Literature DB >> 30045931

Real-Time Tumor Gene Expression Profiling to Direct Gastric Cancer Chemotherapy: Proof-of-Concept "3G" Trial.

Wei Peng Yong1,2, Sun Young Rha3, Iain Bee-Huat Tan4, Su-Pin Choo4, Nicholas L Syn5,2, Vivien Koh5,2, Shi-Hui Tan5,2, Bernadette Reyna Asuncion2, Raghav Sundar5, Jimmy Bok-Yan So6, Asim Shabbir6, Chee-Seng Tan5, Hyo-Song Kim3, Minkyu Jung3, Hyun Cheol Chung3, Matthew C H Ng4, David Wai-Meng Tai4, Ming-Hui Lee7, Jeanie Wu7, Khay Guan Yeoh8, Patrick Tan.   

Abstract

Purpose: The oxaliplatin plus S-1 and cisplatin plus S-1 regimens are interchangeably used in the management of advanced gastric cancer. The previously reported G-intestinal (G1) and G-diffuse (G2) intrinsic gene expression signatures showed promise for stratifying patients according to their tumor sensitivity to oxaliplatin or cisplatin.Experimental Design: The proof-of-concept, multicenter, open-label phase II "3G" trial was done to prospectively evaluate the feasibility and efficacy of using genomic classifiers to tailor treatment in gastric cancer. Patients' tumors were classified as "G1" or "G2" using a nearest-prediction template method, or "G3" (unclear assignment) when FDR ≥ 0.05. The first 30 patients in the "G1" cohort were assigned oxaliplatin plus S-1 (SOX) chemotherapy; thereafter, subsequently recruited "G1" patients were treated with cisplatin plus S-1 (SP) chemotherapy. "G2" patients and "G3" patients were treated with SP and SOX chemotherapy, respectively.
Results: A total of 48, 21, and 12 patients, respectively, were given "G1," "G2," and "G3" genomic assignments. Median turnaround time was 7 days (IQR, 5-9). Response rates were 44.8%, 8.3%, 26.7%, and 55.6% for the "G1-SOX," "G1-SP," "G2," "G3" cohorts, respectively; and was higher in G1 patients treated with SOX compared with SP (P = 0.033). Exploratory analyses using the genomic classifier of Lei and colleagues validated the utility of the metabolic signature as a biomarker for predicting benefit from chemotherapy (log-rank P = 0.004 for PFS), whereas the Asian Cancer Research Group classifier did not demonstrate any predictive value.Conclusions: This bench-to-bedside effort establishes a reasonable turnaround time for gene expression profiling and possible utility of genomic classifiers in gastric cancer treatment stratification. Clin Cancer Res; 24(21); 5272-81. ©2018 AACR. ©2018 American Association for Cancer Research.

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Year:  2018        PMID: 30045931     DOI: 10.1158/1078-0432.CCR-18-0193

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  8 in total

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2.  Single patient classifier as a prognostic biomarker in pT1N1 gastric cancer: Results from two large Korean cohorts.

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5.  A Multi-cohort Study of the Prognostic Significance of Microsatellite Instability or Mismatch Repair Status after Recurrence of Resectable Gastric Cancer.

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Review 7.  Dissection of gastric cancer heterogeneity for precision oncology.

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  8 in total

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