Immune landscape of hepatocellular carcinoma microenvironment: Implications for prognosis and therapeutic applications

Seven immune-related genes prognostic power and correlation with tumor-infiltrating immune cells in hepatocellular carcinoma

Background

Given poor prognosis and the lack of efficient therapy for advanced hepatocellular carcinoma, immunotherapy has emerged as an increasingly important role. However, there were few reports on the correlation between immune‐related genes and HCC. The purpose of this study is to construct a novel immune‐related gene‐based prognostic signature for HCC and to explore the potential mechanisms.

Methods

We organized expression data of 374 HCC samples and 50 nontumor samples from TCGA database. A robust signature was constructed by Cox regression analysis based on the immune‐related genes, which were filtered by differential genes analysis and Cox regression analysis. Then, the correlation analysis between the signature and clinical characteristics was conducted. And the signature was validated in ICGC database. Furthermore, the relationships between immune cell infiltration and the signature were explored by bioinformatics analysis.

Results

Seven genes‐based model (Risk score = BIRC5 * 0.0238 + FOS * 0.0055 + DKK1 * 0.0085 + FGF13 * 0.3432 + IL11 * 0.0135 + IL17D * 0.0878 + SPP1 * 0.0003) was constructed eventually and it was proved to be an independent prognostic factor for HCC patients. The signature‐calculated risk scores were shown to be positively correlated with the infiltration of these five immune cells, including macrophages, neutrophils, CD8+T, dendritic, and B cells. And the results suggested that high amplication of BIRC5, FGF13, IL11, IL17D, and SPP1 were more likely correlated with immune cell infiltration. Finally, PPI network, TFs‐based regulatory network and gene enrichment plots were performed to show potential molecular mechanisms.

Conclusion

We construct a robust immune‐related gene‐based prognostic signature with seven genes and explore potential mechanisms about it, which may contribute to the immunotherapy research for HCC.

RNA N6-Methyladenosine-Related Gene Contribute to Clinical Prognostic Impact on Patients With Liver Cancer

Liver cancer (LC) is the fourth leading cause of cancer-related deaths worldwide. There is an urgent need to identify novel and reliable prognostic biomarkers for LC in order to improve patient outcomes. N6-methyladenosine (m6A) is the most common internal modification in eukaryotic mRNA and has been associated with various cancers, although its roles in the prognosis of LC remains to be elucidated. We analyzed the expression profiles of 15 m6A-related genes in the International Cancer Genome Consortium (ICGC) LIRI-JP dataset, and applied consensus clustering to stratify LC patients into two subgroups (Cluster 1 and Cluster 2). Cluster1 was significantly correlated to lower tumor stage and longer overall survival (OS). Gene set enrichment analysis showed that tumorigenic markers, including DNA repair, E2F targets, G2M checkpoint, and MYC targets V1, were enriched in Cluster2. We then constructed a prognostic risk model using three m6A-related genes that were identified as independent factors affecting OS. The nomogram based on the risk model score indicated good performance in predicting the 1-, 2- and 3-year survival of the LC patients. In conclusion, m6A-related genes are potential prognostic markers and therapeutic targets for LC.

Natural Killer Cell Responses in Hepatocellular Carcinoma: Implications for Novel Immunotherapeutic Approaches

Hepatocellular carcinoma (HCC) still represents a significant complication of chronic liver disease, particularly when cirrhosis ensues. Current treatment options include surgery, loco-regional procedures and chemotherapy, according to specific clinical practice guidelines. Immunotherapy with check-point inhibitors, aimed at rescuing T-cells from exhaustion, has been applied as second-line therapy with limited and variable success. Natural killer (NK) cells are an essential component of innate immunity against cancer and changes in phenotype and function have been described in patients with HCC, who also show perturbations of NK activating receptor/ligand axes. Here we discuss the current status of NK cell treatment of HCC on the basis of existing evidence and ongoing clinical trials on adoptive transfer of autologous or allogeneic NK cells ex vivo or after activation with cytokines such as IL-15 and use of antibodies to target cell-expressed molecules to promote antibody-dependent cellular cytotoxicity (ADCC). To this end, bi-, tri- and tetra-specific killer cell engagers are being devised to improve NK cell recognition of tumor cells, circumventing tumor immune escape and efficiently targeting NK cells to tumors. Moreover, the exciting technique of chimeric antigen receptor (CAR)-engineered NK cells offers unique opportunities to create CAR-NK with multiple specificities along the experience gained with CAR-T cells with potentially less adverse effects.

Tumor-infiltrating immune cells in hepatocellular carcinoma: Tregs is correlated with poor overall survival

Systematic interrogation of tumor-infiltrating immune cells (TIICs) is key to the prediction of clinical outcome and development of immunotherapies. However, little is known about the TIICs of hepatocellular carcinoma (HCC) and its impact on the prognosis of patients and potential for immunotherapy. We applied CIBERSORT of 1090 tumors to infer the infiltration of 22 subsets of TIICs using gene expression data. Unsupervised clustering analysis by 22 TIICs revealed 4 clusters of tumors, mainly defined by macrophages and T cells, with distinct prognosis and associations with immune checkpoint molecules, including PD-1, CD274, CTLA-4, LAG-3 and IFNG. We found tumors with decreased number of M1 macrophages or increased regulatory T cells were associated with poor prognosis. Based on the multivariate Cox analysis, a nomogram was also established for clinical application. In conclusion, composition of the TIICs in HCC was quite different, which is an important determinant of prognosis with great potential to identify candidates for immunotherapy.

A Single-Cell Perspective of the Mammalian Liver in Health and Disease

The liver contains heterogeneous cell types that exhibit distinct spatial, molecular, and functional properties. The cells in the liver communicate with each other via a network of ligands and receptors and undergo cell type-specific transcriptomic reprogramming in disease. The advance of single-cell genomics has provided a powerful tool for unraveling the complexity of liver cells in health and disease with unprecedented resolution. In this review, we discuss insights gained from the recent single-cell RNA sequencing studies that shed new light on the molecular nature of liver cell heterogeneity, intercellular crosstalk, and disease-associated reprogramming.

Integrative analysis of DNA methylation and gene expression reveals distinct hepatocellular carcinoma subtypes with therapeutic implications

We aimed to develop an HCC classification model based on the integrated gene expression and methylation data of methylation-driven genes. Genome, methylome, transcriptome, proteomics and clinical data of 369 HCC patients from The Cancer Genome Atlas Network were retrieved and analyzed. Consensus clustering of the integrated gene expression and methylation data from methylation-driven genes identified 4 HCC subclasses with significant prognosis difference. HS1 was well differentiated with a favorable prognosis. HS2 had high serum α-fetoprotein level that was correlated with its poor outcome. High percentage of CTNNB1 mutations corresponded with its activation in WNT signaling pathway. HS3 was well differentiated with low serum α-fetoprotein level and enriched in metabolism signatures, but was barely involved in immune signatures. HS3 also had high percentage of CTNNB1 mutations and therefore enriched in WNT activation signature. HS4 was poorly differentiated with the worst prognosis and enriched in immune-related signatures, but was barely involved in metabolism signatures. Subsequently, a prediction model was developed. The prediction model had high sensitivity and specificity in distributing potential HCC samples into groups identical with the training cohort. In conclusion, this work sheds light on HCC patient prognostication and prediction of response to targeted therapy.

Current Status and Future Direction of Immunotherapy in Hepatocellular Carcinoma: What Do the Data Suggest?

Most patients with hepatocellular carcinoma (HCC) are diagnosed at an advanced stage of disease. Until recently, systemic treatment options that showed survival benefits in HCC have been limited to tyrosine kinase inhibitors, antibodies targeting oncogenic signaling pathways or VEGF receptors. The HCC tumor microenvironment is characterized by a dysfunction of the immune system through multiple mechanisms, including accumulation of various immunosuppressive factors, recruitment of regulatory T cells and myeloid-derived suppressor cells, and induction of T cell exhaustion accompanied with the interaction between immune checkpoint ligands and receptors. Immune checkpoint inhibitors (ICIs) have been interfered this interaction and have altered therapeutic landscape of multiple cancer types including HCC. In this review, we discuss the use of anti-PD-1, anti-PD-L1, and anti-CTLA-4 antibodies in the treatment of advanced HCC. However, ICIs as a single agent do not benefit a significant portion of patients. Therefore, various clinical trials are exploring possible synergistic effects of combinations of different ICIs (anti-PD-1/PD-L1 and anti-CTLA-4 antibodies) or ICIs and target agents. Combinations of ICIs with locoregional therapies may also improve therapeutic responses.

The role of the innate immune system in the development and treatment of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer. Most patients present with advanced or metastatic HCC at diagnosis and face a dismal prognosis. Tyrosine kinases are the gold standard treatment for this disease but yield limited survival benefits. Immune checkpoint inhibitors that augment adaptive immunity have been tested in HCC. Complex interactions between tumor cells, lymphocytes and the tumor environment determine the efficacy of such immunotherapies. Innate immune mechanisms – known drivers of liver disease progression in pre-HCC conditions such as fibrosis or cirrhosis – may either support or counteract tumor-related immune activation. In this review, we will highlight current concepts of the role of the innate immune system in hepatocarcinogenesis and discuss their relevance for translation into clinics.

Construction of a risk score prognosis model based on hepatocellular carcinoma microenvironment

BACKGROUND

Hepatocellular carcinoma (HCC) is a common cancer with a poor prognosis. Previous studies revealed that the tumor microenvironment (TME) plays an important role in HCC progression, recurrence, and metastasis, leading to poor prognosis. However, the effects of genes involved in TME on the prognosis of HCC patients remain unclear. Here, we investigated the HCC microenvironment to identify prognostic genes for HCC.

AIM

To identify a robust gene signature associated with the HCC microenvironment to improve prognosis prediction of HCC.

METHODS

We computed the immune/stromal scores of HCC patients obtained from The Cancer Genome Atlas based on the ESTIMATE algorithm. Additionally, a risk score model was established based on Differentially Expressed Genes (DEGs) between high‐ and low‐immune/stromal score patients.

RESULTS

The risk score model consisting of eight genes was constructed and validated in the HCC patients. The patients were divided into high- or low-risk groups. The genes (Disabled homolog 2, Musculin, C-X-C motif chemokine ligand 8, Galectin 3, B-cell-activating transcription factor, Killer cell lectin like receptor B1, Endoglin and adenomatosis polyposis coli tumor suppressor) involved in our risk score model were considered to be potential immunotherapy targets, and they may provide better performance in combination. Functional enrichment analysis showed that the immune response and T cell receptor signaling pathway represented the major function and pathway, respectively, related to the immune-related genes in the DEGs between high- and low-risk groups. The receiver operating characteristic (ROC) curve analysis confirmed the good potency of the risk score prognostic model. Moreover, we validated the risk score model using the International Cancer Genome Consortium and the Gene Expression Omnibus database. A nomogram was established to predict the overall survival of HCC patients.

CONCLUSION

The risk score model and the nomogram will benefit HCC patients through personalized immunotherapy.