Published online Sep 21, 2019. doi: 10.3748/wjg.v25.i35.5266
Peer-review started: April 22, 2019
First decision: June 10, 2019
Revised: July 18, 2019
Accepted: August 7, 2019
Article in press: June 10, 2019
Published online: September 21, 2019
Processing time: 153 Days and 18.8 Hours
Hepatocellular carcinoma (HCC) is a common subtype of liver cancer, which has become a serious health threat worldwide. Hepatitis B virus (HBV) has been identified as a leading cause of HCC. Increasing evidence indicates that cancer immune infiltration is associated with clinical outcomes. However, no credible prognosis signature for HBV-associated HCC has been constructed through systemically assessing bulk tumor transcriptomic immune landscape.
Tumor-infiltrating immunocytes represent a vital prognosis clue in HBV-associated HCC patients. In this study, a new immune model for HBV-associated HCC cases was developed through systematically assessing the bulk tumor transcriptomic immune landscape.
The current research aimed to establish a prognosis-related immune signature based on bulk tumor transcriptome-derived immune infiltrate compositions, thus improving the prognosis prediction accuracy for HBV-associated HCC.
The fractions of 22 immunocyte types extracted based on public datasets were predicated using the cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. Furthermore, an immunoscore was calculated based on immunocyte type fractions by the least absolute shrinkage and selection operator (LASSO) model.
The immunoscore constituted by eight immunocyte type fractions was constructed by adopting the LASSO model, which displayed a high sensitivity and specificity for overall survival (OS), and the areas under the curves for the 1-year, 3-year, and 5-year OS were 0.971, 0.912, and 0.975, respectively. Difference in OS between the low-immunoscore and high-immunoscore groups was statistically significant. Additionally, a nomogram was established to expand the applied range of the model, which included the immunoscore as well as other clinical characteristics. The related pathways were enriched through gene set enrichment analysis.
The established immunoscore showed high prognosis prediction accuracy for patients with HBV-associated HCC, which may facilitate the risk stratification and provide valuable clinical suggestions for individual cases.
Findings of this study suggested that the tumor-infiltrating immunocytes could be used as promising biomarkers to predict the prognosis for HBV-associated HCC patients. This forms the framework for identification of efficient prognosis predictors and molecular biomarkers for HCC patients in the future.