Development and validation of 9-long Non-coding RNA signature to predicting survival in hepatocellular carcinoma
Benyuan Deng, Min Yang, Ming Wang, Zhongwu Liu
Abstract
Primary hepatic carcinoma is 1 of the most common malignant tumors globally, of which hepatocellular carcinoma (HCC) accounts for 85% to 90%. Due to the high degree of deterioration and low early detection rate of HCC, most patients are diagnosed when they are already in the middle and advanced stages, and the prognosis are always poor.RNA sequencing data from the cancer genome atlas was used to explore differences in lncRNA expression profiles. LncRNA was extracted by gdcRNAtools in R package. Multivariate cox analysis was performed on the screened lncRNAs. The relationship between the lncRNA model and prognosis as well as clinical characteristics of patients with HCC was analyzed. Finally, a predictive nomogram in the the cancer genome atlas cohort was established and verified internallyBased on the RNA sequencing survival analysis, a 9- lncRNAs prognosis model, including TMCC1-AS1, AC008892.1, AL031985.3, L34079.2, U95743.1, KDM4A-AS1, SACS-AS1, AC005534.1, LINC01116 was established. The 9-lncRNA prognosis model was a reliable tool for predicting prognosis of HCC, and the nomogram of this prognosis model could help clinicians to choose personalized treatment for HCC patientsThis model was significant to complement clinic characteristics of HCC and to promote personalized management of patients, it also provided a new idea for researches on the prognosis of HCC.