Tumor-Infiltrating Leukocyte Composition and Prognostic Power in Hepatitis B- and Hepatitis C-Related Hepatocellular Carcinomas

The Adaptive Immune Response in Hepatitis B Virus-Associated Hepatocellular Carcinoma Is Characterized by Dysfunctional and Exhausted HBV-Specific T Cells

This systematic review investigates the immunosuppressive environment in HBV-associated hepatocellular carcinoma (HCC), characterized by dysfunctional and exhausted HBV-specific T cells alongside an increased infiltration of HBV-specific CD4+ T cells, particularly regulatory T cells (Tregs). Heightened expression of checkpoint inhibitors, notably PD-1, is linked with disease progression and recurrence, indicating its potential as both a prognostic indicator and a target for immunotherapy. Nevertheless, using PD-1 inhibitors has shown limited effectiveness. In a future perspective, understanding the intricate interplay between innate and adaptive immune responses holds promise for pinpointing predictive biomarkers and crafting novel treatment approaches for HBV-associated HCC.

Blockade of PD-1 and CTLA-4: A potent immunotherapeutic approach for hepatocellular carcinoma

Immune checkpoints (ICPs) can promote tumor growth and prevent immunity-induced cancer cell apoptosis. Fortunately, targeting ICPs, such as programmed cell death 1 (PD-1) or cytotoxic T lymphocyte associated protein 4 (CTLA-4), has achieved great success in the past few years and has gradually become an effective treatment for cancers, including hepatocellular carcinoma (HCC). However, many patients do not respond to ICP therapy due to acquired resistance and recurrence. Therefore, clarifying the specific mechanisms of ICP in the development of HCC is very important for enhancing the efficacy of anti-PD-1 and anti-CTLA-4 therapy. In particular, antigen presentation and interferon-γ (IFN-γ) signaling were reported to be involved in the development of resistance. In this review, we have explained the role and regulatory mechanisms of ICP therapy in HCC pathology. Moreover, we have also elaborated on combinations of ICP inhibitors and other treatments to enhance the antitumor effect. Collectively, recent advances in the pharmacological targeting of ICPs provide insights for the development of a novel alternative treatment for HCC.

Prognosis and therapeutic benefits prediction based on NK cell marker genes through single-cell RNA-seq with integrated bulk RNA-seq analysis for hepatocellular carcinoma

Tumor-infiltrating immune cells greatly participate in regulating tumorigenesis and metastasis of hepatocellular carcinoma (HCC). Natural killer cell, as an important role of innate immunity, plays an indispensable role in antitumor immunity and regulate tumor development. In this study, we firstly identified 251 NK cell marker genes of HCC based on single-cell RNA sequencing data. Subsequently, an NK cell marker genes-related prognostic signature (NKPS) was developed in the cancer genome atlas (TCGA) cohort for risk stratification and prognosis prediction. The predictive value of the NKPS in prognosis was well validated in different clinical subgroups and three external datasets (ICGC-LIHC cohort, GSE14520 cohort and Guilin cohort). Moreover, multivariate analysis revealed the independent prognostic value of NKPS for OS in HCC. Further functional analysis indicated the NKPS was associated with basic cellular processes, that may contribute to the development and progression of HCC. Thereafter, immune characteristics as well as the therapeutic benefits in NKPS risk score-defined subgroups were analyzed. Patients with low-risk score exhibited immune-active status, manifested as higher immune scores, more infiltration of CD8+ T cells and macrophage M1, and higher T-cell receptor (TCR) richness and diversity. Remarkably, the NKPS was negatively correlated with immunotherapy response-related signatures. In addition, the low-risk group exhibited significantly improved therapeutic benefits, either from immunotherapy or traditional chemotherapy and target therapy. Overall, the NKPS showed an excellent predictive value for prognosis and therapeutic responses for HCC, which might also provide novel insights into better HCC management strategies.

HIF1A overexpression predicts the high lymph node metastasis risk and indicates a poor prognosis in papillary thyroid cancer

Objective

To investigate the value of Hypoxia-inducible factor 1 A (HIF1A) in predicting lymph node metastasis (LNM) stage and clinical outcomes of papillary thyroid cancer (PTC) patients.

Materials and methods

The HIF1A gene expression analysis in PTC was performed by bioinformatics approaches followed by evaluating its protein level using immunohistochemistry analysis. The role of HIF1A in predicting the LNM stage was evaluated by logistic regression analysis, nomogram construction, and receiver operating characteristic (ROC) analysis. We performed survival analyses to determine its prognostic value. Enrichment analysis was conducted, and immune cell infiltration and stromal content were evaluated to examine the underlying mechanism of HIF1A in PTC.

Results

HIF1A transcription and protein levels were significantly high in PTC tissue (P < 0.05). Its overexpression predicted high LNM risk and unfavorable prognosis for PTC patients (P < 0.05). Cox regression analysis revealed HIF1A as an independent prognostic biomarker for the disease-free interval (DFI) (P < 0.01). In addition, HIF1A was positively related to tumor-suppressive immunity but was negatively correlated with anti-tumor immunity. HIF1A upregulation was also associated with increased stromal content.

Conclusions

HIF1A overexpression is an independent predictor for worse DFI in PTC. The HIF1A expression may affect the prognosis of PTC patients through immune- and stroma-related pathways. Our study provides new insight into the role of HIF1A in PTC biology and clinical management.

Cell cycle kinases (AUKA, CDK1, PLK1) are prognostic biomarkers and correlated with tumor-infiltrating leukocytes in HBV related HCC

Hepatocellular carcinoma (HCC) is one of the high incidence cancers and third leading cause of cancer-related mortality. HBV is the top most risk factor accounting for 50-80% of the HCC cases. Kinases: Aurora kinase A (AURKA), cyclin-dependent kinase (CDK1) and Polo-like kinase 1 (PLK1), the key regulators of cell mitosis are overexpressed in varieties of cancers including HCC. However, the exact role of these genes in prognosis of HCC is not fully unveiled. In addition, there is no such an accurate prognostic biomarker for HBV-related HCC. To address this issue, we performed a multidimensional analysis of AURKA, CDK1 and PLK1 with a series of publicly available databases in multiple cancers and with experimental validation in HBV-related HCC tissues. Overexpression of AURKA, CDK1 and PLK1 was found in multiple cancers including HCC. Elevated expression of these genes could result from lowered DNA methylation and genomic alterations. Transcriptional overexpression was significantly correlated with poor prognosis of HCC patients. The expression levels were also significantly positively associated with tumor grades and stages. Furthermore, the expression levels of these genes had a strong correlation with infiltration of immune cells. Our analysis shows that AURKA, CDK1 and PLK1 are correlated with immune infiltration and are the prognostic biomarkers for HBV-induced HCC.Communicated by Ramaswamy H. Sarma.

A more novel and powerful prognostic gene signature of lung adenocarcinoma determined from the immune cell infiltration landscape

Background

Lung adenocarcinoma (LUAD) is the leading histological subtype of lung cancer worldwide, causing high mortality each year. The tumor immune cell infiltration (ICI) is closely associated with clinical outcome with LUAD patients. The present study was designed to construct a gene signature based on the ICI of LUAD to predict prognosis.

Methods

Downloaded the raw data of three cohorts of the TCGA-LUAD, GSE72094, and GSE68465 and treat them as training cohort, validation cohort one, and validation cohort two for this research. Unsupervised clustering detailed grouped LUAD cases of the training cohort based on the ICI profile. The univariate Cox regression and Kaplan-Meier was adopted to identify potential prognostic genes from the differentially expressed genes recognized from the ICI clusters. A risk score-based prognostic signature was subsequently developed using LASSO-penalized Cox regression analysis. The Kaplan-Meier analysis, Cox analysis, ROC, IAUC, and IBS were constructed to assess the ability to predict the prognosis and effects of clinical variables in another two independent validation cohorts. More innovatively, we searched similar papers in the most recent year and made comprehensive comparisons with ours. GSEA was used to discover the related signaling pathway. The immune relevant signature correlation identification and immune infiltrating analysis were used to evaluate the potential role of the signature for immunotherapy and recognize the critical immune cell that can influence the signature's prognosis capability.

Results

A signature composed of thirteen gene including ABCC2, CCR2, CERS4, CMAHP, DENND1C, ECT2, FKBP4, GJB3, GNG7, KRT6A, PCDH7, PLK1, and VEGFC, was identified as significantly associated with the prognosis in LUAD patients. The thirteen-gene signature exhibited independence in evaluating the prognosis of LUAD patients in our training and validation cohorts. Compared to our predecessors, our model has an advantage in predictive power. Nine well know immunotherapy targets, including TBX2, TNF, CTLA4, HAVCR2, GZMB, CD8A, PRF1, GZMA, and PDCD1 were recognized correlating with our signature. The mast cells were found to play vital parts in backing on the thirteen-gene signature's outcome predictive capacity.

Conclusions

Collectively, the current study indicated a robust thirteen-gene signature that can accurately predict LUAD prognosis, which is superior to our predecessors in predictive ability. The immune relevant signatures, TBX2, TNF, CTLA4, HAVCR2, GZMB, CD8A, PRF1, GZMA, PDCD1, and mast cells infiltrating were found closely correlate with the thirteen-gene signature's power.

A novel fatty acid metabolism-related gene signature predicts the prognosis, tumor immune properties, and immunotherapy response of colon adenocarcinoma patients

Colon adenocarcinoma (COAD) has a high incidence and death rate. Despite the fact that change in fatty acid metabolism promotes tumor growth and metastasis to the greatest degree among metabolite profiles, a thorough investigation on the involvement of fatty acid metabolism-related genes (FAMRGs) in COAD has yet not been conducted. Here, the clinical data as well as the gene expression profiles were extracted from The Cancer Genome Atlas (TCGA) database. Based on the FAMRG expression data and clinical information, a FAMRG risk signature was developed using LASSO as well as multivariate and univariate Cox regression analyses. Then, the nomogram was used to create a customized prognostic prediction model, and the calibration and receiver operating characteristic curves were used to evaluate the nomogram's prediction performance and discriminative capability. Lastly, a number of studies were conducted to assess the influence of independent FAMRGs on COAD, including unsupervised cluster analysis, functional analysis, and drug sensitivity analysis. Three hundred and sixty-seven patients were included in this study, and a 12-FAMRG risk signature was discovered in the training cohort based on a detailed examination of the FAMRGs expression data and clinical information. After that, risk scores were computed to classify patients into low or high-risk groups, and the Kaplan-Meier curve analysis revealed that patients in the low-risk group exhibited an elevated overall survival (OS) rate. The FAMRG was shown to be substantially correlated with prognosis in multivariate Cox regression analysis and was validated using the validation dataset. Then, using the clinical variables and risk signature, we developed and validated a prediction nomogram for OS. Functional characterization showed a strong correlation between this signature and immune cell infiltration and immune modulation. Additionally, by evaluating the GDSC database, it was determined that the high-risk group exhibited medication resistance to many chemotherapeutic and targeted medicines, including VX.680, gemcitabine, doxorubicin, and paclitaxel. Overall, we have revealed the significance of a FAMRG risk signature for predicting the prognosis and response to immunotherapy in COAD, and our findings might contribute to an enhanced comprehension of metabolic pathways and the future development of innovative COAD therapeutic methods.

CTNNB1 mutations, TERT polymorphism and CD8+ cell densities in resected hepatocellular carcinoma are associated with longer time to recurrence

Background

Hepatocellular carcinoma (HCC) is a fatal disease characterized by early genetic alterations in telomerase reverse transcriptase promoter (TERTp) and β-catenin (CTNNB1) genes and immune cell activation in the tumor microenvironment. As a novel approach, we wanted to assess patient survival influenced by combined presence of mutations and densities of CD8+ cytotoxic T cells.

Methods

Tissue samples were obtained from 67 HCC patients who had undergone resection. We analysed CD8+ T cells density, TERTp mutations, rs2853669 polymorphism, and CTNNB1 mutations. These variables were evaluated for time to recurrence (TTR) and disease free survival (DFS).

Results

TERTp mutations were found in 75.8% and CTNNB1 mutations in 35.6% of the patients. TERTp mutations were not associated with survival but polymorphism rs2853669 in TERTp was associated with improved TTR and DFS. CTNNB1 mutations were associated with improving TTR. High density of CD8+ T-lymphocytes in tumor center and invasive margin correlated with longer TTR and DFS. Combined genetic and immune factors further improved survival showing higher predictive values. E.g., combining CTNNB1 mutations and high density of CD8+ T-lymphocytes in tumor center yielded HRs of 0.12 (0.03–0.52), p = 0.005 for TTR and 0.25 (0.09–0.74), p = 0.01 for DFS.

Conclusion

The results outline a novel integrative approach for prognostication through combining independent predictive factors from genetic and immune cell profiles. However, larger studies are needed to explore multiple cell types in the tumor microenvironment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09989-0.

A single-cell atlas of the multicellular ecosystem of primary and metastatic hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents a paradigm of the relation between tumor microenvironment (TME) and tumor development. Here, we generate a single-cell atlas of the multicellular ecosystem of HCC from four tissue sites. We show the enrichment of central memory T cells (T_CM) in the early tertiary lymphoid structures (E-TLSs) in HCC and assess the relationships between chronic HBV/HCV infection and T cell infiltration and exhaustion. We find the MMP9⁺ macrophages to be terminally differentiated tumor-associated macrophages (TAMs) and PPARγ to be the pivotal transcription factor driving their differentiation. We also characterize the heterogeneous subpopulations of malignant hepatocytes and their multifaceted functions in shaping the immune microenvironment of HCC. Finally, we identify seven microenvironment-based subtypes that can predict prognosis of HCC patients. Collectively, this large-scale atlas deepens our understanding of the HCC microenvironment, which might facilitate the development of new immune therapy strategies for this malignancy.

The immune cell constituents and localisation within human hepatocellular carcinoma is not fully understood. Here the authors use single cell RNA sequencing of HCC from four different tissue sites and show differences between primary and metastatic tumours, tumour associated macrophages and immune cell populations.

Prediction of Prognosis and Molecular Mechanism of Ferroptosis in Hepatocellular Carcinoma Based on Bioinformatics Methods

BACKGROUND

As an iron-dependent type of programmed cell death, ferroptosis plays an important role in the pathogenesis and progression of hepatocellular carcinoma (HCC). Long noncoding RNAs (lncRNAs) have been linked to the prognosis of patients with HCC in a number of studies. Nevertheless, the predictive value of lncRNAs (FRLs) associated with ferroptosis in HCC has not been fully elucidated.

METHODS

Download RNA sequencing data and clinical profiles of HCC patients from The Cancer Genome Atlas (TCGA) database. The FRLs associated with prognosis were determined by Pearson's correlation analysis. After that, prognostic signature for FRLs was established using Cox and LASSO regression analyses. Meanwhile, survival analysis, correlation analysis of clinicopathological features, Cox regression, receiver operating characteristic (ROC) curve, and nomogram were used to analyze the FRL signature's predictive capacity. The relationship between signature risk score, immune cell infiltration, and chemotherapy drug sensitivity is further studied.

RESULTS

In total, 93 FRLs were found to be of prognostic value in patients with HCC. A five-FRL signature comprising AC015908.3, LINC01138, AC009283.1, Z83851.1, and LUCAT1 was created in order to enhance the prognosis prediction with HCC patients. The signature demonstrated a good predictive potency, according to the Kaplan-Meier and ROC curves. The five-FRL signature was found to be a risk factor independent of various clinical factors using Cox regression and stratified survival analysis. The high-risk group was shown to be enriched in tumorigenesis and immune-related pathways according to GSEA analysis. Additionally, immune cell infiltration, immune checkpoint molecules, and half-inhibitory concentrations differed considerably between risk groups, implying that this signature could be used to evaluate the clinical efficacy of chemotherapy and immunotherapy.

CONCLUSION

The five-FRL risk signature is helpful for assessing the prognosis of HCC patients and improving therapy options, so it can be further applied clinically.

Analyzing Prognostic Hub Genes in the Microenvironment of Cutaneous Melanoma by Computer Integrated Bioinformatics

Cutaneous melanoma (CM) is attracting increasing attention due to high mortality. In response to this, we synthetically analyze the CM dataset from the TCGA database and explore microenvironment-related genes that effectively predict patient prognosis. Immune/stromal scores of cases are calculated using the ESTIMATE algorithm and are significantly associated with overall patient survival. Then, differentially expressed genes are identified by comparing the immune score and stromal score, also prognostic genes are subsequently screened. Functional analysis shows that these genes are enriched in different activities of immune system. Moreover, 19 prognosis-related hub genes are extracted from the protein-protein interaction network, of which four unreported genes (IL7R, FLT3, C1QC, and HLA-DRB5) are chosen for validation. A significant negative relationship is found between the expression levels of the 4 genes and pathological stages, notably T grade. Furthermore, the K-M plots and TIMER results show that these genes have favorable value for CM prognosis. In conclusion, these results give a novel insight into CM and identify IL7R, FLT3, C1QC, and HLA-DRB5 as crucial roles for the diagnosis and treatment of CM.

Evaluating tumor-infiltrating lymphocytes in hepatocellular carcinoma using hematoxylin and eosin-stained tumor sections

BACKGROUND

Tumor-infiltrating lymphocytes (TILs) constitute a prognostic factor in hepatocellular carcinoma (HCC). However, different methods of assessing TILs have various pre-analytical, analytical, and post-analytical challenges. The evaluation of TILs in hematoxylin and eosin (H&E)-stained tumor sections proposed by the International Immuno-Oncology Biomarker Working Group was demonstrated to be a reproducible, affordable and easily applied method in many tumors.

AIM

To evaluate the prognostic significance of TILs in H&E-stained slides of HCCs.

METHODS

This was a retrospective study performed in the hospital. HCC patients who underwent liver resection between 2015 and 2017 in Zhongshan Hospital were enrolled in this study. Patients who experienced recurrence or received therapy in addition to antiviral therapy before surgery at this time were excluded. A total of 204 patients were enrolled in the study. The ILs were counted manually in tumor sections stained with H&E under an optical microscope at 400 ×. The ILs were assessed separately in the center of the tumor (TILs^CT), the invasive front (TILs^IF), and peritumor (PILs) areas. Univariate and multivariate survival analyses were performed using a Cox regression model. P < 0.05 was considered statistically significant and all P-values were two-sided.

RESULTS

Among the 204 patients, univariate analysis indicated that macrovascular invasion (MaVI) (P = 0.001), microvascular invasion (MVI) (P = 0.012), multiple tumors (P = 0.008), large tumors (> 10 cm) (P = 0.001), absence of a tumor capsule (P = 0.026), macrotrabecular histological subtype (P = 0.001), low density of TILs^CT (P = 0.039), TILs^IF (P = 0.014), and PILs (P = 0.010) were predictors of progression-free survival (PFS). Cox multivariate analysis indicated that MaVI (P = 0.009), absence of a tumor capsule (P = 0.031), low-density of TILs^IF (P = 0.047) and PILs (P = 0.0495) were independent predictors of PFS. A three-category analysis was carried out by combining TILs^CT, TILs^IF, and PILs, after which HCCs were classified into immune^high [(TILs^CT)^high, (TILs^IF)^high, and PILs^high, 83 cases], immune^mod (tumors other than immune^high and immune^low subtypes, 94 cases), and immune^low [(TILs^CT)^low, (TILs^IF)^low, and PILs^low, 27 cases)] subtypes. The immune^high subtype had a lower rate of MVI (40.96%) than the immune^mod (61.70%, P = 0.017) and immune^low (66.67%, P = 0.020) subtypes. The recurrence rates of the immune^high, immune^mod and immune^low subtypes were 10.8%, 25.5% and 33.3%, respectively.

CONCLUSION

HCC patients with high infiltrating lymphocytes tend to have a lower recurrence rate and less MVI. The evaluation of TILs in H&E-stained specimens could be a prognostic parameter for HCC.

Identification and Validation of a Nine-Gene Amino Acid Metabolism-Related Risk Signature in HCC

Background: Hepatocellular carcinoma (HCC) is the world’s second most deadly cancer, and metabolic reprogramming is its distinguishing feature. Among metabolite profiling, variation in amino acid metabolism supports tumor proliferation and metastasis to the most extent, yet a systematic study on the role of amino acid metabolism-related genes in HCC is still lacking. An effective amino acid metabolism-related prediction signature is urgently needed to assess the prognosis of HCC patients for individualized treatment.

Materials and Methods: RNA-seq data of HCC from the TCGA-LIHC and GSE14520 (GPL3921) datasets were defined as the training set and validation set, respectively. Amino acid metabolic genes were extracted from the Molecular Signature Database. Univariate Cox and LASSO regression analyses were performed to build a predictive risk signature. K-M curves, ROC curves, and univariate and multivariate Cox regression were conducted to evaluate the predictive value of this risk signature. Functional enrichment was analyzed by GSEA and CIBERSORTx software.

Results: A nine-gene amino acid metabolism-related risk signature including B3GAT3, B4GALT2, CYB5R3, GNPDA1, GOT2, HEXB, HMGCS2, PLOD2, and SEPHS1 was constructed to predict the overall survival (OS) of HCC patients. Patients were separated into high-risk and low-risk groups based on risk scores and low-risk patients had lower risk scores and longer survival time. Univariate and multivariate Cox regression verified that this signature was an independent risk factor for HCC. ROC curves showed that this risk signature can effectively predict the 1-, 2-, 3- and 5-year survival times of patients with HCC. Additionally, prognostic nomograms were established based on the training set and validation set. These genes were closely correlated with the immune regulation.

Conclusion: Our study identified a nine-gene amino acid metabolism-related risk signature and built predictive nomograms for OS in HCC. These findings will help us to personalize the treatment of liver cancer patients.

Characterization of the Tumor Immune Microenvironment Identifies M0 Macrophage-Enriched Cluster as a Poor Prognostic Factor in Hepatocellular Carcinoma

PURPOSE

Hepatocellular carcinoma (HCC) is characterized by a poor prognosis and a high recurrence rate. The tumor immune microenvironment in HCC has been characterized as shifted toward immunosuppression. We conducted a genomic data-driven classification of immune microenvironment HCC subtypes. In addition, we demonstrated their prognostic value and suggested a potential therapeutic targeting strategy.

METHODS

RNA sequencing data from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma was used (n = 366). Abundance of immune cells was imputed using CIBERSORT and visualized using unsupervised hierarchic clustering. Overall survival (OS) was analyzed using Kaplan-Meier estimates and Cox regression. Differential expression and gene set enrichment analyses were conducted on immune clusters with poor OS and high programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) coexpression. A scoring metric combining differentially expressed genes and immune cell content was created, and its prognostic value and immune checkpoint blockade response prediction was evaluated.

RESULTS

Two clusters were characterized by macrophage enrichment, with distinct M0^Hi and M2^Hi subtypes. M2^Hi (P = .038) and M0^Hi (P = .018) were independently prognostic for OS on multivariable analysis. Kaplan-Meier estimates demonstrated that patients in M0^Hi and M2^Hi treated with sorafenib had decreased OS (P = .041), and angiogenesis hallmark genes were enriched in the M0^Hi group. CXCL6 and POSTN were overexpressed in both the M0^Hi and the PD-1^Hi/PD-L1^Hi groups. A score consisting of CXCL6 and POSTN expression and absolute M0 macrophage content was discriminatory for OS (intermediate: hazard ratio [HR], 1.59; P ≤ .001; unfavorable: HR, 2.08; P = .04).

CONCLUSION

Distinct immune cell clusters with macrophage predominance characterize an aggressive HCC phenotype, defined molecularly by angiogenic gene enrichment and clinically by poor prognosis and sorafenib response. This novel immunogenomic signature may aid in stratification of unresectable patients to receive checkpoint inhibitor and antiangiogenic therapy combinations.

Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis.

Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER).

Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine–cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration.

Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.

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.

Regulatory T cell and activated natural killer cell infiltration in hepatocellular carcinoma: immune cell profiling using the CIBERSORT

BACKGROUND

Hepatocellular carcinoma (HCC) is understood to be an immunogenic tumor caused by chronic liver disease. Emerging research has indicated close interaction between various immune cells and tumor cells. Immunophenotyping, which has shown potential predictive value for the prognosis of various human malignancies, might allow responsive and non-responsive patients to be identified based on the extent and distribution of immune cell infiltration. Several novel immunotherapeutic approaches have been trialed and have shown promising efficacy. However, the efficacy of immunotherapies in HCC is limited by several factors. This study aimed to investigate tumor-infiltrating immune cells in HCC.

METHODS

Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) allows immune cell profiling analysis by deconvolution of gene expression microarray data. In this study, we analyzed the proportions of immune cells in 14 paired samples of HCC tissues obtained from GSE84402 in Gene Expression Omnibus (GEO) database.

RESULTS

In the 14 paired samples, HCC tissues showed significant infiltration by regulatory T cells (Tregs), activated natural killer (NK) cells, and M0 macrophages (P<0.001, P=0.007 and P=0.001, respectively), which were validated in CIBERSORT with the P value set at ≤0.05. In four paired samples identified from those selected by CIBERSORT, HCC tissues were found to have significant Treg and activated NK cell infiltration compared to non-tumor tissues (P=0.007 and P=0.015, respectively). Additionally, Pearson correlation analysis revealed Tregs to be positively correlated with activated NK cells (Correlation coefficient =0.41).

CONCLUSIONS

HCC tumor tissues were markedly infiltrated by Tregs and activated NK cells, which should be considered as candidate therapeutic targets in HCC multidisciplinary treatments.

Nicotinamide N-Methyltransferase Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Gastric Cancer

Gastric cancer (GC) is the third most common cause of cancer-related death in the word. Immunotherapy is a promising treatment of cancer. However, it is unclear which GC subpopulation would benefit most from immunotherapy and it is necessary to develop effective biomarkers for predicting immunotherapy response. Nicotinamide N-methyltransferase (NNMT) is a metabolic regulator of cancer-associated fibroblast (CAF) differentiation and cancer progression. In this study, we explored the correlations of NNMT to tumor-infiltrating immune cells (TIICs) and immune marker sets in The Cancer Genome Atlas Stomach Adenocarcinoma STAD (TCGA-STAD). Subsequently, we screened the NNMT correlated genes and performed the enrichment analysis of these genes. We eventually predicted the 19 most potential small-molecule drugs using the connectivity map (CMap) and Comparative Toxicogenomics Database (CTD). Also, nadolol, tranexamic acid, felbinac and dapsone were considered the four most promising drugs for GC. In summary, NNMT can be used as a prognostic biomarker that reflect immune infiltration level and a novel therapeutic target in GC.

Evaluating Distribution and Prognostic Value of New Tumor-Infiltrating Lymphocytes in HCC Based on a scRNA-Seq Study With CIBERSORTx

Hepatocellular carcinoma (HCC) is a commonly diagnosed cancer with high mortality rates. The immune response plays an important role in the progression of HCC. Immunotherapies are becoming an increasingly promising tool for treating cancers. Advancements in scRNA-seq (single-cell RNA sequencing) have allowed us to identify new subsets in the immune microenvironment of HCC. Yet, distribution of these new cell types and their potential prognostic value in bulk samples from large cohorts remained unclear. This study aimed to investigate the tumor-infiltration and prognostic value of new cell subsets identified by a previous scRNA-seq study in a TCGA HCC cohort using CIBERSORTx, a machine learning method to estimate cell proportion and infer cell-type-specific gene expression profiles. We observed different distributions of tumor-infiltrating lymphocytes between tumor and normal cells. Among these, the CD4-GZMA cell subset showed association with prognosis (log-rank test, p < 0.05). We further analyzed CD4-GZMA cell specific gene expression with CIBERSORTx, and found 19 prognostic genes (univariable cox regression, p < 0.05). Finally, we applied Least absolute shrinkage and selection operator (LASSO) Cox regression to construct an immune risk score model and performed a prognostic assessment of our model in TCGA and ICGC cohorts. Taken together, the immune landscape in HCC bulk samples may be more complex than assumed, with heterogeneity and different tumor-infiltration relative to scRNA-seq results. Additionally, CD4-GZMA cells and their characteristics may yield therapeutic benefits in the immune treatment of HCC.

Hepatocellular Carcinoma-The Influence of Immunoanatomy and the Role of Immunotherapy

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related morbidity and mortality worldwide. Most patients are diagnosed with advanced disease, limiting their options for treatment. While current treatments are adequate for lower staged disease, available systemic treatments are limited, with marginal benefit at best. Chimeric antigen receptor (CAR) T cell therapy, effective in treating liquid tumors such as B-cell lymphoma, presents a potentially promising treatment option for advanced HCC. However, new challenges specific to solid tumors, such as tumor immunoanatomy or the immune cell presence and position anatomically and the tumor microenvironment, need to be defined and overcome. Immunotherapy currently in use must be re-engineered and re-envisioned to treat HCC with the hopes of ushering in an answer to advanced stage solid tumor disease processes. Future therapy options must address the uniqueness of the tumors under the umbrella of HCC. This review strives to summarize HCC, its staging system, current therapy and immunotherapy medications currently being utilized or studied in the treatment of HCC with the hopes of highlighting what is being done and suggesting what needs to be done in the future to champion this therapy as an effective option.

Prognostic Value of Complement Component 2 and Its Correlation with Immune Infiltrates in Hepatocellular Carcinoma

BACKGROUND

Single nucleotide polymorphism (SNP) of complement component 2 (C2) has been found to be significantly associated with hepatocellular carcinoma (HCC). However, little is known about the role and mechanism of C2 in HCC. In the present study, we aimed to explore the prognostic value of C2 and its correlation with tumor-infiltrating immune cells in HCC.

MATERIALS AND METHODS

mRNA expression was downloaded from TCGA (365 HCC patients and 50 healthy controls), GSE14520 (220 HCC patients and 220 adjacent normal tissues), and ICGC HCC (232 HCC patients) cohorts. Unpaired Student's t-tests or ANOVA tests were used to evaluate differences of C2 expression. Univariate and multivariate analyses were used to analyze the prognostic value of C2. CIBERSORT was used to calculate the proportion of 22 kinds of tumor-infiltrating immune cells.

RESULTS

Significantly lower C2 expression was found at HCC compared to healthy controls, and C2 was associated with TNM stages. Higher C2 expression was significantly associated with better prognosis, and multivariate analysis showed that C2 was also an independent factor for the prognosis of HCC. Moreover, elevated CD4 T cells were found at HCC patients with higher C2 expression while the higher proportion of macrophage M0 cells was found in HCC patients with lower C2 expression. KEGG analysis showed that "cell cycle," "AMPK signaling pathway," and "PPAR signaling pathway" were enriched in HCC patients with higher C2 expression.

CONCLUSION

C2 is a prognostic factor for HCC and may be used as a therapeutic target for future treatment of HCC.

Exploration of the molecular characteristics of the tumor-immune interaction and the development of an individualized immune prognostic signature for neuroblastoma

Neuroblastoma (NBL) exists in a complex tumor-immune microenvironment. Immune cell infiltration and tumor-immune molecules play a critical role in tumor development and significantly impact the prognosis of patients. However, the molecular characteristics describing the NBL-immune interaction and their prognostic potential have yet to be investigated systematically. We first employed multiple machine learning algorithms, such as Gene Sets Enrichment Analysis and cell type identification by estimating relative subsets of RNA transcripts, to identify immunophenotypes and immunological characteristics in NBL patient data from public databases and then investigated the prognostic potential and regulatory networks of identified immune-related genes involved in the NBL-immune interaction. The immunity signature combining nine immunity genes was confirmed as more effective for individual risk stratification and survival outcome prediction in NBL patients than common clinical characteristics (area under the curve [AUC] = 0.819, C-index = 0.718, p < .001). A mechanistic exploration revealed the regulatory network of molecules involved in the NBL-immune interaction. These immune molecules were also discovered to possess a significant correlation with plasma cell infiltration, MYCN status, and the level of chemokines and macrophage-related molecules (p < .001). A nomogram was constructed based on the immune signature and clinical characteristics, which showed high potential for prognosis prediction (AUC = 0.856, C-index = 0.755, p < .001). We systematically elucidated the complex regulatory mechanisms and characteristics of the molecules involved in the NBL-immune interaction and their prognostic potential, which may have important implications for further understanding the molecular mechanism of the NBL-immune interaction and identifying high-risk NBL patients to guide clinical treatment.

Anti-PD-1/PD-L1 Blockade Immunotherapy Employed in Treating Hepatitis B Virus Infection-Related Advanced Hepatocellular Carcinoma: A Literature Review

Hepatitis B virus (HBV) infection is regarded as the main etiological risk factor in the process of hepatocellular carcinoma (HCC), as it promotes an immunosuppressive microenvironment that is partially mediated by the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) signaling pathway. The tumor microenvironment (TME) of HBV-related HCC is indeed more immunosuppressive than microenvironments not associated with viruses. And compared to TME in hepatitis C virus (HCV) infected HCC, TME of HBV-related HCC is less vascularized and presents different immune components resulting in similar immunosuppression. However, few studies are focusing on the specific side effects and efficacy of PD-1/PD-L1 blockade immunotherapy in HBV-related HCC patients, as well as on the underlying mechanism. Herein, we reviewed the basic research focusing on potential TME alteration caused by HBV infection, especially in HCC patients. Moreover, we reviewed PD-1/PD-L1 blockade immunotherapy clinical trials to clarify the safety and efficacy of this newly developed treatment in the particular circumstances of HBV infection. We found that patients with HBV-related HCC displayed an acceptable safety profile similar to those of non-infected HCC patients. However, we could not determine the antiviral activity of PD-1/PD-L1 blockade because standard anti-viral therapies were conducted in all of the current clinical trials, which made it difficult to distinguish the potential influence of PD-1/PD-L1 blockade on HBV infection. Generally, the objective response rates (ORRs) of PD-1/PD-L1 blockade immunotherapy did not differ significantly between virus-positive and virus-negative patients, except that disease control rates (DCRs) were obviously lower in HBV-infected HCC patients.

Viral Hepatitis and Iron Dysregulation: Molecular Pathways and the Role of Lactoferrin

The liver is a frontline immune site specifically designed to check and detect potential pathogens from the bloodstream to maintain a general state of immune hyporesponsiveness. One of the main functions of the liver is the regulation of iron homeostasis. The liver detects changes in systemic iron requirements and can regulate its concentration. Pathological states lead to the dysregulation of iron homeostasis which, in turn, can promote infectious and inflammatory processes. In this context, hepatic viruses deviate hepatocytes' iron metabolism in order to better replicate. Indeed, some viruses are able to alter the expression of iron-related proteins or exploit host receptors to enter inside host cells. Lactoferrin (Lf), a multifunctional iron-binding glycoprotein belonging to the innate immunity, is endowed with potent antiviral activity, mainly related to its ability to block viral entry into host cells by interacting with viral and/or cell surface receptors. Moreover, Lf can act as an iron scavenger by both direct iron-chelation or the modulation of the main iron-related proteins. In this review, the complex interplay between viral hepatitis, iron homeostasis, and inflammation as well as the role of Lf are outlined.

Innovating Computational Biology and Intelligent Medicine: ICIBM 2019 Special Issue

The International Association for Intelligent Biology and Medicine (IAIBM) is a nonprofit organization that promotes intelligent biology and medical science. It hosts an annual International Conference on Intelligent Biology and Medicine (ICIBM), which was established in 2012. The ICIBM 2019 was held from 9 to 11 June 2019 in Columbus, Ohio, USA. Out of the 105 original research manuscripts submitted to the conference, 18 were selected for publication in a Special Issue in Genes. The topics of the selected manuscripts cover a wide range of current topics in biomedical research including cancer informatics, transcriptomic, computational algorithms, visualization and tools, deep learning, and microbiome research. In this editorial, we briefly introduce each of the manuscripts and discuss their contribution to the advance of science and technology.

Combined signature of nine immune-related genes: a novel risk score for predicting prognosis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common internal malignancies worldwide and is associated with a poor prognosis. There is an urgent need to identify diagnostic and prognostic biomarkers of HCC pathogenesis and progression. Accordingly, in this study, we analyzed differentially expressed immune-related genes (IRGs) from 329 patients with HCC from The Cancer Genome Atlas datasets. Functional analysis revealed that the IRGs had potential effects on tumor immune processes, such as inflammatory responses and growth factor activity. In the training group, we constructed a nine-IRG formula to predict prognosis in patients with HCC. To validate the protein and mRNA levels of these IRGs, we used the Human Protein Atlas database and quantitative PCR analysis and found that most protein expression levels matched the corresponding mRNA expression levels. Furthermore, we also validated the prognostic value of the new risk model in another independent cohort (n = 277) from a Gene Expression Omnibus dataset (GSE14520). Our data suggested that there was a significant association between our risk model and patient prognosis. Stratification analysis showed that the nine-IRG signature was significantly associated with overall survival in men. Finally, the signature was found to be correlated with various clinicopathological features. Intriguingly, the prognostic index based on the IRGs reflected infiltration by several types of immune cells. In summary, our data provided evidence that the nine-IRG signature could serve as an independent biomarker to predict prognosis in patients with HCC.