P1.02 Predicting Treatment Response Based on Gene Expression Profiling on Primary Biopsy in Cervical Cancer

Abstract

Resistance to anticancer agents is one of the primary impediments to effective cancer therapy. Cervical cancer remains an unsolved problem of oncology both due to increased rate of local failures and to distant metastasis. The aim of this study was to identify molecules involved in prediction of response to therapy in cervical cancer, based on primary biopsies. Twenty two women, having an advanced cervical carcinoma (stages IIB-IIIB), were included in a prospective study. A tumor biopsy was obtained from each patient before starting therapy. Clinical and pathological evaluations of the patients were made at 6 month after therapy. Agilent microarray gene expression (4x44K) was used for Whole Human Genome evaluation. We identified 2896 differentially expressed genes between non responders and responders groups, which were up or down regulated at least 1.5-fold. P values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate (FDR) of 0.01. The most important canonical pathways identified 119 molecules involved in DNA replication, recombination and repair. Next, we identify 13 genes involved in radio-chemotherapy resistance in cervical cancer. The data were validated by qRT-PCR with UPL probes (Roche). Our microarray results provide new information regarding the prediction of treatment response in cervical cancer.