Journal of Clinical Oncology, 2009 ASCO Annual Meeting Proceedings (Post-Meeting Edition).
Vol 27, No 15S (May 20 Supplement), 2009: 4628
© 2009 American Society of Clinical Oncology

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Abstract

Gene expression signatures to predict the response of gastric cancer to cisplatin and fluorouracil

NCI, Bethesda, MD; National Cancer Center, Goyang, Republic of Korea

4628

Background: A prospective high-throughput gene expression study was conducted to identify transcriptional profiles predictive of a clinical response to cisplatin and fluorouracil (CF) combination chemotherapy and to identify dysregulated genes associated with acquired resistance to CF. Methods: Endoscopic biopsy samples were collected from CF-treated metastatic gastric cancer (MGC) patients (pts) prior to CF (n = 123) and following the development of resistance (n = 22) at the National Cancer Center of Korea from 2001 to 2006, and analyzed using CGH and expression microarrays. We developed 2 survival risk predictors. The first predictor was constructed using genes in DNA amplicons and identified in the expression signature that correlates with survival (intrinsic resistance signature). The second predictor was based on the acquired resistance signature, which was identified by comparing matched expression array data from initially responsive patients prior to treatment with profiles obtained at progressive disease. Results: Array CGH revealed the gene amplification of MYC, EGFR, and FGFR2 whose Affymetrix U133A signals significantly correlated with a poor prognosis (P values, 0.0154, 0.0096, and 0.0057) of training set pts (n = 96). Three-gene-predicted high-risk group of the validation cohort (n = 10) demonstrated a shorter median survival than low-risk (n = 17) group (7.4 vs 16.8 months; p = 0.047). The 3-gene signature, as a continuous variable, was the independent predictor for overall survival (OS) and time to progression (TTP) (adjusted P, 0.021, and 0.012). Importantly, the acquired resistance signature strongly overlapped the intrinsic resistance signature (LS P<10^-5), and was highly enriched for MYC target genes (LS p = 2x10^-5). A predictor based on MYC target genes within the acquired resistance signature was the independent predictor for OS and TTP of 101 separate pts (adjusted p, 0.015, and 0.011). Conclusions: Combined overexpression of MYC, EGFR, and FGFR2 predicts a poor response of MGC pts to CF. There is significant overlap between intrinsic and acquired resistance signatures of MGC, where the MYC gene network plays a central role. This is the first demonstration that the acquired resistance signature predicts the initial response to chemotherapy.

No significant financial relationships to disclose.

Abstract presentation from the 2009 ASCO Annual Meeting