Real-time tumor gene expression profiling to direct gastric cancer chemotherapy: Proof-of-concept "3G" trial

Wei Peng Yong, Sun Young Rha, Iain Bee Huat Tan, Su Pin Choo, Nicholas L. Syn, Vivien Koh, Shi Hui Tan, Bernadette Reyna Asuncion, Raghav Sundar, Jimmy Bok Yan So, Asim Shabbir, Chee Seng Tan, Hyo Song Kim, Minkyu Jung, Hyun Cheol Chung, Matthew C.H. Ng, David Wai Meng Tai, Ming Hui Lee, Jeanie Wu, Khay Guan YeohPatrick Tan

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)5272-5281
Number of pages10
JournalClinical Cancer Research
Issue number21
Publication statusPublished - 2018 Nov 1

Bibliographical note

Publisher Copyright:
© 2018 AACR.

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research


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