Multi-omics characterization of molecular features of gastric cancer correlated with response to neoadjuvant chemotherapy.
Zi-Yu LiXiang-Yu GaoXinxin PengMei-Ju May ChenZhe LiBin WeiXianzi WenBaoye WeiYu DongZhaode BuAiwen WuQi WuLei TangZhongwu LiYiqiang LiuLi ZhangShuqin JiaLianhai ZhangFei ShanJi ZhangXiaojiang WuXin JiKe JiXiao-Long WuJinyao ShiXiaofang XingJianmin WuGuoqing LvLin ShenXuwo JiHan LiangJia Fu JiPublished in: Science advances (2020)
Neoadjuvant chemotherapy is a common treatment for patients with gastric cancer. Although its benefits have been demonstrated, neoadjuvant chemotherapy is underutilized in gastric cancer management, because of the lack of biomarkers for patient selection and a limited understanding of resistance mechanisms. Here, we performed whole-genome, whole-exome, and RNA sequencing on 84 clinical samples (including matched pre- and posttreatment tumors) from 35 patients whose responses to neoadjuvant chemotherapy were rigorously defined. We observed increased microsatellite instability and mutation burden in nonresponse tumors. Through comparisons of response versus nonresponse tumors and pre- versus posttreatment samples, we found that C10orf71 mutations were associated with treatment resistance, which was supported by drug response data and potentially through inhibition of cell cycle, and that MYC amplification correlated with treatment sensitivity, whereas MDM2 amplification showed the opposite pattern. Neoadjuvant chemotherapy also reshapes tumor-immune signaling and microenvironment. Our study provides a critical basis for developing precision neoadjuvant regimens.
Keyphrases
- neoadjuvant chemotherapy
- locally advanced
- lymph node
- sentinel lymph node
- cell cycle
- rectal cancer
- squamous cell carcinoma
- stem cells
- radiation therapy
- cell proliferation
- single cell
- machine learning
- ejection fraction
- newly diagnosed
- prognostic factors
- combination therapy
- artificial intelligence
- deep learning
- copy number
- transcription factor
- case report
- patient reported outcomes