Identification of Gene-Set Signature in Early-Stage Hepatocellular Carcinoma and Relevant Immune Characteristics

BackgroundThe incidence of hepatocellular carcinoma (HCC) is rising worldwide, and there is limited therapeutic efficacy due to tumor microenvironment heterogeneity and difficulty in early-stage screening. This study aimed to develop and validate a gene set-based signature for early-stage HCC (eHCC) patients and further explored specific marker dysregulation mechanisms as well as immune characteristics.MethodsWe performed an integrated bioinformatics analysis of genomic, transcriptomic, and clinical data with three independent cohorts. We systematically reviewed the crosstalk between specific genes, tumor prognosis, immune characteristics, and biological function in the different pathological stage samples. Univariate and multivariate survival analyses were performed in The Cancer Genome Atlas (TCGA) patients with survival data. Diethylnitrosamine (DEN)-induced HCC in Wistar rats was employed to verify the reliability of the predictions.ResultsWe identified a Cluster gene that potentially segregates patients with eHCC from non-tumor, through integrated analysis of expression, overall survival, immune cell characteristics, and biology function landscapes. Immune infiltration analysis showed that lower infiltration of specific immune cells may be responsible for significantly worse prognosis in HCC (hazard ratio, 1.691; 95% CI: 1.171–2.441; p = 0.012), such as CD8 Tem and cytotoxic T cells (CTLs) in eHCC. Our results identified that Cluster C1 signature presented a high accuracy in predicting CD8 Tem and CTL immune cells (receiver operating characteristic (ROC) = 0.647) and cancerization (ROC = 0.946) in liver. As a central member of Cluster C1, overexpressed PRKDC was associated with the higher genetic alteration in eHCC than advanced-stage HCC (aHCC), which was also connected to immune cell-related poor prognosis. Finally, the predictive outcome of Cluster C1 and PRKDC alteration in DEN-induced eHCC rats was also confirmed.ConclusionsAs a tumor prognosis-relevant gene set-based signature, Cluster C1 showed an effective approach to predict cancerization of eHCC and its related immune characteristics with considerable clinical value.

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Uncovering of the Association Between m5C Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

10.21203/rs.3.rs-580707/v1 ◽

2021 ◽

Author(s):

Xinyu Gu ◽

Haibo Zhou ◽

Qingfei Chu ◽

Qiuxian Zheng ◽

Jing Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cells ◽

Immune Cell ◽

Enrichment Analysis ◽

Tumour Microenvironment ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Gene Set ◽

Normal Tissues

Abstract Background: 5-Methylcytosine (m5C) plays essential roles in hepatocellular carcinoma (HCC), but the association between m5C regulation and immune cell infiltration in HCC has not yet been clarified.Methods: In this study, we analysed 371 patients with HCC from The Cancer Genome Atlas (TCGA) database, and the expression of 13 m5C regulators was investigated. Additionally, gene set variation analysis (GSVA), unsupervised clustering analysis, single-sample gene set enrichment analysis (ssGSEA), correlation analysis, and immunohistochemical (IHC) staining were performed.Results: Among the 371 patients, 41 had mutations in m5C regulators, the frequency of which was 11.26%. Then, we identified three m5C modification patterns that had obvious tumour microenvironment (TME) cell infiltration characteristics. Cluster-1 had an immune rejection phenotype; Cluster-2 had an immunoinflammatory phenotype; and Cluster-3 had an immune desert phenotype. In addition, we found that DNMT1 was highly expressed in tumour tissues compared with normal tissues in a tissue microarray (TMA) and that it was positively correlated with many TME-infiltrating immune cells. High expression of the m5C regulator DNMT1 was related to a poor prognosis in patients with HCC. Furthermore, we developed three Immu-clusters that were consistent with the immune characteristics of the m5C methylation modification patterns. We also discovered differences in the levels of immune cells and expression of chemokines and cytokines among the three Immu-clusters.Conclusions: Our work revealed the association between m5C modification and immune regulators in the TME. These findings also suggest that DNMT1 has great potential as a prognostic biomarker and therapeutic target for HCC.

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A dual immune signature of CD8+ T Cells and MMP9 improves the survival of hepatocellular carcinoma patients

Bioscience Reports ◽

10.1042/bsr20204219 ◽

2021 ◽

Author(s):

Huan Ding ◽

Huan Hu ◽

Feifei Tian ◽

Huaping Liang

Keyword(s):

Hepatocellular Carcinoma ◽

T Cells ◽

Cd8 T Cells ◽

Immune Cells ◽

Immune Cell ◽

Cox Regression ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

High Recurrence Rate ◽

Immune Signature

The 5-year survival of hepatocellular carcinoma (HCC) is difficult due to the high recurrence rate and metastasis. Tumor infiltrating immune cells (TICs) and immune-related genes (IRGs) bring hope to improve survival and treatment of HCC patients. However, there are problems in predicting immune signatures and identifying novel therapeutic targets. In the study, the CIBERSORT algorithm was used to evaluate 22 immune cell infiltration patterns in gene expression omnibus (GEO) and the cancer genome atlas (TCGA) data. Eight immune cells were found to have significant infiltration differences between the tumor and normal groups. The CD8+ T Cells immune signature was constructed by least absolute shrinkage and selection operator (LASSO) algorithm. The high infiltration level of CD8+ T Cells could significantly improve survival of patients. The weighted gene co-expression network analysis (WGCNA) algorithm identified MMP9 was closely related to the overall survival of HCC patients. K-M survival and tROC analysis confirmed that MMP9 had an excellent prognostic prediction. Cox regression showed that a dual immune signature of CD8+ T Cells and MMP9 was independent survival factor in HCC. Therefore, a dual prognostic immune signature could improve the survival of patient and may provide a new strategy for the immunotherapy of HCC.

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Exploration of the regulatory mechanism for hepatocellular carcinoma based on ceRNA networks analysis and immune infiltration

10.21203/rs.3.rs-885697/v1 ◽

2021 ◽

Author(s):

Ning Huang ◽

Qiang Chen ◽

Xiaoyi Wang

Keyword(s):

Hepatocellular Carcinoma ◽

T Cells ◽

Network Analysis ◽

Correlation Analysis ◽

Immune Cells ◽

Regulatory Mechanism ◽

Immune Cell ◽

Risk Model ◽

The Cancer Genome Atlas ◽

Ppi Network

Abstract Background Hepatocellular carcinoma (HCC) as malignant cancer has been deeply investigated for its widespread distribution and extremely high mortality rate worldwide. Despite efforts to understand the regulatory mechanism in HCC, it remains largely unknown. Methods The RNA (mRNAs, lncRNAs, and miRNAs) profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Based on the Weighted Gene Co-expression Network Analysis (WGCNA), the hub differentially expressed RNAs (DERNAs) were screened out. The competing endogenous RNA (ceRNA) and Protein and Protein Interaction (PPI) network were constructed based on the hub DERNAs. The Cox and LASSO regression analysis were used to find the independent prognostic ceRNAs. We performed the “CIBERSORT” algorithm estimate the abundance of immune cells. The correlation analysis was applied to determine the relationship between HCC-related immune cells and prognostic ceRNAs. GEPIA and TIMER database were used to explore the association of critical genes with survival and immune cell infiltration, respectively. Results A total of 524 hub RNAs (507 DEmRNAs, 13 DElncRNAs and 4 DEmiRNAs) were identified in the turquoise module (cor = 0.78, P = 4.7e − 198) using WGCNA algorithm. PPI network analysis showed that NDC80, BUB1B and CCNB2 as the critical genes in HCC. Subsequently, survival analysis revealed that the low expression of NDC80 and BUB1B resulted in a longer overall survival (OS) time for HCC patients in GEPIA database. These critical genes and several immune cells were all significantly positive correlated in TIMER database. The ceRNA network were establish, and were incorporated to risk model. Subsequently, ROC curve showed that the area under the curve (AUC) of the 1-, 3-, and 5-year were 0.762, 0.705, and 0.688, respectively. Out of the 22 cell types, T cells CD4 memory resting were identified as the HCC-related immune cells by systematic analysis. The correlation analysis shown that T cells CD4 memory resting is negatively associated with both AL021453.1 (R = − 0.44, P = 0.00049) and CCDC137 (R = − 0.47, P = 2e-04). Conclusion The current study provide potential prognostic signatures and therapeutic targets for HCC.

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Tumor hepatitis B virus RNA identifies a clinically and molecularly distinct subset of hepatocellular carcinoma

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008699 ◽

2021 ◽

Vol 17 (2) ◽

pp. e1008699

Author(s):

Huat Chye Lim ◽

John D. Gordan

Keyword(s):

Hepatocellular Carcinoma ◽

Hepatitis B Virus ◽

Hepatitis B ◽

Survival Data ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Nonsynonymous Mutation ◽

Gene Set ◽

Virus Rna ◽

B Virus

Hepatitis B virus (HBV) infection contributes to hepatocellular carcinoma (HCC) initiation and is associated with worse outcomes. Many prior studies of HBV-related HCC have not accounted for potential heterogeneity among HBV-related tumors by assessing whether HBV activity is present in tumor tissue. Here, we measured tumor HBV RNA, a proxy for viral activity, and investigated the association between HBV RNA status and several clinicogenomic characteristics. We obtained clinical, mutation, RNA-Seq and survival data for 439 HCC tumors from The Cancer Genome Atlas and International Cancer Genome Consortium. Tumors were classified as HBV RNA positive if they harbored >1 HBV RNA read per million human reads. We investigated the association between HBV RNA status and nonsynonymous somatic mutations, gene set expression, homologous recombination deficiency (HRD) score and mutation-specific survival. HBV RNA positive status was associated with higher nonsynonymous mutation rates of multiple genes, including TP53 and CDKN2A, while HBV RNA negative status was associated with higher nonsynonymous BAP1 mutation rate. HBV RNA positive status was also associated with increased transcription of genes involved in multiple DNA damage repair pathways, genes upregulated by MYC and mTORC1, and genes overexpressed in several HCC subclasses associated with a proliferative phenotype. Further, HBV RNA positive status was associated with increased three-biomarker HRD score (22.2 for HBV RNA+ vs. 16.0 for HBV RNA-). Finally, HBV RNA status was associated with multiple mutation-specific survival differences, including decreased survival for HBV RNA positive patients with nonsynonymous KEAP1 mutations compared to those without (hazard ratio 4.26). HCC tumors harboring genomic evidence of HBV activity therefore constitute a distinct HCC subset characterized by specific differences in nonsynonymous mutations, gene set expression, three-biomarker HRD score and mutation-specific survival.

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Uncovering the Association Between m5C Regulator-Mediated Methylation Modification Patterns and Tumour Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.727935 ◽

2021 ◽

Vol 9 ◽

Author(s):

Xinyu Gu ◽

Haibo Zhou ◽

Qingfei Chu ◽

Qiuxian Zheng ◽

Jing Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Enrichment Analysis ◽

Tumour Microenvironment ◽

Copy Number Variations ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Gene Set ◽

Cluster 2

Background: 5-Methylcytosine (m5C) plays essential roles in hepatocellular carcinoma (HCC), but the association between m5C regulation and immune cell infiltration in HCC has not yet been clarified.Methods: In this study, we analysed 371 patients with HCC from The Cancer Genome Atlas (TCGA) database, and the expression of 13 m5C regulators was investigated. Additionally, gene set variation analysis (GSVA), unsupervised clustering analysis, single-sample gene set enrichment analysis (ssGSEA), correlation analysis, and immunohistochemical (IHC) staining were performed.Results: Among the 371 patients, 41 had mutations in m5C regulators, the frequency of which was 11.26%. Compared with normal hepatic tissues, the expression of m5C regulators with copy number variations (CNVs) expansion was significantly higher than that in HCC tissues. Then, we identified three m5C modification patterns that had obvious tumour microenvironment (TME) cell infiltration characteristics. The prognostic analysis of the three major m5C modification subtypes showed that Cluster-2 had a clear survival advantage over the others. In addition, we found that DNMT1 was highly expressed in tumour tissues compared with normal tissues in a tissue microarray (TMA) and that it was positively correlated with many TME-infiltrating immune cells. High expression of the m5C regulator DNMT1 was related to a poor prognosis in patients with HCC. Furthermore, we developed three distinct Immu-clusters. Importantly, mRNAs related to the transcription of growth factor β (TGF-β)/EMT pathway were significantly up-regulated in Immu-cluster 2, indicating that this cluster is considered to be the immune rejection phenotype. Immu-cluster 3 showed elevated expression of mRNAs related to immune checkpoint genes.Conclusion: Our work revealed the association between m5C modification and immune regulators in the TME. These findings also suggest that DNMT1 has great potential as a prognostic biomarker and therapeutic target for HCC.

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Integrated analysis of methylation-driven genes and pretreatment prognostic factors in patients with hepatocellular carcinoma

BMC Cancer ◽

10.1186/s12885-021-08314-5 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Dongsheng He ◽

Shengyin Liao ◽

Lifang Cai ◽

Weiming Huang ◽

Xuehua Xie ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Prognostic Factors ◽

Risk Score ◽

Prognostic Model ◽

Cox Regression ◽

The Cancer Genome Atlas ◽

Integrated Analysis ◽

Calibration Plot ◽

Clinical Parameters ◽

T Stage

Abstract Background The potential reversibility of aberrant DNA methylation indicates an opportunity for oncotherapy. This study aimed to integrate methylation-driven genes and pretreatment prognostic factors and then construct a new individual prognostic model in hepatocellular carcinoma (HCC) patients. Methods The gene methylation, gene expression dataset and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Methylation-driven genes were screened with a Pearson’s correlation coefficient less than − 0.3 and a P value less than 0.05. Univariable and multivariable Cox regression analyses were performed to construct a risk score model and identify independent prognostic factors from the clinical parameters of HCC patients. The least absolute shrinkage and selection operator (LASSO) technique was used to construct a nomogram that might act to predict an individual’s OS, and then C-index, ROC curve and calibration plot were used to test the practicability. The correlation between clinical parameters and core methylation-driven genes of HCC patients was explored with Student’s t-test. Results In this study, 44 methylation-driven genes were discovered, and three prognostic signatures (LCAT, RPS6KA6, and C5orf58) were screened to construct a prognostic risk model of HCC patients. Five clinical factors, including T stage, risk score, cancer status, surgical method and new tumor events, were identified from 13 clinical parameters as pretreatment-independent prognostic factors. To avoid overfitting, LASSO analysis was used to construct a nomogram that could be used to calculate the OS in HCC patients. The C-index was superior to that from previous studies (0.75 vs 0.717, 0.676). Furthermore, LCAT was found to be correlated with T stage and new tumor events, and RPS6KA6 was found to be correlated with T stage. Conclusion We identified novel therapeutic targets and constructed an individual prognostic model that can be used to guide personalized treatment in HCC patients.

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48 Immune environment correlates with NSCLC and CRC patient survival

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-sitc2021.048 ◽

2021 ◽

Vol 9 (Suppl 3) ◽

pp. A55-A55

Author(s):

Dannah Miller ◽

Huong Nguyen ◽

Kate Hieber ◽

Charles Caldwell ◽

Roberto Gianani

Keyword(s):

T Cells ◽

Image Analysis ◽

Immune Cells ◽

Survival Data ◽

Immune Cell ◽

Patient Survival ◽

Machine Learning Algorithms ◽

Primary Tumors ◽

Cell Lung Carcinoma ◽

Analysis Platform

BackgroundImmune cells within the tumor microenvironment (TME) play a vital role in regulating tumor progression. Therefore, immunotherapies that stimulate anti-tumor responses are of great interest for the treatment of various cancers. PD-L1 expression on immune cells is positively correlated with increased patient survival. Our hypothesis is that non-small cell lung carcinoma (NSCLC) and colorectal cancer (CRC) patients with high immune infiltration and greater amounts of anti-tumor immune cells within the tumor compartment have an increased time of survival compared to cancers with immune excluded or immune desert environments.MethodsOne NSCLC and one CRC tumor microarray (TMA) containing primary tumors, metastases, and normal tissue were stained via multiplex immunofluorescence (mIF) for 6 different immune markers: CD3, CD8, CD56, CD68, CD163, and PD-L1. This multiplex panel was designed to evaluate the immune cell population as well as tumor and immune cell PD-L1 status to aid in research for immunotherapies, specifically anti-PD-L1 therapies. The stained TMAs were analyzed utilizing Flagship Biosciences’ proprietary image analysis platform. Machine learning algorithms stratified cells as belonging to the tumoral or stromal space based on their cellular features. Core level expression data was pulled and represented on a whole-cohort basis. All staining and image analysis outputs were reviewed by a board-certified, MD pathologist. Kaplan-meier curves were generated based on survival data in relation to the levels of immune cells present within the tumor cores as well as the percentage of immune cells infiltrating into the tumor.ResultsThere is a clear correlation between patient survival and the presence or absence of various types of immune cells, including helper T cells, cytotoxic T cells, M1 macrophages, M2, macrophages, NK cells, as well as PDL1 expression on tumor and immune cells. Specifically, the increased presence of anti-tumor immune cells as well as increased expression of PD-L1 on immune cells within the tumor compartment correlates with an increase in patient survival.ConclusionsData generated through Flagship Biosciences’ image analysis platform showed a strong relationship between immune cell presence and localization and NSCLC and CRC patient survival. Altering the immune cells within the tumor to an anti-tumor immune environment could increase patient survival times. Combining immune checkpoint inhibitors with current FDA approved therapies for NSCLC and CRC are of interest to further extend patient survival. Further, utilizing Flagship Biosciences’ image analysis software to understand cancer immune microenvironments should be further utilized to aid in diagnosis and treatment decisions.

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CYSTM1: A Novel Biomarker for Hepatocellular Carcinoma Prognosis

10.21203/rs.3.rs-150866/v1 ◽

2021 ◽

Author(s):

Jun Du ◽

Jinguo Wang

Keyword(s):

Hepatocellular Carcinoma ◽

Poor Prognosis ◽

Early Stage ◽

Human Tumor ◽

The Cancer Genome Atlas ◽

Data Set ◽

Kaplan Meier ◽

Cancer Genome Atlas ◽

Cox Proportional Hazard Regression ◽

The Relationship

Abstract Background: The expression and molecular mechanism of cysteine rich transmembrane module containing 1 (CYSTM1) in human tumor cells remains unclear. The aim of this study was to determine whether CYSTM1 could be used as a potential prognostic biomarker for hepatocellular carcinoma (HCC).Methods: We first demonstrated the relationship between CYSTM1 expression and HCC in various public databases. Secondly, Kaplan–Meier analysis and Cox proportional hazard regression model were performed to evaluate the relationship between the expression of CYSTM1 and the survival of HCC patients which data was downloaded in the cancer genome atlas (TCGA) database. Finally, we used the expression data of CYSTM1 in TCGA database to predict CYSTM1-related signaling pathways through bioinformatics analysis.Results: The expression level of CYSTM1 in HCC tissues was significantly correlated with T stage (p = 0.039). In addition, Kaplan–Meier analysis showed that the expression of CYSTM1 was significantly associated with poor prognosis in patients with early-stage HCC (p = 0.003). Multivariate analysis indicated that CYSTM1 is a potential predictor of poor prognosis in HCC patients (p = 0.036). The results of biosynthesis analysis demonstrated that the data set of CYSTM1 high expression was mainly enriched in neurodegeneration and oxidative phosphorylation pathways.Conclusion: CYSTM1 is an effective biomarker for the prognosis of patients with early-stage HCC and may play a key role in the occurrence and progression of HCC.

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Identification of a gene set correlated with immune status in ovarian cancer by transcriptome-wide data mining

10.21203/rs.3.rs-17604/v1 ◽

2020 ◽

Author(s):

Lili Fan ◽

Han Lei ◽

Ying Lin ◽

Zhengwei Zhou ◽

Guang Shu ◽

...

Keyword(s):

Ovarian Cancer ◽

Immune Cell ◽

Good Prognosis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Survival Prognosis ◽

Immune Activity ◽

Gene Set ◽

Immune Infiltration ◽

Keywords Ovarian Cancer

Abstract Background : Ovarian cancer (OC) is a serious tumor disease in gynecology. Many papers have reported that high tumor mutational burden (TMB) can generate many neoantigens to result in a higher degree of tumor immune infiltration, so our study aims to predict the key molecules in OC immunotherapy by combined TMB with immunoactivity-related gene. Method: We divided OC cases into two groups: the low & high TMB group hinged on the somatic mutation data from the Cancer Genome Atlas (TCGA). We also used single-sample gene set enrichment analysis (ssGSEA) scores of immune cell types to conduct unsupervised clustering of OC patients in the TCGA cohort and some of them were defined as the low & high immunity group. Besides, to further understand the function of these genes, we conducted Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, protein-protein interaction network, survival prognosis analysis and immune infiltration analysis. Finally, the effects on prognosis and immunotherapy in OC patients were explored by the Group on Earth Observations verification the patients' responses to immunotherapy. Results: We found that the higher the TMB was associated with the higher OC grades. Moreover, both high TMB and high immunity were significantly correlated with a good prognosis of OC. Then, 14 up-regulated differential expression genes (Up-DEGs) that were closely related to the prognosis of OC patients were screened according to the high TMB group and the high immunity group. Next, pathway analysis revealed that Up-DGEs were mainly involved in immune response and T cell proliferation. Finally, four genes had a good prognosis and were validated in the GEO dataset which included CXCL13, FCRLA, PLA2G2D, and MS4A1. We also identified that four genes had a good prognosis in melanoma patients treated with anti-PD-L1 and anti-CTLA-4 in the TIDE database. Conclusion: High TMB can promote immune cell infiltration and increases immune activity. And our analysis also demonstrated that the higher the TMB, the higher the immune activity, the better the prognosis of OC. Altogether, we found that CXCL13, FCRLA, PLA2G2D, and MS4A1 may be biomarkers for OC immunotherapy. Keywords: ovarian cancer, TMB, immune cells infiltration, survival prognosis.

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Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.611058 ◽

2021 ◽

Vol 12 ◽

Author(s):

Zhuomao Mo ◽

Daiyuan Liu ◽

Dade Rong ◽

Shijun Zhang

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Cancer Genome ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Immune Checkpoints ◽

Immune Cell Infiltration ◽

Immunosuppressive Microenvironment

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.

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