Xie Lang, Huang Renli, Huang Hongyun, Liu Xiaoxia, Yu Jinlong
Department of General Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital (Guangdong Gastrointestinal and Anal Hospital), Sun Yat-sen University, Guangzhou, China.
Front Pharmacol. 2022 Apr 8;13:879751. doi: 10.3389/fphar.2022.879751. eCollection 2022.
Tumor dormancy is an important way to develop drug resistance. This study aimed to identify the characteristics of colorectal cancer (CRC) cell dormancy. Based on the CRC cohorts, a total of 1,044 CRC patients were included in this study, and divided into a dormant subgroup and proliferous subgroup. Non-negative matrix factorization (NMF) was used to distinguish the dormant subgroup of CRC transcriptome data of cancer tissues. Gene Set Enrichment Analysis (GSEA) was used to explore the characteristics of dormant CRC. The characteristics were verified in the cell model, which was used to predict key factors driving CRC dormancy. Potential treatments for CRC dormancy were also examined. The dormant subgroup had a poor prognosis and was more likely to relapse. GSEA analysis showed two defining characteristics of the dormant subgroup, a difference in energy metabolism and synergistic effects of cancer-associated fibroblasts (CAFs), which were verified in a dormant cell model. Transcriptome and clinical data identified , and as important factors associated with cell dormancy and verified that erlotinib, and CB-839 were potential treatment options. Dormant CRC is associated with high glutamine metabolism and synergizes with CAFs in 5-FU resistance, and the key effectors are LMOD1, MAB21L2, and ASPN. Austocystin D, erlotinib, and CB-839 may be useful for dormant CRC.
肿瘤休眠是产生耐药性的重要途径。本研究旨在确定结直肠癌(CRC)细胞休眠的特征。基于CRC队列,本研究共纳入1044例CRC患者,并分为休眠亚组和增殖亚组。采用非负矩阵分解(NMF)区分癌组织的CRC转录组数据中的休眠亚组。基因集富集分析(GSEA)用于探索休眠CRC的特征。这些特征在细胞模型中得到验证,该模型用于预测驱动CRC休眠的关键因素。还研究了针对CRC休眠的潜在治疗方法。休眠亚组预后较差,更容易复发。GSEA分析显示了休眠亚组的两个决定性特征,即能量代谢差异和癌症相关成纤维细胞(CAF)的协同作用,这在休眠细胞模型中得到了验证。转录组和临床数据确定LMOD1、MAB21L2和ASPN是与细胞休眠相关的重要因素,并验证了厄洛替尼和CB-839是潜在的治疗选择。休眠CRC与高谷氨酰胺代谢相关,并在5-氟尿嘧啶耐药中与CAF协同作用,关键效应因子为LMOD1、MAB21L2和ASPN。澳洲杯形菌素D、厄洛替尼和CB-839可能对休眠CRC有用。