Actionable gene-based classification toward precision medicine in gastric cancer

• Main Authors: Hiroshi Ichikawa, Masayuki Nagahashi, Yoshifumi Shimada, Takaaki Hanyu, Takashi Ishikawa, Hitoshi Kameyama, Takashi Kobayashi, Jun Sakata, Hiroshi Yabusaki, Satoru Nakagawa, Nobuaki Sato, Yuki Hirata, Yuko Kitagawa, Toshiyuki Tanahashi, Kazuhiro Yoshida, Ryota Nakanishi, Eiji Oki, Dana Vuzman, Stephen Lyle, Kazuaki Takabe, Yiwei Ling, Shujiro Okuda, Kohei Akazawa, Toshifumi Wakai
• Format: Article
• Language: English
• Published: BMC 2017-10-01
• Series: Genome Medicine
• Subjects: Gastric cancer; Next-generation sequencing; Gene panel; Precision medicine; Actionable gene
• Online Access: http://link.springer.com/article/10.1186/s13073-017-0484-3
• ISSN: 1756-994X

Abstract Background Intertumoral heterogeneity represents a significant hurdle to identifying optimized targeted therapies in gastric cancer (GC). To realize precision medicine for GC patients, an actionable gene alteration-based molecular classification that directly associates GCs with targeted therapies is needed. Methods A total of 207 Japanese patients with GC were included in this study. Formalin-fixed, paraffin-embedded (FFPE) tumor tissues were obtained from surgical or biopsy specimens and were subjected to DNA extraction. We generated comprehensive genomic profiling data using a 435-gene panel including 69 actionable genes paired with US Food and Drug Administration-approved targeted therapies, and the evaluation of Epstein-Barr virus (EBV) infection and microsatellite instability (MSI) status. Results Comprehensive genomic sequencing detected at least one alteration of 435 cancer-related genes in 194 GCs (93.7%) and of 69 actionable genes in 141 GCs (68.1%). We classified the 207 GCs into four The Cancer Genome Atlas (TCGA) subtypes using the genomic profiling data; EBV (N = 9), MSI (N = 17), chromosomal instability (N = 119), and genomically stable subtype (N = 62). Actionable gene alterations were not specific and were widely observed throughout all TCGA subtypes. To discover a novel classification which more precisely selects candidates for targeted therapies, 207 GCs were classified using hypermutated phenotype and the mutation profile of 69 actionable genes. We identified a hypermutated group (N = 32), while the others (N = 175) were sub-divided into six clusters including five with actionable gene alterations: ERBB2 (N = 25), CDKN2A, and CDKN2B (N = 10), KRAS (N = 10), BRCA2 (N = 9), and ATM cluster (N = 12). The clinical utility of this classification was demonstrated by a case of unresectable GC with a remarkable response to anti-HER2 therapy in the ERBB2 cluster. Conclusions This actionable gene-based classification creates a framework for further studies for realizing precision medicine in GC.