Identification and characterization of a 25-lncRNA prognostic signature for early recurrence in hepatocellular carcinoma

BMC Cancer

Yi Fu¹  Hailong Wu¹  Qiuqin Han¹  Jiamei Le¹  Ning Liu²  Xuan Wang³  Ying Tong⁴  Jinyang Gu⁵  Yuhui Xu⁶  Xiaoni Kong⁷  Xindong Wei⁸  Xinjie Lin⁹  Yujie Ma⁹ 

[1] Affiliated Zhoupu Hospital, Shanghai University of Medicine and Health Sciences;Department of Clinical Oncology, Taian City Central Hospital;Department of General Surgery, Nanjing General Hospital of Nanjing Military Command;Department of Liver Surgery, Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine;Department of Transplantation, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine;Graduate School of Art and Sciences, Columbia University;Institute of Clinical Immunology, Department of Liver Diseases, Central Laboratory, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine;Nanjing University of Traditional Chinese Medicine;Shanghai Key Laboratory of Molecular Imaging, Collaborative Innovation Center for Biomedicines, Shanghai University of Medicine and Health Sciences;

关键词: Long non-coding RNA signature;    Hepatocellular carcinoma;    Early recurrence;    Tumor infiltrating lymphocytes;   

DOI  :  10.1186/s12885-021-08827-z

来源: DOAJ

【 摘 要 】

Abstract Background Early recurrence is the major cause of poor prognosis in hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) are deeply involved in HCC prognosis. In this study, we aimed to establish a prognostic lncRNA signature for HCC early recurrence. Methods The lncRNA expression profile and corresponding clinical data were retrieved from total 299 HCC patients in TCGA database. LncRNA candidates correlated to early recurrence were selected by differentially expressed gene (DEG), univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. A 25-lncRNA prognostic signature was constructed according to receiver operating characteristic curve (ROC). Kaplan-Meier and multivariate Cox regression analyses were used to evaluate the performance of this signature. ROC and nomogram were used to evaluate the integrated models based on this signature with other independent clinical risk factors. Gene set enrichment analysis (GSEA) was used to reveal enriched gene sets in the high-risk group. Tumor infiltrating lymphocytes (TILs) levels were analyzed with single sample Gene Set Enrichment Analysis (ssGSEA). Immune therapy response prediction was performed with TIDE and SubMap. Chemotherapeutic response prediction was conducted by using Genomics of Drug Sensitivity in Cancer (GDSC) pharmacogenomics database. Results Compared to low-risk group, patients in high-risk group showed reduced disease-free survival (DFS) in the training (p < 0.0001) and validation cohort (p = 0.0132). The 25-lncRNA signature, AFP, TNM and vascular invasion could serve as independent risk factors for HCC early recurrence. Among them, the 25-lncRNA signature had the best predictive performance, and combination of those four risk factors further improves the prognostic potential. Moreover, GSEA showed significant enrichment of “E2F TARGETS”, “G2M CHECKPOINT”, “MYC TARGETS V1” and “DNA REPAIR” pathways in the high-risk group. In addition, increased TILs were observed in the low-risk group compared to the high-risk group. The 25-lncRNA signature negatively associates with the levels of some types of antitumor immune cells. Immunotherapies and chemotherapies prediction revealed differential responses to PD-1 inhibitor and several chemotherapeutic drugs in the low- and high-risk group. Conclusions Our study proposed a 25-lncRNA prognostic signature for predicting HCC early recurrence, which may guide postoperative treatment and recurrence surveillance in HCC patients.

【 授权许可】

Unknown