Development and validation of a robust immune-related risk signature for hepatocellular carcinoma

Immunotherapy Plus Locoregional Therapy Leading to Curative-Intent Hepatectomy in HCC: Proof of Concept Producing Durable Survival Benefits Detectable with Liquid Biopsy

BACKGROUND

Immunotherapy has emerged as an improved systemic treatment for select patients with advanced unresectable HCC. Objective response is reported in 30% of patients, yet complete response (pCR) allowing for curative-intent resection is rare. Locoregional therapies (LRTs) seem to show synergistic effects with immunotherapy, though this effect has not been scientifically reported. We report a cohort of patients showing pCR to immunotherapy + LRT as a proof of concept for the proposed treatment approach for locally unresectable HCC.

METHODS

Patients with unresectable HCC treated with immunotherapy as an intended destination therapy from 2016 to 2023 were included. The electronic health record was queried for oncologic information, locoregional therapies, surgical interventions, and long-term outcomes. Circulating tumor DNA (ctDNA) testing was obtained using Guardant360, and tumor mutational burden (TMB) was defined as the number of somatic mutations per megabase.

RESULTS

Ninety-six patients with advanced HCC received immunotherapy + LRT as a destination therapy. In total, 11 of 96 patients showed a complete response according to mRECIST criteria. Four of these (36.4%) ultimately underwent curative-intent resection. The median follow-up was 24.9 (IQR 15.6-38.3) months. Overall survival rates in those with complete response at 1, 3, and 5 years were 100%, 91%, and 81.8%, respectively, which were significantly improved compared to those of the cohort not achieving pCR (p < 0.001). All four patients undergoing immunotherapy + LRT followed by curative-intent hepatectomy have no evidence of disease (NED). Of those undergoing surgery, ctDNA was cleared in 75% (n = 3), providing an additional objective measurement of complete response. All four patients were TMB+ before beginning this treatment course, with three being TMB-, indicating stable and complete disease response.

CONCLUSIONS

Immunotherapy + locoregional therapy can help downstage a significant proportion of patients with initially unresectable HCC, allowing for curative-intent surgery. The survival benefit associated with complete response seems durable up to 3 years after achieving this response. ctDNA measurement was converted from positive to negative in this cohort, providing additional indication of response.

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.

EIF2S2 is a novel independent prognostic biomarker and correlated with immune infiltrates in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is a highly malignant disease with poor prognosis. It is urgent to find effective biomarkers. Eukaryotic Translation Initiation Factor 2 Subunit Beta (EIF2S2) is a subunit of heterotrimeric G protein EIF2, and its function is still unclear. We studied the role of EIF2S2 in the malignant progression of liver cancer and its relationship with immune infiltration.

Methods: Download the RNA expression and clinical information of EIF2S2 from the Cancer Genome Atlas (TCGA) database, analyze the relationship between the expression of EIF2S2 and the prognosis and clinicopathological characteristics of HCC, analyze the differential genes by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and tumor related immune infiltrating cells. The Protein expression level of EIF2S2 was obtained from Human Protein Atlas (HPA) databases. The relationship between EIF2S2 expression and immune infiltrates in HCC was analyzed on TIMER 2.0. The data processing analysis based on R language. Drug Sensitivity data from Genomics of Drug Sensitivity in Cancer (GDSC).

Results: EIF2S2 is highly expressed in HCC patients and is associated with poor prognosis. The expression of EIF2S2 was also correlated with age, clinical stage and pathological grade. Univariate and multivariate COX regression analysis showed that EIF2S2 was an independent risk factor for survival. The receiver operating characteristic (ROC) curve of EIF2S2 also confirmed the diagnostic value of EIF2S2 in HCC patients. Through GO and KEGG enrichment analysis, EIF2S2 expression was found to be closely related to some immune pathways. The expression of EIF2S2 was correlated with memory B cell, plasma B cell, CD8+ T cell, CD4+ resting memory T cell and the expression of some immune checkpoints, such as PDCD1, TIGIT and CTLA-4. It is also more sensitive to paclitaxel, sunitinib and other drugs.

Conclusion: This study shows that EIF2S2 can be used as a prognostic factor for HCC, which is closely related to immune infiltration and immune checkpoints, and may play a potential regulatory role in predicting drug sensitivity.

A Novel and Robust Prognostic Model for Hepatocellular Carcinoma Based on Enhancer RNAs-Regulated Genes

Evidence has demonstrated that enhancer RNAs (eRNAs) play a vital role in the progression and prognosis of cancers, but few studies have focused on the prognostic ability of eRNA-regulated genes (eRGs) for hepatocellular carcinoma (HCC). Using gene expression profiles of HCC patients from the TCGA-LIHC and eRNA expression profiles from the enhancer RNA in cancers (eRic) data portal, we developed a novel and robust prognostic signature composed of 10 eRGs based on Lasso-penalized Cox regression analysis. According to the signature, HCC patients were stratified into high- and low-risk groups, which have been shown to have significant differences in tumor immune microenvironment, immune checkpoints, HLA-related genes, DNA damage repair-related genes, Gene-set variation analysis (GSVA), and the lower half-maximal inhibitory concentration (IC50) of Sorafenib. The prognostic nomogram combining the signature, age, and TNM stage had good predictive ability in the training set (TCGA-LIHC) with the concordance index (C-index) of 0.73 and the AUCs for 1-, 3-, and 5-year OS of 0.82, 0.77, 0.74, respectively. In external validation set (GSE14520), the nomogram also performed well with the C-index of 0.71 and the AUCs for 1-, 3-, and 5-year OS of 0.74, 0.77, 0.74, respectively. In addition, an important eRG (AKR1C3) was validated using two HCC cell lines (Huh7 and MHCC-LM3) in vitro, and the results demonstrated the overexpression of AKR1C3 is related to cell proliferation, migration, and invasion in HCC. Altogether, our eRGs signature and nomogram can predict prognosis accurately and conveniently, facilitate individualized treatment, and improve prognosis for HCC patients.

An extracellular matrix-based signature associated with immune microenvironment predicts the prognosis of patients with hepatocellular carcinoma

OBJECTIVE

Increased data showed that genes related to extracellular matrix (ECM) are important to hepatocellular carcinoma (HCC) development. In contrast, no research was carried out that proposed that ECM-related genes should be reliable prognostic signature.

METHODS

This study used data from The Cancer Genome Atlas along with The International Cancer Genome Consortium to gather ECM-related gene expression as well as clinical information related to the extracellular matrix. The least absolute shrinkage, Cox analysis, along with selection operator Cox regression and random forest have been utilized for establishing an ECM-related prognostic models.

RESULTS

A series of investigations led us to identify 13 ECMs which we utilized to construct a prognostic signature with a larger area under the curve of 0.808. HCC patients have been categorized into 2 main groups based on the risk score formula: low risk along with high risk. The findings of the Kaplan-Meier curve revealed that there had been a statistically significant difference between these two groups. Our ECM-related signature can be utilized as independent predictor of survival in HCC. Low-risk patients stratified by the final model presented higher sensitivity to 8 targeted drugs (especially sorafenib) and 2 common chemo-drugs. Our gene set enrichment analysis outcomes recommended that high-risk group have been enriched in ECM, tumorigenesis, as well as immune-related pathways. Immune cell analysis showed that high-risk group had lower cell fraction of CD8+ T cells, Macrophages M1, B naïve cells, memory resting CD4+ T cells, Monocytes, resting Dendritic cells and activated Mast cells, along with higher PD-1 and CTLA4 expression levels as compared to low-risk group.

CONCLUSION

Our identified ECM-related signature can also give new insight into underlying mechanisms along with therapeutic strategies in order to treat HCC.

Predictive biomarkers for systemic therapy of hepatocellular carcinoma

Introduction: Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the third cancer-related cause of death worldwide. In recent years, several systemic therapy drugs including sorafenib, lenvatinib, regorafenib, cabozantinib, ramucicurab, nivilumab, and pembrolizumab have been approved by FDA for advanced HCC. However, their insufficient efficacy, toxicity, and drug resistance require clinically applicable and validated predictive biomarkers.Areas covered: Our review covers the recent advancements in the identification of proteomic/genomic/epigenomic/transcriptomic biomarkers for predicting HCC treatment efficacy with the use of multi-kinase inhibitors (MKIs), CDK4/6 inhibitors, and immune checkpoint inhibitors (ICIs). Alpha-fetoprotein, des-carboxyprothrombin, vascular endothelial growth factor, angiopoietin-2, and dysregulated MTOR, VEGFR2, c-KIT, RAF1, PDGFRβ have the potential of proteomic/genomic biomarkers for sorafenib treatment. Alanine aminotransferase, aspartate aminotransferase, and albumin-bilirubin grade can predict the efficacy of other MKIs. Rb, p16, and Ki-67, and genes involved in cell cycle regulation, CDK1-4, CCND1, CDKN1A, and CDKN2A have been proposed for CD4/6 inhibitors, while dysregulated TERT, CTNNB1, TP53 FGF19, and TP53 are found to be predictors for ICI efficacy.Expert opinion: There are still limited clinically applicable and validated predictive biomarkers to identify HCC patients who benefit from systemic therapy. Further prospective biomarker validation studies for HCC personalized systemic therapy are required.