Guangtao Sun1, Kejian Sun1, Chao Shen2. 1. Department of Hepatobiliary Surgery, ZiBo Central Hospital, No. 54, Gongqingtuanxi Road, Zibo, Shandong, 255036, People's Republic of China. 2. Department of Hepatobiliary Surgery, ZiBo Central Hospital, No. 54, Gongqingtuanxi Road, Zibo, Shandong, 255036, People's Republic of China. shenchaozb@outlook.com.
Abstract
BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality in the world. METHOD: We downloaded the mRNA profiles and clinical information of 371 HCC patients from The Cancer Genome Atlas (TCGA) database. The consensus clustering analysis with the mRNA levels of 48 nuclear receptors (NRs) was performed by the "ConsensusClusterPlus." The univariate Cox regression analysis was performed to predict the prognostic significance of NRs on HCC. The risk score was calculated by the prognostic model constructed based on eight optimal NRs. Then multivariate Cox regression analysis was performed to determine whether the risk score is an independent prognostic signature. Finally, the nomogram based on multiple independent prognostic factors was used to predict the long-term survival of HCC patients. RESULTS: The prognostic model constructed based on the eight optimal NRs (NR1H3, ESR1, NR1I2, NR2C1, NR6A1, PPARD, PPARG, and VDR) could effectively predict the prognosis of HCC patients as an independent prognostic signature. Moreover, the nomogram was constructed based on multiple independent prognostic factors including risk score and tumor node metastasis (TNM) stage and could better predict the long-term survival for 3- and 5-year of HCC patients. CONCLUSION: Our results provided novel evidences that NRs could act as the potential prognostic signatures for HCC patients.
BACKGROUND:Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality in the world. METHOD: We downloaded the mRNA profiles and clinical information of 371 HCC patients from The Cancer Genome Atlas (TCGA) database. The consensus clustering analysis with the mRNA levels of 48 nuclear receptors (NRs) was performed by the "ConsensusClusterPlus." The univariate Cox regression analysis was performed to predict the prognostic significance of NRs on HCC. The risk score was calculated by the prognostic model constructed based on eight optimal NRs. Then multivariate Cox regression analysis was performed to determine whether the risk score is an independent prognostic signature. Finally, the nomogram based on multiple independent prognostic factors was used to predict the long-term survival of HCC patients. RESULTS: The prognostic model constructed based on the eight optimal NRs (NR1H3, ESR1, NR1I2, NR2C1, NR6A1, PPARD, PPARG, and VDR) could effectively predict the prognosis of HCC patients as an independent prognostic signature. Moreover, the nomogram was constructed based on multiple independent prognostic factors including risk score and tumor node metastasis (TNM) stage and could better predict the long-term survival for 3- and 5-year of HCC patients. CONCLUSION: Our results provided novel evidences that NRs could act as the potential prognostic signatures for HCC patients.
Entities:
Keywords:
HCC; Human nuclear receptors (NRs); Prognosis; Risk score
Authors: Miral Sadaria Grandhi; Amy K Kim; Sean M Ronnekleiv-Kelly; Ihab R Kamel; Mounes A Ghasebeh; Timothy M Pawlik Journal: Surg Oncol Date: 2016-03-05 Impact factor: 3.279