Immunobiology and immunotherapy of HCC: spotlight on innate and innate-like immune cells

Regulatory T cells and immune escape in HCC: understanding the tumor microenvironment and advancing CAR-T cell therapy

Liver cancer, which most commonly manifests as hepatocellular carcinoma (HCC), is the sixth most common cancer in the world. In HCC, the immune system plays a crucial role in the growth and proliferation of tumor cells. HCC achieve immune escape through the tumor microenvironment, which significantly promotes the development of this cancer. Here, this article introduces and summarizes the functions and effects of regulatory T cells (Tregs) in the tumor microenvironment, highlighting how Tregs inhibit and regulate the functions of immune and tumor cells, cytokines, ligands and receptors, etc, thereby promoting tumor immune escape. In addition, it discusses the mechanism of CAR-T therapy for HCC and elaborate on the relationship between CAR-T and Tregs.

Research trends and hotspots in the immune microenvironment related to hepatocellular carcinoma: A bibliometric and visualization study

BACKGROUND

The immune microenvironment (IME) in hepatocellular carcinoma (HCC) plays a pivotal role in determining patient outcomes and responses to treatment. This area is witnessing rapid growth in research interest. However, there is a lack of comprehensive bibliometric analyses that dissect trends and potential focal points in this field.

AIM

To explore the evolution of research on the IME in HCC from January 1, 2004, to December 31, 2023, using bibliometric methodologies.

METHODS

English articles and reviews concerning the IME of HCC were retrieved from the Web of Science Core Collection with a search date of December 31, 2023. The R package Bibliometrix was employed to compute basic bibliometric characteristics, illustrate collaborations among countries and authors, and create a three-field diagram illustrating the connections between authors, affiliations, and keywords. Analyses of country and institutional co-authorship, as well as keyword co-occurrence, were conducted using VOSviewer. Additionally, CiteSpace was utilized for the cite burst analysis of keywords and cited literature.

RESULTS

The study encompassed 3125 documents in the research areas related to HCC of IME, revealing a substantial and continuous increase in the annual publication trend over time. China and Fudan University emerged as leading contributors, with 2103 and 165 publications, respectively. Frontiers in immunology was the most prolific journal in this domain. Among the top ten researchers in the field, eight are based in China. Key research terms identified include tumour microenvironment, expression, immunotherapy, and prognosis.

CONCLUSION

The relationship between HCC and IME is receiving increasing attention, and related research is in a highly developed stage. Key focus areas, including IME and immune checkpoint inhibitors, immunotherapy are poised to be central to future research endeavors, offering promising pathways for further exploration.

Constructing a prognostic model for hepatocellular carcinoma based on bioinformatics analysis of inflammation-related genes

Background

This study aims to screen inflammation-related genes closely associated with the prognosis of hepatocellular carcinoma (HCC) to accurately forecast the prognosis of HCC patients.

Methods

Gene expression matrices and clinical information for liver cancer samples were obtained from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). An intersection of differentially expressed genes of HCC and normal and GeneCards yielded inflammation-related genes associated with HCC. Cox regression and the minor absolute shrinkage and selection operator (LASSO) regression analysis to filter genes associated with HCC prognosis. The prognostic value of the model was confirmed by drawing Kaplan-Meier and ROC curves. Select differentially expressed genes between the high-risk and low-risk groups and perform GO and KEGG pathways analyses. CIBERSORT analysis was conducted to assess associations of risk models with immune cells and verified using real-time qPCR.

Results

A total of six hub genes (C3, CTNNB1, CYBC1, DNASE1L3, IRAK1, and SERPINE1) were selected using multivariate Cox regression to construct a prognostic model. The validation evaluation of the prognostic model showed that it has an excellent ability to predict prognosis. A line plot was drawn to indicate the HCC patients' survival, and the calibration curve revealed satisfactory predictability. Among the six hub genes, C3 and DNASE1L3 are relatively low expressed in HCCLM3 and 97H liver cancer cell lines, while CTNNB1, CYBC1, IRAK1, and SERPINE1 are relatively overexpressed in liver cancer cell lines.

Conclusion

One new inflammatory factor-associated prognostic model was constructed in this study. The risk score can be an independent predictor for judging the prognosis of HCC patients' survival.

Innate-like T cells in liver disease

Mammalian innate-like T cells (ILTCs), including mucosal-associated invariant T (MAIT), natural killer T (NKT), and γδ T cells, are abundant tissue-resident lymphocytes that have recently emerged as orchestrators of hepatic inflammation, tissue repair, and immune homeostasis. This review explores the involvement of different ILTC subsets in liver diseases. We explore the mechanisms underlying the pro- and anti-inflammatory effector functions of ILTCs in a context-dependent manner. We highlight latest findings regarding the dynamic interplay between ILTC functional subsets and other immune and parenchymal cells which may inform candidate immunomodulatory strategies to achieve improved clinical outcomes in liver diseases. We present new insights into how distinct gene expression programs in hepatic ILTCs are induced, maintained, and reprogrammed in a context- and disease stage-dependent manner.

TGF-β1-Induced SOX18 Elevation Promotes Hepatocellular Carcinoma Progression and Metastasis Through Transcriptionally Upregulating PD-L1 and CXCL12

BACKGROUND & AIMS

Hepatocellular carcinoma (HCC) is characterized by an immune-suppressive microenvironment, which contributes to tumor progression, metastasis, and immunotherapy resistance. Identification of HCC-intrinsic factors regulating the immunosuppressive microenvironment is urgently needed. Here, we aimed to elucidate the role of SYR-Related High-Mobility Group Box 18 (SOX18) in inducing immunosuppression and to validate novel combination strategies for SOX18-mediated HCC progression and metastasis.

METHODS

The role of SOX18 in HCC was investigated in orthotopic allografts and diethylinitrosamine/carbon tetrachloride-induced spontaneous models by using murine cell lines, adeno-associated virus 8, and hepatocyte-specific knockin and knockout mice. The immune cellular composition in the HCC microenvironment was evaluated by flow cytometry and immunofluorescence.

RESULTS

SOX18 overexpression promoted the infiltration of tumor-associated macrophages (TAMs) and regulatory T cells (Tregs) while diminishing cytotoxic T cells to facilitate HCC progression and metastasis in cell-derived allografts and chemically induced HCC models. Mechanistically, transforming growth factor-beta 1 (TGF-β1) upregulated SOX18 expression by activating the Smad2/3 complex. SOX18 transactivated chemokine (C-X-C motif) ligand 12 (CXCL12) and programmed death ligand 1 (PD-L1) to induce the immunosuppressive microenvironment. CXCL12 knockdown significantly attenuated SOX18-induced TAMs and Tregs accumulation and HCC dissemination. Antagonism of chemokine receptor 4 (CXCR4), the cognate receptor of CXCL12, or selective knockout of CXCR4 in TAMs or Tregs likewise abolished SOX18-mediated effects. TGFβR1 inhibitor Vactosertib or CXCR4 inhibitor AMD3100 in combination with anti-PD-L1 dramatically inhibited SOX18-mediated HCC progression and metastasis.

CONCLUSIONS

SOX18 promoted the accumulation of immunosuppressive TAMs and Tregs in the microenvironment by transactivating CXCL12 and PD-L1. CXCR4 inhibitor or TGFβR1 inhibitor in synergy with anti-PD-L1 represented a promising combination strategy to suppress HCC progression and metastasis.

Association of mitochondrial phosphoenolpyruvate carboxykinase with prognosis and immune regulation in hepatocellular carcinoma

Mitochondrial phosphoenolpyruvate carboxykinase (PCK2), a mitochondrial isoenzyme, supports the growth of cancer cells under glucose deficiency conditions in vitro. This study investigated the role and potential mechanism of PCK2 in the occurrence and development of Hepatocellular carcinoma (HCC). The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and other databases distinguish the expression of PCK2 and verified by qRT-PCR and Western blotting. Kaplan-Meier was conducted to assess PCK2 survival in HCC. The potential biological function of PCK2 was verified by enrichment analysis and gene set enrichment analysis (GSEA). The correlation between PCK2 expression and immune invasion and checkpoint was found by utilizing Tumor Immune Estimation Resource (TIMER). Lastly, the effects of PCK2 on the proliferation and metastasis of hepatocellular carcinoma cells were evaluated by cell tests, and the expressions of Epithelial mesenchymal transformation (EMT) and apoptosis related proteins were detected. PCK2 is down-regulated in HCC, indicating a poor prognosis. PCK2 gene mutation accounted for 1.3% of HCC. Functional enrichment analysis indicated the potential of PCK2 as a metabolism-related therapeutic target. Subsequently, we identified several signaling pathways related to the biological function of PCK2. The involvement of PCK2 in immune regulation was verified and key immune checkpoints were predicted. Ultimately, after PCK2 knockdown, cell proliferation and migration were significantly increased, and N-cadherin and vimentin expression were increased. PCK2 has been implicated in immune regulation, proliferation, and metastasis of hepatocellular carcinoma, and is emerging as a novel predictive biomarker and metabolic-related clinical target.

XCR1: A promising prognostic marker that pinpoints targeted and immune-based therapy in hepatocellular carcinoma

Objectives

The lymphotactin receptor X-C motif chemokine receptor 1 (XCR1) is an essential member of the chemokine receptor family and is related to tumor development and progression. Nevertheless, further investigation is required to explore its expression patterns, prognostic values, and functions related to target or immune therapies in patients with hepatocellular carcinoma (HCC).

Materials and methods

The differential expression patterns of XCR1 and its prognostic influences were performed through The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Subsequently, immunohistochemistry (IHC) staining and univariate and multivariate Cox regressions were performed to validate the prognostic values in different subgroups. Furthermore, the potential roles of XCR1 in predicting target and immune therapeutic responses were also investigated.

Results

Increased expression level of XCR1 was associated with favorable overall survival (OS) and recurrence-free survival (RFS). Subgroup analysis revealed that a high expression level of XCR1 or positive immune cell proportion score (iCPS) were associated with favorable OS in the HCC patients with favorable tumor characteristics. In addition, the enhanced XCR1 expression was associated with the tumor environment scores, immune cell infiltration levels, and the expression levels of immune checkpoint genes. Further analysis revealed that improved expression of XCR1 was linked to better OS and RFS in HCC patients who received sorafenib.

Conclusion

This study identified that XCR1 is a valuable prognostic biomarker in the HCC population, especially in those with favorable tumor characteristics. The combination of iCPS status and BCLC status has a synergistic effect on stratifying patients' OS and RFS. Further analyses showed that XCR1 has the potential ability to predict treatment responses to sorafenib and immune-based therapies.

Prognostic signature and immune efficacy of m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is the main type of primary liver cancer, and its related death ranks third worldwide. The curative methods and progress prediction markers of HCC are not sufficient enough. Nevertheless, little progress has been made in the signature of m1A-, m5C-, m6A-, m7G-, and DNA methylation of HCC. Results: We calibrated a risk gene signature model that can be used to categorize HCC patients based on univariate, multivariate, and LASSO Cox regression analysis. This gene signature classified the patients into high- and low-risk subgroups. Patients in the high-risk group showed significantly reduced overall survival (OS) compared with patients in the low-risk group. The gene set variation analysis (GSVA), immune infiltration, and immunotherapy response were analyzed. The results demonstrated that an immunosuppressive environment was exited and the high-risk group had higher sensitivity to 5-fluorouracil, cisplatin, sorafenib, tamoxifen, and epirubicin. These results indicated personalized therapy should be taken into consideration. Conclusions: Our findings enriched our understanding of the molecular heterogeneity, tumor microenvironment (TME), and drug susceptibility of HCC. m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators may be promising biomarkers for future research.

T cell-related ubiquitination genes as prognostic indicators in hepatocellular carcinoma

Background

T lymphocytes, integral to the adaptive immune system, wield pivotal influence in bolstering anti-tumor responses, and are strictly regulated by ubiquitination modification. The objective of this investigation was to devise a novel prognostic and immunotherapeutic efficacy predictor for hepatocellular carcinoma patients utilizing T cell-related ubiquitination genes (TCRUG).

Method

The single-cell RNA sequencing (scRNA-seq) data and bulk RNA data of HCC patients are derived from the GEO database and TCGA database. Based on the processing of scRNA-seq, T cell marker genes are obtained and TCRUG is obtained. Further combined with WGCNA, differential analysis, univariate Cox regression analysis, LASSO analysis, and multivariate Cox regression analysis to filter and screen TCRUG. Finally construct a riskscore for predicting the prognosis of HCC patients, the predictive effect of which is validated in the GEO dataset. In addition, we also studied the correlation between riskscore and immunotherapy efficacy. Finally, the oncogenic role of UBE2E1 in HCC was explored through various in vitro experiments.

Result

Based on patients' scRNA-seq data, we finally obtained 3050 T cell marker genes. Combined with bulk RNA data and clinical data from the TCGA database, we constructed a riskscore that accurately predicts the prognosis of HCC patients. This riskscore is an independent prognostic factor for HCC and is used to construct a convenient column chart. In addition, we found that the high-risk group is more suitable for immunotherapy. Finally, the proliferation, migration, and invasion abilities of HCC cells significantly decreased after UBE2E1 expression reduction.

Conclusion

This study developed a riskscore based on TCRUG that can accurately and stably predict the prognosis of HCC patients. This riskscore is also effective in predicting the immune therapy response of HCC patients.

Hepatocellular Carcinoma and the Multifaceted Relationship with Its Microenvironment: Attacking the Hepatocellular Carcinoma Defensive Fortress

Hepatocellular carcinoma is a malignant tumor that originates from hepatocytes in an inflammatory substrate due to different degrees of liver fibrosis up to cirrhosis. In recent years, there has been growing interest in the role played by the complex interrelationship between hepatocellular carcinoma and its microenvironment, capable of influencing tumourigenesis, neoplastic growth, and its progression or even inhibition. The microenvironment is made up of an intricate network of mesenchymal cells, immune system cells, extracellular matrix, and growth factors, as well as proinflammatory cytokines and translocated bacterial products coming from the intestinal microenvironment via the enterohepatic circulation. The aim of this paper is to review the role of the HCC microenvironment and describe the possible implications in the choice of the most appropriate therapeutic scheme in the prediction of tumor response or resistance to currently applied treatments and in the possible development of future therapeutic perspectives, in order to circumvent resistance and break down the tumor's defensive fort.

RRP8, associated with immune infiltration, is a prospective therapeutic target in hepatocellular carcinoma

BACKGROUND

Ribosomal RNA Processing 8 (RRP8) is a nucleolar Rossman fold-like methyltransferase that exhibits increased expression in many malignant tumours. However, the role of RRP8 in hepatocellular carcinoma (HCC) is still uncertain. We explored the relationships between RRP8 and prognosis and immune infiltration, as well as the putative pathological function and mechanism of RRP8 in HCC.

METHODS

Analysis of RRP8 expression across cancers was performed by using multiple databases. Associations between RRP8 expression and clinicopathological factors were further examined. Gene enrichment analysis was used to identify various putative biological activities and regulatory networks of RRP8 in HCC. The relationship between RRP8 expression and immune infiltration was confirmed by single-sample gene set enrichment analysis (ssGSEA). Univariate and multivariate Cox regression analyses were conducted to assess the impact of clinical variables on patient outcomes. Furthermore, a nomogram was constructed to estimate survival probability based on multivariate Cox regression analysis. Functional validation of RRP8 in HCC was performed with two different systems: doxycycline-inducible shRNA knockdown and CRISPR-Cas9 knockout.

RESULTS

RRP8 was markedly overexpressed in HCC clinical specimens compared to adjacent normal tissues. Further analysis demonstrated that RRP8 was directly connected to multiple clinical characteristics and strongly associated with various immune markers in HCC. Moreover, elevated RRP8 expression indicated an unfavourable prognosis. Our functional studies revealed that both knockdown and knockout of RRP8 dramatically attenuated liver cancer cells to proliferate and migrate. Knockout of RRP8 decreased the phosphorylation of MEK1/2 and β-catenin-(Y654) signalling pathway components; downregulated downstream signalling effectors, including Cyclin D1 and N-cadherin; and upregulated E-cadherin.

CONCLUSIONS

RRP8 is strongly implicated in immune infiltration and could be a potential therapeutic target in HCC.

CXCL9 Overexpression Predicts Better HCC Response to Anti-PD-1 Therapy and Promotes N1 Polarization of Neutrophils

Background

Anti-programmed death-1 (PD1) antibodies have changed the treatment landscape for hepatocellular carcinoma (HCC) and exhibit promising treatment efficacy. However, the majority of HCCs still do not respond to anti-PD-1 therapy.

Methods

We analyzed the expression of CXCL9 in blood samples from patients who received anti-PD-1 therapy and evaluated its correlation with clinicopathological characteristics and treatment outcomes. Based on the results of Cox regression analysis, a nomogram was established for predicting HCC response to anti-PD-1 therapy. qRT‒PCR and multiple immunofluorescence assays were utilized to analyze the proportions of N1-type neutrophils in vitro and in tumor samples, respectively.

Results

The nomogram showed good predictive efficacy in the training and validation cohorts and may be useful for guiding clinical treatment of HCC patients. We also found that HCC cell-derived CXCL9 promoted N1 polarization of neutrophils in vitro and that AMG487, a specific CXCR3 inhibitor, significantly blocked this process. Moreover, multiple immunofluorescence (mIF) showed that patients with higher serum CXCL9 levels had greater infiltration of the N1 phenotype of tumor-associated neutrophils (TANs).

Conclusion

Our study highlights the critical role of CXCL9 as an effective biomarker of immunotherapy efficacy and in promoting the polarization of N1-type neutrophils; thus, targeting the CXCL9-CXCR3 axis could represent a novel pharmaceutical strategy to enhance immunotherapy for HCC.

New insights into mechanisms and interventions of locoregional therapies for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is responsible for a significant number of cancer-related deaths worldwide and its incidence is increasing. Locoregional treatments, which are precision procedures guided by imaging to specifically target liver tumors, play a critical role in the management of a substantial portion of HCC cases. These therapies have become an essential element of the HCC treatment landscape, with transarterial chemoembolization (TACE) being the treatment of choice for patients with intermediate to advanced stages of the disease. Other locoregional therapies, like radiofrequency ablation, are highly effective for small, early-stage HCC. Nevertheless, the advent of targeted immunotherapy has challenged these established treatments. Tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) have shown remarkable efficacy in clinical settings. However, their specific uses and the development of resistance in subsequent treatments have led clinicians to reevaluate the future direction of HCC therapy. This review concentrates on the distinct features of both systemic and novel locoregional therapies. We investigate their effects on the tumor microenvironment at the molecular level and discuss how targeted immunotherapy can be effectively integrated with locoregional therapies. We also examine research findings from retrospective studies and randomized controlled trials on various combined treatment regimens, assessing their validity to determine the future evolution of locoregional therapies within the framework of personalized, comprehensive treatment.

Immunosuppressive tumor microenvironment and immunotherapy of hepatocellular carcinoma: current status and prospectives

Hepatocellular carcinoma (HCC) is a major health concern worldwide, with limited therapeutic options and poor prognosis. In recent years, immunotherapies such as immune checkpoint inhibitors (ICIs) have made great progress in the systemic treatment of HCC. The combination treatments based on ICIs have been the major trend in this area. Recently, dual immune checkpoint blockade with durvalumab plus tremelimumab has also emerged as an effective treatment for advanced HCC. However, the majority of HCC patients obtain limited benefits. Understanding the immunological rationale and exploring novel ways to improve the efficacy of immunotherapy has drawn much attention. In this review, we summarize the latest progress in this area, the ongoing clinical trials of immune-based combination therapies, as well as novel immunotherapy strategies such as chimeric antigen receptor T cells, personalized neoantigen vaccines, oncolytic viruses, and bispecific antibodies.

Prognostic Value of an Immune Long Non-Coding RNA Signature in Liver Hepatocellular Carcinoma

In recent years, there has been a growing recognition of the important role that long non-coding RNAs (lncRNAs) play in the immunological process of hepatocellular carcinoma (LIHC). An increasing number of studies have shown that certain lncRNAs hold great potential as viable options for diagnosis and treatment in clinical practice. The primary objective of our investigation was to devise an immune lncRNA profile to explore the significance of immune-associated lncRNAs in the accurate diagnosis and prognosis of LIHC. Gene expression profiles of LIHC samples obtained from TCGA database were screened for immune-related genes. The optimal immune-related lncRNA signature was built via correlational analysis, univariate and multivariate Cox analysis. Then, the Kaplan-Meier plot, ROC curve, clinical analysis, gene set enrichment analysis, and principal component analysis were performed to evaluate the capability of the immune lncRNA signature as a prognostic indicator. Six long non-coding RNAs were identified via correlation analysis and Cox regression analysis considering their interactions with immune genes. Subsequently, tumor samples were categorized into two distinct risk groups based on different clinical outcomes. Stratification analysis indicated that the prognostic ability of this signature acted as an independent factor. The Kaplan-Meier method was employed to conduct survival analysis, results showed a significant difference between the two risk groups. The predictive performance of this signature was validated by principal component analysis (PCA). Additionally, data obtained from gene set enrichment analysis (GSEA) revealed several potential biological processes in which these biomarkers may be involved. To summarize, this study demonstrated that this six-lncRNA signature could be identified as a potential factor that can independently predict the prognosis of LIHC patients.

A prognostic and immune related risk model based on zinc homeostasis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. The dysfunction of zinc homeostasis participates in the early and advancing malignancy of HCC. However, the prognostic ability of zinc homeostasis in HCC has not been clarified yet. Here, we showed a zinc-homeostasis related risk model in HCC. Five signature genes including ADAMTS5, PLOD2, PTDSS2, KLRB1, and UCK2 were screened out via survival analyses and regression algorithms to construct the nomogram with clinical characteristics. Experimental researches indicated that UCK2 participated in the progression of HCC. Patients with higher risk scores always had worse outcomes and were more associated with immune suppression according to the analyses of immune related-pathway activation, cell infiltration, and gene expression. Moreover, these patients were likely to exhibit more sensitivity to sorafenib and other antitumor drugs. This study highlights the significant prognostic role of zinc homeostasis and suggests potential treatment strategies in HCC.

Comprehensive pan-cancer analysis of YBX family reveals YBX2 as a potential biomarker in liver cancer

Background

The Y-box-binding proteins (YBX) act as a multifunctional role in tumor progression, metastasis, drug resistance by regulating the transcription and translation process. Nevertheless, their functions in a pan-cancer setting remain unclear.

Methods

This study examined the clinical features expression, prognostic value, mutations, along with methylation patterns of three genes from the YBX family (YBX1, YBX2, and YBX3) in 28 different types of cancer. Data used for analysis were obtained from Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. A novel YBXs score was created using the ssGSEA algorithm for the single sample gene set enrichment analysis. Additionally, we explored the YBXs score's association with the tumor microenvironment (TME), response to various treatments, and drug resistance.

Results

Our analysis revealed that YBX family genes contribute to tumor progression and are indicative of prognosis in diverse cancer types. We determined that the YBXs score correlates significantly with numerous malignant pathways in pan-cancer. Moreover, this score is also linked with multiple immune-related characteristics. The YBXs score proved to be an effective predictor for the efficacy of a range of treatments in various cancers, particularly immunotherapy. To summarize, the involvement of YBX family genes is vital in pan-cancer and exhibits a significant association with TME. An elevated YBXs score indicates an immune-activated TME and responsiveness to diverse therapies, highlighting its potential as a biomarker in individuals with tumors. Finally, experimental validations were conducted to explore that YBX2 might be a potential biomarker in liver cancer.

Conclusion

The creation of YBXs score in our study offered new insights into further studies. Besides, YBX2 was found as a potential therapeutic target, significantly contributing to the improvement of HCC diagnosis and treatment strategies.

Unlocking the future of hepatocellular carcinoma treatment: A comprehensive analysis of disulfidptosis-related lncRNAs for prognosis and drug screening

Background

The disulfide stress-induced cell death known as disulfidptosis is characterized by the disintegration of cytoskeletal proteins and F-actin as a result of an excessive buildup of disulfides within the cell. The relationship between disulfidptosis-associated long non-coding RNA (lncRNA) in hepatocellular carcinoma (HCC) progression is still not clearly understood. In this article, we aim to explore the crucial role of lncRNA in HCC.

Methods

We initially obtained lncRNA related to HCC and clinical data from TCGA. The genes associated with disulfidptosis were identified through co-expression analysis, Cox regression, and Lasso regression. Additionally, we established a prognostic model for verification.

Results

The risk model constructed with disulfidptosis-related lncRNA has been confirmed to be a good predictor of high and low-risk groups of HCC patients through survival curves, independent prognostic analysis, concordance index (C-index), ROC curves, and Kaplan-Meier plots. We also discovered differences in the response to immune targets and anticancer drugs between the two groups of patients, with GDC0810, Osimertinib, Paclitaxel, and YK-4-279 being more effective for patients in the high-risk group.

Conclusion

In conclusion, we have developed a risk model that can guide future efforts to diagnose and treat HCC.

Three-dimensional morphology scoring of hepatocellular carcinoma stratifies prognosis and immune infiltration

BACKGROUND

The morphological attributes could serve as pivotal indicators precipitating early recurrence and dismal overall survival in hepatocellular carcinoma (HCC), and quantifying morphological features may better stratify the prognosis of HCC.

OBJECTIVE

To develop a radiomics approach based on 3D tumor morphology features for predicting the prognosis of HCC and identifying differentially expressed genes related to morphology to guide HCC treatment.

MATERIALS AND METHODS

Retrospective study of 357 HCC patients. Radiomic features were extracted from MRI tumor regions; 14 morphology-related features predicted early HCC recurrence and patient stratification via LASSO-Cox modeling. Overall survival (OS) and recurrence-free survival (RFS) were analyzed. RNA sequencing from the Cancer Imaging Archive (TCIA) examined drug sensitivity and stratified HCC using morphological immunity genes, validating recurrence and prognosis.

RESULTS

Patients were split into training (n = 225), test (n = 132), and 50 TCIA dataset cohorts. Two features (Maximum2DdiameterColumn, Sphericity) in Cox regression stratified patients into high/low-risk Morphological Radiological Score (Morph-RS) groups. Significant OS and RFS were seen across all sets. Differentially expressed genes focused on T cell receptor signaling; low-risk group had higher T cells (P = 0.039), B cells (P = 0.041), NK cells (P = 0.018). SN-38, GSK2126458 might treat high-risk morphology. Morphology-immune genes stratified HCC, showing significant RFS/OS differences.

CONCLUSION

Tumor Morph-RS effectively stratifies HCC patients' recurrence and prognosis. Limited immune infiltration seen in Morph-RS high-risk groups signifies the potential of employing tumor morphology as a potent visual biomarker for diagnosing and managing HCC.

[High expression of UBE2S promotes progression of hepatocellular carcinoma by increasing cancer cell stemness]

OBJECTIVE

To investigate the expression of the ubiquitination enzyme UBE2S in different cell types in hepatocellular carcinoma (HCC) microenvironment and its impact on proliferation and stemness of HCC cells.

METHODS

TCGA and CPTAC database were used to analyze the transcriptional and promoter methylation levels and protein expressions of UBE2S in HCC. Specific expression patterns of UBE2S, intercellular communication and key transcription factors in different cell types were analyzed based on single-cell sequencing data from TISCH website. We further examined UBE2S expressions in clinical samples of HCC tissues, HCC cells and T cells using immunohistochemistry and immunofluorescence staining. We also tested the effects of UBE2S knockdown on stemness of HCC-LM3 and HepG2 cells using clone formation experiments and sphere formation assay.

RESULTS

Analysis based on TCGA database suggested significant overexpression of UBE2S in both paired and non-paired tumor tissues (P < 0.001), and its transcriptional level increased with tumor grades. The methylation level of UBE2S promoter was significantly decreased in HCC (P < 0.001), and its transcription level increased obviously in HCC with TP53 mutation (P < 0.001). Analysis of CPTAC database also demonstrated overexpression of UBE2S protein in HCC tissues (P < 0.001). Three prognostic models suggested that HCC patients with high UBE2S expression had poorer prognosis (P < 0.001). Single-cell sequencing data analysis revealed high expressions of UBE2S in T cells and high intensities of interaction between endothelial cells, epithelial cells and fibroblasts in HCC microenvironment. Immunohistochemistry and immunofluorescence staining demonstrated high UBE2S expressions in clinical samples of HCC tissues, HCC cells and T cells. In HCC-LM3 and HepG2 cells, UBE2S knockdown significantly inhibited cell clone formation and tumor sphere formation (P < 0.05).

CONCLUSION

UBE2S is highly expressed in T cells in HCC microenvironment in close correlation with a poor prognosis. High UBE2S expression promotes the stemness of HCC cells.

Identification of hub genes within the CCL18 signaling pathway in hepatocellular carcinoma through bioinformatics analysis

Introduction

Hepatocellular carcinoma (HCC) is an aggressive malignancy, and CCL18, a marker of M2 macrophage activation, is often associated with tumor immune suppression. However, the role of CCL18 and its signaling pathway in HCC is still limited. Our study focuses on investigating the prognostic impact of CCL18 and its signaling pathway in HCC patients and biological functions in vitro.

Methods

HCC-related RNA-seq data were obtained from TCGA, ICGC, and GEO. The 6 hub genes with the highest correlation to prognosis were identified using univariate Cox and LASSO regression analysis. Multivariate Cox regression analysis was performed to assess their independent prognostic potential and a nomogram was constructed. In vitro experiments, including CCK8, EdU, RT-qPCR, western blot, and transwell assays, were conducted to investigate the biological effects of exogenous CCL18 and 6 hub genes. A core network of highly expressed proteins in the high-risk group of tumors was constructed. Immune cell infiltration was evaluated using the ESTIMATE and CIBERSORT packages. Finally, potential treatments were explored using the OncoPredict package and CAMP database.

Results

We identified 6 survival-related genes (BMI1, CCR3, CDC25C, CFL1, LDHA, RAC1) within the CCL18 signaling pathway in HCC patients. A nomogram was constructed using the TCGA_LIHC cohort to predict patient survival probability. Exogenous CCL18, as well as overexpression of BMI1, CCR3, CDC25C, CFL1, LDHA, and RAC1, can promote proliferation, migration, invasion, stemness, and increased expression of PD-L1 protein in LM3 and MHCC-97H cell lines. In the high-risk group of patients from the TCGA_LIHC cohort, immune suppression was observed, with a strong correlation to 21 immune-related genes and suppressive immune cells.

Conclusion

Exogenous CCL18 promotes LM3 and MHCC-97H cells proliferation, migration, invasion, stemness, and immune evasion. The high expression of BMI1, CCR3, CDC25C, CFL1, LDHA, and RAC1 can serve as a biomarkers for immune evasion in HCC.

LAPTM4B-mediated hepatocellular carcinoma stem cell proliferation and MDSC migration: implications for HCC progression and sensitivity to PD-L1 monoclonal antibody therapy

In hepatocellular carcinoma (HCC), immunotherapy is vital for advanced-stage patients. However, diverse individual responses and tumor heterogeneity have resulted in heterogenous treatment outcomes. Our mechanistic investigations identified LAPTM4B as a crucial gene regulated by ETV1 (a transcription factor), especially in liver cancer stem cells (LCSCs). The influence of LAPTM4B on LCSCs is mediated via the Wnt1/c-Myc/β-catenin pathway. CXCL8 secretion by LAPTM4B drove myeloid-derived suppressor cell (MDSC) migration, inducing unfavorable patient prognosis. LAPTM4B affected PD-L1 receptor expression in tumor microenvironment and enhanced tumor suppression induced by PD-L1 monoclonal antibodies in HCC patients. LAPTM4B up-regulation is correlated with adverse outcomes in HCC patients, sensitizing them to PD-L1 monoclonal antibody therapy.

Development of a novel lncRNA-derived immune gene score using machine learning-based ensembles for predicting the survival of HCC

BACKGROUND

Long noncoding RNAs (lncRNAs) are implicated in the tumor immunology of hepatocellular carcinoma (HCC).

METHODS

HCC mRNA and lncRNA expression profiles were used to extract immune-related genes with the ImmPort database, and immune-related lncRNAs with the ImmLnc algorithm. The MOVICS package was used to cluster immune-related mRNA, immune-related lncRNA, gene mutation and methylation data on HCC from the TCGA. GEO and ICGC datasets were used to validate the model. Data from single-cell sequencing was used to determine the expression of genes from the model in various immune cell types.

RESULTS

With this model, the area under the curve (AUC) for 1-, 3- and 5-year survival of HCC patients was 0.862, 0.869 and 0.912, respectively. Single-cell sequencing showed EREG was significantly expressed in a variety of immune cell types. Knockdown of the EREG target gene resulted in significant anti-apoptosis, pro-proliferation and pro-migration effects in HepG2 and HUH7 cells. Moreover, serum and liver tissue EREG levels in HCC patients were significantly higher than those of healthy control patients.

CONCLUSION

We built a prognostic model with good accuracy for predicting HCC patient survival. EREG is a potential immunotherapeutic target and a promising prognostic biomarker.

The Gut Microbiome Controls Liver Tumors via the Vagus Nerve

Liver cancer ranks amongst the deadliest cancers. Nerves have emerged as an understudied regulator of tumor progression. The parasympathetic vagus nerve influences systemic immunity via acetylcholine (ACh). Whether cholinergic neuroimmune interactions influence hepatocellular carcinoma (HCC) remains uncertain. Liver denervation via hepatic vagotomy (HV) significantly reduced liver tumor burden, while pharmacological enhancement of parasympathetic tone promoted tumor growth. Cholinergic disruption in Rag1KO mice revealed that cholinergic regulation requires adaptive immunity. Further scRNA-seq and in vitro studies indicated that vagal ACh dampens CD8+ T cell activity via muscarinic ACh receptor (AChR) CHRM3. Depletion of CD8+ T cells abrogated HV outcomes and selective deletion of Chrm3 on CD8 + T cells inhibited liver tumor growth. Beyond tumor-specific outcomes, vagotomy improved cancer-associated fatigue and anxiety-like behavior. As microbiota transplantation from HCC donors was sufficient to impair behavior, we investigated putative microbiota-neuroimmune crosstalk. Tumor, rather than vagotomy, robustly altered fecal bacterial composition, increasing Desulfovibrionales and Clostridial taxa. Strikingly, in tumor-free mice, vagotomy permitted HCC-associated microbiota to activate hepatic CD8+ T cells. These findings reveal that gut bacteria influence behavior and liver anti-tumor immunity via a dynamic and pharmaceutically targetable, vagus-liver axis.

The Biological Function of POLA2 in Hepatocellular Carcinoma

INTRODUCTION

The role and prognostic value of POLA2 in liver cancer were comprehensively analyzed through TCGA, GEO, and ICGC databases, and the role of POLA2 in liver cancer cells and the regulatory mechanism involved were further verified through cell experiments. Hepatocellular carcinoma (HCC) is the most prevalent malignancy with high morbidity and mortality. Consequently, it is critical to identify robust and reliable predictive biomarkers and therapeutic targets for HCC patients. POLA2 is involved in the regulation of various tumors, but the specific role of POLA2 in HCC has not been reported. The regulatory role and prognostic value of POLA2 in HCC were determined by bioinformatics techniques and cell experiments.

METHODS

The specific role and prognostic value of POLA2 in HCC were comprehensively analyzed by combining the expression data of POLA2 in TCGA, GEO, and ICGC databases and clinical data. In clinical samples, the expression of POLA2 in liver cancer was verified by QPCR. Further, the regulatory role of POLA2 in HCC was explored through cell experiments such as CCK-8, clonal formation experiment, EDU cell proliferation experiment, and flow cytometry. In terms of mechanism exploration, western blot was used to verify the specific regulatory mechanism that POLA2 participated in. Finally, the relationship between POLA2 and immune invasion of HCC was analyzed by using the TIMER database.

RESULTS

A POLA2 expression and prognosis analysis of HCC patients was conducted using the TCGA, GEO, and ICGC databases. We hypothesized that POLA2 might be one of the key factors contributing to the HCC progression. According to a combined analysis of TCGA, ICGC, and GEO databases, POLA2 was highly expressed in HCC. This was further confirmed in clinical samples using the qPCR. POLA2 knockdown was also performed in vitro on HCC cell lines to study the changes in their biological behavior. We confirmed that POLA2 was associated with HCC proliferation by CCK-8, Colony Formation, and EDU assay. We verified the POLA2's involvement in cell cycle regulation using flow techniques. The relationship between POLA2 and PI3K/AKT/mTOR pathway was explored using Western Blotting experiments regarding its mechanism. Further analysis revealed that the POLA2 expression was significantly associated with HCC immune infiltration.

CONCLUSION

Our study demonstrated POLA2's importance in HCC development and progression and its potential role as a biomarker for disease progression on multiple levels. POLA2 has an important role in regulating the cell cycle and cell proliferation. By interfering with the cell cycle and proliferation, HCC cell growth is inhibited. Furthermore, POLA2 expression was significantly associated with immune infiltration. POLA2 may play a role in HCC immunotherapy based on its correlation with several immune cell types' genetic markers. The findings of this study are expected to lead to new anticancer strategies for HCC.

Prediction Model for Immunotherapy Efficacy in Hepatocellular Carcinoma Based on Alternative Splicing Sequencing Data

Background: Integrating immune checkpoint inhibitors with multi-target tyrosine kinase inhibitors presents an innovative and hopeful strategy in liver cancer treatment. Nonetheless, a degree of resistance to this treatment is noticeable in certain patients. Alternative splicing (AS) represents a common biological process that controls the variety of life functions via isoforms. Purpose: Investigating how gene AS affects the effectiveness of combined immunotherapy in treating hepatocellular carcinoma (HCC). Methods: Our retrospective examination focused on AS's effect on immune therapy effectiveness, utilizing accessible tissue sequencing and clinical records for HCC. For corroborating our results, we gathered samples of drug-resistant HCC tissue, nearby tissues, HCC tissue with high drug responsiveness, and healthy liver tissue from clinical studies. Results: The study revealed a link between the frequency of AS occurrences, the expression levels of programmed cell death 1 ligand 1, and the resistance to tumor medications. Our study detailed the AS occurrences in HCC, leading to the creation of a risk-assessment function and a predictive model using AS data. The results of our study revealed that the risk score effectively distinguished between various immune subtypes and the effectiveness of immune therapy. Additional examination of the chosen AS occurrences uncovered their effects on both the immune microenvironment and cellular immunity. Our investigation also delved into the regulatory framework of AS, uncovering the role of stringently controlled splicing factors in the emergence of tumors and the modulation of the body's immune response. Conclusions: Increased AS in HCC diminishes the efficacy of immunotherapy; conversely, more AS in peritumoral tissue elevates the likelihood of tumor immune evasion.

Role of the immune system in liver transplantation and its implications for therapeutic interventions

Liver transplantation (LT) stands as the gold standard for treating end-stage liver disease and hepatocellular carcinoma, yet postoperative complications continue to impact survival rates. The liver's unique immune system, governed by a microenvironment of diverse immune cells, is disrupted during processes like ischemia-reperfusion injury posttransplantation, leading to immune imbalance, inflammation, and subsequent complications. In the posttransplantation period, immune cells within the liver collaboratively foster a tolerant environment, crucial for immune tolerance and liver regeneration. While clinical trials exploring cell therapy for LT complications exist, a comprehensive summary is lacking. This review provides an insight into the intricacies of the liver's immune microenvironment, with a specific focus on macrophages and T cells as primary immune players. Delving into the immunological dynamics at different stages of LT, we explore the disruptions after LT and subsequent immune responses. Focusing on immune cell targeting for treating liver transplant complications, we provide a comprehensive summary of ongoing clinical trials in this domain, especially cell therapies. Furthermore, we offer innovative treatment strategies that leverage the opportunities and prospects identified in the therapeutic landscape. This review seeks to advance our understanding of LT immunology and steer the development of precise therapies for postoperative complications.

Identification of topoisomerase 2A as a novel bone metastasis-related gene in liver hepatocellular carcinoma

BACKGROUND

Bone is the second most frequent site of metastasis for Liver hepatocellular carcinoma (LIHC), which leads to an extremely poor prognosis. Identifying novel biomarkers and therapeutic targets for LIHC patients with bone metastasis is urgently needed.

METHODS

In this study, we used multiple databases for comprehensive bioinformatics analysis, including TCGA, GEO, ICGC, GTEx, TISIDB, and TIMER, to identify key genes related to bone metastasis of LIHC. Clinical tissues and tissue microarray were adopted to assess the expression of TOP2A through qRT-PCR and immunohistochemistry analyses in LIHC. Gene enrichment analysis, DNA methylation, gene mutation, prognosis, and tumor immunity associated with TOP2A in LIHC were investigated. In vitro and in vivo experiments were performed to explore the functional role of TOP2A in LIHC bone metastasis.

RESULTS

We identified that TOP2A was involved in LIHC bone metastasis. Clinically, TOP2A was highly expressed in LIHC tumoral specimens, with the highest level in the bone metastasis lesions. TOP2A was an independent prognostic factor that higher expression of TOP2A was markedly associated with poorer prognosis in LIHC. Moreover, the abnormal expression of TOP2A might be related to DNA hypomethylation, often accompanied by TP53 mutation, immune escape and immunotherapy failure. Enrichment analysis and validation experiments unveiled that TOP2A stimulated the Hippo-YAP signaling pathway in LIHC. Functional assays confirmed that TOP2A could promote bone-specific metastatic potential and tumor-induced osteolysis in LIHC.

CONCLUSIONS

These findings unveil that TOP2A might be a novel prognostic biomarker and therapeutic target for LIHC bone metastasis.

Overexpression of TMEM79 combined with SMG5 is related to prognosis, tumor immune infiltration and drug sensitivity in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a primary liver malignancy that is now relatively common worldwide. TMEM79 has been reported to play diagnostic and prognostic markers in a variety of cancers and was found to be closely associated with immune infiltration. SMG5 is associated with immune cell infiltration in HCC. Multiple nonsense-mediated mRNA processes require the involvement of SMG5. TMEM79 and SMG5 complexes may be prognostic markers for prostate cancer. However, the relationship between TMEM79 expression in HCC and prognosis, its role and mechanism of action, and its relationship with SMG5 have not been studied. This article focuses on not only the prognostic role of TMEM79 and its biological significance, including immuno-infiltration, tumor mutations and drug sensitivity, but also the interaction with SMG5 in HCC.

METHODS

Differential expression analysis and the multiCox proportional hazards regression analyses of TMEM79 and SMG5 were performed by multiple databases. Then, use IHC to verify our results. Subsequently, we used R software to analyze the clinical phenotype of both: analysis of clinicopathological features, enrichment analysis, analysis of immune infiltration, analysis of immune checkpoints, analysis of drug sensitivity, and immunotherapy.

RESULTS

Both the database studies and the results of our research group showed that TMEM79 and SMG5 were differentially expressed in HCC and normal tissues. Validation of immunohistochemistry showed that differential expression of TMEM79 and SMG5, which influenced the prognosis of patients with HCC, could be an independent prognostic factor. Results of the TCGA database study showed that TMEM79 and SMG5 were correlated with immune infiltration, immune checkpoints, drug sensitivity, and immunotherapy. We typed TMEM79-related molecules in HCC according to R software. Two types of TMEM79 correlated with clinical features, survival of patients with HCC, and immune infiltration.

CONCLUSION

TMEM79 are highly expressed in HCC and play an important role in the prognosis of patients with HCC. TMEM79 and SMG5 are positively correlated and may both associated with immune infiltration, and closely linked to immune checkpoints, drug sensitivity, and immunotherapy in HCC.

Advances in Immunotherapy for Hepatocellular Carcinoma (HCC)

Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related deaths in the world. More than half of patients with HCC present with advanced stage, and highly active systemic therapies are crucial for improving outcomes. Immune checkpoint inhibitor (ICI)-based therapies have emerged as novel therapy options for advanced HCC. Only one third of patients achieve an objective response with ICI-based therapies due to primary resistance or acquired resistance. The liver tumor microenvironment is naturally immunosuppressive, and specific mutations in cell signaling pathways allow the tumor to evade the immune response. Next, gene sequencing of the tumor tissue or circulating tumor DNA may delineate resistance mechanisms to ICI-based therapy and provide a rationale for novel combination therapies. In this review, we discuss the results of key clinical trials that have led to approval of ICI-based therapy options in advanced HCC and summarize the ongoing clinical trials. We review resistance mechanisms to ICIs and discuss how immunotherapies may be optimized based on the emerging research of tumor biomarkers and genomic alterations.

Biomarkers for immunotherapy of hepatocellular carcinoma

Immune-checkpoint inhibitors (ICIs) are now widely used for the treatment of patients with advanced-stage hepatocellular carcinoma (HCC). Two different ICI-containing regimens, atezolizumab plus bevacizumab and tremelimumab plus durvalumab, are now approved standard-of-care first-line therapies in this setting. However, and despite substantial improvements in survival outcomes relative to sorafenib, most patients with advanced-stage HCC do not derive durable benefit from these regimens. Advances in genome sequencing including the use of single-cell RNA sequencing (both of tumour material and blood samples), as well as immune cell identification strategies and other techniques such as radiomics and analysis of the microbiota, have created considerable potential for the identification of novel predictive biomarkers enabling the accurate selection of patients who are most likely to derive benefit from ICIs. In this Review, we summarize data on the immunology of HCC and the outcomes in patients receiving ICIs for the treatment of this disease. We then provide an overview of current biomarker use and developments in the past 5 years, including gene signatures, circulating tumour cells, high-dimensional flow cytometry, single-cell RNA sequencing as well as approaches involving the microbiome, radiomics and clinical markers. Novel concepts for further biomarker development in HCC are then discussed including biomarker-driven trials, spatial transcriptomics and integrated 'big data' analysis approaches. These concepts all have the potential to better identify patients who are most likely to benefit from ICIs and to promote the development of new treatment approaches.

The XOR-IDH3α axis controls macrophage polarization in hepatocellular carcinoma

BACKGROUND & AIMS

Tumor-associated macrophages (TAMs) are indispensable in the hepatocellular carcinoma (HCC) tumor microenvironment. Xanthine oxidoreductase (XOR), also known as xanthine dehydrogenase (XDH), participates in purine metabolism, uric acid production, and macrophage polarization to a pro-inflammatory phenotype. However, the role of XOR in HCC-associated TAMs is unclear.

METHODS

We evaluated the XOR level in macrophages isolated from HCC tissues and paired adjacent tissues. We established diethylnitrosamine/carbon tetrachloride (CCl4)-induced and orthotopically implanted HCC mouse models using mice with Xdh-specific depletion in the myeloid cell lineage (Xdhf/fLyz2cre) or Kupffer cells (Xdhf/fClec4fcre). We determined metabolic differences using specific methodologies, including metabolomics and metabolic flux.

RESULTS

We found that XOR expression was downregulated in HCC TAMs and positively correlated with patient survival, which was strongly related to the characteristics of the tumor microenvironment, especially hypoxia. Using HCC-inflicted mice (Xdhf/fLyz2cre and Xdhf/fClec4fcre), we revealed that XOR loss in monocyte-derived TAMs rather than Kupffer cells promoted their M2 polarization and CD8+ T-cell exhaustion, which exacerbated HCC progression. In addition, the tricarboxylic acid cycle was disturbed, and the generation of α-ketoglutarate was enhanced within XOR-depleted macrophages. XOR inhibited α-ketoglutarate production by interacting with IDH3α catalytic sites (K142 and Q139). The increased IDH3α activity caused increased adenosine and kynurenic acid production in TAMs, which enhanced the immunosuppressive effects of TAMs and CD8+ T cells.

CONCLUSIONS

The XOR-IDH3α axis mediates TAM polarization and HCC progression and may be a small-molecule therapeutic or immunotherapeutic target against suppressive HCC TAMs.

IMPACT AND IMPLICATIONS

Immunotherapies have been widely applied to the treatment of hepatocellular carcinoma (HCC), but to date they have been associated with unsatisfactory efficacy. The tumor microenvironment of HCC is full of different infiltrating immune cells. Tumor-associated macrophages (TAMs) are vital components in the tumor microenvironment and are involved in HCC progression. Herein, we confirm the downregulation of XOR expression in TAMs isolated from human HCC. The loss of XOR in monocyte-derived macrophages increases IDH3 activity and results in an increase in α-ketoglutarate production, which can promote M2-like polarization. Additionally, XOR-null TAMs derived from monocytes promote CD8+ T-cell exhaustion via the upregulation of immunosuppressive metabolites, including adenosine and kynurenic acid. Given the prevalence and high rate of incidence of HCC and the need for improved therapeutic options for patients, our findings identify potential therapeutic targets that may be further studied to develop improved therapies.

Identifying immune infiltration by deep learning to assess the prognosis of patients with hepatocellular carcinoma

BACKGROUND

The treatment situation for hepatocellular carcinoma remains critical. The use of deep learning algorithms to assess immune infiltration is a promising new diagnostic tool.

METHODS

Patient data and whole slide images (WSIs) were obtained for the Xijing Hospital (XJH) cohort and TCGA cohort. We wrote programs using Visual studio 2022 with C# language to segment the WSI into tiles. Pathologists classified the tiles and later trained deep learning models using the ResNet 101V2 network via ML.NET with the TensorFlow framework. Model performance was evaluated using AccuracyMicro versus AccuracyMacro. Model performance was examined using ROC curves versus PR curves. The percentage of immune infiltration was calculated using the R package survminer to calculate the intergroup cutoff, and the Kaplan‒Meier method was used to plot the overall survival curve of patients. Cox regression was used to determine whether the percentage of immune infiltration was an independent risk factor for prognosis. A nomogram was constructed, and its accuracy was verified using time-dependent ROC curves with calibration curves. The CIBERSORT algorithm was used to assess immune infiltration between groups. Gene Ontology was used to explore the pathways of differentially expressed genes.

RESULTS

There were 100 WSIs and 165,293 tiles in the training set. The final deep learning models had an AccuracyMicro of 97.46% and an AccuracyMacro of 82.28%. The AUCs of the ROC curves on both the training and validation sets exceeded 0.95. The areas under the classification PR curves exceeded 0.85, except that of the TLS on the validation set, which might have had poor results (0.713) due to too few samples. There was a significant difference in OS between the TIL classification groups (p < 0.001), while there was no significant difference in OS between the TLS groups (p = 0.294). Cox regression showed that TIL percentage was an independent risk factor for prognosis in HCC patients (p = 0.015). The AUCs according to the nomogram were 0.714, 0.690, and 0.676 for the 1-year, 2-year, and 5-year AUCs in the TCGA cohort and 0.756, 0.797, and 0.883 in the XJH cohort, respectively. There were significant differences in the levels of infiltration of seven immune cell types between the two groups of samples, and gene ontology showed that the differentially expressed genes between the groups were immune related. Their expression levels of PD-1 and CTLA4 were also significantly different.

CONCLUSION

We constructed and tested a deep learning model that evaluates the immune infiltration of liver cancer tissue in HCC patients. Our findings demonstrate the value of the model in assessing patient prognosis, immune infiltration and immune checkpoint expression levels.

Baseline Albumin-Bilirubin grade as a predictor of response and outcome of regorafenib therapy in patients with hepatocellular carcinoma: a systematic review and meta-analysis

BACKGROUND

The use of regorafenib in the treatment of hepatocellular carcinoma (HCC) is widespread. Albumin-Bilirubin (ALBI) has been shown to be a potential prognostic marker for regorafenib treatment, but its prognostic value remains controversial. Therefore, we conducted a meta-analysis to investigate the value of the baseline ALBI grade in predicting the efficacy and survival outcomes of HCC patients after regorafenib treatment.

METHODS

PubMed, Embase, Cochrane library, Web of Science, CNKI, Wan Fang Data, and Vip Database were searched from January 2010 to October 2022. Studies treating HCC patients with regorafenib and with ALBI as a categorical variable, overall survival (OS) and progression-free survival (PFS) as outcome indicators were included. After applying Newcastle-Ottawa Scale (NOS) to evaluate the quality of the included studies, Review Manager 5.4 was used to statistically analyze. Chi-square Q test and I2 statistics were used to detect heterogeneity. Funnel plot asymmetry, Egger's and Begg's test were used to evaluate publication bias.

RESULTS

A total of 12 studies, comprising 1,918 patients, were included in the meta-analysis. The included studies were all evaluated as high quality. Compared to the high-grade baseline ALBI group, patients in the low-grade group had a longer survival time after receiving regorafenib and also more suitable for regorafenib treatment [odds ratio (OR) = 6.50, 95% confidence interval (CI): 2.22-18.96, P < 0.01]. The low-grade baseline ALBI group before sorafenib treatment was significantly correlated with better OS [hazard ratio (HR) = 2.36, 95% CI: 1.68-3.31, P < 0.00001] and PFS (HR = 1.56, 95% CI: 1.16-2.08, P = 0.003). Likewise, the low-grade baseline ALBI group before regorafenib was also significantly correlated with better OS (HR = 1.56, 95% CI: 1.15-2.13, P = 0.005) and PFS (HR = 2.06, 95% CI: 1.37-3.11, P = 0.0005). In addition, the ALBI grade was significantly correlated with disease control rate (DCR) (OR = 2.90, 95% CI: 1.45-5.79, P = 0.003), but not the objective response rate (OR = 1.98, 95% CI: 0.71-5.46, P = 0.19).

CONCLUSIONS

The baseline ALBI grade could be a valuable prognostic indicator for predicting response and outcomes in HCC patients treated with regorafenib.

Identification and validation of a cancer-associated fibroblasts-related scoring system to predict prognosis and immune landscape in hepatocellular carcinoma through integrated analysis of single-cell and bulk RNA-sequencing

BACKGROUND

Cancer-associated fibroblasts (CAFs) regulate the malignant biological behaviour of hepatocellular carcinoma (HCC) as a significant component of the tumour immune microenvironment (TIME). This study aimed to develop a CAFs-based scoring system to predict the prognosis and TIME of patients with HCC.

METHODS

Data for the TCGA-LIHC and GSE14520 cohorts were downloaded from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Single-cell RNA-sequencing data for HCC samples were retrieved from the GSE166635 cohort. The Least Absolute Shrinkage and Selection Operator algorithm was employed to develop a CAFs-related scoring system (CAFRss). The predictive value of the CAFRss was determined using Kaplan-Meier, Cox regression and Receiver Operating Characteristic curves. Additionally, the TIMER platform, single sample Gene Set Enrichment Analysis and the Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data algorithms were performed to determine the TIME landscape. Finally, the pRRophic algorithm was utilised for drug sensitivity analysis.

RESULTS

The evaluation of the CAFRss system demonstrated its superior ability to predict the clinical outcome of patients with HCC. Additionally, CAFRss effectively distinguished HCC populations with distinct TIME landscapes. Furthermore, CAFRss-based risk stratification identified individuals with immune 'hot tumours' and predicted the survival of patients treated with ICBs.

CONCLUSIONS

The developed CAFRss can serve as a predictive tool for determining the clinical outcome of HCC and differentiating populations with diverse TIME characteristics.

Oroxylin a promoted apoptotic extracellular vesicles transfer of glycolytic kinases to remodel immune microenvironment in hepatocellular carcinoma model

Although oroxylin A, a natural flavonoid compound, suppressed progression of hepatocellular carcinoma, whether the tumor microenvironment especially the communication between cancer cells and immune cells was under its modulation remained obscure. Here we investigated the effect of extracellular vesicles from cancer cells elicited by oroxylin A on macrophages in vitro. The data shows oroxylin A elicits apoptosis-related extracellular vesicles through caspase-3-mediated activation of ROCK1in HCC cells, which regulates M1-like polarization of macrophage. Moreover, oroxylin A downregulates the population of M2-like macrophage and promotes T cells infiltration in tumor microenvironment, accompanied by suppression of HCC development and enhancement of immune checkpoint inhibitor treatment in mice model. Mechanistically, glycolytic proteins enriched in oroxylin A-elicited extracellular vesicles from HCC cells are transferred to macrophages where ROS-dependent NLRP3 inflammasome is activated, therefore contributing to anti-tumor phenotype of macrophage. Taken together, this study highlights that oroxylin A promotes metabolic shifts between tumor cells and immune cells, facilitates to inhibit tumor development, and improves immunotherapy response in HCC model.

Interplay of Extracellular Vesicles and TLR4 Signaling in Hepatocellular Carcinoma Pathophysiology and Therapeutics

Hepatocellular carcinoma (HCC) stands as a significant contributor to global cancer-related mortality. Chronic inflammation, often arising from diverse sources such as viral hepatitis, alcohol misuse, nonalcoholic fatty liver disease (NAFLD), and nonalcoholic steatohepatitis (NASH), profoundly influences HCC development. Within this context, the interplay of extracellular vesicles (EVs) gains prominence. EVs, encompassing exosomes and microvesicles, mediate cell-to-cell communication and cargo transfer, impacting various biological processes, including inflammation and cancer progression. Toll-like receptor 4 (TLR4), a key sentinel of the innate immune system, recognizes both pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs), thereby triggering diverse signaling cascades and pro-inflammatory cytokine release. The intricate involvement of the TLR4 signaling pathway in chronic liver disease and HCC pathogenesis is discussed in this study. Moreover, we delve into the therapeutic potential of modulating the TLR4 pathway using EVs as novel therapeutic agents for HCC. This review underscores the multifaceted role of EVs in the context of HCC and proposes innovative avenues for targeted interventions against this formidable disease.

MEX3C as a potential target for hepatocellular carcinoma drug and immunity: combined therapy with Lenvatinib

BACKGROUND

The immune microenvironment within hepatocellular carcinoma (HCC) is remarkably intricate. Although the combination of an immune checkpoint inhibitor and Lenvatinib can extend the overall survival of HCC patients, the outcome remains suboptimal.

METHODS

We assessed alterations in MEX3C expression during hepatocarcinogenesis by validating multiple databases and subsequently developed a predictive model. Subsequently, we enriched the associated genes of MEX3C to investigate its functional role. We examined the correlation between MEX3C expression levels and immune infiltrating cells. The effects of MEX3C knockdown and Lenvatinib on hepatoma cells were observed by cell function experiments.

RESULTS

MEX3C expression is elevated in HCC compared to normal tissues, and its high expression correlates with poor prognosis. Immune checkpoint expression was elevated in the high MEX3C expression group, concomitant with heightened myeloid-derived suppressor cell (MDSC) expression. The combination of MEX3C knockdown and Lenvatinib demonstrated a stronger inhibitory effect on HCC cells compared to Lenvatinib alone.

CONCLUSION

MEX3C shows promise as a potential therapeutic target for treating HCC. Furthermore, the combination of MEX3C knockdown and Lenvatinib could offer a novel therapeutic avenue for HCC treatment.

Cholesterol Efflux Drives the Generation of Immunosuppressive Macrophages to Promote the Progression of Human Hepatocellular Carcinoma

Cholesterol is often enriched in tumor microenvironment (TME); however, its impact on disease progression varies in different tissues and cells. Monocytes/macrophages (Mφ) are major components and regulators of the TME and play pivotal roles in tumor progression and therapeutic responses. We aimed to investigate the profile, effects, and regulatory mechanisms of Mφ cholesterol metabolism in the context of human hepatocellular carcinoma (HCC). Here, we found that patients with high serum levels of cholesterol had shorter survival times and lower response rates to anti-PD-1 treatment. However, the cholesterol content in tumor-infiltrating monocytes/Mφ was significantly lower than that in their counterparts in paired nontumor tissues. The expression of the cholesterol efflux transporter, ABCA1, was upregulated in tumor monocytes/Mφ, and ABCA1 upregulation positively associated with decreased cellular cholesterol content and increased serum cholesterol levels. Mechanistically, autocrine cytokines from tumor-treated monocytes increased LXRα and ABCA1 expression, which led to the generation of immature and immunosuppressive Mφ. Although exogenous cholesterol alone had little direct effect on Mφ, it did act synergistically with tumor-derived factors to promote ABCA1 expression in Mφ with more immunosuppressive features. Moreover, high numbers of ABCA1+ Mφ in HCC tumors associated with reduced CD8+ T-cell infiltration and predicted poor clinical outcome for patients. Our results revealed that dysregulated cholesterol homeostasis, due to the collaborative effects of tumors and exogenous cholesterol, drives the generation of immunosuppressive Mφ. The selective modulation of cholesterol metabolism in Mφ may represent a novel strategy for cancer treatment.

Development of a prognostic model based on anoikis-related genes for predicting clinical prognosis and immunotherapy of hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is the predominant cause of cancer-related mortality worldwide. The majority of HCC patients are diagnosed at advanced stages of the disease, with a high likelihood of metastasis and unfavorable prognosis. Anoikis resistance is a crucial factor contributing to tumor invasion and metastasis, although its specific role in HCC remains unclear. Based on the results of univariate Cox regression and least absolute shrink-age and selection operator (LASSO) analysis, a subset of anoikis-related genes (ARGs) significantly associated with overall survival (OS) was identified. A multivariate Cox regression analysis subsequently identified PDK4, STK11, and TFDP1 as three prognostic ARGs, which were then used to establish a prognostic risk model. Differences in OS caused by risk stratification in HCC patients were demonstrated. The nomogram analysis indicated that the ARGs prognostic signature served as an independent prognostic predictor. In vitro experiments further confirmed the abnormal expression of selected ARGs in HCC. The association between risk scores and OS was further examined through Kaplan-Meier analysis, CIBERSORT analysis, and single-sample gene set enrichment analysis (ssGSEA). This study is a pioneering effort to integrate multiple ARGs and establish a risk-predictive model, providing a unique perspective for the development of personalized and precise therapeutic strategies for HCC.

A novel prognostic signature based on immunogenic cell death score predicts outcomes and response to transcatheter arterial chemoembolization and immunotherapy in hepatocellular carcinoma

PURPOSE

The phenomenon of immunogenic cell death (ICD) is intricately linked to numerous antitumor treatments and exerts a profound regulatory function in the tumor immune microenvironment (TIME). We aimed to establish a prognostic signature from the ICD-related biomarkers to differentiate the TIME in hepatocellular carcinoma and predict diverse outcomes for patients with liver cancer.

METHODS

ICD score-related genes (ICDSGs) were identified using the weighted gene co-expression network analysis (WGCNA). The ICD score-related signature (ICDSsig) was established by applying LASSO and Cox regression. Model precision was verified using the external datasets. We used independent prognostic variables in clinicopathologic factors to develop a nomogram. Further, clinical characteristics, immune and molecular landscapes, the responses of transcatheter arterial chemoembolization (TACE) and immunotherapy, and chemotherapy sensitivity were analyzed for high- and low-risk patients.

RESULTS

ICD score-calculated using the single-sample gene set enrichment analysis (ssGSEA)-displayed strong associations with the TIME in HCC. We identified 34 ICDSGs after integrating the TCGA and GSE104580 datasets. Then, three novel ICDSGs (DNASE1L3, KLRB1, and LILRB1) were screened out to construct the ICDSsig; the prognostic signature performed well in the external databases. The high-risk patients had worse outcomes owing to their advanced pathological state, non-response of TACE, and immune-cold phenotype in the immune landscapes. The immune checkpoint genes, N6-methyladenosine-relevant genes, and microsatellite instability score were increased in the high-risk subgroup, thereby indicating a favorable sensitivity to immunotherapy. Common chemotherapy drugs were more effective in high-risk patients due to low half-maximal inhibitory concentration values.

CONCLUSION

The ICDSsig can potentially predict outcomes and therapeutic responses for patients with liver cancer and may assist clinicians in designing individualized treatment strategies.

Comprehensive bioinformatics analysis of a RBM family-based prognostic signature with experiment validation in hepatocellular carcinoma

BACKGROUND

Although some RBM proteins family members play important roles in hepatocellular carcinoma (HCC) development, their value of prognosis and tumor treatment is not clear. To reveal the expression patterns and clinical significance of RBM family members in HCC, we constructed a RBM family-based prognosis signature.

METHOD

We collected the data of HCC patients from TCGA and ICGC database. The prognostic signature was constructed in TCGA and verified using ICGC cohort. Based on this model, risk score was calculated and patients were divided into high- and low-risk group. Comparison of immune cell infiltration, the response to immunotherapy, and IC50 of chemotherapeutic drugs were employed between different risk subgroups. Besides, CCK-8 and EdU assays were performed to investigate the role of RBM45 in HCC.

RESULT

Among 19 differential expression RBM protein family genes, 7 prognostic genes were picked out. Through LASSO Cox regression, a 4-gene prognostic model was successfully constructed, which included RBM8A, RBM19, RBM28 and RBM45. Results of validation and estimation suggested this model could be applied for prognostic prediction in HCC patients with a well predictive value. Risk score was shown to be an independent predictor and high-risk patients had poor prognosis. High-risk patients had an immunosuppressive tumor microenvironment while patients with low risk could benefit more from ICI therapy and sorafenib treatment. In addition, knockdown of RBM45 inhibited the proliferation of HCC.

CONCLUSION

This prognostic signature based on RBM family had a great value for predicting OS of HCC patients. Low-risk patients were more suitable for receiving immunotherapy and sorafenib treatment. The RBM family members made of the prognostic model might promote the progression of HCC.

Comprehensive analysis of the lncRNAs-related immune gene signatures and their correlation with immunotherapy in lung adenocarcinoma

BACKGROUND

Long non-coding RNAs (lncRNAs)-related immune genes (lrRIGs) play a crucial role in the development and progression of lung adenocarcinoma (LUAD). However, reliable prognostic signatures based on lrRIGs have not yet been identified.

METHODS

We screened lrRIGs associated with the prognosis of LUAD using The Cancer Genome Atlas (TCGA) database and then established a novel prognostic nine-gene signature composed of CD79A, INHA, SHC3, LIFR, TNFRSF11A, GPI, F2RL1, SEMA7A and WFDC2 through bioinformatic approaches. A risk score derived from this gene signature was used to divide LUAD patients into the low- and high-risk groups. The latter was confirmed to have markedly worse overall survival (O.S.). A nomogram was developed using the risk score and other independent prognostic elements, demonstrating excellent performance in predicting the O.S. rate of LUAD patients.

RESULTS

We observed that the infiltration of diverse immune cell subtypes and response to immunotherapy and chemotherapy significantly differed between the low- and high-risk groups.

CONCLUSIONS

Overall, stratification based on this gene signature could be used to guide better therapeutic management and improve outcomes for LUAD patients.

Response Assessment of Primary Liver Tumors to Novel Therapies: an Imaging Perspective

The latest developments in cancer immunotherapy, namely the introduction of immune checkpoint inhibitors, have led to a fundamental change in advanced cancer treatments. Imaging is crucial to identify tumor response accurately and delineate prognosis in immunotherapy-treated patients. Simultaneously, advances in image acquisition techniques, notably functional and molecular imaging, have facilitated more accurate pretreatment evaluation, assessment of response to therapy, and monitoring for tumor recurrence. Traditional approaches to assessing tumor progression, such as RECIST, rely on changes in tumor size, while new strategies for evaluating tumor response to therapy, such as the mRECIST and the EASL, rely on tumor enhancement. Moreover, the assessment of tumor volume, enhancement, cellularity, and perfusion are some novel techniques that have been investigated. Validation of these novel approaches should rely on comparing their results with those of standard evaluation methods (EASL, mRECIST) while considering the ultimate outcome, which is patient survival. More recently, immunotherapy has been used in the management of primary liver tumors. However, little is known about its efficacy. This article reviews imaging modalities and techniques for assessing tumor response and survival in immunotherapy-treated patients with primary hepatic malignancies.

CSF-1R+ Macrophages Control the Gut Microbiome-Enhanced Liver Invariant NKT Function through IL-18

The gut microbiome is an important modulator of the host immune system. In this study, we found that altering the gut microbiome by oral vancomycin increases liver invariant NKT (iNKT) cell function. Enhanced iNKT cytokine production and activation marker expression were observed in vancomycin-treated mice following both Ag-specific and Ag-independent in vivo iNKT stimulations, with a more prominent effect in the liver than in the spleen. Fecal transplantation studies demonstrated that the iNKT functional regulation is mediated by altering the gut microbiome but uncoupled from the modulation of iNKT cell population size. Interestingly, when stimulated in vitro, iNKT cells from vancomycin-treated mice did not show increased activation, suggesting an indirect regulation. iNKT cells expressed high levels of IL-18 receptor, and vancomycin increased the expression of IL-18 in the liver. Blocking IL-18 by neutralizing Ab or using genetically deficient mice attenuated the enhanced iNKT activation. Liver macrophages were identified as a major source of IL-18. General macrophage depletion by clodronate abolished this iNKT activation. Using anti-CSF-1R depletion or LyzCrexCSF-1RLsL-DTR mice identified CSF-1R+ macrophages as a critical modulator of iNKT function. Vancomycin treatment had no effect on iNKT cell function in vivo in IL-18 knockout macrophage reconstituted mice. Together, our results demonstrate that the gut microbiome controls liver iNKT function via regulating CSF-1R+ macrophages to produce IL-18.

Immune landscape and immunotherapy of hepatocellular carcinoma: focus on innate and adaptive immune cells

Hepatocellular carcinoma (HCC) is responsible for roughly 90% of all cases of primary liver cancer, and the cases are on the rise. The treatment of advanced HCC is a serious challenge. Immune checkpoint inhibitor (ICI) therapy has marked a watershed moment in the history of HCC systemic treatment. Atezolizumab in combination with bevacizumab has been approved as a first-line treatment for advanced HCC since 2020; however, the combination therapy is only effective in a limited percentage of patients. Considering that the tumor immune microenvironment (TIME) has a great impact on immunotherapies for HCC, an in-depth understanding of the immune landscape in tumors and the current immunotherapeutic approaches is extremely necessary. We elaborate on the features, functions, and cross talk of the innate and adaptive immune cells in HCC and highlight the benefits and drawbacks of various immunotherapies for advanced HCC, as well as future projections. HCC consists of a heterogeneous group of cancers with distinct etiologies and immune microenvironments. Almost all the components of innate and adaptive immune cells in HCC have altered, showing a decreasing trend in the number of tumor suppressor cells and an increasing trend in the pro-cancer cells, and there is also cross talk between various cell types. Various immunotherapies for HCC have also shown promising efficacy and application prospect. There are multilayered interwoven webs among various immune cell types in HCC, and emerging evidence demonstrates the promising prospect of immunotherapeutic approaches for HCC.

The Era of Immunotherapy in Hepatocellular Carcinoma: The New Mission and Challenges of Magnetic Resonance Imaging

In recent years, significant advancements in immunotherapy for hepatocellular carcinoma (HCC) have shown the potential to further improve the prognosis of patients with advanced HCC. However, in clinical practice, there is still a lack of effective biomarkers for identifying the patient who would benefit from immunotherapy and predicting the tumor response to immunotherapy. The immune microenvironment of HCC plays a crucial role in tumor development and drug responses. However, due to the complexity of immune microenvironment, currently, no single pathological or molecular biomarker can effectively predict tumor responses to immunotherapy. Magnetic resonance imaging (MRI) images provide rich biological information; existing studies suggest the feasibility of using MRI to assess the immune microenvironment of HCC and predict tumor responses to immunotherapy. Nevertheless, there are limitations, such as the suboptimal performance of conventional MRI sequences, incomplete feature extraction in previous deep learning methods, and limited interpretability. Further study needs to combine qualitative features, quantitative parameters, multi-omics characteristics related to the HCC immune microenvironment, and various deep learning techniques in multi-center research cohorts. Subsequently, efforts should also be undertaken to construct and validate a visual predictive tool of tumor response, and assess its predictive value for patient survival benefits. Additionally, future research endeavors must aim to provide an accurate, efficient, non-invasive, and highly interpretable method for predicting the effectiveness of immune therapy.

Comprehensive analysis of prognostic value and immune infiltration of IAPs family in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality rates. The inhibitors of apoptosis (IAP) family act as oncogenes in various tumor types; however, their functions in HCC remain unclear. Here, we used integrated bioinformatics analysis and experimental verification to assess the expression and the prognostic and clinical value of the IAP family in HCC. Using the University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) and the Tumor Immune Estimation Resource (TIMER), we analyzed the expression profiles of IAP family members in HCC tissue, normal tissues, and in patients with different stages and grades of HCC. We further verified the expression level of BIRC2 in 25 HCC samples and matched adjacent normal tissues using quantitative real-time PCR (qRT-PCR), and analyzed its correlation with the marker gene of T-helper type 1 cells (Th1)-STAT1. Meanwhile, the association between BIRC2 and the immunotherapeutic response or immunomodulators was confirmed using the Biomarker Exploration of Solid Tumors (BEST) database. The results showed that NAIP, BIRC2, BIRC3, XIAP, BIRC5, and BIRC6 mRNAs were overexpressed in HCC. The clinical stages, pathological grades, and other clinicopathological features of HCC were closely related to the expression levels of the IAP family members, especially the BIRC2 and BIRC5, which were found to be potential prognostic biomarkers for HCC. Expression of the IAPs was strongly associated with immune cell infiltration. Based on the infiltrative status of various immune cells, HCC patients with high BIRC2 and BIRC5 expression demonstrated poor overall survival (OS) rates. In patients with HCC, BIRC2 expression was noticeably elevated. Concurrently, the expression levels of BIRC2 and STAT1 showed a favorable correlation. BEST database analysis revealed that BIRC2 was a negative predictor of responsiveness to anti-programmed cell death ligand 1 (PD-L1)/cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4) inhibitor treatment in HCC, and BIRC2 mRNA expression levels were positively correlated with the expression levels of the immune checkpoint genes programmed cell death protein 1 (PD-1), PD-L1, and CTLA-4 in HCC. Consequently, the IAP family may play a role in carcinogenesis and cancer-immune system interactions in HCC. Our results demonstrate that IAP family members may be viable predictive biomarkers and therapeutic targets for HCC.

Robust analysis of a novel PANoptosis-related prognostic gene signature model for hepatocellular carcinoma immune infiltration and therapeutic response

PANoptosis, an interplay between pyroptosis, apoptosis, and necroptosis, is deeply involved in cancer development and immunity. However, the influence of PANoptosis in hepatocellular carcinoma (HCC) remains to be further investigated. The differentially expressed PANoptosis-related genes (PANRGs) was screened in The Cancer Genome Atlas (TCGA) database. Accordingly, mutation, bioinformatics, and consensus clustering analyses were performed. Then, a prognostic risk model was developed by least absolute shrinkage and selection operator (LASSO) Cox regression. Furthermore, the prognostic value, immunity correlation and therapeutic response prediction ability of risk model were explored. A total of 18 PANRGs were differently expressed in the TCGA-HCC cohort and were mainly involved in cancer- and cell death-related signal pathways. Using unsupervised clustering method, we identified two PANRGs-mediated clustering patterns. The remarkable differences between the two clusters on overall survival (OS) and clinical features were demonstrated respectively. Based on the five-gene prognostic risk model, the calculated PANRG-scores were used to categorize the subgroups as high- and low-risk. Notably, the high-risk subgroup had a dismal prognosis and exhibited much lower immune infiltration levels of mast cells, nature killer cells and pDCs, but higher levels of aDCs, iDCs and Treg cells than those in the low-risk subgroup. Furthermore, we constructed a reliable nomogram combining clinical traits and PANRG-score to predict the OS of HCC patients. The significantly negative correlation between PANoptosis and tumor mutation burden (TMB), ferroptosis were revealed. In drug sensitivity analysis, the high-risk subgroup had a considerably lower TIDE score, suggesting a preferable response to immunotherapy, and may be more sensitive to Tipifarnib, Imatinib, Doxorubicin, and Gemcitabine. The upregulated mRNA expressions of FADD were validated in 16 paired HCC tissues of Guangxi cohort. Based on PANoptosis-related genes, an integrated risk signature was constructed to provide a roadmap for patient stratification and predict HCC patient's prognosis. The patients with the higher PANRG-score may carry a dismal survival and relatively low immune infiltration, but a potential better immunotherapy response. Therefore, future HCC therapy perspectives should emphasize the setting of PANoptosis to achieve a personalized, practicable and effective therapeutic regimen.

Establishment of nucleic acid sensing pathways-based model in predicting response to immunotherapy and targeted drug in hepatitis virus-related hepatocellular carcinoma

Hepatocellular carcinoma (HCC) accounts for 80% of liver cancers, while 70%-80% of HCC developed from chronic liver disease with hepatitis B virus (HBV) and hepatitis C virus (HCV) infection as the major etiology. Immunotherapy is assuming a role as a pillar of HCC treatment, but the remarkable immune-mediated responses are restricted in a minority of patients. Nucleic acid sensing (NAS) pathways are the central pathway of the innate immune system and antiviral immune response to viral infection, but their role in hepatitis virus-related HCC remains undetermined. In our study, we performed a comprehensive bioinformatics analysis based on transcriptomic data of hepatitis virus related-HCC tissues collected from multiple public data sets. Two subgroups were validated based on NAS-related genes in virus-related HCC patients, which were defined as NAS-activated subgroups and NAS-suppressed subgroups based on the expression of NAS-related genes. On this basis, a NAS-related risk score (NASRS) predictive model was established for risk stratification and prognosis prediction in the hepatitis virus-related HCC (TCGA-LIHC and ICGC cohorts). The predictive values of the NASRS in prognosis and immunotherapy were also verified in multiple data sets. A nomogram was also established to facilitate the clinical use of NASRS and demonstrate its effectiveness through different approaches. Additionally, six potential drugs binding to the core target of the NAS signature were predicted via molecular docking strategy. We subsequently evaluated the cytotoxic capabilities of potential drug in vitro and in vivo. Based on these results, we conclude that the NASRS model could serve as a power prognostic biomarker and predict responses to immunotherapy, which is meaningful in clinical decision-making of hepatitis virus-related HCC patients.