Machine-learning model derived gene signature predictive of paclitaxel survival benefit in gastric cancer: results from the randomised phase III SAMIT trial. Issue 4 (12th May 2021)

• Record Type: Journal Article
• Authors: Sundar, Raghav; Barr Kumarakulasinghe, Nesaretnam; Huak Chan, Yiong; Yoshida, Kazuhiro; Yoshikawa, Takaki; Miyagi, Yohei; Rino, Yasushi; Masuda, Munetaka; Guan, Jia; Sakamoto, Junichi; Tanaka, Shiro; Tan, Angie Lay-Keng; Hoppe, Michal Marek; Jeyasekharan, Anand D.; Ng, Cedric Chuan Young; De Simone, Mark; Grabsch, Heike I.; Lee, Jeeyun; Oshima, Takashi; Tsuburaya, Akira; Tan, Patrick
• Is Part Of: Gut. Volume 71:Issue 4(2022)
• Page Start: 676
• Page End: 685
• Publication Date: 2021-05-12
• Subjects: gastric cancer -- chemotherapy -- adjuvant treatment; Gastroenterology -- Periodicals; 616.33
• DOI: 10.1136/gutjnl-2021-324060
• Languages: English
• ISSNs: 0017-5749

Abstract

Abstract : Objective: To date, there are no predictive biomarkers to guide selection of patients with gastric cancer (GC) who benefit from paclitaxel. Stomach cancer Adjuvant Multi-Institutional group Trial (SAMIT) was a 2×2 factorial randomised phase III study in which patients with GC were randomised to Pac-S-1 (paclitaxel +S-1), Pac-UFT (paclitaxel +UFT), S-1 alone or UFT alone after curative surgery. Design: The primary objective of this study was to identify a gene signature that predicts survival benefit from paclitaxel chemotherapy in GC patients. SAMIT GC samples were profiled using a customised 476 gene NanoString panel. A random forest machine-learning model was applied on the NanoString profiles to develop a gene signature. An independent cohort of metastatic patients with GC treated with paclitaxel and ramucirumab (Pac-Ram) served as an external validation cohort. Results: From the SAMIT trial 499 samples were analysed in this study. From the Pac-S-1 training cohort, the random forest model generated a 19-gene signature assigning patients to two groups: Pac-Sensitive and Pac-Resistant. In the Pac-UFT validation cohort, Pac-Sensitive patients exhibited a significant improvement in disease free survival (DFS): 3-year DFS 66% vs 40% (HR 0.44, p=0.0029). There was no survival difference between Pac-Sensitive and Pac-Resistant in the UFT or S-1 alone arms, test of interaction p<0.001. In the external Pac-Ram validation cohort, the signature predicted benefit for Pac-Sensitive (median PFS 147 days vs 112 days, HR 0.48, p=0.022). Conclusion: Using machine-learning techniques on one of the largest GC trials (SAMIT), we identify a gene signature representing the first predictive biomarker for paclitaxel benefit. Trial registration number: UMIN Clinical Trials Registry: C000000082 (SAMIT); ClinicalTrials.gov identifier, 02628951 (South Korean trial)