Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma

Abstract

BACKGROUNDHepatitis 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.AIMTo 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.METHODSRNA 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.RESULTSA 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.CONCLUSIONThe established immunoscore can potentially serve as a candidate marker to estimate the OS for HBV-related HCC cases.

Immune system‑associated genes increase malignant progression and can be used to predict clinical outcome in patients with hepatocellular carcinoma

“…Thus, although patients with a high degree of immune cell infiltration may have a high IRS, the IRS based on the five immune associated genes primarily accounted for the functional status of the microenvironment in HCC tissues. Recent studies have focused on the roles of infiltrating immune cells in the tumor microenvironment, to explain the mechanisms underlying immune evasion and to predict drug response or prognosis (75)(76)(77). Further analysis of the sub-types of immune cells in HCC may improve our understanding of immune function in tumor, and with advances in technologies, changing the types of immune cells present may be considered as a potential treatment strategy, emphasizing the importance of restoring immune function in HCC (78)(79)(80).…”

Profiles of m6A RNA methylation regulators for the prognosis of hepatocellular carcinoma

“…Subsequently, the thirteen m 6 A RNA methylation regulators were screened and verified by least absolute shrinkage and selection operator (LASSO) regression using the 'glmnet' R software. Finally, the regulator-based prognostic risk score was constructed through linearly multiplying the expression level with the regression model (β) according to the following formula: Risk=β regulator 1 x regulator 1 expression + β regulator 2 x regulator 2 expression + • •••• + β regulator n x regulator n expression (15,16).…”

Identification of a Five-Immune Gene Model as an Independent Prognostic Factor in Hepatocellular Carcinoma

“…These results similarly con rm the dependability of the risk model. Previous reports have shown that immune in ltration is a vital factor affecting the e cacy as well as the prognosis of HCC [22,23]. Ma et al [24] reported that PD1 Hi CD8 + T cells correlated with poor clinical outcome in HCC.…”