Integrative Analysis of MUC4 to Prognosis and Immune Infiltration in Pan-Cancer: Friend or Foe?

Abstract

MUC4, a transmembrane mucin, plays important roles in epithelial renewal and differentiation. Recent studies suggest that MUC4 has been implicated in pancreatic cancer pathogenesis and is expressed in various normal and cancer tissues. The underlying features of MUC4 across various cancer types may allow us to ensure appropriate treatment and patient monitoring. However, the contributions of MUC4 to pan-cancer have not been well characterized. In this study, we investigated the expression pattern and prognostic value of MUC4 across multiple databases. We further explored genomic and epigenetic alterations of MUC4, its association with proliferation and metastasis, and the correlation with immune infiltration in different cancers. Our results characterized the distinct expression profile and prognostic values of MUC4 in pan-cancer. Through examining its association with genomic alteration, tumor proliferation, and metastasis, as well as tumor infiltration, we revealed multiple function effects of MUC4. MUC4 may influence prognosis, proliferation, metastasis, and immune response in opposite directions. In conclusion, our findings suggested the necessity to more carefully evaluate MUC4 as a biomarker and therapeutic target and develop the new antibodies for cancer detection and intervention.

Keywords: bioinformatic analysis; mucin; pan-cancer; prognosis; tumor immune microenvironment.

FIGURE 1

MUC4 mRNA expression levels in pan-cancer. (A) Upregulated or downregulated expression of MUC4 in tumor tissues, compared with normal tissues of each cancer type in Oncomine. Red signifies the gene’s overexpression in the analyses represented by that cell in the table; blue represents the gene’s underexpression in those analyses. Intensity of color signifies the best rank of that gene in those analyses. The number in each cell represents the number of analyses that meet your thresholds within those analyses and cancer types. (B) MUC4 expression profile across all tumor samples and paired normal tissues in GEPIA2. Each dot represents a distinct tumor or normal sample.

FIGURE 2

Overall survival curves comparing the high and low expression of MUC4 and pathological stage plot across different cancer types. (A,B) Kaplan–Meier plot in PrognoScan panel (A) and Kaplan–Meier Plotter panel (B). The X-axis represents time, and the Y-axis represents survival rate. Ninety-five percent confidence intervals for each group are also indicated by dotted lines from PrognoScan. (C) Expression violin plot based on patient pathological stage in GEPIA2. HR, hazard ratio.

FIGURE 3

Genomic alteration and methylation of MUC4 across different cancer types. (A) Alteration frequency of MUC4 across different cancer types in cBioPortal. (B) The prognostic value of MUC4 alteration in LUSC and UCEC. (C) MUC4 promoter methylation level in tumor and normal samples of the TCGA database in UALCAN. The beta value indicates level of DNA methylation ranging from 0 (unmethylated) to 1 (fully methylated). Different beta value cutoffs have been considered to indicate hyper-methylation [beta value: 0.7–0.5] or hypo-methylation [beta-value: 0.3–0.25].

FIGURE 4

Functional effects of MUC4. (A) PPI network. Network nodes represent proteins and edges represent protein–protein associations, including both functional and physical protein associations. Line thickness indicates the strength of data support. (B) Correlation of MUC4 with proliferation in CVCDAP. (C) Enrichment of MUC4 in EMT in CVCDAP. Values of NES denote positive and negative enrichment. EMT, epithelial–mesenchymal transition.

FIGURE 5

Coefficients for correlation between MUC4 and immune cell infiltration of KIRC and PAAD in TIMER2.0.

FIGURE 6

Correlation between mRNA expression of MUC4 and immune markers of KIRC (A) and PAAD (B) in TIMER2.0. TAM, tumor-associated macrophages; M1, type-1 macrophage; M2, type-2 macrophage.

FIGURE 7

Relations between expression of MUC4 and three kinds of immunomodulators and chemokines in TISIDB. Spearman correlations between expression of MUC4 and immunoinhibitors (A), immunostimulators (B), MHCs (C), and chemokines (D) across human cancers.