Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Gene expression profiling of 60 pre-chemotherapy FFPE endoscopic oesophageal adenocarcinoma biopsies

ABSTRACT: Oesophageal cancer is the ninth most common cancer in the UK and accounts for 5% of all cancer deaths. The incidence of the disease in men has risen 50% in the last 25 years with the commonest pathological subtype in the West being adenocarcinoma, while in East Asia oesophageal squamous cell carcinoma predominates. Despite efforts to screen for Barrett’s oesophagus, and pre-operatively select OAC patients who are likely to benefit from potentially curative surgery, survival remains poor. The five year survival rate is less than 17% and even in early stage locoregional confined disease this figure lies between 25-35%. A significant improvement in overall survival has been demonstrated with neo-adjuvant or peri-operative chemotherapy but the optimal approach for individual patients remains unclear. A consistent finding has been that complete histopathological response to neo-adjuvant chemotherapy is a prognostic biomarker for increased survival benefit. Therefore, there is a pressing need to identify biomarkers capable of predicting response, enabling clinicians to select patients for whom neo-adjuvant therapies would be beneficial. This experiment represents gene expression profiling of 60 pre-treatment formalin-fixed paraffin embedded (FFPE) oesophageal adenocarcinoma biopsies. All patients were treated with neo-adjuvant cisplatin-based chemotherapy prior to surgical resection at the Northern Ireland Cancer Centre from 2004-2012. The aim of the experiment was to carry out functional enrichment of pathological responders and non-responders to neo-adjuvant chemotherapy in order to identify novel mechanism of drug resistance or chemo-sensitivity.

ORGANISM(S): Homo sapiens

SUBMITTER: Richard Turkington

PROVIDER: E-MTAB-4666 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:In patients with advanced colorectal cancer, leucovorin, fluorouracil, and irinotecan (FOLFIRI) is considered as one of the reference first-line treatments. However, only about half of treated patients respond to this regimen, and there is no clinically useful marker that predicts response. A major clinical challenge is to identify the subset of patients who could benefit from this chemotherapy. We aimed to identify a gene expression profile in primary colon cancer tissue that could predict chemotherapy response. Patients and Methods:- Tumor colon samples from 21 patients with advanced colorectal cancer were analyzed for gene expression profiling using Human Genome GeneChip arrays U133. At the end of the first-line treatment, the best observed response, according to WHO criteria, was used to define the responders and nonresponders. Discriminatory genes were first selected by the significance analysis of microarrays algorithm and the area under the receiver operating characteristic curve. A predictor classifier was then constructed using support vector machines. Finally, leave-one-out cross validation was used to estimate the performance and the accuracy of the output class prediction rule. Results:- We determined a set of 14 predictor genes of response to FOLFIRI. Nine of nine responders (100% specificity) and 11 of 12 nonresponders (92% sensitivity) were classified correctly, for an overall accuracy of 95%. Conclusion:- After validation in an independent cohort of patients, our gene signature could be used as a decision tool to assist oncologists in selecting colorectal cancer patients who could benefit from FOLFIRI chemotherapy, both in the adjuvant and the first-line metastatic setting. All tissue samples were maintained at −180°C (liquid nitrogen) until RNA extraction and were weighed before homogenization. Tissue samples were then disrupted directly into a lysis buffer using Mixer Mill MM 300 (Qiagen, Valencia, CA). Total RNA was isolated from tissue lysates using the RNeasy Mini Kit (Qiagen), and additional DNAse digestion was performed on all samples during the extraction process (RNase-Free DNase Set Protocol for DNase treatment on RNeasy Mini Spin Columns; Qiagen). After each extraction, a small fraction of the total RNA preparation was taken to determine the quality of the sample and the yield of total RNA. Controls analyses were performed by UV spectroscopy and analysis of total RNA profile using the Agilent RNA 6000 Nano LabChip Kit with the Agilent 2100 Bioanalyser (Agilent Technologies, Palo Alto, CA) to determine RNA purity, quantity, and integrity.

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Gene expression profiling of 60 pre-chemotherapy FFPE endoscopic oesophageal adenocarcinoma biopsies

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