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
Hepatitis B virus (HBV) has been recognized as a leading cause of hepatocellular carcinoma (HCC). Numerous reports suggest that immune infiltration can predict the prognosis of HCC. Nonetheless, no creditable markers for prognosis of HBV-related HCC have been established by systematically assessing the immune-related markers based on tumor transcriptomes.
To establish an immune-related marker based on the cell compositions of immune infiltrate obtained based on tumor transcriptomes, so as to enhance the prediction accuracy of HBV-related HCC prognosis.
RNA expression patterns as well as the relevant clinical data of HCC patients were obtained from The Cancer Genome Atlas. Twenty-two immunocyte fraction types were estimated by cell type identification by estimating relative subsets of RNA transcripts. Subsequently, the least absolute shrinkage and selection operator (LASSO) Cox regression model was employed to construct an immunoscore based on the immunocyte fraction types. Afterwards, the receiver operating characteristic (ROC) curve, Kaplan-Meier, and multivariate Cox analyses were performed. Additionally, a nomogram for prognosis that integrated the immunoscore as well as the clinical features was established. Meanwhile, the correlation of immunoscore with immune genes was also detected, and gene set enrichment analysis (GSEA) of the immunoscore was conducted.
A total of 22 immunocyte fraction types were predicted and compared among the tumor as well as non-tumor samples. An immunoscore was constructed through adopting the LASSO model, which contained eight immunocyte fraction types. Meanwhile, the areas under the ROC curves for the immunoscore biomarker prognostic model were 0.971, 0.912, and 0.975 for 1-, 3-, and 5-year overall survival (OS), respectively. Difference in OS between the high-immunoscore group and the low-immunoscore group was statistically significant [hazard ratio (HR) = 66.007, 95% confidence interval (CI): 8.361-521.105; P < 0.0001]. Moreover, multivariable analysis showed that the immunoscore was an independent factor for predicting the prognosis (HR = 2.997, 95%CI: 1.737-5.170). A nomogram was established, and the C-index was 0.757 (95%CI: 0.648-0.866). The immunoscore showed a significant negative correlation with the expression of PD-1 (P = 0.024), PD-L1 (P = 0.026), PD-L2 (P = 0.029), and CD27 (P = 0.033). Eight pathways were confirmed by GSEA.
The established immunoscore can potentially serve as a candidate marker to estimate the OS for HBV-related HCC cases.
Core tip: Hepatitis B virus (HBV) infection is epidemiologically related to hepatocellular carcinoma (HCC) development. Immune cells have been recognized to play crucial roles in the prognosis of various types of cancers, including HCC. The immune signature for HBV-related HCC remains unknown. In this study, we explored the proportions of immunocytes, and constructed a robust immune signature to predict the prognosis. These results might contribute to risk stratification and facilitate individualized clinical approach for HBV-related HCC.