Immune Gene Expression Profile in Hepatocellular Carcinoma and Surrounding Tissue Predicts Time to Tumor Recurrence

Identification of Two Distinct Immune Subtypes in Hepatitis B Virus (HBV)-Associated Hepatocellular Carcinoma (HCC)

HBV is the most common risk factor for HCC development, accounting for almost 50% of cases worldwide. Despite significant advances in immunotherapy, there is limited information on the HBV-HCC tumor microenvironment (TME), which may influence the response to checkpoint inhibitors. Here, we characterize the TME in a unique series of liver specimens from HBV-HCC patients to identify who might benefit from immunotherapy. By combining an extensive immunohistochemistry analysis with the transcriptomic profile of paired liver samples (tumor vs. nontumorous tissue) from 12 well-characterized Caucasian patients with HBV-HCC, we identified two distinct tumor subtypes that we defined immune-high and immune-low. The immune-high subtype, seen in half of the patients, is characterized by a high number of infiltrating B and T cells in association with stromal activation and a transcriptomic profile featuring inhibition of antigen presentation and CTL activation. All the immune-high tumors expressed high levels of CTLA-4 and low levels of PD-1, while PD-L1 was present only in four of six cases. In contrast, the immune-low subtype shows significantly lower lymphocyte infiltration and stromal activation. By whole exome sequencing, we documented that four out of six individuals with the immune-low subtype had missense mutations in the CTNNB1 gene, while only one patient had mutations in this gene in the immune-high subtype. Outside the tumor, there were no differences between the two subtypes. This study identifies two distinctive immune subtypes in HBV-associated HCC, regardless of the microenvironment observed in the surrounding nontumorous tissue, providing new insights into pathogenesis. These findings may be instrumental in the identification of patients who might benefit from immunotherapy.

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 role of Neanderthal introgression in liver cancer

BACKGROUND

Neanderthal introgressed DNA has been linked to different normal and disease traits including immunity and metabolism-two important functions that are altered in liver cancer. However, there is limited understanding of the relationship between Neanderthal introgression and liver cancer risk. The aim of this study was to investigate the relationship between Neanderthal introgression and liver cancer risk.

METHODS

Using germline and somatic DNA and tumor RNA from liver cancer patients from The Cancer Genome Atlas, along with ancestry-match germline DNA from unaffected individuals from the 1000 Genomes Resource, and allele specific expression data from normal liver tissue from The Genotype-Tissue Expression project we investigated whether Neanderthal introgression impacts cancer etiology. Using a previously generated set of Neanderthal alleles, we identified Neanderthal introgressed haplotypes. We then tested whether somatic mutations are enriched or depleted on Neanderthal introgressed haplotypes compared to modern haplotypes. We also computationally assessed whether somatic mutations have a functional effect or show evidence of regulating expression of Neanderthal haplotypes. Finally, we compared patterns of Neanderthal introgression in liver cancer patients and the general population.

RESULTS

We find Neanderthal introgressed haplotypes exhibit an excess of somatic mutations compared to modern haplotypes. Variant Effect Predictor analysis revealed that most of the somatic mutations on these Neanderthal introgressed haplotypes are not functional. We did observe expression differences of Neanderthal alleles between tumor and normal for four genes that also showed a pattern of enrichment of somatic mutations on Neanderthal haplotypes. However, gene expression was similar between liver cancer patients with modern ancestry and liver cancer patients with Neanderthal ancestry at these genes. Provocatively, when analyzing all genes, we find evidence of Neanderthal introgression regulating expression in tumor from liver cancer patients in two genes, ARK1C4 and OAS1. Finally, we find that most genes do not show a difference in the proportion of Neanderthal introgression between liver cancer patients and the general population.

CONCLUSION

Our results suggest that Neanderthal introgression provides opportunity for somatic mutations to accumulate, and that some Neanderthal introgression may impact liver cancer risk.

Characterization of glucose metabolism in breast cancer to guide clinical therapy

Background

Breast cancer (BRCA) ranks as a leading cause of cancer death in women worldwide. Glucose metabolism is a noticeable characteristic of the occurrence of malignant tumors. In this study, we aimed to construct a novel glycometabolism-related gene (GRG) signature to predict overall survival (OS), immune infiltration and therapeutic response in BRCA patients.

Materials and methods

The mRNA sequencing and corresponding clinical data of BRCA patients were obtained from public cohorts. Lasso regression was applied to establish a GRG signature. The immune infiltration was evaluated with the ESTIMATE and CIBERSORT algorithms. The drug sensitivity was estimated using the value of IC50, and further forecasted the therapeutic response of each patient. The candidate target was selected in Cytoscape. A nomogram was constructed via the R package of “rms”.

Results

We constructed a six-GRG signature based on CACNA1H, CHPF, IRS2, NT5E, SDC1 and ATP6AP1, and the high-risk patients were correlated with poorer OS (P = 2.515 × 10⁻⁷). M2 macrophage infiltration was considerably superior in high-risk patients, and CD8⁺ T cell infiltration was significantly higher in low-risk patients. Additionally, the high-risk group was more sensitive to Lapatinib. Fortunately, SDC1 was recognized as candidate target and patients had a better OS in the low-SDC1 group. A nomogram integrating the GRG signature was developed, and calibration curves were consistent between the actual and predicted OS.

Conclusions

We identified a novel GRG signature complementing the present understanding of the targeted therapy and immune biomarker in breast cancer. The GRGs may provide fresh insights for individualized management of BRCA patients.

Distinct Gene Expression Profiles in Viable Hepatocellular Carcinoma Treated With Liver-Directed Therapy

Background

Hepatocellular carcinoma is a heterogeneous tumor that accumulates a mutational burden and dysregulated signaling pathways that differ from early to advanced stages. Liver transplant candidates with early-stage hepatocellular carcinoma (HCC) undergo liver-directed therapy (LDT) to delay disease progression and serve as a bridge to liver transplantation (LT). Unfortunately, >80% of LDT-treated patients have viable HCC in the explant liver, dramatically increasing recurrence risk. Understanding the effect of LDT on early-stage HCC could help identify therapeutic targets to promote complete pathologic necrosis and improve recurrence-free survival. In this study, transcriptomic data from viable HCC in LDT-treated bridged to transplant patients were investigated to understand how treatment may affect tumor signaling pathways.

Methods

Multiplex transcriptomic gene analysis was performed with mRNA extracted from viable tumors of HCC patients bridged to transplant using LDT. The NanoString nCounter® Tumor Signaling 360 panel was used that contained 780 genes from 48 pathways involved in tumor biology within the microenvironment as well as antitumoral immune responses.

Results

Hierarchical clustering separated tumors into three subtypes (HCC-1, HCC-2, and HCC-3) each with distinct differences in anti-tumoral signaling and immune infiltration within the tumor microenvironment. Immune infiltration (neutrophils, T cells, and macrophages) were all lowest in subtype HCC-3. The tumor inflammatory signature consisting of 18 genes associated with PD-1/PD-L1 inhibition, antigen presentation, chemokine secretion, and adaptive immune responses was highest in subtype HCC-1 and lowest in HCC-3. History of decompensation and etiology were associated with HCC subtype favoring downregulations in inflammation and immune infiltration with upregulation of lipid metabolism. Gene expression among intrahepatic lesions was remarkably similar with >85% of genes expressed in both lesions. Genes differentially expressed (<8 genes per patient) in multifocal disease were all upregulated in LDT-treated tumors from pathways involving epithelial mesenchymal transition, extracellular matrix remodeling, and/or inflammation potentially implicating intrahepatic metastases.

Conclusion

Incomplete response to LDT may drive expression patterns that inhibit an effective anti-tumoral response through immune exclusion and induce intrahepatic spread.

Molecular classification of hepatocellular carcinoma: prognostic importance and clinical applications

Hepatocellular carcinoma (HCC) is a lethal human malignancy with a very low overall and long-term survival rate. Poor prognostic outcomes are predominantly associated with HCC due to a huge landscape of heterogeneity found in the deadliest disease. However, molecular subtyping of HCC has significantly improved the knowledge of the underlying mechanisms that contribute towards the heterogeneity and progression of the disease. In this review, we have extensively summarized the current information available about molecular classification of HCC. This review can be of great significance for providing the insight information needed for development of novel, efficient and personalized therapeutic options for the treatment of HCC patients globally.

Finding the seed of recurrence: Hepatocellular carcinoma circulating tumor cells and their potential to drive the surgical treatment

The treatment for hepatocellular carcinoma (HCC) relies on liver resection, which is, however, burdened by a high rate of recurrence after surgery, up to 60% at 5 years. No pre-operative tools are currently available to assess the recurrence risk tailored to every single patient. Recently liquid biopsy has shown interesting results in diagnosis, prognosis and treatment allocation strategies in other types of cancers, since its ability to identify circulating tumor cells (CTCs) derived from the primary tumor. Those cells were advocated to be responsible for the majority of cases of recurrence and cancer-related deaths for HCC. In fact, after being modified by the epithelial-mesenchymal transition, CTCs circulate as “seeds” in peripheral blood, then reach the target organ as dormant cells which could be subsequently “awakened” and activated, and then initiate metastasis. Their presence may justify the disagreement registered in terms of efficacy of anatomic vs non-anatomic resections, particularly in the case of microvascular invasion, which has been recently pointed as a histological sign of the spread of those cells. Thus, their presence, also in the early stages, may justify the recurrence event also in the contest of liver transplant. Understanding the mechanism behind the tumor progression may allow improving the treatment selection according to the biological patient-based characteristics. Moreover, it may drive the development of novel biological tailored tests which could address a specific patient to neoadjuvant or adjuvant strategies, and in perspective, it could also become a new method to allocate organs for transplantation, according to the risk of relapse after liver transplant. The present paper will describe the most recent evidence on the role of CTCs in determining the relapse of HCC, highlighting their potential clinical implication as novel tumor behavior biomarkers able to influence the surgical choice.

Integrated analysis of the rhesus monkey liver transcriptome during development and human primary HCC AFP-related gene expression

Embryonic development and tumorigenesis have a certain degree of similarity. Alpha-fetoprotein (AFP), a protein related to embryonic development, is a well-known biomarker for the diagnosis and prognosis of hepatocellular carcinoma (HCC). In this study, we analyzed the differences in gene expression profiles and molecular mechanisms in human HCC tissues from patients in AFP^high (serum AFP level ≥ 25 ng/mL) and AFP^low (serum AFP level < 25 ng/mL) groups. The results indicated that AFP^high HCC has more malignant biological characteristics. Single-sample gene set enrichment analysis (ssGSEA) showed significantly higher levels of genes expressed in dendritic cells, neutrophils, and natural killer cells in the AFP^low group than in the AFP^high group. Then, we defined a rhesus monkey fetal liver developmental landscape and compared it to the HCC gene expression profile. The gene signatures of AFP^high HCC tissues were similar to those of early embryonic liver tissues. In this study, we comprehensively analyzed the rhesus monkey liver transcriptome during development and human primary HCC AFP-related gene expression profiles and clarified the function of AFP in the occurrence and development of HCC from the perspective of developmental biology, which might provide a new perspective on the pathogenesis of HCC.

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

BACKGROUND

Increasing evidence has indicated immune-related genes (IRGs) play a key role in the development of hepatocellular carcinoma (HCC). Whereas, there have been no investigations proposing a reliable prognostic signature in terms of IRGs. This study aimed to develop a robust signature based on IRGs in HCC. A total of 597 HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were enrolled in this study.

METHODS

The TCGA cohort was utilized for discovery, and the ICGC cohort was utilized for validation. Multiple algorithms were implemented to identify key prognostic IRGs and establish an immune-related risk signature. Bioinformatics analysis and R soft tools were utilized to annotate underlying biological functions.

RESULTS

A total of 1416 differentially expressed mRNAs (DEMs) were screened, of which 90 were differentially expressed IRGs (DEIRGs). Using univariate Cox regression analysis, we identified 33 prognostically relevant DEIRGs. Using least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis, we extracted 8 optimal DEIRGs to construct a risk signature in the TCGA cohort, and the signature was verified in the ICGC cohort. We also built a nomogram to increase the accuracy of predicting HCC prognosis. By investigating the relationship of the risk score and 8 risk genes from our signature with clinical traits, we found that the aberrant expression of the immune-related risk genes is correlated with the development of HCC. Moreover, the high-risk group was higher than the low-risk group in terms of tumor mutation burden (TMB), immune cell infiltration, and the expression of immune checkpoints (programmed cell death protein 1 [PD-1], programmed cell death ligand 1 [PD-L1], and cytotoxic T-lymphocyte-related protein 4 [CTLA-4]), and functional enrichment analysis indicated the signature enriched an intensive immune phenotype.

CONCLUSION

This study developed a robust immune-related risk signature and built a predictive nomogram that reliably predict overall survival in HCC, which may be helpful for clinical management and personalized immunotherapy decisions.

Prognostic value of a novel glycolysis-related gene expression signature for gastrointestinal cancer in the Asian population

BACKGROUND

Globally, gastrointestinal (GI) cancer is one of the most prevalent malignant tumors. However, studies have not established glycolysis-related gene signatures that can be used to construct accurate prognostic models for GI cancers in the Asian population. Herein, we aimed at establishing a novel glycolysis-related gene expression signature to predict the prognosis of GI cancers.

METHODS

First, we evaluated the mRNA expression profiles and the corresponding clinical data of 296 Asian GI cancer patients in The Cancer Genome Atlas (TCGA) database (TCGA-LIHC, TCGA-STAD, TCGA-ESCA, TCGA-PAAD, TCGA-COAD, TCGA-CHOL and TCGA-READ). Differentially expressed mRNAs between GI tumors and normal tissues were investigated. Gene Set Enrichment Analysis (GSEA) was performed to identify glycolysis-related genes. Then, univariate, LASSO regression and multivariate Cox regression analyses were performed to establish a key prognostic glycolysis-related gene expression signature. The Kaplan-Meier and receiver operating characteristic (ROC) curves were used to evaluate the efficiency and accuracy of survival prediction. Finally, a risk score to predict the prognosis of GI cancers was calculated and validated using the TCGA data sets. Furthermore, this risk score was verified in two Gene Expression Omnibus (GEO) data sets (GSE116174 and GSE84433) and in 28 pairs of tissue samples.

RESULTS

Prognosis-related genes (NUP85, HAX1, GNPDA1, HDLBP and GPD1) among the differentially expressed glycolysis-related genes were screened and identified. The five-gene expression signature was used to assign patients into high- and low-risk groups (p < 0.05) and it showed a satisfactory prognostic value for overall survival (OS, p = 6.383 × 10^-6). The ROC curve analysis revealed that this model has a high sensitivity and specificity (0.757 at 5 years). Besides, stratification analysis showed that the prognostic value of the five-gene signature was independent of other clinical characteristics, and it could markedly discriminate between GI tumor tissues and normal tissues. Finally, the expression levels of the five prognosis-related genes in the clinical tissue samples were consistent with the results from the TCGA data sets.

CONCLUSIONS

Based on the five glycolysis-related genes (NUP85, HAX1, GNPDA1, HDLBP and GPD1), and in combination with clinical characteristics, this model can independently predict the OS of GI cancers in Asian patients.

Identification of a prognostic and therapeutic immune signature associated with hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most prevalent and inflammation-associated cancers. The tumor microenvironment (TME) plays an essential role in HCC development and metastasis, leading to poor prognosis. The overall TME immune cells infiltration characterizations mediated by immune-related genes (IRGs) remain unclear. In this study, we aimed to investigate whether immune-related genes could be indicators for the prognosis of HCC patients and TME cell infiltration characterization as well as responses to immunotherapy.

Methods

We obtained differentially expressed immune-related genes (DE IRGs) between normal liver tissues and liver cancer tissues from The Cancer Genome Atlas (TCGA) database. To identify the prognostic genes and establish an immune risk signature, we performed univariable Cox regression survival analysis and the Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the DE IRGs by robust rank aggregation method. Cox regression analysis was used to identify independent prognostic factors in HCC. We estimated the immune cell infiltration in TME via CIBERSORT and immunotherapy response through TIDE algorithm.

Results

We constructed an immune signature and validated its predictive capability. The immune signature included 7 differentially expressed IRGs: BIRC5, CACYBP, NR0B1, RAET1E, S100A8, SPINK5, and SPP1. The univariate and multivariate cox analysis showed that the 7-IRGs signature was a robust independent prognostic factor in the overall survival of HCC patients. The 7-IRG signature was associated with some clinical features, including gender, vascular invasion, histological grade, clinical stage, T stage. We also found that the 7-IRG signature could reflect the infiltration characterization of different immunocytes in the tumor microenvironment (TME) and had a good correlation with immune checkpoint molecules, revealing that the poor prognosis might be partly due to immunosuppressive TME. The Tumour Immune Dysfunction and Exclusion (TIDE) analysis data showed that the 7-IRG signature had great potential for indicating the immunotherapy response in HCC patients. The mutation analysis demonstrated a significant difference in the tumor mutation burden (TMB) between the high- and low-risk groups, partially explaining this signature's predictive value.

Conclusion

In a word, we constructed and validated a novel, immune-related prognostic signature for HCC patients. This signature could effectively indicate HCC patients' survival and immunotherapy response. And it might act as potential immunotherapeutic targets for HCC patients.

Inflammatory microenvironment of fibrotic liver promotes hepatocellular carcinoma growth, metastasis and sorafenib resistance through STAT3 activation

The pro‐inflammatory and pro‐fibrotic liver microenvironment facilitates hepatocarcinogenesis. However, the effects and mechanisms by which the hepatic fibroinflammatory microenvironment modulates intrahepatic hepatocellular carcinoma (HCC) progression and its response to systematic therapy remain largely unexplored. We established a syngeneic orthotopic HCC mouse model with a series of persistent liver injury induced by CCl₄ gavage, which mimic the dynamic effect of hepatic pathology microenvironment on intrahepatic HCC growth and metastasis. Non‐invasive bioluminescence imaging was applied to follow tumour progression over time. The effect of the liver microenvironment modulated by hepatic injury on sorafenib resistance was investigated in vivo and in vitro. We found that the persistent liver injury facilitated HCC growth and metastasis, which was positively correlated with the degree of liver inflammation rather than the extent of liver fibrosis. The inflammatory cytokines in liver tissue were clearly increased after liver injury. The two indicated cytokines, tumour necrosis factor‐α (TNF‐α) and interleukin‐6 (IL‐6), both promoted intrahepatic HCC progression via STAT3 activation. In addition, the hepatic inflammatory microenvironment contributed to sorafenib resistance through the anti‐apoptotic protein mediated by STAT3, and STAT3 inhibitor S3I‐201 significantly improved sorafenib efficacy impaired by liver inflammation. Clinically, the increased inflammation of liver tissues was accompanied with the up‐regulated STAT3 activation in HCC. Above all, we concluded that the hepatic inflammatory microenvironment promotes intrahepatic HCC growth, metastasis and sorafenib resistance through activation of STAT3.

N6-methyladenosine (m6A)-mediated messenger RNA signatures and the tumor immune microenvironment can predict the prognosis of hepatocellular carcinoma

Background

N6-methyladenosine (m6A)-mediated ribonucleic acid (RNA) methylation is considered to be the most significant and abundant epigenetic modification in eukaryotic cells, and plays an essential role in the carcinogenesis and molecular pathogenesis of hepatocellular carcinoma (HCC). However, the relationship between m6A regulation and immune cell infiltration of the tumor immune microenvironment (TIME) has not yet been clarified. We aimed to investigate the roles of m6A RNA gene regulators in HCC immune regulation and prognosis.

Methods

The Cancer Genome Atlas (TCGA) database was used, and unsupervised clustering of 21 m6A regulators was performed based on differential gene expression. Gene Set Variation Analysis (GSVA), single-sample Gene Set Enrichment Analysis (ssGSEA), the empirical Bayes method, and m6A scores were used in our analyses.

Results

Of 433 samples, 101 (23.22%) had m6A regulatory factor mutations. From these, we identified three m6A subtypes, which correlated with different TIME phenotypes: immune rejection, immune infiltration, and immune deficiency. Tumors with low methyltransferase-like 3 (METTL3) expression had increased infiltration of dendritic cells (DCs) in the TIME. Reduced METTL3 expression also led to an overall increase in expression of major histocompatibility complex (MHC) molecules, costimulatory molecules, and adhesion molecules. The m6A subtypes were scored and analyzed for correlations. Patients with epithelial-mesenchymal transition (EMT) subtypes had lower m6A scores than the other three molecular subtypes. Survival analysis found that patients with low m6A scores had better overall survival [hazard ratio (HR) 1.6 (1.1–2.3)] and a 1.16 times better 5-year survival rate than patients with high m6A scores (56% vs. 48%).

Conclusions

Our results demonstrated that three different m6A modification subtypes contribute to immune regulation in HCC and have potential as novel prognostic indicators and immune therapeutic targets.

Molecular subtypes based on immune-related genes predict the prognosis for hepatocellular carcinoma patients

BACKGROUND

Hepatocellular carcinoma (HCC) is a malignancy exhibiting the highest lethality. The present study aimed to identify different immune-related clusters in HCC and a robust tumor gene signature to facilitate the prognosis prediction for HCC patients.

METHODS

For the 375 HCC cases collected from the dataset of Cancer Genome Atlas (TCGA), their overall survival (OS) and immune-related genes (IRGs) expression patterns were collected. Thereafter, consensus clustering was employed for grouping and functional enrichment, whereas the ESTIMATE algorithm and the CIBERSORT algorithm were used in subsequent assessment. Immunohistochemistry (IHC) was conducted to verify the protein expression of model genes in HCC and adjacent tissues.

RESULTS

According to consensus clustering with 93-survival related IRGs, a total of five subgroups were found. These five clusters had different prognoses, immune statuses, and expression of immune checkpoints. Afterwards, 11 genes were enrolled for constructing the OS-related prediction model for TCGA HCC cases, which was then validated using the database of International Cancer Genome Consortium (ICGC). The protein expression of LCN2, S100A10, FABP6, PLXNA1, KITLG and OXTR were enhanced in HCC tissues relative to that in normal hepatic tissues, while the protein expression of S100A1, CCL26, CMTM4, IL1RN and RARG were reduced in HCC compared with normal tissues. In addition, different immunocyte infiltration levels between low- and high- groups were further examined.

CONCLUSIONS

According to our results, the IRGs-based classifications assist in explaining the HCC heterogeneity, which may help to develop the more efficient individualized treatments.

Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma

Background

The tumor immune microenvironment is pivotal in predicting clinical outcomes and therapeutic efficacy in cancer patients. This study aims to develop an immune prediction model (IPM) to effectively predict prognosis and immunotherapeutic response in patients with hepatocellular carcinoma (HCC).

Methods

An IPM was constructed and validated based on immune-related genes. The influence of IPM on the HCC immune microenvironment, as well as the possible mechanism, was comprehensively analyzed. The value of the model in predicting the response of HCC patients to immunotherapy was also evaluated.

Results

A novel IPM based on eight genes was developed and validated to predict the prognosis of HCC patients. These genes are matrix metalloproteinase 12 (MMP12), heme oxygenase 1 (HMOX1), C-X-C motif chemokine receptor 6 (CXCR6), hepatoma-derived growth factor (HDGF), placental growth factor (PGF), tyrosine kinase 2 (TYK2), retinoid X receptor beta (RXRB), and cyclin-dependent kinase 4 (CDK4). High-risk patients showed significantly poorer survival than low-risk patients. A nomogram was also established based on the IPM and tumor, node, metastasis (TNM) classification, which showed some net clinical benefit. Gene set enrichment analysis (GSEA) revealed several significantly enriched oncological signatures and immunologic signatures. Furthermore, high-risk patients were characterized by severe clinicopathological characteristics and immune cell infiltration. Finally, we found the that the IPM showed a significant positive correlation with programmed cell death 1 (PDCD1), cluster of differentiation 274 (CD274), and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) expression, suggesting a potentially enhanced effects of immunotherapy antibodies in HCC patients with a high risk score.

Conclusions

A novel IPM that could predict clinical prognosis and immunotherapeutic response in HCC patients was developed. Our findings not only provide new insights into the identification of HCC patients with poor survival, but also deepen our understanding of the immune microenvironment, as well as the mechanism of immunotherapy, in HCC.

Development of an immune-related prognostic index associated with hepatocellular carcinoma

Liver hepatocellular carcinoma (LIHC), an inflammation-associated cancer induced by a variety of etiological factors, is still one of the most prevalent and lethal cancers in human population. In this study, the expression profiles of immune-related genes (IRGs) were integrated with the overall survival (OS) of 378 LIHC patients based on the Cancer Genome Atlas (TCGA) dataset. Moreover, the differentially expressed and survival related IRGs among LIHC patients were predicted through the computational difference algorithm and COX regression analysis. As a result, 7 genes, including HSPA4, S100A10, FABP6, CACYBP, HDAC1, FCGR2B and SHC1, were retrieved to construct a predictive model associated with the overall survival (OS) of LIHC patients. Typically, the as-constructed model performed moderately in predicting prognosis, which was also correlated with tumor grade. Functional enrichment analysis revealed that the genes of high-risk group were actively involved in mRNA binding and the spliceosome pathway. Intriguingly, the prognostic index established based on IRGs reflected infiltration by multiple types of immunocytes. Our findings screen several IRGs with clinical significance, reveal the drivers of immune repertoire, and illustrate the importance of a personalized, IRG-based immune signature in LIHC recognition, surveillance, and prognosis prediction.

Role of spleen tyrosine kinase in liver diseases

Spleen tyrosine kinase (SYK) is a non-receptor tyrosine kinase expressed in most hematopoietic cells and non-hematopoietic cells and play a crucial role in both immune and non-immune biological responses. SYK mediate diverse cellular responses via an immune-receptor tyrosine-based activation motifs (ITAMs)-dependent signalling pathways, ITAMs-independent and ITAMs-semi-dependent signalling pathways. In liver, SYK expression has been observed in parenchymal (hepatocytes) and non-parenchymal cells (hepatic stellate cells and Kupffer cells), and found to be positively correlated with the disease severity. The implication of SYK pathway has been reported in different liver diseases including liver fibrosis, viral hepatitis, alcoholic liver disease, non-alcoholic steatohepatitis and hepatocellular carcinoma. Antagonism of SYK pathway using kinase inhibitors have shown to attenuate the progression of liver diseases thereby suggesting SYK as a highly promising therapeutic target. This review summarizes the current understanding of SYK and its therapeutic implication in liver diseases.

Immune landscape of hepatocellular carcinoma microenvironment: Implications for prognosis and therapeutic applications

The development of immunotherapy for solid tumours has boosted interest in the contexture of tumour immune microenvironment (TIME). Several lines of evidence indicate that the interplay between tumour cells and TIME components is a key factor for the evolution of hepatocellular carcinoma (HCC) and for the likelihood of response to immunotherapeutics. The availability of high-resolution methods will be instrumental for a better definition of the complexity and diversity of TIME with the aim of predicting disease outcome, treatment response and possibly new therapeutic targets. Here, we review current knowledge about the immunological mechanisms involved in shaping the clinical course of HCC. Effector cells, regulatory cells and soluble mediators are discussed for their role defining TIME and as targets for immune modulation, together with possible immune signatures for optimization of immunotherapeutic strategies.

Immunogenomic landscape of hepatocellular carcinoma with immune cell stroma and EBV-positive tumor-infiltrating lymphocytes

BACKGROUND & AIMS

The immunogenomic characteristics of hepatocellular carcinomas (HCCs) with immune cell stroma (HCC-IS), defined histologically, have not been clarified. We investigated the clinical and molecular features of HCC-IS and the prognostic impact of Epstein-Barr virus (EBV) infection.

METHODS

We evaluated 219 patients with conventional HCC (C-HCC) and 47 with HCC-IS using in situ hybridization for EBV, immunohistochemistry, multiplex immunofluorescence staining, and whole exome and transcriptome sequencing. Human leukocyte antigen types were also extracted from the sequencing data. Genomic and prognostic parameters were compared between HCC-IS and C-HCC.

RESULTS

CD8 T cell infiltration was more frequent in HCC-IS than C-HCC (mean fraction/sample, 22.6% vs. 8.9%, false discovery rate q <0.001), as was EBV positivity in CD20-positive tumor-infiltrating lymphocytes (TILs) (74.5% vs. 4.6%, p <0.001). CTNNB1 mutations were not identified in any HCC-IS, while they were present in 24.1% of C-HCC (p = 0.016). Inhibitory and stimulatory immune modulators were expressed at similar levels in HCC-IS and EBV-positive C-HCC. Global hypermethylation, and expression of PD-1 and PD-L1 in TILs, and PD-L1 in tumors, were also associated with HCC-IS (p <0.001), whereas human leukocyte antigen type did not differ according to HCC type or EBV positivity. HCC-IS was an independent factor for favorable recurrence-free survival (adjusted hazard ratio [aHR] 0.23; p = 0.002). However, a subgroup of tumors with a high density of EBV-positive TILs had poorer recurrence-free (aHR 25.48; p <0.001) and overall (aHR 9.6; p = 0.003) survival, and significant enrichment of CD8 T cell exhaustion signatures (q = 0.0296).

CONCLUSIONS

HCC-IS is a distinct HCC subtype associated with a good prognosis and frequent EBV-positive TILs. However, paradoxically, a high density of EBV-positive TILs in tumors is associated with inferior prognostic outcomes. Patients with HCC-IS could be candidates for immunotherapy.

LAY SUMMARY

Hepatocellular carcinomas with histologic evidence of abundant immune cell infiltration are characterized by frequent activation of Epstein-Barr virus in tumor-infiltrating lymphocytes and less aggressive clinical behavior. However, a high density of Epstein-Barr virus-positive tumor-infiltrating lymphocytes is associated with inferior prognostic outcomes, possibly as a result of immune escape due to significant CD8 T cell exhaustion.