Identification of CDC20 As an Immune Infiltration-Correlated Prognostic Biomarker in Hepatocellular Carcinoma

Abstract Hepatocellular carcinoma (HCC) is a malignancy with a poor prognosis. Some E3 ubiquitin-protein ligases play essential roles in HCC development. We aimed to explore a hub E3 ubiquitin-protein ligase gene and verify its association with prognosis and immune cell infiltration in HCC. We identified cell division cycle 20 (CDC20) as a hub E3 ubiquitin-protein ligase in HCC by determining the intersecting genes in a protein-protein interaction (PPI) network of differentially expressed genes (DEGs) in HCC data from the International Cancer Genome Consortium (ICGC) and 919 E3 ubiquitin-protein ligase genes from the Integrated annotations for Ubiquitin and Ubiquitin-like Conjugation Database (IUUCD). DEGs and their correlations with clinicopathological features were explored in The Cancer Genome Atlas (TCGA), ICGC, and Gene Expression Omnibus (GEO) databases via the Wilcoxon signed-rank test. The prognostic value of CDC20 was illustrated by Kaplan-Meier (K-M) curves and Cox regression analyses. Subsequently, the correlation between CDC20 and immune infiltration was demonstrated via the Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA). CDC20 expression was significantly higher in HCC than in normal tissues (all P < 0.05). K-M curves and Cox regression analyses showed that high CDC20 expression predicted a poor prognosis and might be an independent risk factor for HCC prognosis (P < 0.05). Additionally, the TIMER and GEPIA results indicated that CDC20 is correlated with the immune infiltration of CD8 + T cells, T cells (general), monocytes, and exhausted T cells. This research revealed the potential prognostic value of CDC20 in HCC and demonstrated that CDC20 might be an immune-associated therapeutic target in HCC because of its correlation with immune infiltration.

Download Full-text

The diagnostic and prognostic value of H2AFY in hepatocellular carcinoma

10.21203/rs.3.rs-17889/v2 ◽

2020 ◽

Author(s):

xuyang ma ◽

Ying Ding ◽

Li Zeng

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Poor Prognosis ◽

Prognostic Value ◽

Clinical Characteristics ◽

Cox Regression ◽

Normal Liver ◽

Diagnostic Value ◽

The Relationship ◽

Diagnostic And Prognostic Value

Abstract Background: The potential correlation between H2AFY (also known as MacroH2A1) and the clinical characteristics of hepatocellular carcinoma (HCC) patients was analysed through gene expression profiles and clinical data in The Cancer Genome Atlas (TCGA) database, and the diagnostic and prognostic value of H2AFY in HCC was discussed. Methods: The gene expression data of HCC and the corresponding clinical characteristics of HCC patients were downloaded from the TCGA database. The differences in H2AFY in normal liver tissues and HCC were analysed. The relationship between H2AFY and clinical characteristics was analysed by Wilcoxon signed-rank test, logistic regression and Kruskal-Wallis test. The Kaplan-Meier method and the Cox regression method were used to analyse the relationship between overall survival and clinical characteristics of the patients. An ROC curve was used to predict the diagnostic value of H2AFY in HCC. Gene set enrichment analysis (GSEA) was used to analyse the pathway enrichment of H2AFY. Result: Compared with normal liver tissues, H2AFY was significantly highly expressed in HCC. H2AFY was positively correlated with the age, clinical stage, G stage (grade) and T stage (tumor stage) of liver cancer patients. Higher H2AFY expression predicted a poor prognosis in HCC patients. Cox regression analysis suggested that H2AFY was an independent risk factor for the prognosis of HCC patients. The ROC curve suggested that H2AFY had certain diagnostic value in HCC. GSEA suggested that H2AFY was correlated with lipid metabolism and a variety of tumour pathways. Conclusion: Our study showed that H2AFY was significantly overexpressed in HCC. H2AFY may be a potential diagnostic and prognostic marker for HCC, and high expression of H2AFY predicts a poor prognosis in patients with HCC.

Download Full-text

Identification and Validation of a Novel Metabolism‑Related Prognostic Signature in Hepatocellular Carcinoma

10.21203/rs.3.rs-50552/v1 ◽

2020 ◽

Author(s):

Zhihao Wang ◽

Kidane Siele Embaye ◽

Qing Yang ◽

Lingzhi Qin ◽

Chao Zhang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Regression Analysis ◽

Prognostic Value ◽

Cox Regression ◽

Cancer Genome ◽

Regression Analyses ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Tcga Dataset

Abstract Background: Given that metabolic reprogramming has been recognized as an essential hallmark of cancer cells, this study sought to investigate the potential prognostic values of metabolism-related genes(MRGs) for hepatocellular carcinoma (HCC) diagnosis and treatment. Methods: The metabolism-related genes sequencing data of HCC samples with clinical information were obtained from the International Cancer Genome Consortium(ICGC) and The Cancer Genome Atlas (TCGA). The differentially expressed MRGs were identified by Wilcoxon rank sum test. Then, univariate Cox regression analysis were performed to identify metabolism-related DEGs that related to overall survival(OS). A novel metabolism-related prognostic signature was developed using the least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analyses . Furthermore, the signature was validated in the TCGA dataset. Finally, cox regression analysis was applied to identify the prognostic value and clinical relationship of the signature in HCC. Results: A total of 178 differentially expressed MRGs were detected between the ICGA dataset and the TCGA dataset. We found that 17 MRGs were most significantly associated with OS by using the univariate Cox proportional hazards regression analysis in HCC. Then, the Lasso and multivariate Cox regression analyses were applied to construct the novel metabolism-relevant prognostic signature, which consisted of six MRGs. The prognostic value of this prognostic model was further successfully validated in the TCGA dataset. Further analysis indicated that this signature could be an independent prognostic indicator after adjusting to other clinical factors. Six MRGs (FLVCR1, MOGAT2, SLC5A11, RRM2, COX7B2, and SCN4A) showed high prognostic performance in predicting HCC outcomes, and were further associated with tumor TNM stage, gender, age, and pathological stage. Finally, the signature was found to be associated with various clinicopathological features. Conclusions: In summary, our data provided evidence that the metabolism-based signature could serve as a reliable prognostic and predictive tool for overall survival in patients with HCC.

Download Full-text

The diagnostic and prognostic value of H2AFY in hepatocellular carcinoma

BMC Cancer ◽

10.1186/s12885-021-08161-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xuyang Ma ◽

Ying Ding ◽

Li Zeng

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Poor Prognosis ◽

Prognostic Value ◽

Clinical Characteristics ◽

Cox Regression ◽

Normal Liver ◽

Diagnostic Value ◽

The Relationship ◽

Diagnostic And Prognostic Value

Abstract Background The potential correlation between H2AFY (also known as MacroH2A1) and the clinical characteristics of hepatocellular carcinoma (HCC) patients was analysed through gene expression profiles and clinical data in The Cancer Genome Atlas (TCGA) database, and the diagnostic and prognostic value of H2AFY in HCC was discussed. Methods The gene expression data of HCC and the corresponding clinical characteristics of HCC patients were downloaded from the TCGA database. The differences in H2AFY in normal liver tissues and HCC were analysed. The relationship between H2AFY and clinical characteristics was analysed by Wilcoxon signed-rank test, logistic regression and Kruskal-Wallis test. The Kaplan-Meier method and the Cox regression method were used to analyse the relationship between overall survival and clinical characteristics of the patients. An ROC curve was used to predict the diagnostic value of H2AFY in HCC. Gene set enrichment analysis (GSEA) was used to analyse the pathway enrichment of H2AFY. Result Compared with normal liver tissues, H2AFY was significantly highly expressed in HCC. H2AFY was positively correlated with the age, clinical stage, G stage (grade) and T stage (tumor stage) of liver cancer patients. Higher H2AFY expression predicted a poor prognosis in HCC patients. Cox regression analysis suggested that H2AFY was an independent risk factor for the prognosis of HCC patients. The ROC curve suggested that H2AFY had certain diagnostic value in HCC. GSEA suggested that H2AFY was correlated with lipid metabolism and a variety of tumour pathways. Conclusion Our study showed that H2AFY was significantly overexpressed in HCC. H2AFY may be a potential diagnostic and prognostic marker for HCC, and high expression of H2AFY predicts a poor prognosis in patients with HCC.

Download Full-text

The diagnostic and prognostic value of H2AFY in hepatocellular carcinoma

10.21203/rs.3.rs-17889/v1 ◽

2020 ◽

Author(s):

xuyang ma ◽

Ying Ding ◽

Li Zeng

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Poor Prognosis ◽

Prognostic Value ◽

Clinical Characteristics ◽

Cox Regression ◽

Normal Liver ◽

Diagnostic Value ◽

The Relationship ◽

Diagnostic And Prognostic Value

Abstract Background The potential correlation between H2AFY (also known as MacroH2A1) and the clinical characteristics of hepatocellular carcinoma (HCC) patients was analysed through gene expression profiles and clinical data in The Cancer Genome Atlas (TCGA) database, and the diagnostic and prognostic value of H2AFY in HCC was discussed. Methods The gene expression data of HCC and the corresponding clinical characteristics of HCC patients were downloaded from the TCGA database. The differences in H2AFY in normal liver tissues and HCC were analysed. The relationship between H2AFY and clinical characteristics was analysed by Wilcoxon signed-rank test, logistic regression and Kruskal-Wallis test. The Kaplan-Meier method and the Cox regression method were used to analyse the relationship between overall survival and clinical characteristics of the patients. An ROC curve was used to predict the diagnostic value of H2AFY in HCC. Gene set enrichment analysis (GSEA) was used to analyse the pathway enrichment of H2AFY. Result Compared with normal liver tissues, H2AFY was significantly highly expressed in HCC. H2AFY was positively correlated with the age, clinical stage, G stage and T stage of liver cancer patients. Higher H2AFY expression predicted a poor prognosis in HCC patients. Cox regression analysis suggested that H2AFY was an independent risk factor for the prognosis of HCC patients. The ROC curve suggested that H2AFY had certain diagnostic value in HCC. GSEA suggested that H2AFY was correlated with lipid metabolism and a variety of tumour pathways. Conclusion Our study showed that H2AFY was significantly overexpressed in HCC. H2AFY may be a potential diagnostic and prognostic marker for HCC, and high expression of H2AFY predicts a poor prognosis in patients with HCC.

Download Full-text

A Nomogram Based on a Three-Gene Signature Derived from AATF Coexpressed Genes Predicts Overall Survival of Hepatocellular Carcinoma Patients

BioMed Research International ◽

10.1155/2020/7310768 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17

Author(s):

Jun Liu ◽

Jianjun Lu ◽

Zhanzhong Ma ◽

Wenli Li

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Overall Survival ◽

Clinical Practice ◽

Correlation Coefficient ◽

Cox Regression ◽

Prognostic Significance ◽

Gene Signature ◽

Cancer Genome ◽

Survival Prediction

Background. Hepatocellular carcinoma (HCC) is a common cancer with an extremely high mortality rate. Therefore, there is an urgent need in screening key biomarkers of HCC to predict the prognosis and develop more individual treatments. Recently, AATF is reported to be an important factor contributing to HCC. Methods. We aimed to establish a gene signature to predict overall survival of HCC patients. Firstly, we examined the expression level of AATF in the Gene Expression Omnibus (GEO), the Cancer Genome Atlas (TCGA), and the International Union of Cancer Genome (ICGC) databases. Genes coexpressed with AATF were identified in the TCGA dataset by the Poisson correlation coefficient and used to establish a gene signature for survival prediction. The prognostic significance of this gene signature was then validated in the ICGC dataset and used to build a combined prognostic model for clinical practice. Results. Gene expression data and clinical information of 2521 HCC patients were downloaded from three public databases. AATF expression in HCC tissue was higher than that in matched normal liver tissues. 644 genes coexpressed with AATF were identified by the Poisson correlation coefficient and used to establish a three-gene signature (KIF20A, UCK2, and SLC41A3) by the univariate and multivariate least absolute shrinkage and selection operator Cox regression analyses. This three-gene signature was then used to build a combined nomogram for clinical practice. Conclusion. This integrated nomogram based on the three-gene signature can predict overall survival for HCC patients well. The three-gene signature may be a potential therapeutic target in HCC.

Download Full-text

The Landscape of Glycosyltransferase Gene Signature for Overall Survival Prediction in Hepatocellular Carcinoma

10.21203/rs.3.rs-114747/v1 ◽

2020 ◽

Author(s):

Qiang Cai ◽

Shizhe Yu ◽

Jian Zhao ◽

Duo Ma ◽

Long Jiang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Risk Score ◽

Prognostic Value ◽

Cox Regression ◽

Risk Groups ◽

Gene Signature ◽

Low Risk ◽

Regression Analyses ◽

Risk Patients

Abstract Background: Hepatocellular carcinoma (HCC) is heterogeneous disease occurring in the background of chronic liver diseases. The role of glycosyltransferase (GT) genes have recently been the focus of research associating with the development of tumors. However, the prognostic value of GT genes in HCC remains not elucidated. This study aimed to demonstrate the GT genes related to the prognosis of HCC through bioinformatics analysis.Methods: The GT genes signatures were identified from the training set of The Cancer Genome Atlas (TCGA) dataset using univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Then, we analyzed the prognostic value of GT genes signatures related to the overall survival (OS) of HCC patients. A prognostic model was constructed, and the risk score of each patient was calculated as formula, which divided HCC patients into high- and low-risk groups. Kaplan-Meier (K-M) and Receiver operating characteristic (ROC) curves were used to assess the OS of HCC patients. The prognostic value of GT genes signatures was further investigated in the validation set of TCGA database. Univariate and multivariate Cox regression analyses were performed to demonstrate the independent factors on OS. Finally, we utilized the gene set enrichment analysis (GSEA) to annotate the function of these genes between the two risk categories. Results: In this study, we identified and validated 4 GT genes as the prognostic signatures. The K-M analysis showed that the survival rate of the high-risk patients was significantly lower than that of the low-risk patients. The risk score calculated with 4 gene signatures could predict OS for 3-, 5-, and 7-year in patients with HCC, revealing the prognostic ability of these gene signature. In addition, Multivariate Cox regression analyses indicated that the risk score was an independent prognostic factor for HCC. Functional analysis further revealed that immune-related pathways were enriched, and immune status in HCC were different between the two risk groups.Conclusion: In conclusion, a novel GT genes signature can be used for prognostic prediction in HCC. Thus, targeting GT genes may be a therapeutic alternative for HCC.

Download Full-text

Identification and Validation of Ubiquitin-Specific Proteases as a Novel Prognostic Signature for Hepatocellular Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.629327 ◽

2021 ◽

Vol 11 ◽

Author(s):

Wenkai Ni ◽

Saiyan Bian ◽

Mengqi Zhu ◽

Qianqian Song ◽

Jianping Zhang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

High Risk ◽

Poor Prognosis ◽

Cox Regression ◽

Expression Profiles ◽

Prognostic Significance ◽

Cancer Genome ◽

Advanced Tumor Stage ◽

Genomic Alterations ◽

Advanced Tumor

PurposeUbiquitin-specific proteases (USPs), as a sub-family of deubiquitinating enzymes (DUBs), are responsible for the elimination of ubiquitin-triggered modification. USPs are recently correlated with various malignancies. However, the expression features and clinical significance of USPs have not been systematically investigated in hepatocellular carcinoma (HCC).MethodsGenomic alterations and expression profiles of USPs were investigated in CbioPortal and The Cancer Genome Atlas (TCGA) Liver hepatocellular carcinoma (LIHC) dataset. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were conducted to establish a risk signature for HCC prognosis in TCGA LIHC cohort. Subsequently, Kaplan-Meier analysis, receiver operating characteristic (ROC) curves and univariate/multivariate analyses were performed to evaluate the prognostic significance of the risk signature in TCGA LIHC and international cancer genome consortium (ICGC) cohorts. Furthermore, we explored the alterations of the signature genes during hepatocarcinogenesis and HCC progression in GSE89377. In addition, the expression feature of USP39 was further explored in HCC tissues by performing western blotting and immunohistochemistry.ResultsGenomic alterations and overexpression of USPs were observed in HCC tissues. The consensus analysis indicated that the USPs-overexpressed sub-Cluster was correlated with aggressive characteristics and poor prognosis. Cox regression with LASSO algorithm identified a risk signature formed by eight USPs for HCC prognosis. High-risk group stratified by the signature score was correlated with advanced tumor stage and poor survival HCC patients in TCGA LIHC cohort. In addition, the 8-USPs based signature could also robustly predict overall survival of HCC patients in ICGC(LIRI-JP) cohort. Furthermore, gene sets enrichment analysis (GSEA) showed that the high-risk score was associated with tumor-related pathways. According to the observation in GSE89377, USP39 expression was dynamically increased with hepatocarcinogenesis and HCC progression. The overexpression of USP39 was further determined in a local HCC cohort and correlated with poor prognosis. The co-concurrence analysis suggested that USP39 might promote HCC by regulating cell-cycle- and proliferation- related genes.ConclusionThe current study provided a USPs-based signature, highlighting its robust prognostic significance and targeted value for HCC treatment.

Download Full-text

Identification and validation of an immune-related prognostic signature for hepatocellular carcinoma

10.21203/rs.3.rs-25879/v1 ◽

2020 ◽

Author(s):

Xinxin Xia ◽

Hui Liu ◽

Yuejun Li

Keyword(s):

Hepatocellular Carcinoma ◽

Regression Analysis ◽

Cox Regression ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Immune Gene ◽

Regression Analyses ◽

Prognostic Signature ◽

Biological Mechanisms ◽

Cox Regression Analysis

Abstract Background: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality. The immune system plays vital roles in HCC initiation and progression. The present study aimed to construct an immune-gene related prognostic signature (IRPS) for predicting the prognosis of HCC patients. Methods: Gene expression data were retrieved from The Cancer Genome Atlas database. Univariate Cox regression analysis was carried out to identify differentially expressed genes that associated with overall survival. The IRPS was established via Lasso and multivariate Cox regression analysis. Both Cox regression analyses were conducted to determine the independent prognostic factors for HCC. Next, the association between the IRPS and clinical-related factors were evaluated. The prognostic values of the IRPS were further validated using the International Cancer Genome Consortium (ICGC) dataset. Gene set enrichment analyses (GSEA) were conducted to understand the biological mechanisms of the IRPS. Results: A total of 62 genes were identified to be candidate immune-related prognostic genes. Transcription factors-immunogenes network was generated to explore the interactions among these candidate genes. According to the results of Lasso and multivariate Cox regression analysis, we established an IRPS and confirmed its stability and reliability in ICGC dataset. The IRPS was significantly associated with advanced clinicopathological characteristics. Both Cox regression analyses revealed that the IRPS could be an independent risk factor influencing the prognosis of HCC patients. The relationships between the IRPS and infiltration immune cells demonstrated that the IRPS was associated with immune cell infiltration. GSEA identified significantly enriched pathways, which might assist in elucidating the biological mechanisms of the IRPS. Furthermore, a nomogram was constructed to estimate the survival probability of HCC patients.Conclusions: The IRPS was effective for predicting prognosis of HCC patients, which might serve as novel prognostic and therapeutic biomarkers for HCC.

Download Full-text

Gene Risk Signature of m6A Regulators, KIAA1429, YTHDF1, YTHDF2, METTL3 and Its Relationship with Immune Infiltration in Hepatocellular Carcinoma

10.21203/rs.3.rs-47948/v1 ◽

2020 ◽

Author(s):

Jingjing Guo ◽

Liwei Wang ◽

Hanfeng Xu ◽

Chuandong Zhu ◽

Jianning Wang ◽

...

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Cox Regression ◽

Clinical Information ◽

High Risk Group ◽

Consensus Clustering ◽

Immune Infiltration ◽

Infiltrating Cells ◽

Cancer Tissues ◽

The Relationship

Abstract Background: Hepatocellular carcinoma (HCC) is a tumor of the digestive system with high mortality. N6-methyladenosine (m6A) is one of the most common forms of mRNA modification. Tumor neoantigens play an important role in anti-tumor immune response and predict the clinical response of immunotherapy. There are few studies on the relationship between m6A regulators and immune infiltrating cells. The objective of this study was to determine the gene expression and prognostic value of m6A regulators in hepatocellular carcinoma. Further, we explored the relationship between m6A regulators and immune-infiltrating cells.Methods: 13 m6A regulators expressions in 374 cancer tissues and 50 normal tissues were analyzed using RNA-seq data and clinical information in the TCGA database. Survival package was used to analyze the survival of patients in the two groups, and the corresponding clinical characteristics and gene expression were analyzed using univariate and multivariate Cox regression. We evaluated the expression of KIAA1429, YTHDF1, YTHDF2, and METTL3 in HCC and its correlation with TIICs using TIMER and CIBERSORT.Results: Most m6A regulators had higher expression levels in 374 cancer tissues. We confirmed two groups of HCC patients using a consensus clustering method. The prognosis of the cluster 1 group was poor compared with that of the cluster 2 group. The m6A regulators, KIAA1429, YTHDF1, YTHDF2, and METTL3 are highly expressed in the high-risk group of HCC. Furthermore, it was found that four m6A regulators (KIAA1429, YTHDF1, YTHDF2, and METTL3) are closely related to the clinicopathological characteristics and poor prognostic marker of hepatocellular carcinoma. We analyzed the correlation between KIAA1429, YTHDF1, YTHDF2, and METTL3 expression and the level of immune invasion of HCC.Conclusion: KIAA1429, YTHDF1, YTHDF2, and METTL3 as m6A regulators may regulate the tumor microenvironment through tumor immune infiltration cells to exert immune anti-tumor effects. KIAA1429, YTHDF1, YTHDF2, and METTL3 as molecular markers providing a new target for therapy of HCC in the further.

Download Full-text

Analysis of the Expression and Prognostic Value of MSH2 in Pan-Cancer Based on Bioinformatics

BioMed Research International ◽

10.1155/2021/9485273 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Wenli Qiu ◽

Ke Ding ◽

Lusheng Liao ◽

Yongchang Ling ◽

Xiaoqiong Luo ◽

...

Keyword(s):

T Cells ◽

Prognostic Value ◽

Cox Regression ◽

Cancer Susceptibility ◽

Prognostic Significance ◽

Housekeeping Gene ◽

Significant Negative Correlation ◽

Immune Infiltration ◽

Potential Biomarker ◽

Pan Cancer

Background. MutS homolog 2 (MSH2), with the function of identifying mismatches and participating in DNA repair, is the “housekeeping gene” in the mismatch repair (MMR) system. MSH2 deficiency has been reported to enhance cancer susceptibility for the association of hereditary nonpolyposis colorectal cancer. However, the expression and prognostic significance of MSH2 have not been studied from the perspective of pan-cancer. Methods. The GTEx database was used to analyze the expression of MSH2 in normal tissues. The TCGA database was used to analyze the differential expression of MSH2 in pan-cancers. The prognostic value of MSH2 in pan-cancer was assessed using Cox regression and Kaplan-Meier analysis. Spearman correlations were used to measure the relationship between the expression level of MSH2 in pan-cancer and the level of immune infiltration, tumor mutational burden (TMB), and microsatellite instability (MSI). Results. MSH2 is highly expressed in most type of cancers and significantly correlated with prognosis. In COAD, KIRC, LIHC, and SKCM, the expression of MSH2 was significantly positively correlated with the abundance of B cells, CD4+ T cells, CD8+ T cells, dendritic cells, macrophages, and neutrophils. In THCA, MSH2 expression correlated with CD8+T Cell showed a significant negative correlation. MSH2 had significantly negative correlations with stromal score and immune score in a variety of cancers and significantly correlated with TMB and MSI of a variety of tumors. Conclusions. MSH2 may play an important role in the occurrence, development, and immune infiltration of cancer. MSH2 can emerge as a potential biomarker for cancer diagnosis and prognosis.

Download Full-text