Transcriptional landscape and predictive potential of long noncoding RNAs in peritoneal recurrence of gastric cancer

作者：Xiaoxia Cai, Guo-Ming Chen, Zi‐Qi Zheng, Yixin Yin, Shuang Wang, Qiao Li, Xiao Jiang Chen, Bai-Wei Zhao, Jin‐Ling Duan, Chengcai Liang, Ruo-Peng Zhang, Chengzhi Wei, Feiyang Zhang, Bowen Huang, Zexian Liu, Zhi-Wei Zhou, Dan Xie, Muyan Cai, Shuqiang Yuan, Yuanfang Li, Run‐Cong Nie · 发表于：Molecular Cancer · 年份：2024 · DOI：10.1186/s12943-024-02196-4 · 被引用次数：11 · 研究领域：Cancer-related molecular mechanisms research、Gastric Cancer Management and Outcomes、Ferroptosis and cancer prognosis

BACKGROUND: Long noncoding RNAs (lncRNAs) play a critical role in gastric cancer (GC) progression and metastasis. However, research comprehensively exploring tissue-derived lncRNAs for predicting peritoneal recurrence in patients with GC remains limited. This study aims to investigate the transcriptional landscape of lncRNAs in GC with peritoneal metastasis (PM) and to develop an integrated lncRNA-based score to predict peritoneal recurrence in patients with GC after radical gastrectomy. METHODS: We analyzed the transcriptome profile of lncRNAs in paired peritoneal, primary gastric tumor, and normal tissue specimens from 12 patients with GC in the Sun Yat-sen University Cancer Center (SYSUCC) discovery cohort. Key lncRNAs were identified via interactive analysis with the TCGA database and SYSUCC validation cohort. A score model was constructed using the LASSO regression model and nomogram COX regression and evaluated using receiver operating characteristic curves. The role of lncRNAs in the PM of GC was then examined through wound healing, Transwell, 3D multicellular tumor spheroid invasion, and peritoneal cavity xenograft tumorigenicity assays in mice. RESULT: Five essential lncRNAs were screened and incorporated into the PM risk score to predict peritoneal recurrence-free survival (pRFS). We developed a comprehensive, integrated nomogram score, including the PM risk score, pT, pN, and tumor size, which could effectively predict the 5-year pRFS with an Area under the curve o...