The Use of Machine Learning to Create a Risk Score to Predict Survival in Patients with Hepatocellular Carcinoma: A TCGA Cohort Analysis

Introduction. Hepatocellular carcinoma (HCC) accounts for approximately 90% of primary liver malignancies and is currently the fourth most common cause of cancer-related death worldwide. Due to varying underlying etiologies, the prognosis of HCC differs greatly among patients. It is important to develop ways to help stratify patients upon initial diagnosis to provide optimal treatment modalities and follow-up plans. The current study uses Artificial Neural Network (ANN) and Classification Tree Analysis (CTA) to create a gene signature score that can help predict survival in patients with HCC. Methods. The Cancer Genome Atlas (TCGA-LIHC) was analyzed for differentially expressed genes. Clinicopathological data were obtained from cBioPortal. ANN analysis of the 75 most significant genes predicting disease-free survival (DFS) was performed. Next, CTA results were used for creation of the scoring system. Cox regression was performed to identify the prognostic value of the scoring system. Results. 363 patients diagnosed with HCC were analyzed in this study. ANN provided 15 genes with normalized importance >50%. CTA resulted in a set of three genes (NRM, STAG3, and SNHG20). Patients were then divided in to 4 groups based on the CTA tree cutoff values. The Kaplan–Meier analysis showed significantly reduced DFS in groups 1, 2, and 3 (median DFS: 29.7 months, 16.1 months, and 11.7 months, p < 0.01) compared to group 0 (median not reached). Similar results were observed when overall survival (OS) was analyzed. On multivariate Cox regression, higher scores were associated with significantly shorter DFS (1 point: HR 2.57 (1.38–4.80), 2 points: 3.91 (2.11–7.24), and 3 points: 5.09 (2.70–9.58), p < 0.01). Conclusion. Long-term outcomes of patients with HCC can be predicted using a simplified scoring system based on tumor mRNA gene expression levels. This tool could assist clinicians and researchers in identifying patients at increased risks for recurrence to tailor specific treatment and follow-up strategies for individual patients.

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The Oncogenic Role of CENPA in Hepatocellular Carcinoma Development: Evidence from Bioinformatic Analysis

BioMed Research International ◽

10.1155/2020/3040839 ◽

2020 ◽

Vol 2020 ◽

pp. 1-8

Author(s):

Yuan Zhang ◽

Lei Yang ◽

Jia Shi ◽

Yunfei Lu ◽

Xiaorong Chen ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Cox Regression ◽

Disease Free Survival ◽

Progression Free Survival ◽

Bioinformatic Analysis ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Free Survival ◽

Tcga Dataset ◽

High Level

Objective. This study is aimed at investigating the predictive value of CENPA in hepatocellular carcinoma (HCC) development. Methods. Using integrated bioinformatic analysis, we evaluated the CENPA mRNA expression in tumor and adjacent tissues and correlated it with HCC survival and clinicopathological features. A Cox regression hazard model was also performed. Results. CENPA mRNA was significantly upregulated in tumor tissues compared with that in adjacent tissues, which were validated in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) series (all P<0.01). In the Kaplan-Meier plotter platform, the high level of CENPA mRNA was significantly correlated with overall survival (OS), disease-free survival (DFS), recurrence-free survival (RFS), and progression-free survival (PFS) in HCC patients (all log rank P<0.01). For validation in GSE14520 and pan-TCGA dataset, HCC patients with CNEPA mRNA overexpression had poor OS compared with those with low CENPA mRNA (log rank P=0.025 and P<0.0001, respectively), and those with high CENPA had poor DFS in TCGA (log rank P=0.0001). Additionally, CENPA mRNA were upregulated in HCC patients with alpha-fetoprotein (AFP) elevation, advanced TNM stage, larger tumor size, advanced AJCC stage, advanced pathology grade, and vascular invasion (all P<0.05). A Cox regression model including CENPA, OIP5, and AURKB could predict OS in HCC patients effectively (AUC=0.683). Conclusion. Overexpressed in tumors, CENPA might be an oncogenic factor in the development of HCC patients.

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The GNAQ T96S Mutation Affects Cell Signaling and Enhances the Oncogenic Properties of Hepatocellular Carcinoma

International Journal of Molecular Sciences ◽

10.3390/ijms22063284 ◽

2021 ◽

Vol 22 (6) ◽

pp. 3284

Author(s):

Eugene Choi ◽

Sung Jean Park ◽

Gunhee Lee ◽

Seung Kew Yoon ◽

Minho Lee ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Expression Vector ◽

Signal Transduction Pathway ◽

Inhibitory Effect ◽

The Cancer Genome Atlas ◽

Treatment Modalities ◽

Protein Signaling ◽

Wild Type ◽

Anchorage Independent Growth ◽

Mapk Pathways

Hepatocellular carcinoma (HCC), the most common malignant tumor in the liver, grows and metastasizes rapidly. Despite advances in treatment modalities, the five-year survival rate of HCC remains less than 30%. We sought genetic mutations that may affect the oncogenic properties of HCC, using The Cancer Genome Atlas (TCGA) data analysis. We found that the GNAQ T96S mutation (threonine 96 to serine alteration of the Gαq protein) was present in 12 out of 373 HCC patients (3.2%). To examine the effect of the GNAQ T96S mutation on HCC, we transfected the SK-Hep-1 cell line with the wild-type or the mutant GNAQ T96S expression vector. Transfection with the wild-type GNAQ expression vector enhanced anchorage-independent growth, migration, and the MAPK pathways in the SK-Hep-1 cells compared to control vector transfection. Moreover, cell proliferation, anchorage-independent growth, migration, and the MAPK pathways were further enhanced in the SK-Hep-1 cells transfected with the GNAQ T96S expression vector compared to the wild-type GNAQ-transfected cells. In silico structural analysis shows that the substitution of the GNAQ amino acid threonine 96 with a serine may destabilize the interaction between the regulator of G protein signaling (RGS) protein and GNAQ. This may reduce the inhibitory effect of RGS on GNAQ signaling, enhancing the GNAQ signaling pathway. Single nucleotide polymorphism (SNP) genotyping analysis for Korean HCC patients shows that the GNAQ T96S mutation was found in only one of the 456 patients (0.22%). Our data suggest that the GNAQ T96S hotspot mutation may play an oncogenic role in HCC by potentiating the GNAQ signal transduction pathway.

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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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Expression and clinical significance of CMTM1 in hepatocellular carcinoma

Open Medicine ◽

10.1515/med-2021-0221 ◽

2021 ◽

Vol 16 (1) ◽

pp. 217-223

Author(s):

Xin Song ◽

Shidong Zhang ◽

Run Tian ◽

Chuanjun Zheng ◽

Yuge Xu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Transmembrane Domain ◽

Disease Free Survival ◽

Clinicopathological Characteristics ◽

The Cancer Genome Atlas ◽

High Expression ◽

Chi Square ◽

Tumor Tissues ◽

The Relationship ◽

Low Expression

Abstract Background CKLF Like Marvel Transmembrane Domain Containing 1 (CMTM1) plays a role in breast cancer and lung cancer, but studies on the occurrence and development of CMTM1 in hepatocellular carcinoma (HCC) have not been reported. Methods The Cancer Genome Atlas (TCGA) database and immunohistochemistry (IHC) were used to detect CMTM1 expression in HCC tissues. The relationship between CMTM1 expression and the clinicopathological characteristics of HCC patients was analyzed by chi-square test, and the relationship between CMTM1 expression and the prognosis of HCC patients was tested by the Kaplan–Meier model. Results Bioinformatics analysis showed that the mRNA expression of CMTM1 was upregulated in HCC tissues, and low expression of CMTM1 is associated with longer disease-free survival in patients with HCC. Similarly, the survival time of HCC patients in CMTM1 high expression group was significantly shorter than that in CMTM1 low expression group. IHC detection indicated that CMTM1 protein was highly expressed in both HCC and adjacent non-tumor tissues, with a positive expression in 84% (63/75) of HCC tissues and 89.3% (67/75) of adjacent non-tumor tissues. Moreover, CMTM1 expression was related to family history and TNM stage of HCC patients (P < 0.05), but had no relationship with other clinicopathological characteristics. The survival analysis based on IHC results showed that the prognosis of HCC patients in CMTM1 negative group was significantly poorer than that in CMTM1 positive group (P < 0.05). Conclusion CMTM1 has a high expression in HCC tissues and is related to the prognosis of HCC patients.

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A stemness-based eleven-gene signature correlates with the clinical outcome of hepatocellular carcinoma

BMC Cancer ◽

10.1186/s12885-021-08351-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Liang Hong ◽

Yu Zhou ◽

Xiangbang Xie ◽

Wanrui Wu ◽

Changsheng Shi ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Cox Regression ◽

Molecular Subtypes ◽

Prognostic Significance ◽

Predictive Performance ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Cumulative Distribution ◽

Gene Module ◽

Expression Levels

Abstract Background Cumulative evidences have been implicated cancer stem cells in the tumor environment of hepatocellular carcinoma (HCC) cells, whereas the biological functions and prognostic significance of stemness related genes (SRGs) in HCC is still unclear. Methods Molecular subtypes were identified by cumulative distribution function (CDF) clustering on 207 prognostic SRGs. The overall survival (OS) predictive gene signature was developed, internally and externally validated based on HCC datasets including The Cancer Genome Atlas (TCGA), GEO and ICGC datasets. Hub genes were identified in molecular subtypes by protein-protein interaction (PPI) network analysis, and then enrolled for determination of prognostic genes. Univariate, LASSO and multivariate Cox regression analyses were performed to assess prognostic genes and construct the prognostic gene signature. Time-dependent receiver operating characteristic (ROC) curve, Kaplan-Meier curve and nomogram were used to assess the performance of the gene signature. Results We identified four molecular subtypes, among which the C2 subtype showed the highest SRGs expression levels and proportions of immune cells, whereas the worst OS; the C1 subtype showed the lowest SRGs expression levels and was associated with most favorable OS. Next, we identified 11 prognostic genes (CDX2, PON1, ADH4, RBP2, LCAT, GAL, LPA, CYP19A1, GAST, SST and UGT1A8) and then constructed a prognostic 11-gene module and validated its robustness in all three datasets. Moreover, by univariate and multivariate Cox regression, we confirmed the independent prognostic ability of the 11-gene module for patients with HCC. In addition, calibration analysis plots indicated the excellent predictive performance of the prognostic nomogram constructed based on the 11-gene signature. Conclusions Findings in the present study shed new light on the role of stemness related genes within HCC, and the established 11-SRG signature can be utilized as a novel prognostic marker for survival prognostication in patients with HCC.

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Pituitary surgery as alternative to dopamine agonists treatment for microprolactinomas, a cohort study

Acta Endocrinologica ◽

10.1530/eje-21-0293 ◽

2021 ◽

Author(s):

Bertrand Baussart ◽

Chiara Villa ◽

Anne Jouinot ◽

Marie-Laure Raffin-Sanson ◽

Luc Foubert ◽

...

Keyword(s):

Dopamine Agonists ◽

Cox Regression ◽

Disease Free Survival ◽

Pituitary Surgery ◽

Cerebrospinal Fluid Leakage ◽

Neurosurgical Department ◽

Free Survival ◽

Kaplan Meier ◽

Disease Free

Objective: Microprolactinomas are currently treated with dopamine agonists. Outcome information on microprolactinoma patients treated by surgery is limited. This study reports the first large series of consecutive non-invasive microprolactinoma patients treated by pituitary surgery and evaluates the efficiency and safety of this treatment. Design: Follow-up of a cohort of consecutive patients treated by surgery. Methods: Between January 2008 and October 2020, 114 adult patients with pure microprolactinomas were operated on in a single tertiary expert neurosurgical department, using an endoscopic endonasal transsphenoidal approach. Eligible patients were presenting a microprolactinoma with no obvious cavernous invasion on MRI. Prolactin was assayed before and after surgery. Disease-free survival was modeled using Kaplan-Meier representation. A cox regression model was used to predict remission. Results: Median follow-up was 18.2 months (range: 2.8 to 155). In this cohort, 14/114 (12%) patients were not cured by surgery, including 10 early surgical failures, and 4 late relapses occurring 37.4 months (33 to 41.8) after surgery. From Kaplan Meier estimates, 1-year and 5-year disease free survival were 90.9% (95% CI, 85.6%-96.4%) and 81% (95% CI,71.2%-92.1%) respectively. The preoperative prolactinemia was the only significant preoperative predictive factor for remission (P<0.05). No severe complication was reported, with no anterior pituitary deficiency after surgery, one diabetes insipidus, and one postoperative cerebrospinal fluid leakage properly treated by muscle plasty. Conclusions: In well selected microprolactinoma patients, pituitary surgery performed by an expert neurosurgical team is a valid first-line alternative treatment to dopamine agonists.

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Development and Validation of Prognostic Nomograms Predicting Recurrence and Survival in Patients with Solitary Hepatocellular Carcinoma Following Curative Liver Resection

10.21203/rs.3.rs-1070685/v1 ◽

2021 ◽

Author(s):

Xinxin Chen ◽

Wenxia Qiu ◽

Xuekun Xie ◽

Zefeng Chen ◽

Zhiwei Han ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Liver Resection ◽

Cox Regression ◽

Disease Free Survival ◽

Clinicopathological Characteristics ◽

Tumor Diameter ◽

Cox Regression Analysis ◽

Tumor Capsule ◽

Calibration Curves ◽

Solitary Hepatocellular Carcinoma

Abstract Background: This work was designed to establish and verify our nomograms integrating clinicopathological characteristics with hematological biomarkers to predict both disease-free survival (DFS) and overall survival (OS) in solitary hepatocellular carcinoma (HCC) patients following hepatectomy.Methods: We scrutinized the data retrospectively from 414 patients with a clinicopathological diagnosis of solitary HCC from Guangxi Medical University Cancer Hospital (Nanning, China) between January 2004 and December 2012. Following the random separation of the samples in a 7:3 ratio into the training set and validation set, the former set was assessed by Cox regression analysis to develop two nomograms to predict the 1-year and 3-year DFS and OS (3-years and 5-years). This was followed by discrimination and calibration estimation employing Harrell’s C-index (C-index) and calibration curves, while the internal validation was also assessed.Results: In the training cohort, the tumor diameter, tumor capsule, macrovascular invasion, and alpha-fetoprotein (AFP) were included in the DFS nomogram. Age, tumor diameter, tumor capsule, macrovascular invasion, microvascular invasion, and aspartate aminotransferase (AST) were included in the OS nomogram. The C-index was 0.691 (95% CI: 0.644-0.738) for the DFS-nomogram and 0.713 (95% CI: 0.670-0.756) for the OS-nomogram. The survival probability calibration curves displayed a fine agreement between the predicted and observed ranges in both data sets. Conclusion: Our nomograms combined clinicopathological features with hematological biomarkers to emerge effective in predicting the DFS and OS in solitary HCC patients following curative liver resection. Therefore, the potential utility of our nomograms for guiding individualized treatment clinically and monitor the recurrence monitoring in these patients.

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NDRG3 overexpression is associated with a poor prognosis in patients with hepatocellular carcinoma

Bioscience Reports ◽

10.1042/bsr20180907 ◽

2018 ◽

Vol 38 (6) ◽

Cited By ~ 1

Author(s):

Ji-sheng Jing ◽

Hongbo Li ◽

Shun-cai Wang ◽

Jiu-ming Ma ◽

La-qing Yu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Cox Regression ◽

Survival Curve ◽

Disease Free Survival ◽

Prognostic Indicator ◽

Clinicopathological Characteristics ◽

Pcr Analysis ◽

Kaplan Meier ◽

Tumor Tissues ◽

The Relationship

N-myc downstream-regulated gene 3 (NDRG3), an important member of the NDRG family, is involved in cell proliferation, differentiation, and other biological processes. The present study analyzed NDRG3 expression in hepatocellular carcinoma (HCC) and explored the relationship between expression of NDRG3 in HCC patients and their clinicopathological characteristics. We performed quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) analysis and immunohistochemistry (IHC) analyses on HCC tissues to elucidate NDRG3 expression characteristics in HCC patients. Kaplan–Meier survival curve and Cox regression analyses were used to evaluate the prognoses of 102 patients with HCC. The results revealed that compared with non-tumor tissues, HCC tissues showed significantly higher NDRG3 expression. In addition, our analyses showed that NDRG3 expression was statistically associated with tumor size (P=0.048) and pathological grade (P=0.001). Survival analysis and Kaplan–Meier curves revealed that NDRG3 expression is an independent prognostic indicator for disease-free survival (P=0.002) and overall survival (P=0.005) in HCC patients. The data indicate that NDRG3 expression may be considered as a oncogenic biomarker and a novel predictor for HCC prognosis.

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High Expression of ANXA2 Pseudogene ANXA2P2 Promotes an Aggressive Phenotype in Hepatocellular Carcinoma

Disease Markers ◽

10.1155/2019/9267046 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 4

Author(s):

Qiu-shuang Wang ◽

Liang-Liang Shi ◽

Fei Sun ◽

Yi-fan Zhang ◽

Ren-Wang Chen ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Disease Free Survival ◽

Annexin A2 ◽

The Cancer Genome Atlas ◽

High Expression ◽

Migration And Invasion ◽

Targeted Drugs ◽

Noncancerous Tissue ◽

Expression Levels ◽

Hcc Cells

Objective. Accumulating evidence suggests that pseudogenes play potential roles in the regulation of their cognate wild-type genes, oncogenes, and tumor suppressor genes. ANXA2P2 (annexin A2 pseudogene 2) is one of three pseudogenes of annexin A2 that have recently been shown to be aberrantly transcribed in hepatocellular carcinoma (HCC) cells. However, its clinical meaning and biological function in HCC have remained unclear. Therefore, the present study was aimed at exploring the prognostic value of a high expression of ANXA2P2 in HCC tissue and at identifying whether it can affect the efficacy of targeted drugs (sorafenib, regorafenib, and lenvatinib). Methods. We obtained ANXA2P2 mRNA expression levels from The Cancer Genome Atlas (TCGA) RNA sequence database. The expression levels of ANXA2P2 in 49 pairs of intratumoral and peritumoral liver tissues were examined by RT-PCR. Wound healing and transwell assays were performed to confirm the tumor-promoting properties of ANXA2P2 in HCC cells. CCK8 assay was conducted to identify whether ANXA2P2 can affect the growth of HCC cells when administered with targeted drugs (sorafenib, regorafenib, and lenvatinib). Results. The expression of ANXA2P2 in HCC tissues was significantly higher than that in adjacent cancerous tissues from TCGA database and validation group. Additionally, patients with high ANXA2P2 expression in HCC tissue had a shorter overall survival, whereas no statistically significant correlation was found between ANXA2P2 expression and disease-free survival (p=0.08) as well as other clinical parameters, such as age, gender, histological grade, T classification, stage, albumin level, alpha-fetoprotein, and vascular invasion (p=0.7323, 0.8807, 0.5762, 0.8515, 0.7113, 0.242, 1.0000, and 0.7685, respectively). Furthermore, in vitro experiments showed that knockdown of ANXA2P2 inhibited migration and invasion of HCC cells but did not have an influence on the HCC cell proliferation when treated with targeted drugs (sorafenib, regorafenib, and lenvatinib). Conclusion. Our study confirmed elevated ANXA2P2 expression levels in HCC tissue compared with adjacent noncancerous tissue and a worse prognosis of patients with high ANXA2P2 levels in the HCC tissue. The newly found properties of promoting migration and invasion of ANXA2P2 in HCC help to explain this phenomenon. ANXA2P2 could be a novel and suitable predicative biomarker for the risk assessment of recurrence or metastasis of HCC patients but may not be effective to predict the efficacy of targeted drugs.

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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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