Prognostic role of immune cells in hepatocellular carcinoma

Prognostic significance of LRPPRC and its association with immune infiltration in liver hepatocellular carcinoma

BACKGROUND

Leucine rich pentatricopeptide repeat containing (LRPPRC) protein is a multifunctional protein involved in cell cycle progression and tumor development. However, its prognostic significance and association with immune infiltration in Liver hepatocellular carcinoma (LIHC) remain unclear.

METHODS

We utilized transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases of LIHC patients to investigate the potential pro-cancer role of LRPPRC, including differential expression of LRPPRC in LIHC, prognostic value, clinicopathological features, immune cell infiltration relevance and function enrichment analysis.

RESULTS

Our findings suggest that LRPPRC is upregulated in LIHC and exhibits correlations with survival, clinical stage, and tumor grade in LIHC patients. Additionally, immune infiltration analysis revealed significant negative correlations between LRPPRC expression and multiple tumor-infiltrating immune cells, including CTLs, DCs, pDCs, B cells, Th17 cells, neutrophils, T cells, Mast cells, Th1 cells, Tregs, and NK cells, whereas a significant positive correlation was observed with infiltration of Th2 cells, T helper cells and Tcms. Furthermore, functional enrichment analysis indicated that LRPPRC may be involved in G2m checkpoint, mitotic spindle, E2f targets, Wnt Beta catenin signaling, spermatogenesis and other processes.

Identification of PANoptosis-related subtypes, construction of a prognosis signature, and tumor microenvironment landscape of hepatocellular carcinoma using bioinformatic analysis and experimental verification

Background

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies worldwide. PANoptosis is a recently unveiled programmed cell death pathway, Nonetheless, the precise implications of PANoptosis within the context of HCC remain incompletely elucidated.

Methods

We conducted a comprehensive bioinformatics analysis to evaluate both the expression and mutation patterns of PANoptosis-related genes (PRGs). We categorized HCC into two clusters and identified differentially expressed PANoptosis-related genes (DEPRGs). Next, a PANoptosis risk model was constructed using LASSO and multivariate Cox regression analyses. The relationship between PRGs, risk genes, the risk model, and the immune microenvironment was studies. In addition, drug sensitivity between high- and low-risk groups was examined. The expression profiles of these four risk genes were elucidate by qRT-PCR or immunohistochemical (IHC). Furthermore, the effect of CTSC knock down on HCC cell behavior was verified using in vitro experiments.

Results

We constructed a prognostic signature of four DEPRGs (CTSC, CDCA8, G6PD, and CXCL9). Receiver operating characteristic curve analyses underscored the superior prognostic capacity of this signature in assessing the outcomes of HCC patients. Subsequently, patients were stratified based on their risk scores, which revealed that the low-risk group had better prognosis than those in the high-risk group. High-risk group displayed a lower Stromal Score, Immune Score, ESTIMATE score, and higher cancer stem cell content, tumor mutation burden (TMB) values. Furthermore, a correlation was noted between the risk model and the sensitivity to 56 chemotherapeutic agents, as well as immunotherapy efficacy, in patient with. These findings provide valuable guidance for personalized clinical treatment strategies. The qRT-PCR analysis revealed that upregulated expression of CTSC, CDCA8, and G6PD, whereas downregulated expression of CXCL9 in HCC compared with adjacent tumor tissue and normal liver cell lines. The knockdown of CTSC significantly reduced both HCC cell proliferation and migration.

Conclusion

Our study underscores the promise of PANoptosis-based molecular clustering and prognostic signatures in predicting patient survival and discerning the intricacies of the tumor microenvironment within the context of HCC. These insights hold the potential to advance our comprehension of the therapeutic contribution of PANoptosis plays in HCC and pave the way for generating more efficacious treatment strategies.

CDK1-SRC Interaction-Dependent Transcriptional Activation of HSP90AB1 Promotes Antitumor Immunity in Hepatocellular Carcinoma

This study aimed to analyze multiomics data and construct a regulatory network involving kinases, transcription factors, and immune genes in hepatocellular carcinoma (HCC) prognosis. The researchers used transcriptomic, proteomic, and clinical data from TCGA and GEO databases to identify immune genes associated with HCC. Statistical analysis, meta-analysis, and protein-protein interaction analyses were performed to identify key immune genes and their relationships. In vitro and in vivo experiments validated the CDK1-SRC-HSP90AB1 network's effects on HCC progression and antitumor immunity. A prognostic risk model was developed using clinicopathological features and immune infiltration. The immune genes LPA, BIRC5, HSP90AB1, ROBO1, and CCL20 were identified as the key prognostic factors. The CDK1-SRC-HSP90AB1 network promoted HCC cell proliferation and migration, with HSP90AB1 being transcriptionally activated by the CDK1-SRC interaction. Manipulating SRC or HSP90AB1 reversed the effects of CDK1 and SRC on HCC. The CDK1-SRC-HSP90AB1 network also influenced HCC tumor formation and antitumor immunity. Overall, this study highlights the importance of the CDK1-SRC-HSP90AB1 network as a crucial immune-regulatory network in the HCC prognosis.

TRIP13 overexpression in hepatocellular carcinoma: implications for poor prognosis and immune cell infiltration

PURPOSE

The overexpression of TRIP13 has been observed in many types of cancer and has been identified as an oncogene. However, its role in hepatocellular carcinoma (HCC) has not been extensively studied. This study aimed to investigate the expression of TRIP13 in HCC and its impact on immune cell infiltration and prognosis.

METHODS

We analyzed TCGA and GSE62232 datasets to assess TRIP13 expression in HCC. Kaplan-Meier and subgroup analysis were performed to examine the correlation between TRIP13 expression and HCC. Univariate and Cox regression analysis were conducted to determine the predictive value of TRIP13 in assessing patient outcomes. A nomogram was developed using TRIP13 mRNA expression to predict HCC prognosis. TRIP13 expression was validated using immunohistochemistry in our patient cohort. Survival and subgroup analyses were conducted to investigate the role of TRIP13 in HCC prognosis.

RESULTS

The results indicated that TRIP13 upregulation in HCC was a strong independent predictor of poor outcome, as determined by Kaplan-Meier and Cox regression analyses. A high AUC value of 0.982 from ROC curves suggested that TRIP13 upregulation could serve as a reliable diagnostic indicator for HCC. The immunohistochemical validation of TRIP13 expression in the patient cohort confirmed its prognostic significance, and high TRIP13 expression was found to be associated with increased infiltration of Th2 cells and decreased infiltration of neutrophils, Th17 cells, and dendritic cells.

CONCLUSION

These findings suggest that TRIP13 could be a potential prognostic biomarker for HCC.

Overexpression of POLA2 in hepatocellular carcinoma is involved in immune infiltration and predicts a poor prognosis

BACKGROUND

Hepatocellular carcinoma (HCC) is the second malignancy worldwide. POLA2 initiates DNA replication, regulates cell cycle and gene repair that promote tumorigenesis and disease progression. However, the prognostic and biological function roles of POLA2 in HCC had not been conclusively determined.

METHODS

The expression levels and prognosis role of POLA1 and POLA2 in HCC were analyzed based on TCGA-LIHC database and recruited 24 HCC patients. Gene mutations were analyzed using "maftools" package. POLA2 and immune cells correlations were analyzed by TIMER. POLA2 co-expressed genes functional enrichment were evaluated using Metascape. The mRNA and protein level of POLA2 was detected in HCC cells and tissues. Cell migration, invasion, proliferation, cell cycle and HCC cell lines derived xenograft model were performed to investigate POLA2 biological function.

RESULTS

POLA2 was significantly high expressed in HCC than in normal liver tissue in both TCGA-LIHC and our collected HCC samples. In validation cohort, POLA2 significantly related to tumor differentiation, tumor size and Ki-67 (p < 0.05). In TCGA-LIHC cohort, overexpression of POLA2 predicted a low OS and associated with different clinical stages. Multivariate Cox regression showed overexpression of POLA2 effectively distinguished the prognosis at different T, N, M, stages and grades of HCC. POLA2 expression correlated with mutation burden, immune cells infiltration and immune-associated genes expression of HCC. Functional enrichment revealed that POLA2 co-expressed genes were linked to cellular activity, plasma membrane protein complex and leukocyte activity, immune response-regulated cell surface receptor signaling pathway, and immune response-regulated signaling pathway. Moreover, POLA2 was also positively co-expressed with some immune checkpoints (CD274, CTL-4, HAVCR2, PDCD1, PDCD1LG2, TIGIT, and LAG3) (p < 0.001). Gene knockdown revealed that POLA2 promoted proliferation, migration, invasion, and cell cycle of SMMC-7721 and HepG2. The HCC xenograft tumor model also demonstrated remarkably tumor size inhibition, tumor proliferation inhibtion and tumor necrosis promotion when POLA2 knockdown.

CONCLUSIONS

POLA2 influenced immune microenvironment and tumor progression of HCC indicated that it might be a potential molecular marker for prognostic evaluation or a therapeutic target for HCC.

Identification of PANoptosis-Based Prognostic Signature for Predicting Efficacy of Immunotherapy and Chemotherapy in Hepatocellular Carcinoma

Background

PANoptosis has been a research hotspot, but the role of PANoptosis in hepatocellular carcinoma (HCC) remains widely unknown. Drug resistance and low response rate are the main limitations of chemotherapy and immunotherapy in HCC. Thus, construction of a prognostic signature to predict prognosis and recognize ideal patients for corresponding chemotherapy and immunotherapy is necessary.

Method

The mRNA expression data of HCC patients was collected from TCGA database. Through LASSO and Cox regression, we developed a prognostic signature based on PANoptosis-related genes. KM analysis and ROC curve were implemented to evaluate the prognostic efficacy of this signature, and ICGC and GEO database were used as external validation cohorts. The immune cell infiltration, immune status, and IC50 of chemotherapeutic drugs were compared among different risk subgroups. The relationships between the signature and the efficacy of ICI therapy, sorafenib treatment, and transcatheter arterial chemoembolization (TACE) therapy were investigated.

Result

A 3-gene prognostic signature was constructed which divided the patients into low- and high-risk subgroups. Low-risk patients had better prognosis, and the risk score was proved to be an independent predictor of overall survival (OS), which had a well predictive effect. Patients in high-risk population had more immunosuppressive cells (Tregs, M0 macrophages, and MDSCs), higher TIDE score and TP53 mutation rate, and elevated activity of base excision repair (BER) pathways. Patients with low risk benefited more from ICI, TACE, and sorafenib therapy. The predictive value of the risk score was comparable with TIDE and MSI for OS under ICI therapy. The risk score could be a biomarker to predict the response to ICI, TACE, and sorafenib therapy.

Conclusion

The novel signature based on PANoptosis is a promising biomarker to distinguish the prognosis predict the benefit of ICI, TACE, and sorafenib therapy, and forecast the response to them.

Screening prognostic markers for hepatocellular carcinoma based on pyroptosis-related lncRNA pairs

BACKGROUND

Pyroptosis is closely related to cancer prognosis. In this study, we tried to construct an individualized prognostic risk model for hepatocellular carcinoma (HCC) based on within-sample relative expression orderings (REOs) of pyroptosis-related lncRNAs (PRlncRNAs).

METHODS

RNA-seq data of 343 HCC samples derived from The Cancer Genome Atlas (TCGA) database were analyzed. PRlncRNAs were detected based on differentially expressed lncRNAs between sample groups clustered by 40 reported pyroptosis-related genes (PRGs). Univariate Cox regression was used to screen out prognosis-related PRlncRNA pairs. Then, based on REOs of prognosis-related PRlncRNA pairs, a risk model for HCC was constructed by combining LASSO and stepwise multivariate Cox regression analysis. Finally, a prognosis-related competing endogenous RNA (ceRNA) network was built based on information about lncRNA-miRNA-mRNA interactions derived from the miRNet and TargetScan databases.

RESULTS

Hierarchical clustering of HCC patients according to the 40 PRGs identified two groups with a significant survival difference (Kaplan-Meier log-rank, p = 0.026). Between the two groups, 104 differentially expressed lncRNAs were identified (|log₂(FC)|> 1 and FDR < 5%). Among them, 83 PRlncRNA pairs showed significant associations between their REOs within HCC samples and overall survival (Univariate Cox regression, p < 0.005). An optimal 11-PRlncRNA-pair prognostic risk model was constructed for HCC. The areas under the curves (AUCs) of time-dependent receiver operating characteristic (ROC) curves of the risk model for 1-, 3-, and 5-year survival were 0.737, 0.705, and 0.797 in the validation set, respectively. Gene Set Enrichment Analysis showed that inflammation-related interleukin signaling pathways were upregulated in the predicted high-risk group (p < 0.05). Tumor immune infiltration analysis revealed a higher abundance of regulatory T cells (Tregs) and M2 macrophages and a lower abundance of CD8 + T cells in the high-risk group, indicating that excessive pyroptosis might occur in high-risk patients. Finally, eleven lncRNA-miRNA-mRNA regulatory axes associated with pyroptosis were established.

CONCLUSION

Our risk model allowed us to determine the robustness of the REO-based PRlncRNA prognostic biomarkers in the stratification of HCC patients at high and low risk. The model is also helpful for understanding the molecular mechanisms between pyroptosis and HCC prognosis. High-risk patients may have excessive pyroptosis and thus be less sensitive to immune therapy.

Effects of dexmedetomidine on oxidative stress, programmed cell death, liver function, and expression of peripheral immune cells in patients with primary liver cancer undergoing hepatectomy

Study background: Primary liver cancer is a severe health issue that imposes a significant health burden on families. Oxidation and subsequent cell death impair liver function and provoke an immune response. The present article investigates the effect of Dexmedetomidine on oxidation, cell death, the expression of peripheral immune cells, and liver function. The clinical data will represent the facts and evidence of the effects of this intervention. Methods: We analyzed clinical data reporting various accounts of the effects of Dexmedetomidine on oxidation, cell death, the expression of peripheral immune cells, and liver function among patients who underwent hepatectomy. The surgical procedure reported the differences in cell death as procedural outcomes among pre- and post-treatment records were compared and contrasted. Results: We found decreased cell apoptosis in the treatment group: the number of incisions to remove dead cells was lower in the treatment group than in the pre-treatment group. Likewise, lower oxidation was reported in pre-treatment than in post-treatment records. The expression of peripheral immune cells was higher in the pre-treatment clinical data than in post-treatment, suggesting a reduction in oxidation following dexmedetomidine treatment. Liver function was a function of oxidation and cell death outcomes. In the pre-treatment clinical data, liver function was poor, whereas improved functions were reported in the post-treatment clinical data. Discussion: We found compelling evidence of Dexmedetomidine's effects on oxidative stress and programmed cell death. The intervention suppresses the production of reactive oxygen species and the consequential apoptosis. Additionally, liver functions improve due to the decrease in hepatocyte apoptosis. Since the peripheral immune cells are expressed against tumors, a decrease in the progression of primary liver cancer decreased the expression of the peripheral immune cells. Conclusion: Dexmedetomidine's positive effects stood out in the present research article. The intervention reduced oxidation by balancing the production of reactive oxygen species and the detoxification processes. Reduced oxidation induced reduced cell death through apoptosis, resulting in a low expression of peripheral immune cells and improved liver functions.

Recent progress in molecular mechanisms of postoperative recurrence and metastasis of hepatocellular carcinoma

Hepatectomy is currently considered the most effective option for treating patients with early and intermediate hepatocellular carcinoma (HCC). Unfortunately, the postoperative prognosis of patients with HCC remains unsatisfactory, predominantly because of high postoperative metastasis and recurrence rates. Therefore, research on the molecular mechanisms of postoperative HCC metastasis and recurrence will help develop effective intervention measures to prevent or delay HCC metastasis and recurrence and to improve the long-term survival of HCC patients. Herein, we review the latest research progress on the molecular mechanisms underlying postoperative HCC metastasis and recurrence to lay a foundation for improving the understanding of HCC metastasis and recurrence and for developing more precise prevention and intervention strategies.

The Functional Roles of Immune Cells in Primary Liver Cancer

Primary liver cancer includes hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA). Incidence of liver cancer has been increasing in recent years, and the 5-year survival is <20%. HCC and CCA are often accompanied with a dense stroma coupled with infiltrated immune cells, which is referred to as the tumor microenvironment. Populations of specific immune cells, such as high density of CD163⁺ macrophages and low density of CD8⁺ T cells, are associated with prognosis and survival rates in both HCC and CCA. Immune cells in the tumor microenvironment can be a therapeutic target for liver cancer treatments. Previous studies have introduced immunotherapy using immune checkpoint inhibitors, pulsed dendritic cells, or transduced T cells, to enhance cytotoxicity of immune cells and inhibit tumor growth. This review summarizes current understanding of the roles of immune cells in primary liver cancer covering HCC and CCA.

The Role of Immune Checkpoint Molecules on Macrophages in Cancer, Infection, and Autoimmune Pathologies

Immune checkpoint inhibitors have revolutionized immunotherapy against various cancers over the last decade. The use of checkpoint inhibitors results in remarkable re-activation of patients’ immune system, but is also associated with significant adverse events. In this review, we emphasize the importance of cell-type specificity in the context of immune checkpoint-based interventions and particularly focus on the relevance of macrophages. Immune checkpoint blockade alters the dynamic macrophage phenotypes and thereby substantially manipulates therapeutical outcome. Considering the macrophage-specific immune checkpoint biology, it seems feasible to ameliorate the situation of patients with severe side effects and even increase the probability of survival for non-responders to checkpoint inhibition. Apart from malignancies, investigating immune checkpoint molecules on macrophages has stimulated their fundamental characterization and use in other diseases as well, such as acute and chronic infections and autoimmune pathologies. Although the macrophage-specific effect of checkpoint molecules has been less studied so far, the current literature shows that a macrophage-centered blockade of immune checkpoints as well as a stimulation of their expression represents promising therapeutic avenues. Ultimately, the therapeutic potential of a macrophage-focused checkpoint therapy might be maximized by diagnostically assessing individual checkpoint expression levels on macrophages, thereby personalizing an effective treatment approach for each patient having cancer, infection, or autoimmune diseases.

Identification of Immune-Related Prognostic mRNA and lncRNA in Patients with Hepatocellular Carcinoma

Background

As the most common hepatic malignancy, hepatocellular carcinoma (HCC) has a high incidence; therefore, in this paper, the immune-related genes were sought as biomarkers in liver cancer.

Methods

In this study, a differential expression analysis of lncRNA and mRNA in The Cancer Genome Atlas (TCGA) dataset between the HCC group and the normal control group was performed. Enrichment analysis was used to screen immune-related differentially expressed genes. Cox regression analysis and survival analysis were used to determine prognostic genes of HCC, whose expression was detected by molecular experiments. Finally, important immune cells were identified by immune cell infiltration and detected by flow cytometry.

Results

Compared with the normal group, 1613 differentially expressed mRNAs (DEmRs) and 1237 differentially expressed lncRNAs (DElncRs) were found in HCC. Among them, 143 immune-related DEmRs and 39 immune-related DElncRs were screened out. These genes were mainly related to MAPK cascade, PI3K-AKT signaling pathway, and TGF-beta. Through Cox regression analysis and survival analysis, MMP9, SPP1, HAGLR, LINC02202, and RP11-598F7.3 were finally determined as the potential diagnostic biomarkers for HCC. The gene expression was verified by RT-qPCR and western blot. In addition, CD4 + memory resting T cells and CD8 + T cells were identified as protective factors for overall survival of HCC, and they were found highly expressed in HCC through flow cytometry.

Conclusion

The study explored the dysregulation mechanism and potential biomarkers of immune-related genes and further identified the influence of immune cells on the prognosis of HCC, providing a theoretical basis for the prognosis prediction and immunotherapy in HCC patients.

Identification of the Immune Cell Infiltration Landscape in Hepatocellular Carcinoma to Predict Prognosis and Guide Immunotherapy

Background: Globally, hepatocellular carcinoma (HCC) is the sixth most frequent malignancy with a high incidence and a poor prognosis. Immune cell infiltration (ICI) underlies both the carcinogenesis and immunogenicity of tumors. However, a comprehensive classification system based on the immune features for HCC remains unknown.

Methods: The HCC dataset from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts was used in this study. The ICI patterns of 571 patients were characterized using two algorithms: the patterns were determined based on the ICI using the ConsensusClusterPlus package, and principal component analysis (PCA) established the ICI scores. Differences in the immune landscape, biological function, and somatic mutations across ICI scores were evaluated and compared, followed by a predictive efficacy evaluation of ICI scores for immunotherapy by the two algorithms and validation using an external immunotherapy cohort.

Results: Based on the ICI profile of the HCC patients, three ICI patterns were identified, including three subtypes having different immunological features. Individual ICI scores were determined; the high ICI score subtype was characterized by enhanced activation of immune-related signaling pathways and a significantly high tumor mutation burden (TMB); concomitantly, diminished immunocompetence and enrichment of pathways associated with cell cycle and RNA degradation were found in the low ICI score subtype. Taken together, our results contribute to a better understanding of an active tumor and plausible reasons for its poor prognosis.

Conclusion: The present study reveals that ICI scores may serve as valid prognostic biomarkers for immunotherapy in HCC.

Regulatory T-Cell Therapy in Liver Transplantation and Chronic Liver Disease

The constant exposure of the liver to gut derived foreign antigens has resulted in this organ attaining unique immunological characteristics, however it remains susceptible to immune mediated injury. Our understanding of this type of injury, in both the native and transplanted liver, has improved significantly in recent decades. This includes a greater awareness of the tolerance inducing CD4+ CD25+ CD127low T-cell lineage with the transcription factor FoxP3, known as regulatory T-Cells (Tregs). These cells comprise 5-10% of CD4+ T cells and are known to function as an immunological "braking" mechanism, thereby preventing immune mediated tissue damage. Therapies that aim to increase Treg frequency and function have proved beneficial in the setting of both autoimmune diseases and solid organ transplantations. The safety and efficacy of Treg therapy in liver disease is an area of intense research at present and has huge potential. Due to these cells possessing significant plasticity, and the potential for conversion towards a T-helper 1 (Th1) and 17 (Th17) subsets in the hepatic microenvironment, it is pre-requisite to modify the microenvironment to a Treg favourable atmosphere to maintain these cells' function. In addition, implementation of therapies that effectively increase Treg functional activity in the liver may result in the suppression of immune responses and will hinder those that destroy tumour cells. Thus, fine adjustment is crucial to achieve this immunological balance. This review will describe the hepatic microenvironment with relevance to Treg function, and the role these cells have in both native diseased and transplanted livers.

Construction of an Immune-Related Six-lncRNA Signature to Predict the Outcomes, Immune Cell Infiltration, and Immunotherapy Response in Patients With Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the world's most lethal malignant tumors with a poor prognosis. Growing evidence has been demonstrating that immune-related long non-coding RNAs (lncRNAs) are relevant to the tumor microenvironment (TME) and can help assess the effects of immunotherapy and evaluate one's prognosis. This study aims to identify an immune-related lncRNA signature for the prospective assessment of the immunotherapy and prognosis in HCC.

METHOD

We downloaded HCC RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) project database. We first used ESTIMATE to evaluate the TME. Then, we conducted a cox regression analysis to construct a prognostic signature and the riskScore. We then applied the univariate Cox regression, multivariate Cox regression, principal components analysis (PCA), receiver operating characteristic (ROC) curve, and stratification analyses to confirm our previous assessments. Afterward, we employed a gene set enrichment analysis (GSEA) to explore the biological processes and pathways. Besides, we used CIBERSORT to estimate the abundance of tumor-infiltrating immune cells (TIICs). Furthermore, we investigated the relationship between the immune-related lncRNA signature and immune checkpoint genes. Finally, we used the quantitative real-time polymerase chain reaction (qRT-PCR) assays to demonstrate the expression of the six lncRNAs.

RESULTS

We identified six immune-related lncRNAs - MSC-AS1, AC145207.5, SNHG3, AL365203.2, AL031985.3, NRAV - which show the ability to stratify patients into high-risk and low-risk groups with significantly different survival rates. The univariate Cox regression, multivariate Cox regression, ROC, and stratification analyses confirmed that the immune-related six-lncRNA signature was a novel independent prognostic factor in HCC patients. The high-risk group and low-risk group illustrated contrasting distributions in PCA. The GSEA suggested that the immune-related six-lncRNA signature was involved in the immune-related biological processes and pathways. Besides, the immune-related six-lncRNA signature was associated with the infiltration of immune cells. Furthermore, it was linked with the expression of critical immune genes and could predict immunotherapy's clinical response. Finally, the qRT-PCR demonstrated that the six lncRNAs were significantly differentially expressed in HCC cell lines and normal hepatic cell lines.

CONCLUSION

In summary, we identified an immune-related six-lncRNA signature that can predict the outcomes, immune cell infiltration, and immunotherapy response in patients with hepatocellular carcinoma.

Immune signature-based hepatocellular carcinoma subtypes may provide novel insights into therapy and prognosis predictions

Background

Hepatocellular carcinoma (HCC) has a poor prognosis and has become the sixth most common malignancy worldwide due to its high incidence. Advanced approaches to therapy, including immunotherapeutic strategies, have played crucial roles in decreasing recurrence rates and improving clinical outcomes. The HCC microenvironment is important for both tumour carcinogenesis and immunogenicity, but a classification system based on immune signatures has not yet been comprehensively described.

Methods

HCC datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Cancer Genome Consortium (ICGC) were used in this study. Gene set enrichment analysis (GSEA) and the ConsensusClusterPlus algorithm were used for clustering assessments. We scored immune cell infiltration and used linear discriminant analysis (LDA) to improve HCC classification accuracy. Pearson's correlation analyses were performed to assess relationships between immune signature indices and immunotherapies. In addition, weighted gene co-expression network analysis (WGCNA) was applied to identify candidate modules closely associated with immune signature indices.

Results

Based on 152 immune signatures from HCC samples, we identified four distinct immune subtypes (IS1, IS2, IS3, and IS4). Subtypes IS1 and IS4 had more favourable prognoses than subtypes IS2 and IS3. These four subtypes also had different immune system characteristics. The IS1 subtype had the highest scores for IFNγ, cytolysis, angiogenesis, and immune cell infiltration among all subtypes. We also identified 11 potential genes, namely, TSPAN15, TSPO, METTL9, CD276, TP53I11, SPINT1, TSPO, TRABD2B, WARS2, C9ORF116, and LBH, that may represent potential immunological biomarkers for HCC. Furthermore, real-time PCR revealed that SPINT1, CD276, TSPO, TSPAN15, METTL9, and WARS2 expression was increased in HCC cells.

Conclusions

The present gene-based immune signature classification and indexing may provide novel perspectives for both HCC immunotherapy management and prognosis prediction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02033-4.

Biomarkers in Hepatobiliary Cancers: What is Useful in Clinical Practice?

Hepatocellular carcinoma (HCC) and biliary tract cancers (BTC) exhibit a poor prognosis with 5-year overall survival rates around 15%, all stages combined. Most of these primary liver malignancies are metastatic at diagnostic, with only limited therapeutic options, relying mainly on systemic therapies. Treatment modalities are different yet partially overlapping between HCC and BTC. The complex molecular profile of BTC yields to several actionable therapeutic targets, contrary to HCC that remains the field of antiangiogenic drugs in non-molecularly selected patients. Immunotherapy is now validated in the first line in HCC in combination with bevacizumab, while clinical activity of single agent immunotherapy appears limited to a subset of patients in BTC, still poorly characterized, and combinations are currently under investigation. In this review, we provide a critical evaluation and grading of clinical relevance on (i) the main prognostic biomarkers in HCC and BTC, (ii) the main theragnostic biomarkers in both tumors, and lastly (iii) what is recommended in clinical practice.

Progress and Challenges of Predictive Biomarkers for Immune Checkpoint Blockade

Over the past decade, immune checkpoint blockade (ICB) therapy has revolutionized the outlook for oncology with significant and sustained improvement in the overall patient survival. Unlike traditional cancer therapies, which target the cancer cells directly, ICB acts on the immune system to enhance anti-tumoral immunity. However, the response rate is still far from satisfactory and most patients are refractory to such treatment. Unfortunately, the mechanisms underlying such heterogeneous responses between patients to ICB therapy remain unclear. In addition, escalating costs of cancer care and unnecessary immune-related adverse events also are pertinent considerations with applications of ICB. Given these issues, identifying explicit predictive biomarkers for patient selection is an urgent unmet need to increase the efficacy of ICB therapy. The markers can be classified as tumor related and non-tumor-related biomarkers. Although substantial efforts have been put into investigating various biomarkers, none of them has been found to be sufficient for effectively stratifying patients who may benefit from immunotherapy. The present write up is an attempt to review the various emerging clinically relevant biomarkers affecting the efficacy of immune checkpoint inhibitors, as well as the limitations associated with their clinical application.

A metabolism-related gene signature for predicting the prognosis and therapeutic responses in patients with hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) often has an insidious onset and rapid progression. Often, when the disease is first diagnosed, the opportune time for surgical intervention has already lapsed. In addition, the effects of systemic treatment is relatively unsatisfactory. Metabolic reprogramming is one of the hallmarks of cancer. This study aimed to identify a set of genes related to metabolism to construct a predictive model for the prognosis of HCC.

Methods

The transcriptomic and clinical data of 352 HCC patients were obtained from The Cancer Genome Atlas (TCGA) Liver Hepatocellular Carcinoma (LIHC) dataset and divided into a training cohort (n=212) and a testing cohort (n=140) at a ratio of 6:4. Univariate Cox regression analysis and the LASSO Cox regression model were used to identify 5 genes to establish a risk score for predicting the prognosis of HCC patients. Subsequently, the molecular characteristics of the model were assessed and the ability of the model to predict the tumor immune microenvironment and patient response to immunotherapy and chemotherapy was also examined.

Results

The risk score model was constructed based on the five genes, methyltransferase-like protein 6 (METTL6), RNA polymerase III subunit G (POLR3G), phosphoribosyl pyrophosphate amidotransferase (PPAT), SET Domain Bifurcated 2 (SETDB2), and suppressor of variegation 3-9 homolog 2 (SUV39H2). The Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) curves demonstrated that high-risk patients had a poorer overall survival (OS) compared to low-risk patients. he nomogram score had a better predictive ability compared to the common factors. Our results finally showed that high-risk cases were associated with cell proliferation and cell cycle related gene sets, high tumor protein P53 (TP53) mutation rate, suppressive immunity and increased sensitivity to cisplatin, gemcitabine and docetaxel. Meanwhile, low-risk cases were associated with cell cycle and immune response related pathways, low TP53 mutation rate, active immunity and more benefit from immunotherapy.

Conclusions

This study provided novel insights into the role of metabolism-related genes in HCC, and demonstrated that our model could be a promising prognostic biomarker for distinguishing the molecular and immune characteristics and inferring the potential response to chemotherapy and immunotherapy.

Impact of regulatory T cells on the prognosis of hepatocellular carcinoma: A protocol for systematic review and meta analysis

BACKGROUND

This meta-analysis aimed to systematically review current available literature to assess the impact of regulatory T cells (Tregs) on the prognosis of hepatocellular carcinoma (HCC).

METHODS

We will browse the online databases of PubMed and Cochrane Library. The summary hazard ratio (HR) and their 95% confidence intervals (CIs) will be combined to present the value reported in the study.

CONCLUSION

Our meta-analysis will provide useful guidance in treatment of HCC based on the reported evidences regarding the impact of Tregs on the prognosis of HCC.

OSF REGISTRATION NUMBER

10.17605/OSF.IO/3Q8PW.

Immunotherapy for Hepatocellular Carcinoma: A 2021 Update

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