MUTYH is a potential prognostic biomarker and correlates with immune infiltrates in hepatocellular carcinoma

Abstract

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. The development of biomarkers for early detection and monitoring of HCC has not shown significant progress. Meanwhile, the second adenomatous polyposis-related gene, MUTYH, which encodes a DNA glycosylase, has been observed in its contribution to oxidative DNA damage repair. Abnormal expression of MUTYH can reduce cell survival rate. Therefore, this study investigated the usefulness of MUTYH in diagnosing and prognosis HCC.

Materials and methods: Using The Cancer Genome Atlas (TCGA) data, we analyzed the prognostic value of MUTYH in HCC. We used logistic regression, Wilcoxon signed-rank test, and Kruskal-Wallis test to examine MUTYH expression concerning clinical-pathologic characteristics. Univariate and multivariate Cox regression methods and Kaplan-Meier analysis were applied to determine the related prognostic factors of HCC. The enrichment analysis (GSEA) was used to determine the critical pathways associated with MUTYH. The single-sample gene set enrichment analysis (ssGSEA) was conducted to examine the correlation between MUTYH expression and cancer immune infiltration.

Results: The higher expression of MUTYH in HCC patients was associated with a poorer overall survival rate and a shorter disease-specific survival rate. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that all differentially expressed genes (DEGs) between the high and low expression levels of MUTYH significantly enriched in the trace ligand-receptor interaction, cell cycle, oocyte meiosis, gap junction, and DNA replication. Group analysis revealed the signals of their open access. The neuron system, M phase, DNA repair, Rho GTPase effector, and cell cycle checkpoints were significantly enriched. ssGSEA showed a positive correlation between MUTYH expression and the infiltration levels of Th2 cells, NK cells, and T helper cells. Moreover, a negative correlation was found between MUTYH expression and the infiltration levels of dendritic cells (DCs) and cytotoxic cells.

Conclusions: MUTYH expression levels were positively correlated with immune checkpoint gene expression levels in HCC tissues. The expression level of MUTYH was related to the prognosis of HCC and the immune infiltration of HCC.

Keywords: Bioinformatics; Hepatocellular carcinoma (HCC); Immune infiltrates; MUTYH; Prognostic biomarker.

Fig. 1

MUTYHexpression has been significantly up-regulated in HCC and many other cancers. (A) TCGA database analysis revealed that higher MUTYH expression levels have also been identified in 33 cancer tissues than in their adjacent normal tissue. ∗P < 0.05; ∗∗∗P < 0.001. (B, C) Based on the TCGA database, MUTYH mRNA expression is displayed in HCC tissues and adjacent tissues (P < 0.001). (D–F) According to GEO 112790, GEO 101685 and GEO 121248 databases, MUTYH mRNA expression levels are detected in HCC tissue and adjacent tissues (P < 0.001). (G) Volcano plots depict differential RNA expression. Based on median MUTYH levels, 424 HCC patients from the LIHC project were divided into groups with high- and low-MUTYH expression levels. (H) In the TCGA-LIHC project (n = 422), an analysis of MUTYH mRNA expression in HCC patients with high and low levels of expression is shown on a heat map in which 30 genes are correlated with MUTYH. Abbreviations: GEO, Gene Expression Omnibus; HCC, hepatocellular carcinoma; LIHC, liver hepatocellular carcinoma; TCGA, The Cancer Genome Atlas.

Fig. 2

MUTYH expression in HCC is associated with poor prognosis. (A) Data analysis using the Kaplan-Meier plotter in TCGA shows differences in OS of all patients. (B) Stages I and II of pathology patients, (C) stages III and IV of pathology patients, (D) T1 and T2 patients, (E) T3 and T4 patients, (F) Grade 1 and Grade 2 patients, and (G) Grade3 and Grade 4 patients. (H) From TCGA data, a nomogram that incorporates MUTYH with other prognostic factors in HCC. (I) Calibrating curve for nomograms. Abbreviations: HCC, hepatocellular carcinoma; OS, overall survival; TCGA, The Cancer Genome Atlas.

Fig. 3

MUTYH expression levels are associated with many clinicopathological characteristics of HCC patients. Association between the MUTYH expression and the (A) DSS event of HCC. (B) OS event of HCC. (C) T stage of HCC. (D) Histologic grade of HCC. (E) Pathologic stage of HCC. (F) Vascular invasion of HCC. The statistical test was performed using Wilcoxon rank sum test. ∗P < 0.05; ∗∗P < 0.01; ∗∗∗P < 0.001. Abbreviations: DSS, disease-specific survival; HCC, hepatocellular carcinoma; ns, not significant; OS, overall survival.

Fig. 4

Logistic regression analysis with univariate and multivariate variables. (A) The association between MUTYH expression and other clinicopathologic characteristics and OS in HCC patients in univariate and multivariate regression analysis. (B) Survival status and expression distribution of MUTYH. 0: dead; 1: alive. (C) A diagnostic ROC curve for MUTYH. (D) MUTYH ROC curve with time dependance. Abbreviations: HCC, hepatocellular carcinoma; OS, overall survival; ROC, receiver operation characteristic.

Fig. 5

Analysis of MUTYH enrichment in HCC. (A–C) The top 300 genes that were most positively associated with MUTYH have a significant Gene Ontology term associated with them, in addition to (A) biological processes, (B) cell components, and (C) molecular function. (D, E) Analysis of MUTYH gene sets, including the KEGG pathway, shows significant GSEA results (D) and Reactome pathways (E). (F) An interaction network between MUTYH and 50 co-interaction proteins. Abbreviations: HCC, hepatocellular carcinoma; KEGG, Kyoto Encyclopedia of Genes and Genomes; GSEA, Gene Set Enrichment Analysis.

Fig. 6

Analysis of immune infiltration and MUTYH expression. (A) Correlation between MUTYH and immune cell infiltration levels. Red indicates a positive correlation; blue indicates a negative correlation, and the deeper the color, the more significant the correlation. (B) Infiltration of immune cells in high MUTYH expression group and low MUTYH expression group in TCGA HCC. (C) Immune cells interact with tumor-infiltrating cells. ∗P < 0.05; ∗∗P < 0.01; ∗∗∗P < 0.001. Abbreviations: HCC, hepatocellular carcinoma; ns, not significant; TCGA, The Cancer Genome Atlas.

Fig. 7

Analyses of the correlation between MUTYH expression and immune checkpoint genes. Abbreviations: ADORA2, adenosine receptor A2a; ALK, anaplastic lymphoma kinase; BRAF, V-Raf murine sarcoma viral oncogene homolog B1; BTLA, B and T lymphocyte attenuator; BTNL2, butyrophilin like 2; CTLA4, cytotoxic T lymphocyte associated protein 4; EGFR, epidermal growth factor receptor; HAVCR2, hepatitis A virus cellular receptor 2; HHLA2, HERV-H LTR-associating 2; ICOS, inducible T cell costimulator; ICOSLG, inducible T cell costimulator ligand; IDO1, indoleamine 2,3-dioxygenase; K-RAS, kirsten rat sarcoma; LAG3, lymphocyte activating 3; LAIR1, leukocyte associated immunoglobulin like receptor 1; LGALS9, lectin galactoside binding soluble 9; PDCD1LG2, programmed cell death one ligand 2; PDCD1, programmed cell death 1; TIGIT, T cell immunoreceptor with Ig and ITIM domains; TMIGD2, transmembrane and immunoglobulin domain containing 2; TNFRSF, TNF receptor superfamily member; VSIR, V-set immunoregulatory receptor; VTCN1, V-set domain containing T cell activation inhibitor 1.