Mutation characteristics and molecular evolution of ovarian metastasis from gastric cancer and potential biomarkers for paclitaxel treatment

Pengfei Yu, Can Hu, Guangyu Ding, Xiaoliang Shi, Jingli Xu, Yang Cao, Xiangliu Chen, Wei Wu, Qi Xu, Jingquan Fang, Xingmao Huang, Shaohua Yuan, Hui Chen, Zhizheng Wang, Ling Huang, Fei Pang, Yian Du and Xiangdong Cheng ()
Additional contact information
Pengfei Yu: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Can Hu: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Guangyu Ding: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Xiaoliang Shi: Ltd
Jingli Xu: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Yang Cao: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Xiangliu Chen: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Wei Wu: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Qi Xu: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Jingquan Fang: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Xingmao Huang: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Shaohua Yuan: Ltd
Hui Chen: Ltd
Zhizheng Wang: Ltd
Ling Huang: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Fei Pang: Ltd
Yian Du: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences
Xiangdong Cheng: Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: Abstract Ovarian metastasis is one of the major causes of treatment failure in patients with gastric cancer (GC). However, the genomic characteristics of ovarian metastasis in GC remain poorly understood. In this study, we enroll 74 GC patients with ovarian metastasis, with 64 having matched primary and metastatic samples. Here, we show a characterization of the mutation landscape of this disease, alongside an investigation into the molecular heterogeneity and pathway mutation enrichments between synchronous and metachronous metastasis. We classify patients into distinct clonal evolution patterns based on the distribution of mutations in paired samples. Notably, the parallel evolution group exhibits the most favorable prognosis. Additionally, by analyzing the differential response to chemotherapy, we identify potential biomarkers, including SALL4, CCDC105, and CLDN18, for predicting the efficacy of paclitaxel treatment. Furthermore, we validate that CLDN18 fusion mutations improve tumor response to paclitaxel treatment in GC with ovarian metastasis in vitro and vivo.

Date: 2024
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DOI: 10.1038/s41467-024-48144-0

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