The treatment modalities for several solid tumors have entered a new era of immunological therapy.19 But for HCC, a highly devastating malignancy with high mortality rates and poor prognosis, the efficacy of immunological treatment was not satisfactory yet.20 A stringent barrier in optimizing HCC treatment efficacy was its immunosuppressive microenvironment, which causes low response rates to targeted therapy and limited improvements in OS, including immune checkpoint inhibitors (ICIs) based immunotherapy.21,22 The comprehension of TME in HCC was the key to develop optimized treatment modalities. The development of scRNA-seq and transcriptomes sequencing techniques provided researchers with a potential opportunity to explore and reveal TME. The infiltration of specific immune cell types could be reflected via the expression levels of markers by using algorithms such MCP-counter and TIMER. The correlation between expression levels of specific immune cell type markers and HCC patient prognosis could be established with complete survival data in multiple HCC cohorts.
In this study, we first observed that the infiltration of T cell types were associated with patient
survival. Then, we tried to explore the marker genes related to T cell infiltration by analyzing the intratumoral heterogeneity in HCC using sc-RNA-seq profiles. The functions of T cell marker genes were enriched in T cell activation, regulation of immune effector process, Th1, Th2 and Th17 cell differentiation, etc. Subsequently, we applied LASSO cox regression to constructe TCMS for higher accuracy based on gene expression matrix and follow-up data in training set and validated the TCMS with TCGA-LIHC dataset. In validation set, TCMS were still serving as an independently prognostic risk factor of OS. Besides, immune analysis in TIMER 2.0 database further confirmed the strong correlation between merker genes and T cell infiltration, which made the result more convincing.
Over the years a greater emphasis of TME research were placed on immune cell infiltration, in particular, the correlation between T cell infiltration and tumor prognosis.23–25 A comprehensive transcriptomic analysis comparing data from the Genotype-Tissue Expression project and TCGA-LIHC defined the increased T cell markers expression and T cell infiltration associated with a good prognosis.26,27 Consistent with this, the real-word cohort study including 65 HCC tissue specimens from stage I to IV data indicated high infiltration of CD8 + T cells in HCC were generally associated with better prognoses, lower recurrence and a more prolonged disease free survival (RFS). 11,28 Our results also supported the view that T cell infiltration in HCC were is an excellent classifier for predicting prognoses. Specifically, CD8 + T cells could develop powful antitumoral immune responses via scereting perforin, granzyme eradicating cancer cells.29,30 But the inhibitory immune checkpoints generating the immunosuppressive tumor microenvironment substantially exhausted CD8 + cytotoxic T lymphocytes (CTLs) and attenuated antitumoral immune responses, e.g., programmed death-ligand 1 (PD-L1), cytotoxic T-lymphocyte antigen 4 (CTLA-4) and lymphocyte activating gene 3 protein (LAG-3).31–33 The immune checkpoint inhibitors (ICIs), one of the innovative immunotherapy therapeutic approach, selectively block the inhibitory immune checkpoints to repair antitumoral immune responses mediated by T cells.
Previous studies concentrated on studying HCC-TME at transcriptome level and developed the biomarkers of HCC prognosis.34,35 However, few of them explored the heterogeneity of HCC-TME and prognostic marker genes by analysing scRNA-seq. Here, we tried to explore prognostic T cells marker genes and further constructed a prognostic model in HCC (TCMS) using scRNA-seq data and 3 HCC transcriptome cohorts with bulk sequencing. The TCMS model might reflect T cell function in HCC-TME somehow on account of the specific T cell marker genes expression profile identified by analysing scRNA-seq data. Regrettably, further analysis of subtype in T cell cluster were limited by the small scRNA-seq sample and T cell counts and could not be performed. Nevertheless. TCMS model was still a powerful predictor of OS in both training and validation dataset. And the T cell marker genes we screened out provided a basis for further research of the role of T cell in TME and immunotherapy.
Four T cell marker genes (HELZ, GZMA, SLC2A2, JAK3) included in TCMS model indicated pivotal roles in T cells’ biological behaviours in HCC-TME. In correlation analysis, GZMA was
strongly associated with CD8 + T cell infiltration (Rho = 0.571, P = 3.49e-31). GZMA (Granzyme A) encoded a specific serine protease which may function as a necessary component for cytolytic T lymphocytes (CTL) to recognize and lyse specific target cells. The CTL-derived GZMA catalyzed the cleavage of gasdermin B, unleashed pore-forming activity and promoted pyroptosis.30 Therefore, GZMA may serve as an noteworthy component in antitumor immunity. Previous studies have indicated the correlation between GZMA and outcomes of HCC.36 In this study, we found high expression of GZMA predicted high degree of T cell infiltration and good prognosis, indicating GZMA functions anti-neoplastic roles in HCC. SLC2A2 was the member of solute carrier family 2 and encoded the integral plasma menbrance glycoprotein which was responsible for glucose uptake and mediated the bidirectional transfer of glucose across the hepatocytes plasma membrane. Cancer cells necessitated high glucose transport rates for satisfying the high metabolic demands, and because of this property cancer cells up-regulate the glucose transporters expressions.37 But the study of metabolic genes in HCC cell lines reported the expression of SLC2A2 were down-regulated, 38 and another research form Korea showed high SLC2A2 HCC patients had a good prognosis,37 which were consistent with the regression coefficients of SLC2A2 in TCMS model. In our scRNA-seq analysis, SLC2A2 was high expression in T cell cluster compared with other cell clusters and identified as the marker gene of T cell. However, in immuno-infiltration analyse based on the RNA sequencing data and TIMER database SLC2A2 were negative correlation with T cell infiltration (Fig. 5D, Fig. 6), which were not in conformity with the aforementioned results, even though the spearmans correlation coefficient were weak. Further researches were necessary to explain SLC2A2 in HCC-TME. JAK3 was primarily expressed in immune cells and mediated essential intracellular signal transduction via tyrosine phosphorylation activated by interleukin receptors. Non-receptor tyrosine kinase (JAK) involved in various biological processes like cell growth, development, or differentiation, particularly, played a crucial role during T-cells development. Previous studies have reported that mutations of JAK3 were identified in HCC patients and cell lines. 39 HELZ was the member of the superfamily I class of RNA helicases and implicated in various aspects of RNA metabolism. Nevertheless, functions of JAK3 in T cell were largely unknown and few research mentioned the relationship between HELZ and HCC patients.40 In this study, HELZ was identified a T cell marker gene and associated with HCC patients outcome, suggesting a novel role of HELZ.
Although our conclusions have been vcalidated by independent data set, we have not implemented futher prospective clinical study or molecular biology experiments to validate the results, which were the largest limitation in this study. So we would conduct bioinformatics research, subsequently, to confirm our conclusions and underlying molecular mechanism.
In conclusion, we successfully constructed the T cell marker genes signature with powerful predictive function and provided a new understanding of T cell infiltration in tumor microenvironment which might offer practices instructions for HCC immunotherapy.