Immunotherapy For Hepatocellular Carcinoma Research Articles

Neoadjuvant immunotherapy for resectable hepatocellular carcinoma: a systematic review and meta-analysis.

Immune checkpoint inhibitors have initiated a new era in hepatocellular carcinoma (HCC) treatment. For improving the prognosis of patients with resectable HCC and reducing postoperative recurrence, immunotherapy is being developed in the neoadjuvant setting. However, the efficacy and safety of neoadjuvant immunotherapy remain unclear. PubMed, Embase, Medline, and Cochrane Library databases were systematically searched for the clinical trials of neoadjuvant immunotherapy for resectable HCC. A single-arm meta-analysis was conducted to calculate the odds ratio and 95% confidence interval (CI), and statistical transformation was performed to obtain the pooled rate P(t) and its CI. Subgroup analyses were performed according to the type of combination therapy. 81 patients from four studies were included in this meta-analysis. In patients with resectable HCC, the pooled major pathological response (MPR) rate and pathological complete response (pCR) rate for neoadjuvant immunotherapy were 0.23 (95% CI, 0.14-0.36) and 0.19 (95% CI, 0.10-0.30), respectively. The pooled objective response rate (ORR) was 0.18 (95% CI, 0.10-0.28), comparable to the results of immunotherapy for advanced HCC. The overall treatment-related adverse events (TRAE) rate was 0.80 (95% CI, 0.68-0.89), but the grade ≥3 TRAE rate was low at 0.21 (95% CI, 0.13-0.33). The pooled surgical resection rate and surgical delay rate were 0.95 (95% CI, 0.85-0.98) and 0.05 (95% CI, 0.02-0.16), respectively. Subgroup analyses revealed no significant differences in clinical outcomes between immunotherapy combinations. This meta-analysis provides preliminary evidence of the efficacy and safety of neoadjuvant immunotherapy for HCC, suggesting that it is a promising perioperative treatment option. Conclusive evidence supporting its use requires additional data from large-scale clinical trials.

Role of radiotherapy and its contribution to immunotherapy in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a major contributor to cancer-related deaths, with the incidence of HCC increasing in regions of the world with a high incidence of hepatitis B and C. The therapeutic landscape for HCC management has substantially transformed over recent years, shifting towards a multimodal treatment paradigm. This approach provides a range of medical and surgical interventions aimed at managing the disease effectively. Radiotherapy (RT) has surfaced as a critical player in the preoperative management of inoperable HCC, demonstrating potential in downstaging the disease and achieving disease stability. This advantage may potentially be attributed to the abscopal effect, where localized radiation leads to the regression of metastatic cancer outside of the irradiated site through upregulation of the immune system. The advent of recent technological breakthroughs has paved the way for innovative approaches, notably the integration of immunotherapy and RT. This strategy is emerging as a promising avenue for managing HCC. Preliminary findings from the fusion of RT and immunotherapy are encouraging, with ongoing trials keenly evaluating the optimal parameters for therapy administration, such as timing, dosage, and sequence. The development of combined treatments involving immune checkpoint inhibitors (ICIs) has opened new avenues for advanced HCC treatment. Several immunotherapeutic agents with RT are concurrently being explored for their potential contributions to HCC management.

Leucocyte-hitchhiking liposomes loading gemcitabine and pyroptosis for potentiated immunotherapy of hepatocellular carcinoma.

168 Background: Hepatocellular carcinoma (HCC), as a malignant tumor with high incidence worldwide, faces the challenge of low efficacy of traditional chemotherapy drugs and immunotherapy drugs. Pyroptosis is a type of programmed cell death that can alleviate tumor immunosuppressive microenvironment and promote systemic immune response, which has great potential in improving the efficacy of immunotherapy drugs. The selection of more effective pyroptosis-inducing drugs and immunotherapy drugs, supplemented by more precise drug delivery strategies, is one of the research focuses in the treatment of HCC. Methods: In this study, Western Blot were performed to screen suitable pyroptosis-inducing drugs. A leucocyte-hitchhiking liposome nanodrug delivery system was designed to co-deliver a pyroptosis-inducing drug and a small molecule immunotherapy drug. The ability of the nanocarrier to induce pyroptosis of liver cancer cells and to activate immune cells were investigated in vitro. The targeting ability of the nanocarrier to peripheral blood leucocytes, the function of tumor inhibition and immune activation were evaluated in vivo. Results: In this study, gemcitabine was confirmed to induce pyroptosis in liver cancer cells. E-selectin modified liposomes were designed to co-deliver gemcitabine and the small molecule PD-1/PD-L1 complex inhibitor BMS-202. In vitro experiments confirmed that the nanocarrier could induce pyroptosis in liver cancer cells and activate immune cells. In vitro experiments confirmed the targeting ability of the nanocarrier to leukocytes and its ability to inhibit tumor and activate immunity. Conclusions: Leucocyte-hitchhiking liposomes loading gemcitabine and BMS-202 was successfully synthesized. After intravenous injection, liposomes effectively adhere to the surface of peripheral blood leukocytes mediated by E-selectin, thus hitchhiking with leukocytes to achieve high accumulation at the tumor site. The released gemcitabine can evoke tumor cell pyroptosis and generate anti-tumor immunity, while BMS-202 can alleviate immune suppression by inhibiting the formation of PD-1/PD-L1 complex, further enhance gemcitabine-induced anti-tumor immunity. This leucocyte-hitchhiking dual-delivery liposomal nanoplatform might provide a promising strategy for high-efficiency immunotherapy, exhibiting a great potential for clinical translation of HCC treatment.

Unveiling efferocytosis-related signatures through the integration of single-cell analysis and machine learning: a predictive framework for prognosis and immunotherapy response in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) represents a prominent gastrointestinal malignancy with a grim clinical outlook. In this regard, the discovery of novel early biomarkers holds substantial promise for ameliorating HCC-associated mortality. Efferocytosis, a vital immunological process, assumes a central position in the elimination of apoptotic cells. However, comprehensive investigations exploring the role of efferocytosis-related genes (EFRGs) in HCC are sparse, and their regulatory influence on HCC immunotherapy and targeted drug interventions remain poorly understood. RNA sequencing data and clinical characteristics of HCC patients were acquired from the TCGA database. To identify prognostically significant genes in HCC, we performed the limma package and conducted univariate Cox regression analysis. Subsequently, machine learning algorithms were employed to identify hub genes. To assess the immunological landscape of different HCC subtypes, we employed the CIBERSORT algorithm. Furthermore, single-cell RNA sequencing (scRNA-seq) was utilized to investigate the expression levels of ERFGs in immune cells and to explore intercellular communication within HCC tissues. The migratory capacity of HCC cells was evaluated using CCK-8 assays, while drug sensitivity prediction reliability was determined through wound-healing assays. We have successfully identified a set of nine genes, termed EFRGs, that hold significant potential for the establishment of a hepatocellular carcinoma-specific prognostic model. Furthermore, leveraging the individual risk scores derived from this model, we were able to stratify patients into two distinct risk groups, unveiling notable disparities in terms of immune infiltration patterns and response to immunotherapy. Notably, the model's capacity to accurately predict drug responses was substantiated through comprehensive experimental investigations, encompassing wound-healing assay, and CCK8 experiments conducted on the HepG2 and Huh7 cell lines. We constructed an EFRGs model that serves as valuable tools for prognostic assessment and decision-making support in the context of immunotherapy and chemotherapy.

D-lactate modulates M2 tumor-associated macrophages and remodels immunosuppressive tumor microenvironment for hepatocellular carcinoma.

The polarization of tumor-associated macrophages (TAMs) from M2 to M1 phenotype demonstrates great potential for remodeling the immunosuppressive tumor microenvironment (TME) of hepatocellular carcinoma (HCC). d-lactate (DL; a gut microbiome metabolite) acts as an endogenous immunomodulatory agent that enhances Kupffer cells for clearance of pathogens. In this study, the potential of DL for transformation of M2 TAMs to M1 was confirmed, and the mechanisms underlying such polarization were mainly due to the modulation of phosphatidylinositol 3-kinase/protein kinase B pathway. A poly(lactide-co-glycolide) nanoparticle (NP) was used to load DL, and the DL-loaded NP was modified with HCC membrane and M2 macrophage-binding peptide (M2pep), forming a nanoformulation (DL@NP-M-M2pep). DL@NP-M-M2pep transformed M2 TAMs to M1 and remodeled the immunosuppressive TME in HCC mice, promoting the efficacy of anti-CD47 antibody for long-term animal survival. These findings reveal a potential TAM modulatory function of DL and provide a combinatorial strategy for HCC immunotherapy.

Dual mRNA co-delivery for in situ generation of phagocytosis-enhanced CAR macrophages augments hepatocellular carcinoma immunotherapy

Hepatocellular carcinoma (HCC) is a prevalent and lethal disease, and tumor regression rarely occurs in advanced HCC patients due to limited effective therapies. Given the enrichment of macrophages in HCC and their role in tumor immunity, transforming them into chimeric antigen receptor macrophages (CAR-Ms) is thought to increase HCC cell-directed phagocytosis and tumoricidal immunity. To test this hypothesis, mRNA encoding CAR is encapsulated in a lipid nanoparticle (LNP) that targets liver macrophages. Notably, the LNPs adsorb specific plasma proteins that enable them to target HCC-associated macrophages. Moreover, mRNA encoding Siglec-G lacking ITIMs (Siglec-GΔITIMs) is codelivered to liver macrophages by LNP to relieve CD24-mediated CAR-Ms immune suppression. Mice treated with LNPs generating CAR-Ms as well as CD24-Siglec-G blockade significantly elevate the phagocytic function of liver macrophages, reduce tumor burden and increase survival time in an HCC mouse model. Arguably, our work suggests an efficacious and flexible strategy for the treatment of HCC and warrants further rigorous evaluation in clinical trials.

Molecular subtypes based on DNA sensors predict prognosis and tumor immunophenotype in hepatocellular carcinoma.

DNA sensors play crucial roles in inflammation and have been indicated to be involved in antitumor or tumorigenesis, while it is still unclear whether DNA sensors have potential roles in the prognosis and immunotherapy of hepatocellular carcinoma (HCC). Herein, The Cancer Genome Atlas and Gene Expression Omnibus databases were used to analyze RNA sequencing data and clinical information. A total of 14 DNA sensors were collected and performed consensus clustering to determine their molecular mechanisms in HCC. Two distinct molecular subtypes (Clusters C1 and C2) were identified and were associated with different overall survival (OS). Immune subtype analysis revealed that C1 was mainly characterized by inflammation, while C2 was characterized by lymphocyte depletion. Immune scoring and immunomodulatory function analysis confirmed the different immune microenvironment of C1 and C2. Notably, significant differences in "Hot Tumor" Immunophenotype were observed between the two subtypes. Moreover, the prognostic model based on DNA sensors is capable of effectively predicting the OS of HCC patients. Besides, the chemotherapeutic drug analysis showed the different sensitivity of two subtypes. Taken together, our study shows that the proposed DNA sensors were a reliable signature to predict the prognosis and immunotherapy response with potential application in the clinical decision and treatment of HCC.

Application of adoptive cell therapy in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) remains a global health challenge. Novel treatment modalities are urgently needed to extend the overall survival of patients. The liver plays an immunomodulatory function due to its unique physiological structural characteristics. Therefore, following surgical resection and radiotherapy, immunotherapy regimens have shown great potential in the treatment of hepatocellular carcinoma. Adoptive cell immunotherapy is rapidly developing in the treatment of hepatocellular carcinoma. In this review, we summarize the latest research on adoptive immunotherapy for hepatocellular carcinoma. The focus is on chimeric antigen receptor (CAR)-T cells and T cell receptor (TCR) engineered T cells. Then tumour-infiltrating lymphocytes (TILs), natural killer (NK) cells, cytokine-induced killer (CIK) cells, and macrophages are briefly discussed. The main overview of the application and challenges of adoptive immunotherapy in hepatocellular carcinoma. It aims to provide the reader with a comprehensive understanding of the current status of HCC adoptive immunotherapy and offers some strategies. We hope to provide new ideas for the clinical treatment of hepatocellular carcinoma.

The potential of mRNA vaccine in HCC treatment

Neoantigen mRNA vaccines are a potential form of immunotherapy for Hepatocellular Carcinoma (HCC). These neoantigens can be targeted with personalized mRNA vaccines, which are designed to stimulate the patient’s immune system to recognize and destroy cancer cells. Neoantigen mRNA vaccines are developed using RNA sequences that are synthesized based on the genetic mutations found in HCC patients. These RNA sequences are formulated into a vaccine and administered to the patient, typically in combination with other cancer treatments for enhancing the anti-cancer effect. Several preclinical and clinical studies have shown promising results for neoantigen mRNA vaccines in HCC immunotherapy. Early results suggest that they may be a valuable addition to the treatment options available for HCC patients. However, more research is needed to determine the safety and efficacy of these vaccines.

Comprehensive analysis of anoikis-related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma.

Nowadays, primary liver cancer is still a major threat to human health. Anoikis is a particular form of programed cell death that has an inhibitory effect on neoplasm metastasis. Although several prognostic models based on anoikis-related genes for Hepatocellular carcinoma (HCC) have been established, signatures associated with anoikis-related lncRNAs have not been identified. To fill this blank space, the authors built up a prognostic signature and appraised its value in guiding immunotherapy. Eleven prognostic anoikis-related lncRNAs were identified through Least Absolute Shrinkage and Selection Operator Cox analysis. The accuracy of the risk signature in predicting prognosis was verified by K-M survival analysis and Receiver operating characteristic analysis. We further discovered that the high-risk group was often enriched in signal pathways related to cell growth and death and immune response; in addition, in the low-risk group, cells often undergo metabolic changes through gene set enrichment analysis. Finally, we realised that HCC patients in the high-risk group were upregulated in immune-checkpoint molecules and tend to have a higher tumour mutation burden level which indicated a higher sensitivity to immunotherapy. All in all, the anoikis-related lncRNAs risk signature showed excellent ability in predicting prognosis and may guide the application of immunotherapy in future clinical practice.

Characterization of neutrophil extracellular traps related gene pair for predicting prognosis in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignant disease with a high incidence rate, high mortality and poor prognosis. Neutrophil extracellular traps (NETs), as an extracellular reticular structure, promote the development and progression of cancer in the tumor microenvironment, and have a promising prospect as a prognostic indicator. In the present study, we elucidated the prognostic value of NET-related genes. The NETs gene pair of The Cancer Genome Atlas cohort was constructed by least absolute shrinkage and selection operator analysis. Samples from the International Cancer Genome Consortium were performed to verify its feasibility. Kaplan-Meier analysis was used to compare the overall survival (OS) rate of the two subgroups. The independent predictors of OS were determined by univariate and multivariate Cox analysis. Furthermore, Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway were analyzed by gene set enrichment analysis. The single sample gene set enrichment analysis method was performed to deplore the relationship of risk score with tumor immune microenvironment. The GSE149614 dataset was applied as single cell RNA level validation. PCR was performed to the detect mRNA expression profiles of NETs-related genes. Our analysis of the NETs-related model provides a promising prospect as a prognostic indicator. The OS of high-risk group patients was significantly reduced. The risk score was an important independent predictor of HCC prognosis. The Nomogram model suggested a favorable classification performance. The drug resistance and sensitivity of tumor cells to chemotherapeutics was significantly correlated with the prognostic gene expression. The immune status of the two risk groups showed a marked difference. The novel prognostic gene pair and immune landscape could predict the prognosis of HCC patients and provide a new understanding of immunotherapy in HCC.

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

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

New techniques: a roadmap for the development of HCC immunotherapy.

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. The absence of effective early diagnostic methods and the limitations of conventional therapies have led to a growing interest in immunotherapy as a novel treatment approach for HCC. The liver serves as an immune organ and a recipient of antigens from the digestive tract, creating a distinctive immune microenvironment. Key immune cells, including Kupffer cells and cytotoxic T lymphocytes, play a crucial role in HCC development, thus offering ample research opportunities for HCC immunotherapy. The emergence of advanced technologies such as clustered regularly interspaced short palindromic repeats (CRISPR) and single-cell ribonucleic acid sequencing has introduced new biomarkers and therapeutic targets, facilitating early diagnosis and treatment of HCC. These advancements have not only propelled the progress of HCC immunotherapy based on existing studies but have also generated new ideas for clinical research on HCC therapy. Furthermore, this review analysed and summarised the combination of current therapies for HCC and the improvement of CRISPR technology for chimeric antigen receptor T cell therapy, instilling renewed hope for HCC treatment. This review comprehensively explores the advancements in immunotherapy for HCC, focusing on the use of new techniques.

Bioinformatics prediction and experimental verification identify cuproptosis-related lncRNA as prognosis biomarkers of hepatocellular carcinoma

Cuproptosis is a form of cell death caused by intracellular copper excess, which plays an important regulatory role in the development and progression of cancers, including hepatocellular carcinoma (HCC), a prevalent malignancy with high morbidity and mortality.This study aimed to create a cuproptosis associated long non-coding RNAs (CAlncRNAs)signature to predict HCC patient survival and immunotherapy response. Firstly, we identified 509 CAlncRNAs using Pearson correlation analysis in The Cancer Genome Atlas (TCGA) datasets, before the three CAlncRNAs (MKLN1-AS, FOXD2-AS1, LINC02870) with the most prognostic value were further screened. Then, we constructed a prognostic risk model for HCCwas using univariate and LASSO Cox regression analyses. Multivariate Cox regression analyses illustrated that this model was an independent prognostic factor for overall survival (OS) prediction, outperforming traditional clinicopathological factors. And the risk score not only could be prognostic factors independent of other factors but also suited for patients with diverse ages, stages, and grades. The 1-, 3-, and 5- years areas under the curves (AUC) values of the model were 0.759, 0.668 and 0.674 respectively. Pathway analyses showed that the high-risk groupenriched in immune-related pathways. Importantly, patients with higher risk scores exhibited higher mutation frequency, higher TMB scores, and lower TIDE scores. Besides, we screened for two chemical drugs (A-443654 and Pyrimethamine) with the greatest value for high-risk HCC patients. Finally, the abnormal high expression of the three CAlncRNAs were confirmed in HCC tissues and cells by Real Time Quantitative PCR (RT-qPCR). And proliferative, migratory and invasion abilities of HCC cell were restrained via silencing CAlncRNAs expression in vitro.In summary, we built a CAlncRNAs-based risk score model, which can be a candidate for HCC patients prognostic prediction and offer some useful information for immunotherapies.

Identification and validation of Birc5 as a novel activated cell cycle program biomarker associated with infiltration of immunosuppressive myeloid-derived suppressor cells in hepatocellular carcinoma.

Preclinical studies and clinical trials have demonstrated that tumor-intrinsic activation of the cell cycle program impedes anticancer immunotherapy. Identification of cell cycle-related biomarkers may provide novel therapeutic targets to augment the efficacy of immunotherapy in hepatocellular carcinoma (HCC). Based on the genes related to cell cycle program, two clusters (Cluster 1 and Cluster 2) were detected in HCC patients via non-negative matrix factorization algorithm. Multivariable-adjusted Cox regression analysis indicated that the cell cycle gene-based classification was a significant prognostic factor for predicting the clinical outcome of HCC patients. Cluster 1 showed shorter overall survival time and progression-free interval time was associated with activated cell cycle program, higher infiltration of myeloid-derived suppressor cells (MDSCs) and less sensitivity to immunotherapy. A three-gene prognostic model, including BIRC5, C8G, and SPP1, was constructed to characterize the cell cycle-based classification of HCC, which had strong robustness and a stable predictive performance. Notably, Birc5 was positively correlated with CD11b expression (a MDSC marker) in HCC tissue. Concordant high expression of Birc5 and intratumor infiltration level of MDSCs were correlated with worse prognosis of HCC patients. In vitro, hepatocellular Birc5 overexpression promoted immunosuppressive CD11b+ CD33+ HLA-DR- MDSC expansion from human peripheral blood mononuclear cells. Genetically modified animal model of liver cancer revealed that Birc5 depletion upregulated the genes related to lymphocyte-mediated immunity, natural killer cell-mediated immunity, interferon-gamma production, T-cell activation, and T-cell-mediated cytotoxicity. These results suggest an immunosuppressive function of Birc5 in HCC. Birc5 was a potential biomarker and inducer of intratumor infiltration of MDSCs, which led to T cell exclusion or dysfunction in tumor immune microenvironment, consequently resulting in reduced response to ICIs in HCC.

Combination of alpha-fetoprotein and neutrophil-to-lymphocyte ratio to predict treatment response and survival outcomes of patients with unresectable hepatocellular carcinoma treated with immune checkpoint inhibitors

BackgroundImmune-checkpoint inhibitors (ICIs) have revolutionized the treatment of hepatocellular carcinoma (HCC). However, long-term survival outcomes and treatment response of HCC patients undergoing immunotherapy is unpredictable. The study aimed to evaluate the role of alpha-fetoprotein (AFP) combined with neutrophil-to-lymphocyte ratio (NLR) to predict the prognosis and treatment response of HCC patients receiving ICIs.MethodsPatients with unresectable HCC who received ICI treatment were included. The HCC immunotherapy score was developed from a retrospective cohort at the Eastern Hepatobiliary Surgery Hospital to form the training cohort. The clinical variables independently associated with overall survival (OS) were identified using univariate and multivariate Cox regression analysis. Based on multivariate analysis of OS, a predictive score based on AFP and NLR was constructed, and patients were stratified into three risk groups according to this score. The clinical utility of this score to predict progression-free survival (PFS) and differentiate objective response rate (ORR) and disease control rate (DCR) was also performed. This score was validated in an independent external validation cohort at the First Affiliated Hospital of Wenzhou Medical University.ResultsBaseline AFP ≤ 400 ng/ml (hazard ratio [HR] 0.48; 95% CI, 0.24–0.97; P = 0.039) and NLR ≤ 2.77 (HR 0.11; 95% CI, 0.03–0.37; P<0.001) were found to be independent risk factors of OS. The two labolatory values were used to develop the score to predict survival outcomes and treatment response in HCC patients receiving immunotherapy, which assigned 1 point for AFP > 400 ng/ml and 3 points for NLR > 2.77. Patients with 0 point were classified as the low-risk group. Patients with 1–3 points were categorized as the intermediate-risk group. Patients with 4 points were classified as the high-risk group. In the training cohort, the median OS of the low-risk group was not reached. The median OS of the intermediate-risk group and high-risk group were 29.0 (95% CI 20.8–37.3) months and 16.0 (95% CI 10.8–21.2) months, respectively (P < 0.001). The median PFS of the low-risk group was not reached. The median PFS of the intermediate-risk group and high-risk group were 14.6 (95% CI 11.3–17.8) months and 7.6 (95% CI 3.6–11.7) months, respectively (P < 0.001). The ORR and DCR were highest in the low-risk group, followed by the intermediate-risk group and the high-risk group (P < 0.001, P = 0.007, respectively). This score also had good predictive power using the validation cohort.ConclusionThe HCC immunotherapy score based on AFP and NLR can predict survival outcomes and treatment response in patients receiving ICI treatments, suggesting that this score could serve as a useful tool for identification of HCC patients likely to benefit from immunotherapy.

Efferocytosis signatures as prognostic markers for revealing immune landscape and predicting immunotherapy response in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is a highly lethal liver cancer with late diagnosis; therefore, the identification of new early biomarkers could help reduce mortality. Efferocytosis, a process in which one cell engulfs another cell, including macrophages, dendritic cells, NK cells, etc., plays a complex role in tumorigenesis, sometimes promoting and sometimes inhibiting tumor development. However, the role of efferocytosis-related genes (ERGs) in HCC progression has been poorly studied, and their regulatory effects in HCC immunotherapy and drug targeting have not been reported. Methods: We downloaded efferocytosis-related genes from the Genecards database and screened for ERGs that showed significant expression changes between HCC and normal tissues and were associated with HCC prognosis. Machine learning algorithms were used to study prognostic gene features. CIBERSORT and pRRophetic R packages were used to evaluate the immune environment of HCC subtypes and predict treatment response. CCK-8 experiments conducted on HCC cells were used to assess the reliability of drug sensitivity prediction. Results: We constructed a prognostic prediction model composed of six genes, and the ROC curve showed good predictive accuracy of the risk model. In addition, two ERG-related subgroups in HCC showed significant differences in tumor immune landscape, immune response, and prognostic stratification. The CCK-8 experiment conducted on HCC cells confirmed the reliability of drug sensitivity prediction. Conclusion: Our study emphasizes the importance of efferocytosis in HCC progression. The risk model based on efferocytosis-related genes developed in our study provides a novel precision medicine approach for HCC patients, allowing clinicians to customize treatment plans based on unique patient characteristics. The results of our investigation carry noteworthy implications for the development of individualized treatment approaches involving immunotherapy and chemotherapy, thereby potentially facilitating the realization of personalized and more efficacious therapeutic interventions for HCC.

The Emerging Role of Metformin in the Treatment of Hepatocellular Carcinoma: Is There Any Value in Repurposing Metformin for HCC Immunotherapy?

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. There has been significant progress in understanding the risk factors and epidemiology of HCC during the last few decades, resulting in efficient preventative, diagnostic and treatment strategies. Type 2 diabetes mellitus (T2DM) has been demonstrated to be a major risk factor for developing HCC. Metformin is a widely used hypoglycemic agent for patients with T2DM and has been shown to play a potentially beneficial role in improving the survival of patients with HCC. Experimental and clinical studies evaluating the outcomes of metformin as an antineoplastic drug in the setting of HCC were reviewed. Pre-clinical evidence suggests that metformin may enhance the antitumor effects of immune checkpoint inhibitors (ICIs) and reverse the effector T cells' exhaustion. However, there is still limited clinical evidence regarding the efficacy of metformin in combination with ICIs for the treatment of HCC. We appraised and analyzed in vitro and animal studies that aimed to elucidate the mechanisms of action of metformin, as well as clinical studies that assessed its impact on the survival of HCC patients.

CD38 marks the exhausted CD8+ tissue-resident memory T cells in hepatocellular carcinoma.

Despite recent advances in immunotherapy for hepatocellular carcinoma (HCC), the overall modest response rate underscores the need for a better understanding of the tumor microenvironment (TME) of HCC. We have previously shown that CD38 is widely expressed on tumor-infiltrating leukocytes (TILs), predominantly on CD3+ T cells and monocytes. However, its specific role in the HCC TME remains unclear. In this current study, we used cytometry time-of-flight (CyTOF), bulk RNA sequencing on sorted T cells, and single-cell RNA (scRNA) sequencing to interrogate expression of CD38 and its correlation with T cell exhaustion in HCC samples. We also employed multiplex immunohistochemistry (mIHC) for validating our findings. From CyTOF analysis, we compared the immune composition of CD38-expressing leukocytes in TILs, non-tumor tissue-infiltrating leukocytes (NIL), and peripheral blood mononuclear cells (PBMC). We identified CD8+ T cells as the dominant CD38-expressing TILs and found that CD38 expression was significantly higher in CD8+ TRM in TILs than in NILs. Furthermore, through transcriptomic analysis on sorted CD8+ TRM from HCC tumors, we observed a higher expression of CD38 along with T cell exhaustion genes, including PDCD1 and CTLA4, compared to the circulating memory CD8 T cells from PBMC. This was validated by scRNA sequencing that revealed co-expression of CD38 with PDCD1, CTLA4, and ITGAE (CD103) in T cells from HCC tumors. The protein co-expression of CD38 and PD-1 on CD8+ T cells was further demonstrated by mIHC on HCC FFPE tissues, marking CD38 as a T cell co-exhaustion marker in HCC. Lastly, the higher proportions of CD38+PD-1+ CD8+ T cells and CD38+PD-1+ TRM were significantly associated with the higher histopathological grades of HCC, indicating its role in the aggressiveness of the disease. Taken together, the concurrent expression of CD38 with exhaustion markers on CD8+ TRM underpins its role as a key marker of T cell exhaustion and a potential therapeutic target for restoring cytotoxic T cell function in HCC.

Nanodelivery of scutellarin induces immunogenic cell death for treating hepatocellular carcinoma

Hepatocellular carcinoma (HCC) causes the immunosuppressive tumor microenvironment (TME) resistant to current immunotherapy. The immunogenic apoptosis (currently termed immunogenic cell death, ICD) of cancer cells may induce the adaptive immunity against tumors, thereby providing great potential for treating HCC. In this study, we have confirmed the potential of scutellarin (SCU, a flavonoid found in Erigeron breviscapus) for triggering ICD in HCC cells. To facilitate in vivo application of SCU for HCC immunotherapy, an aminoethyl anisamide-targeted polyethylene glycol-modified poly(lactide-co-glycolide) (PLGA-PEG-AEAA) was produced to facilitate SCU delivery in this study. The resultant nanoformulation (PLGA-PEG-AEAA.SCU) remarkably promoted blood circulation and tumor delivery in the orthotopic HCC mouse model. Consequently, PLGA-PEG-AEAA.SCU reversed the immune suppressive TME and achieved the immunotherapeutic efficacy, resulting in significantly longer survival of mice, without inducing toxicity. These findings uncover the ICD potential of SCU and provide a promising strategy for HCC immunotherapy.