LncRNA model predicts liver cancer drug resistance and validate in vitro experiments

Qiushi Yin; Xiaolong Huang; Qiuxi Yang; Shibu Lin; Qifeng Song; Weiqiang Fan; Wang Li; Zhongyi Li; Lianghui Gao

doi:10.3389/fcell.2023.1174183

LncRNA model predicts liver cancer drug resistance and validate in vitro experiments

Front Cell Dev Biol. 2023 Apr 3:11:1174183. doi: 10.3389/fcell.2023.1174183. eCollection 2023.

Authors

Qiushi Yin¹, Xiaolong Huang¹, Qiuxi Yang¹, Shibu Lin¹, Qifeng Song¹, Weiqiang Fan¹, Wang Li¹, Zhongyi Li², Lianghui Gao¹

Affiliations

¹ Department of Hepatobiliary Surgery, The First Affiliated Hospital of Hainan Medical University, Haikou, Hainan Province, China.
² Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany.

Abstract

Introduction: Hepatocellular carcinoma (HCC) patients may benefit from chemotherapy, but drug resistance is an important obstacle to favorable prognoses. Overcoming drug resistance is an urgent problem to be solved. Methods: Differential expression analysis was used to identify long non-coding RNAs (LncRNAs) that differed in chemotherapy-sensitive and chemotherapy-resistant patients. Machine learning algorithms including random forest (RF), lasso regression (LR), and support vector machines (SVMs) were used to identify important chemotherapy-related LncRNAs. A back propagation (BP) network was then used to validate the predictive capacity of important LncRNAs. The molecular functions of hub LncRNAs were investigated via qRT-PCR and cell proliferation assay. Molecular-docking technique was used to explore candidate drug of targets of hub LncRNA in the model. Results: A total of 125 differentially expressed LncRNAs between sensitive and resistant patients. Seventeen important LncRNAs were identified via RF, and seven factors were identified via LR. With respect to SVM, the top 15 LncRNAs of AvgRank were selected. Five merge chemotherapy-related LncRNAs were used to predict chemotherapy resistance with high accuracy. CAHM was a hub LncRNA of model and expression high in sorafenib resistance cell lines. In addition, the results of CCK8 showed that the sensitivity of HepG2-sorafenib cells to sorafenib was significantly lower than that of HepG2; and the sensitivity of HepG2-sorafenib cells transfected with sh-CAHM was significantly higher than that of Sorafenib. In the non-transfection group, the results of clone formation experiments showed that the number of clones formed by HepG2-sorafenib cells treated with sorafenib was significantly more than that of HepG2; after HepG2-sorafenib cells were transfected with sh-CAHM, the number of clones formed by Sorafenib treatment was significantly higher than that of HepG2 cells. The number was significantly less than that of HepG2-s + sh-NC group. Molecular Docking results indicate that Moschus was candidate drug for target protein of CAHM. Conclusion: Five chemotherapy-related LncRNAs could predict drug resistance in HCC with high accuracy, and the hub LncRNA CAHM has potential as a new biomarker for HCC chemotherapy resistance.

Keywords: CAHM; TCGA database; chemotherapy resistance; hepatocellular carcinoma; lncRNA.