Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene Expression Profiling of FFPE Pre-treatment Endoscopic Biopsies from Oesophageal Adenocarcinoma Patients Treated with Neo-adjuvant Chemotherapy and Surgical Resection

ABSTRACT: Gene expression profiling of 273 pre-treatment endoscopic FFPE oesophageal and oesophago-gastric junctional adenocarcinomas for validation of a DNA Damage Response Deficiency Assay. All patients were treated with neo-adjuvant chemotherapy followed by surgical resection and were collected at four UK centres in the Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) consortium between 2004 and 2013. Biopsies were reviewed for pathological subtype prior to marking for macrodissection and samples containing at least 50% adenocarcinoma tissue by area were taken forward. Total RNA was extracted using the RecoverallTM Total Nucleic Acid Isolation Kit for FFPE (Thermo Fisher Scientific, Waltham, MA) and amplified using the NuGen Ovation FFPE Amplification System v3 (NuGen San Carlos, CA). The amplified product was hybridized to the Almac Diagnostics Xcel™ array (Almac, Craigavon, United Kingdom), a cDNA microarray-based technology optimized for archival FFPE tissue, and analysed using the Affymetrix 7G scanner (Affymetrix, Santa Clara, CA)

ORGANISM(S): Homo sapiens

SUBMITTER: Richard Turkington

PROVIDER: E-MTAB-6969 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

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

Dataset Information

Gene Expression Profiling of FFPE Pre-treatment Endoscopic Biopsies from Oesophageal Adenocarcinoma Patients Treated with Neo-adjuvant Chemotherapy and Surgical Resection

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets