Enfa Zhao1, Shimin Chen2, Ying Dang3. 1. Department of Structural Heart Disease, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China. 2. Department of Gastroenterology, Traditional Chinese Medicine Hospital of Taihe Country, Taihe, China. 3. Department of Ultrasound Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Abstract
Objective: The purpose of this study was to develop and validate a novel immune checkpoint-related gene signature for prediction of overall survival (OS) in hepatocellular carcinoma (HCC). Methods: mRNA expression profiles and clinical follow-up information were obtained in the International Cancer Genome Consortium database. An external dataset from The Cancer Genome Atlas (TCGA) Liver Hepatocellular Carcinoma database was used to validate the results. The univariate and multivariate Cox regression analyses were performed based on the differentially expressed genes. We generated a four-mRNA signature to predict patient survival. Furthermore, the reliability and validity were validated in TCGA cohort. An integrated bioinformatics approach was performed to evaluate its diagnostic and prognostic value. Results: A four-gene (epidermal growth factor, mutated in colorectal cancer, mitogen-activated protein kinase kinase 2, and NRAS proto-oncogene, GTPase) signature was built to classify patients into two risk groups using a risk score with different OS in two cohorts (all P < 0.0001). Multivariate regression analysis demonstrated the signature was an independent predictor of HCC. Furthermore, the signature presented an excellent diagnostic power in differentiating HCC and adjacent tissues. Immune cell infiltration analysis revealed that the signature was associated with a number of immune cell subtypes. Conclusion: We identified a four-immune checkpoint-related gene signature as a robust biomarker with great potential for clinical application in risk stratification and OS prediction in HCC patients and could be a potential indicator of immunotherapy in HCC. The diagnostic signature had been validated to accurately distinguish HCC from adjacent tissues.
Objective: The purpose of this study was to develop and validate a novel immune checkpoint-related gene signature for prediction of overall survival (OS) in hepatocellular carcinoma (HCC). Methods: mRNA expression profiles and clinical follow-up information were obtained in the International Cancer Genome Consortium database. An external dataset from The Cancer Genome Atlas (TCGA) Liver Hepatocellular Carcinoma database was used to validate the results. The univariate and multivariate Cox regression analyses were performed based on the differentially expressed genes. We generated a four-mRNA signature to predict patient survival. Furthermore, the reliability and validity were validated in TCGA cohort. An integrated bioinformatics approach was performed to evaluate its diagnostic and prognostic value. Results: A four-gene (epidermal growth factor, mutated in colorectal cancer, mitogen-activated protein kinase kinase 2, and NRAS proto-oncogene, GTPase) signature was built to classify patients into two risk groups using a risk score with different OS in two cohorts (all P < 0.0001). Multivariate regression analysis demonstrated the signature was an independent predictor of HCC. Furthermore, the signature presented an excellent diagnostic power in differentiating HCC and adjacent tissues. Immune cell infiltration analysis revealed that the signature was associated with a number of immune cell subtypes. Conclusion: We identified a four-immune checkpoint-related gene signature as a robust biomarker with great potential for clinical application in risk stratification and OS prediction in HCCpatients and could be a potential indicator of immunotherapy in HCC. The diagnostic signature had been validated to accurately distinguish HCC from adjacent tissues.
Authors: Richard Todd Stravitz; Douglas M Heuman; Nisha Chand; Richard K Sterling; Mitchell L Shiffman; Velimir A Luketic; Arun J Sanyal; Adil Habib; Anastasios A Mihas; Ho-Chong S Giles; Daniel G Maluf; Adrian H Cotterell; Marc P Posner; Robert A Fisher Journal: Am J Med Date: 2008-02 Impact factor: 4.965
Authors: Shanique K E Edwards; Jacqueline Baron; Carissa R Moore; Yan Liu; David H Perlman; Ronald P Hart; Ping Xie Journal: J Hematol Oncol Date: 2014-09-09 Impact factor: 17.388