Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis

A novel tumor 4-driver gene signature for the prognosis of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC), the main type of liver cancer, is the second most lethal tumor worldwide, with a 5-year survival rate of only 18%. Driver genes facilitate cancer cell growth and spread in the tumor microenvironment. Here, a comprehensive driver gene signature for the prognosis of HCC was developed.

Methods

HCC driver genes were analyzed comprehensively to develop a better prognostic signature. The dataset of HCC patients included mRNA sequencing data and clinical information from the TCGA, the ICGC, and the Guangxi Medical University Cancer Hospital cohorts. First, LASSO was performed to develop a prognostic signature for differentially expressed driver genes in the TCGA cohort. Then, the robustness of the signature was assessed using survival and time-dependent ROC curves. Furthermore, independent predictors were determined using univariate and multivariate Cox regression analyses. Stepwise multi-Cox regression analysis was employed to identify significant variables for the construction of a nomogram that predicts survival rates. Functional analysis by Spearman correlation analysis, enrichment analysis (GO, KEGG, and GSEA), and immunoassay (ssGSEA and xCell) were performed.

Result

A 4-driver gene signature (CLTC, DNMT3A, GMPS, and NRAS) was successfully constructed and showed excellent predictive efficiency in three cohorts. The nomogram indicated high predictive accuracy for the 1-, 3-, and 5-year prognoses of HCC patients, which included clinical information and risk score. Enrichment analysis revealed that driver genes were involved in regulating oncogenic processes, including the cell cycle and metabolic pathways, which were associated with the progression of HCC. ssGSEA and xCell showed differences in immune infiltration and the immune microenvironment between the two risk groups.

Conclusion

The 4-driver gene signature is closely associated with the survival prediction of HCC and is expected to provide new insights into targeted therapy for HCC patients.

T-cell exhaustion signatures characterize the immune landscape and predict HCC prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing

Background

Hepatocellular carcinoma (HCC), the third most prevalent cause of cancer-related death, is a frequent primary liver cancer with a high rate of morbidity and mortality. T-cell depletion (TEX) is a progressive decline in T-cell function due to continuous stimulation of the TCR in the presence of sustained antigen exposure. Numerous studies have shown that TEX plays an essential role in the antitumor immune process and is significantly associated with patient prognosis. Hence, it is important to gain insight into the potential role of T cell depletion in the tumor microenvironment. The purpose of this study was to develop a trustworthy TEX-based signature using single-cell RNA-seq (scRNA-seq) and high-throughput RNA sequencing, opening up new avenues for evaluating the prognosis and immunotherapeutic response of HCC patients.

Methods

The International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases were used to download RNA-seq information for HCC patients. The 10x scRNA-seq. data of HCC were downloaded from GSE166635, and UMAP was used for clustering descending, and subgroup identification. TEX-related genes were identified by gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). Afterward, we established a prognostic TEX signature using LASSO-Cox analysis. External validation was performed in the ICGC cohort. Immunotherapy response was assessed by the IMvigor210, GSE78220, GSE79671, and GSE91061cohorts. In addition, differences in mutational landscape and chemotherapy sensitivity between different risk groups were investigated. Finally, the differential expression of TEX genes was verified by qRT-PCR.

Result

11 TEX genes were thought to be highly predictive of the prognosis of HCC and substantially related to HCC prognosis. Patients in the low-risk group had a greater overall survival rate than those in the high-risk group, according to multivariate analysis, which also revealed that the model was an independent predictor of HCC. The predictive efficacy of columnar maps created from clinical features and risk scores was strong.

Conclusion

TEX signature and column line plots showed good predictive performance, providing a new perspective for assessing pre-immune efficacy, which will be useful for future precision immuno-oncology studies.

Tumor Mutational Burden for Predicting Prognosis and Therapy Outcome of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), the primary hepatic malignancy, represents the second-highest cause of cancer-related death worldwide. Many efforts have been devoted to finding novel biomarkers for predicting both patients' survival and the outcome of pharmacological treatments, with a particular focus on immunotherapy. In this regard, recent studies have focused on unravelling the role of tumor mutational burden (TMB), i.e., the total number of mutations per coding area of a tumor genome, to ascertain whether it can be considered a reliable biomarker to be used either for the stratification of HCC patients in subgroups with different responsiveness to immunotherapy, or for the prediction of disease progression, particularly in relation to the different HCC etiologies. In this review, we summarize the recent advances on the study of TMB and TMB-related biomarkers in the HCC landscape, focusing on their feasibility as guides for therapy decisions and/or predictors of clinical outcome.

The safety concerns regarding immune checkpoint inhibitors in liver cancer patients rising mainly from CHB

Aim: To analyze the safety of immune checkpoint inhibitors in primary liver cancer patients and to identify the risk factors for immune-related adverse events (irAEs). Methods: The study enrolled 106 patients with primary liver cancer, including 81 with hepatocellular carcinoma and 25 with intrahepatic cholangiocarcinoma. We analyzed the differences between groups in irAE occurrence, including those with and without targeted drugs and those who received interventional therapy. Results: The incidence of irAEs was 39%, with thyroid function, liver function, and skin events being the most common. There was no correlation among irAE incidence and the liver cancer type, stage, or severity; grade of Child-Pugh score; and Barcelona Clinical Liver Cancer classification. However, being overweight was a significant risk factor for irAEs, correlating with high body mass index. The combination of targeted drugs and/or transcatheter arterial chemoembolization therapy did not increase the incidence of irAEs. Conclusion: Being overweight is a potential risk factor for irAEs in primary liver cancer patients. However, there is no correlation between irAE incidence and the liver cancer type, stage, or severity or a combination of targeted drugs or transarterial chemoembolization therapy.

MMP1 acts as a potential regulator of tumor progression and dedifferentiation in papillary thyroid cancer

Papillary thyroid cancer (PTC) is one of the malignancies with an excellent prognosis. However, in PTC, progression or dedifferentiation into poorly differentiated thyroid cancer (PDTC) or anaplastic thyroid cancer (ATC) extremely jeopardizes patients’ prognosis. MMP1 is a zinc-dependent endopeptidase, and its role in PTC progression and dedifferentiation is unclear. In this study, transcriptome data of PDTC/ATC and PTC from the Gene Expression Omnibus and The Cancer Genome Atlas databases were utilized to perform an integrated analysis of MMP1 as a potential regulator of tumor progression and dedifferentiation in PTC. Both bulk and single-cell RNA-sequencing data confirmed the high expression of MMP1 in ATC tissues and cells, and further study verified that MMP1 possessed good diagnostic and prognostic value in PTC and PDTC/ATC. Up-regulated MMP1 was found to be positively related to more aggressive clinical characteristics, worse survival, extracellular matrix-related pathways, oncogenic immune microenvironment, more mutations, higher stemness, and more dedifferentiation of PTC. Meanwhile, in vitro experiments verified the high level of MMP1 in PDTC/ATC cell lines, and MMP1 knockdown and its inhibitor triolein could both inhibit the cell viability of PTC and PDTC/ATC. In conclusion, our findings suggest that MMP1 is a potential regulator of tumor progression and dedifferentiation in PTC, and might become a novel therapeutic target for PTC, especially for more aggressive PDTC and ATC.

Which role for predictors of response to immune checkpoint inhibitors in hepatocellular carcinoma?

INTRODUCTION

Hepatocellular carcinoma (HCC) remains a frequently diagnosed malignancy worldwide, still representing an important cause of cancer-related death. Recent years have seen the emergence of novel systemic treatments for HCC patients, including immune checkpoint inhibitors (ICIs). Nonetheless, several questions regarding HCC immunotherapy remain unanswered, especially in terms of biochemical predictors of response.

AREAS COVERED

In the current paper, we will discuss available evidence regarding predictive biomarkers of response to HCC immunotherapy. A literature search was conducted in January 2022 of Pubmed/Medline, Cochrane library, and Scopus databases.

EXPERT OPINION

The identification of predictive biomarkers represents an unmet need in HCC patients receiving ICIs. The HCC medical community is called to further efforts aimed to elucidate the effective role of PD-L1 expression, TMB, MSI, gut microbiota, and other emerging biomarkers.

Predictive Biomarkers for Checkpoint Inhibitor-Based Immunotherapy in Hepatocellular Carcinoma: Where Do We Stand?

Hepatocellular carcinoma (HCC) remains the sixth most commonly diagnosed malignancy worldwide, still representing an important cause of cancer-related death. Over the next few years, novel systemic treatment options have emerged. Among these, immune checkpoint inhibitors (ICIs) have been widely evaluated and are under assessment, as monotherapy or in combination with other anticancer agents in treatment-naïve and previously treated patients. In particular, the approval of the PD-L1 inhibitor atezolizumab plus the antiangiogenic agent bevacizumab as front-line treatment for advanced HCC has led to the adoption of this combination in this setting, and the IMbrave 150 phase III trial has established a novel standard of care. However, several questions remain unanswered, including the identification of reliable predictors of response to ICIs in HCC patients. In the current paper, we will provide an updated overview of potentially useful predictive biomarkers of response to immunotherapy in advanced HCC. A literature search was conducted in September 2021 of Pubmed/Medline, Cochrane library and Scopus databases.

Liquid-Liquid Phase Separation-Related Genes Associated with Tumor Grade and Prognosis in Hepatocellular Carcinoma: A Bioinformatic Study

Aim

The aim of the present study was to identify the association between tumor grade and liquid-liquid phase separation (LLPS)-related genes, and to generate a LLPS-related gene-based risk index (LLPSRI) as a prognostic tool for hepatocellular carcinoma (HCC).

Methods

Weighted gene correlation network analysis was performed to test whether the LLPS-related gene modules were associated with tumor grade of HCC. The candidate modules were subjected to functional enrichment analysis. We generated a LLPSRI using the expression profiles of the hub genes among the candidate modules in order to identify patients at high risk. Then, the biological characteristics of the high-risk patients were revealed using gene set enrichment analysis. Additionally, an independent external data set was used to validate the LLPSRI.

Results

Four gene modules showed a significant positive correlation with tumor grade and involved various cancer-related pathways. Among the hub genes, six were selected to generate the LLPSRI, which was significantly associated with prognosis of HCC patients. The LLPSRI could successfully divide patients with HCC into high- and low-risk groups, and patients in the high-risk group showed shorter overall survival than those in the low-risk group. E2F, MYC, and mTORC1 signaling may be important determinants of survival in the high-risk group. The prognostic value of the LLPSRI was validated with the independent external data set.

Conclusion

We identified LLPS-related gene modules that are associated with HCC tumor grade. The LLPSRI may be useful as a prognostic marker of HCC, and it may reliably stratify patients into groups at low or high risk of worse survival. Our analysis also suggests that certain biological characteristics of HCC may be associated with high risk of worse survival.

Immunogenomic Landscape Analysis of Prognostic Immune-Related Genes in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death. HBV infection is an important risk factor for the tumorigenesis of HCC, given that the inflammatory environment is closely related to morbidity and prognosis. Consequently, it is of urgent importance to explore the immunogenomic landscape to supplement the prognosis of HCC. The expression profiles of immune-related genes (IRGs) were integrated with 377 HCC patients to generate differentially expressed IRGs based on the Cancer Genome Atlas (TCGA) dataset. These IRGs were evaluated and assessed in terms of their diagnostic and prognostic values. A total of 32 differentially expressed immune-related genes resulted as significantly correlated with the overall survival of HCC patients. The Gene Ontology functional enrichment analysis revealed that these genes were actively involved in cytokine-cytokine receptor interaction. A prognostic signature based on IRGs (HSPA4, PSME3, PSMD14, FABP6, ISG20L2, TRAF3, NDRG1, NRAS, CSPG5, and IL17D) stratified patients into high-risk versus low-risk groups in terms of overall survival and remained as an independent prognostic factor in multivariate analyses after adjusting for clinical and pathologic factors. Several IRGs (HSPA4, PSME3, PSMD14, FABP6, ISG20L2, TRAF3, NDRG1, NRAS, CSPG5, and IL17D) of clinical significance were screened in the present study, revealing that the proposed clinical-immune signature is a promising risk score for predicting the prognosis of HCC.

PD-L1, TMB, and other potential predictors of response to immunotherapy for hepatocellular carcinoma: how can they assist drug clinical trials?

INTRODUCTION

Hepatocellular carcinoma (HCC) represents the sixth most commonly diagnosed malignancy worldwide, accounting for millions of deaths annually. Despite immune checkpoint inhibitors (ICIs) reported important results, only a minority of HCC patients benefit from these treatments, and the identification of predictive biomarkers of response still remains a highly unmet need.

AREAS COVERED

Herein, we provide a timely overview of available evidence on biochemical predictors of response to immunotherapy in advanced HCC patients; we speculate on how PD-L1, TMB, and other emerging biomarkers could assist drug clinical trials in the near future. A literature search was conducted in June 2021 using Pubmed/Medline, Cochrane library, and Scopus databases.

EXPERT OPINION

Reliable predictors of response to ICIs are of pivotal importance to allow a proper stratification and selection of HCC patients that could derive more benefit from immunotherapy. Well-designed, multicenter clinical trials specifically focused on predictive biomarkers are warranted in this setting, where most of evidence currently derives from retrospective, single-center studies with small sample size.

Immunotherapy against programmed death-1/programmed death ligand 1 in hepatocellular carcinoma: Importance of molecular variations, cellular heterogeneity, and cancer stem cells

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy related to diverse etiological factors. Different oncogenic mechanisms and genetic variations lead to multiple HCC molecular classifications. Recently, an immune-based strategy using immune checkpoint inhibitors (ICIs) was presented in HCC therapy, especially with ICIs against the programmed death-1 (PD-1) and its ligand PD-L1. However, despite the success of anti-PD-1/PD-L1 in other cancers, a substantial proportion of HCC patients fail to respond. In this review, we gather current information on biomarkers of anti-PD-1/PD-L1 treatment and the contribution of HCC heterogeneity and hepatic cancer stem cells (CSCs). Genetic variations of PD-1 and PD-L1 are associated with chronic liver disease and progression to cancer. PD-L1 expression in tumoral tissues is differentially expressed in CSCs, particularly in those with a close association with the tumor microenvironment. This information will be beneficial for the selection of patients and the management of the ICIs against PD-1/PD-L1.

Biochemical predictors of response to immune checkpoint inhibitors in unresectable hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents the most commonly diagnosed liver cancer worldwide, and the overall survival of patients with unresectable disease is poor. In the last five years, immune checkpoint inhibitors (ICIs) have revolutionized the treatment scenario of several hematological and solid tumors, and these agents have been actively explored in unresectable HCC. Firstly, promising findings of phase I and II clinical studies reporting durable responses and a tolerable safety profile have led to the assessment of ICIs as single agents in phase III clinical studies; however, the latter have provided controversial results, and the activity of ICI monotherapy seems limited to a small subgroup of patients. Conversely, the IMbrave150 trial recently showed that, among patients with previously untreated unresectable HCC, treatment with atezolizumab plus bevacizumab resulted in significantly longer overall survival and progression-free survival compared to sorafenib monotherapy. In addition, the activity of several other ICIs is under investigation, as combination immunotherapy as well as combinations of immunotherapy with antiangiogenic agents. Nonetheless, there are currently no validated predictive biomarkers able to guide treatment choice in this setting, where the identification of specific predictors of response to ICIs represents a major challenge. In this review, we aim to provide a critical overview of recent evidence on biochemical predictors of response to ICIs in patients with unresectable HCC, especially focusing on PD-L1, TMB, MSI, and other emerging biomarkers.