. Paclitaxel predictor also significantly stratified patients' responses (p = 0.033) with sensitivity = 96%, specificity = 26%, PPV = 61%, and NPV = 86%. The combination predictor for platinum-taxane combination demonstrated a significant survival difference between the predicted responders and nonresponders with median survival of 12.9 months vs. 8.1 months (p = 0.045). Conclusions: COXEN predictors successfully stratified platinum resistance and taxane response in this retrospective cohort, especially based on their FFPE tumor samples. Accurate prediction of chemotherapeutic response, especially to platinum agents is highly clinically relevant and could alter primary management of ovarian cancer. Gene expression data from 58 stage III-IV ovarian cancer patients treated with Carboplatin and Taxol agents

Project description:Purpose: Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Most of these patients are treated with platinum-based chemotherapies, but there is no biomarker model to guide their responses to these therapeutic agents. We have developed and independently tested our novel multivariate molecular predictors for forecasting patients' responses to individual drugs on a cohort of 58 ovarian cancer patients. Experimental Design: We adapted and applied the previously-published COXEN algorithm to develop molecular predictors for therapeutic responses of patients' tumors based on expression signatures derived from the NCI-60 in vitro drug activities and genomic expression data. Genome-wide candidate biomarkers were first triaged by examining expression patterns of frozen and formalin-fixed paraffin embedded (FFPE) tissue samples. We then identify initial drug sensitivity biomarkers for carboplatin and paclitaxel, respectively. These biomarkers were further narrowed by examining concordant expression patterns between cell lines and a historical set of ovarian cancer patients. Multivariate predictors were obtained from the NCI-60 cell lines and refined using historical patient cohorts. To independent validate these molecular predictors, we performed genome-wide profiling on FFPE samples of 58 ovarian cancer patients obtained prior to adjuvant chemotherapy. Results: Carboplatin predictor significantly stratified platinum sensitive and resistant patients (p = 0.019) with sensitivity = 93%, specificity = 33%, PPV = 65%, and NPV = 78%. Paclitaxel predictor also significantly stratified patients' responses (p = 0.033) with sensitivity = 96%, specificity = 26%, PPV = 61%, and NPV = 86%. The combination predictor for platinum-taxane combination demonstrated a significant survival difference between the predicted responders and nonresponders with median survival of 12.9 months vs. 8.1 months (p = 0.045). Conclusions: COXEN predictors successfully stratified platinum resistance and taxane response in this retrospective cohort, especially based on their FFPE tumor samples. Accurate prediction of chemotherapeutic response, especially to platinum agents is highly clinically relevant and could alter primary management of ovarian cancer.

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Dissecting tumor/stroma pretreatment endoscopic biopsies and posttreatment surgical specimen in rectal cancer

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