1. Machine-learning model derived gene signature predictive of paclitaxel survival benefit in gastric cancer: results from the randomised phase III SAMIT trial
- Author
-
Jia Guan, Takaki Yoshikawa, Shiro Tanaka, Heike I. Grabsch, Yohei Miyagi, Yasushi Rino, Jeeyun Lee, Junichi Sakamoto, Nesaretnam Barr Kumarakulasinghe, Yiong Huak Chan, Takashi Oshima, Michal Marek Hoppe, Anand D. Jeyasekharan, Mark De Simone, Munetaka Masuda, Akira Tsuburaya, Kazuhiro Yoshida, Cedric Chuan Young Ng, Raghav Sundar, Angie Lay-Keng Tan, Patrick Tan, RS: GROW - R2 - Basic and Translational Cancer Biology, and Pathologie
- Subjects
Oncology ,medicine.medical_specialty ,Paclitaxel ,medicine.medical_treatment ,adjuvant treatment ,Adenocarcinoma ,THERAPY ,Disease-Free Survival ,Ramucirumab ,Machine Learning ,chemistry.chemical_compound ,CISPLATIN ,Stomach Neoplasms ,Internal medicine ,Antineoplastic Combined Chemotherapy Protocols ,medicine ,Humans ,Stomach cancer ,UFT ,DOCETAXEL ,Chemotherapy ,business.industry ,gastric cancer ,Gastroenterology ,Cancer ,Gene signature ,CHEMOTHERAPY ,medicine.disease ,COMPREHENSIVE MOLECULAR CHARACTERIZATION ,TUMORS ,FAMILY ,Clinical trial ,chemistry ,Cohort ,5-FLUOROURACIL ,SENSITIVITY ,business - Abstract
ObjectiveTo 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.DesignThe 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.ResultsFrom 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 pConclusionUsing 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 numberUMIN Clinical Trials Registry: C000000082 (SAMIT); ClinicalTrials.gov identifier, 02628951 (South Korean trial)
- Published
- 2022