Immunological Basis of Genesis of Hepatocellular Carcinoma: Unique Challenges and Potential Opportunities through Immunomodulation

Identification of enhancer RNA AC005515.1 as a novel biomarker for prognosis in esophageal cancer and predictors of immunotherapy response

Background

The enhancer RNA (eRNA) signature shows excellent promise in the prognostic role of many malignancies, but its value has not been fully explored in esophageal cancer (ESCA).

Methods

We comprehensively analyzed 33 oncogene expression matrices and clinical data from The Cancer Genome Atlas (TCGA) and identified ESCA prognostic-related key eRNAs by Kaplan-Meier and co-expression analysis. We also investigated the prognostic role of the key eRNA using a series of bioinformatics approaches, including immune infiltration, immune function, immune subtypes, and the tumor microenvironment. Finally, the tumor immune dysfunction and exclusion (TIDE) score was used to predict the immune response to immune checkpoint blockade (ICB) therapy.

Results

We identified eRNA AC005515.1, AC012368.1, AP003469.2, Clorf61, and WDFY3-AS2 were associated with the prognosis of ESCA. AC005515.1 is a critical prognostic-related eRNA in ESCA and was significantly co-expressed with immune checkpoint genes (CTLA4, CD274, etc.). In the pan-cancer analysis, AC005515.1 was also associated with the prognosis of seven cancers, including kidney renal papillary cell carcinoma and low-grade brain glioma. It was also found to be co-expressed with immune checkpoint genes in these tumors. Moreover, high expression of AC005515.1 was associated with CD8+ T cells and M1 macrophages infiltration, and the AC005515.1 high-expression group had a higher TIDE score in ESCA.

Conclusions

Overall, eRNA AC005515.1 is associated with the local immune environment of ESCA and may become a new biomarker of ESCA prognosis and immunotherapy response.

Prognostic value of the S100 calcium-binding protein family members in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains a crucial public health problem around the world, and the outlook remains bleak. More accurate prediction models are urgently needed because of the great heterogeneity of HCC. The S100 protein family contains over 20 differentially expressed members, which are commonly dysregulated in cancers. In the present study, we analyzed the expression profile of S100 family members in patients with HCC based on the TCGA database. A novel prognostic risk score model, based on S100 family members, was developed using the least absolute shrinkage and selection operator regression algorithm, to analyze the clinical outcome. Our prediction model showed a powerful predictive value (1-year AUC: 0.738; 3-year AUC: 0.746; 5-year AUC: 0.813), while two former prediction models had less excellent performances than ours. And the S100 family members-based subtypes reveal the heterogeneity in many aspects, including gene mutations, phenotypic traits, tumor immune infiltration, and predictive therapeutic efficacy. We further investigated the role of S100A9, one member with the highest coefficient in the risk score model, which was mainly expressed in para-tumoral tissues. Using the Single-Sample Gene Set Enrichment Analysis algorithm and immunofluorescence staining of tumor tissue sections, we found that S100A9 may be associated with macrophages. These findings provide a new potential risk score model for HCC and support further study of S100 family members in patients, especially S100A9.

Research Progress in Alpha-Fetoprotein-Induced Immunosuppression of Liver Cancer

Abstract:

Liver cancer is one of the most common malignant tumors, with limited treatment and 8.2% high mortality. Liver cancer is the fourth leading cause of cancer-related deaths, which seriously endangers human life and health. Approximately 70% of liver cancer patients show increased serum alpha-fetoprotein (AFP) levels. AFP is the main diagnostic and prognostic indicator of liver cancer. AFP, a key marker of liver cancer, plays a crucial role in regulating the proliferation of tumor cells, apoptosis, and induction of cellular immune escape. High levels of AFP during embryonic development protect the embryos from maternal immune attack. AFP also promotes immune escape of liver cancer cells by inhibiting tumor-infiltrating lymphocytes (TILs), natural killer cells (NK), dendritic cells (DC), and macrophages; thus, it is also used as a target antigen in immunotherapy for liver cancer. AFP is highly expressed in liver cancer cells. In addition to being used in the diagnosis of liver cancer, it has become a target of immunotherapy for liver cancer as a tumor-associated antigen. In immunotherapy, it was also confirmed that early AFP response was positively correlated with the efficacy of immunotherapy. Early AFP responders had longer PFS and OS than non-responders. At present, the methods of immunotherapy for liver cancer mainly include Adoptive Cell Transfer Therapy (ACT), tumor vaccine therapy, immune checkpoint inhibitors (ICIs) therapy and so on. A large number of studies have shown that AFP mainly plays a role in ACT and liver cancer vaccines. This review presents the research progress of AFP and immunosuppression of liver cancer.

Involvement of the circular RNA/microRNA/glucose-6-phosphate dehydrogenase axis in the pathological mechanism of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death worldwide with high mortality. The incidence of HCC is increasing in China. Abnormal activation of glucose-6-phosphate dehydrogenase (G6PD) exists in all malignant tumors, including HCC, and is closely related to the development of HCC. In addition, the differential expression of non-coding RNAs is closely related to the development of HCC. This systematic review focuses on the relationship between G6PD, HCC, and non-coding RNA, which form the basis for the circRNA/miRNA/G6PD axis in HCC. The circular RNA (circRNA)/microRNA (miRNA)/G6PD axis is involved in development of HCC. We proposed that non-coding RNA molecules of the circRNA/miRNA/G6PD axis may be novel biomarkers for the pathological diagnosis, prognosis, and targeted therapy of HCC.

Systematic Construction and Validation of a Prognostic Model for Hepatocellular Carcinoma Based on Immune-Related Genes

Hepatocellular carcinoma (HCC), a highly aggressive tumor, has high incidence and mortality rates. Recently, immunotherapies have been shown to be a promising treatment in HCC. The results of either the CheckMate-040 or IMbrave 150 trials demonstrate the importance of immunotherapy in the systemic treatment of liver cancer. Thus, in this study, we tried to establish a reliable prognostic model for liver cancer based on immune-related genes (IRGs) and to provide a new insight for immunotherapy of HCC. In this study, we used four datasets that incorporated 851 HCC samples, including 340 samples with complete clinical information from the cancer genome atlas (TCGA) database, to establish an effective model for predicting the prognosis of HCC patients based on the differential expression of IRGs and validated the prognostic model using the data from International Cancer Genome Consortium (ICGC). The top 6 characteristic IRGs identified by protein-protein interaction (PPI) network analysis, MMP9, FOS, CAT, ESR1, ANGPTL3, and KLKB1, were selected for further study. In addition, we assessed the correlations of the six characteristic IRGs with the tumor immune microenvironment, clinical stage, and sensitivity to anti-cancer drugs. We also explored whether the differential expression of the characteristic IRGs was specific to HCC or present in pan-cancer. The expression levels of the six characteristic IRGs were significantly different between most tumor tissues and adjacent normal tissues. In addition, these characteristic IRGs showed a strong association with immune cell infiltration in HCC patients. We found that MMP9 and ESR1 were independent prognostic factors for HCC, while CAT, ESR1, and KLKB1 were associated with the clinical stage. We collected HCC paraffin sections from 24 patients from Xijing hospital to identify the differential expression of the five genes (MMP9, ESR1, CAT, FOS, and KLKB1). Finally, the results of decision curve analysis (DCA) and nomogram revealed that our models provided a prognostic benefit for most HCC patients and the predicted overall survival (OS) was consistent with the actual OS. In conclusion, we systemically constructed a novel prognostic model that provides new insights into HCC.

Integrative Characterization of Immune-relevant Genes in Hepatocellular Carcinoma

BACKGROUND AND AIMS

Tumor microenvironment plays an essential role in cancer development and progression. Cancer immunotherapy has become a promising approach for the treatment of hepatocellular carcinoma (HCC). We aimed to analyze the HCC immune microenvironment characteristics to identify immune-related genetic changes.

METHODS

Key immune-relevant genes (KIRGs) were obtained through integrating the differentially expressed genes of The Cancer Genome Atlas, immune genes from the Immunology Database and Analysis Portal, and immune differentially expressed genes determined by single-sample gene set enrichment analysis scores. Cox regression analysis was performed to mine therapeutic target genes. A regulatory network based on KIRGs, transcription factors, and immune-related long non-coding RNAs (IRLncRNAs) was also generated. The outcomes of risk score model were validated in a testing cohort and in clinical samples using tissue immunohistochemistry staining. Correlation analysis between risk score and immune checkpoint genes and immune cell infiltration were investigated.

RESULTS

In total, we identified 21 KIRGs, including programmed cell death-1 (PD-1) and cytotoxic T-lymphocyte associated protein 4 (CTLA4), and found IKBKE, IL2RG, EDNRA, and IGHA1 may be equally important to PD-1 or CTLA4. Meanwhile, KIRGs, various transcription factors, and IRLncRNAs were integrated to reveal that the NRF1-AC127024.5-IKBKE axis might be involved in tumor immunity regulation. Furthermore, the immune-related risk score model was established according to KIRGs and key IRLncRNAs, and verified more obvious discriminating power in the testing cohort. Correlation analysis indicated TNFSF4 , LGALS9 , KIAA1429 , IDO2, and CD276 were closely related to the risk score, and CD4 T cells, macrophages, and neutrophils were the primary immune infiltration cell types.

CONCLUSIONS

Our results highlight the importance of immune genes in the HCC microenvironment and further unravel the underlying molecular mechanisms in the development of HCC.

Identification and Validation of an Immune-Related eRNA Prognostic Signature for Hepatocellular Carcinoma

Background

Enhancer RNAs (eRNAs) are intergenic long non-coding RNAs (lncRNAs) that participate in the progression of malignancies by targeting tumor-related genes and immune checkpoints. However, the potential role of eRNAs in hepatocellular carcinoma (HCC) is unclear. In this study, we aimed to construct an immune-related eRNA prognostic model that could be used to prospectively assess the prognosis of patients with HCC.

Methods

Gene expression profiles of patients with HCC were downloaded from The Cancer Genome Atlas (TCGA). The eRNAs co-expressed from immune genes were identified as immune-related eRNAs. Cox regression analyses were applied in a training cohort to construct an immune-related eRNA signature (IReRS), that was subsequently used to analyze a testing cohort and combination of the two cohorts. Kaplan-Meier and receiver operating characteristic (ROC) curves were used to validate the predictive effect in the three cohorts. Gene Set Enrishment Analysis (GSEA) computation was used to identify an IReRS-related signaling pathway. A web-based cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) computation was used to evaluate the relationship between the IReRS and infiltrating immune cells.

Results

A total of sixty-four immune-related eRNAs (IReRNAs) was identified in HCC, and 14 IReRNAs were associated with overall survival (OS). Five IReRNAs were used for constructing an immune-related eRNA signature (IReRS), which was shown to correlate with poor survival and to be an independent prognostic biomarker for HCC. The GSEA results showed that the IReRS was correlated to cancer-related and immune-related pathways. Moreover, we found that IReRS was correlated to infiltrating immune cells, including CD8⁺ T cells and M0 macrophages. Finally, differential expressions of the five risk IReRNAs in tumor tissues vs. adjacent normal tissues and their prognostic values were verified, in which the AL445524.1 may function as an oncogene that affects prognosis partly by regulating CD4-CLTA4 related genes.

Conclusion

Our results suggest that the IReRS could serve as a biomarker for predicting prognosis in patients with HCC. Additionally, it may be correlated to the tumor immune microenvironment and could also be used as a biomarker in immunotherapy for HCC.

Identification of Hub Genes Associated With Immune Infiltration and Predict Prognosis in Hepatocellular Carcinoma via Bioinformatics Approaches

Aims

In the cancer-related research field, there is currently a major need for a greater number of valuable biomarkers to predict the prognosis of hepatocellular carcinoma (HCC). In this study, we aimed to screen hub genes related to immune cell infiltration and explore their prognostic value for HCC.

Methods

We analyzed five datasets (GSE46408, GSE57957, GSE74656, GSE76427, and GSE87630) from the Gene Expression Omnibus database to screen the differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes; then, the hub genes were identified. Functional enrichment of the genes was performed on the Metascape website. Next, the expression of these hub genes was validated in several databases, including Oncomine, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Human Protein Atlas. We explored the correlations between the hub genes and infiltrated immune cells in the TIMER2.0 database. The survival curves were generated in GEPIA2, and the univariate and multivariate Cox regression analyses were performed using TIMER2.0.

Results

The top ten hub genes [DNA topoisomerase II alpha (TOP2A), cyclin B2 (CCNB2), protein regulator of cytokinesis 1 (PRC1), Rac GTPase-activating protein 1 (RACGAP1), aurora kinase A (AURKA), cyclin-dependent kinase inhibitor 3 (CDKN3), nucleolar and spindle-associated protein 1 (NUSAP1), cell division cycle-associated 5 (CDCA5), abnormal spindle microtubule assembly (ASPM), and non-SMC condensin I complex subunit G (NCAPG)] were identified in subsequent analysis. These genes are most markedly enriched in cell division, suggesting their close association with tumorigenesis. Multi-database analyses validated that the hub genes were upregulated in HCC tissues. All hub genes positively correlated with several types of immune infiltration, including B cells, CD4⁺ T cells, macrophages, and dendritic cells. Furthermore, these hub genes served as independent prognostic factors, and the expression of these hub genes combing with the macrophage levels could help predict an unfavorable prognosis of HCC.

Conclusion

In sum, these hub genes (TOP2A, CCNB2, PRC1, RACGAP1, AURKA, CDKN3, NUSAP1, CDCA5, ASPM, and NCAPG) may be pivotal markers for prognostic prediction as well as potentially work as targets for immune-based intervention strategies in HCC.

Immunotherapy for Hepatocellular Carcinoma: A 2021 Update

Hepatocellular carcinoma (HCC) is one of one of the most frequent liver cancers and the fourth leading cause of cancer-related mortality worldwide. Current treatment options such as surgery, neoadjuvant chemoradiotherapy, liver transplantation, and radiofrequency ablation will benefit only a very small percentage of patients. Immunotherapy is a novel treatment approach representing an effective and promising option against several types of cancer. The aim of our study is to present the currently ongoing clinical trials and to evaluate the efficacy of immunotherapy in HCC. In this paper, we demonstrate that combination of different immunotherapies or immunotherapy with other modalities results in better overall survival (OS) and progression-free survival (PFS) compared to single immunotherapy agent. Another objective of this paper is to demonstrate and highlight the importance of tumor microenvironment as a predictive and prognostic marker and its clinical implications in immunotherapy response.