Abstract 1253: Pan-cancer comparative and integrative analyses of driver alterations using Japanese and international genomic databases
Authors: Horie Sara , Saito Yuki , Kogure Yasunori , Mizuno Kota , Ito Yuta , Tabata Mariko , Murakami Koichi , Koya Junji , Kataoka Keisuke 
Published: March 2024

Recent large-scale pan-cancer genome projects have broadened our understanding of the cancer genome. However, these projects mainly consisted of White patients, with a limited focus on Asian populations. In addition, while pairwise relationships between driver alterations can provide valuable functional insights, the majority of these analyses are limited to those using The Cancer Genome Atlas (TCGA) dataset.

Here we present a pan-cancer landscape of driver alterations in Japanese patients with advanced solid tumors using targeted sequencing data of 48,627 samples from the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) in Japan. This data set had a greater number of samples from Asian-prevalent cancer types, such as intrahepatic cholangiocarcinoma and stomach adenocarcinoma, compared to the Genomics Evidence Neoplasia Information Exchange (GENIE) cohort. In the C-CAT cohort, the most frequently mutated gene was TP53 (56%), followed by KRAS (25%), APC (17%), and PIK3CA (12%). Gene fusions were detected in 1,166 samples (2%), including ERG fusions in prostate adenocarcinoma (n = 129), and RET and ALK fusions in lung adenocarcinoma (n = 30 and 32). At least one clinically actionable genetic lesion was found in 16% of patients, with well-differentiated thyroid cancer having the highest proportion.

A comparative analysis of somatic mutation frequencies was conducted between the C-CAT cohort and the White population in the GENIE cohort. Among 352 driver gene-cancer type combinations, 14 and 4 were significantly higher and lower in the C-CAT cohort (&gt; 10% difference with q-value &lt; 0.01). Notably, TP53 mutation frequencies were elevated in the C-CAT cohort across 10 cancer types, suggesting racial differences in TP53 mutation frequencies.

We then integrated C-CAT, GENIE, and TCGA data consisting of more than 150,000 patients to conduct a meta-analysis of co-occurring and mutually exclusive relationships between 1,790 cancer-driver combinations. This analysis not only validated 215 previously reported relationships but identified 484 novel ones. Interestingly, we found significantly co-occurring mutations within the epigenetic pathway, with 13 epigenetic regulators co-occurring in ten cancer types. Gene set enrichment analysis using RNA-sequencing data in TCGA revealed that accumulation of mutations in epigenetic regulators causes increased proliferation-related transcriptomic signatures. In addition, loss-of-function mutations in epigenetic drivers suppresses proliferation in wild-type cell lines, but this effect is reduced in cells with mutations in both the same and other epigenetic drivers.

Our multi-cohort analyses uncover differences in the driver landscape between Asian and White populations, provides valuable resources for precision cancer medicine, and offers insights into epigenetic regulator-associated oncogenesis.

Citation Format: Sara Horie, Yuki Saito, Yasunori Kogure, Kota Mizuno, Yuta Ito, Mariko Tabata, Koichi Murakami, Junji Koya, Keisuke Kataoka. Pan-cancer comparative and integrative analyses of driver alterations using Japanese and international genomic databases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1253.