The prognostic value and immunological role of CD44 in pan-cancer study

Abstract

To investigate the correlation between cluster of differentiation-44 (CD44) expression and immunotherapy response and identify its possible predictive value in pan-cancer. Datasets of 33 cancer types from The Cancer Genome Atlas (TCGA) database were applied to investigate the relationship of CD44 expression with prognosis, tumor mutational burden (TMB), and microsatellite instability (MSI), and determine its potential prognostic value in pan-cancer. Patients were split into high-risk and low-risk cancer groups based on the survival outcomes of various cancer types. Additionally, the underlying mechanisms of CD44 in the tumor microenvironment (TME) were analyzed using ESTIMATE and CIBERSORT algorithms and Gene Set Enrichment Analysis (GSEA). Subsequently, the biological role of CD44 at single-cell level was investigated using CancerSEA database. Variable expression levels of CD44 between tumor and adjacent normal tissues were identified in pan-cancer datasets, further survival analysis revealed that CD44 expression was associated with multiple clinical annotations and survival indicators. Besides, the expression of CD44 was significantly associated with TMB and MSI in 10 types and 6 types of cancer, respectively, indicating it could be exploited as a potential biomarker predicting immunotherapy outcomes. Meanwhile, CD44 could influence several crucial immune cell-related pathways. and the results revealed by CancerSEA database denoted the correlation of CD44 with malignant phenotype and functional states, further indicating it can serve as a potential therapeutic target in cancer management. Our study demonstrated that CD44 shows great promise as a prognostic biomarker in numerous cancers, which will assist in developing new strategies in cancer management.

Figure 1

The expression level of CD44 in different cancers based on the TCGA database. CD44 cluster of differentiation-44, TCGA The Cancer Genome Atlas. *P < 0.05, **P < 0.01, and ***P < 0.005.

Figure 2

Correlation between CD44 expression level and OS (A), PFI (B), DFI (C), and DSS (D) as determined by Kaplan–Meier curve analyses. OS overall survival, PFI progression-free interval, DFI disease-free interval, DSS disease-specific survival.

Figure 3

Correlation between CD44 expression and different components in the high-risk cancer group (A) and low-risk cancer group (B).

Figure 4

Correlation between the infiltrating status of immune cells with CD44 expression in BLCA (A–D), KIRC (E–K), KIRP (L–P), LGG (Q), OV (R–U), and UCEC (V–Y). BLCA bladder urothelial carcinoma, KIRP kidney renal papillary cell carcinoma, LGG brain lower grade glioma, OV ovarian serous cystadenocarcinoma.

Figure 5

Correlation between CD44 expression and immune-related genes (A). Correlation between CD44 expression and immune checkpoint genes (B). *P < 0.05, **P < 0.01, and ***P < 0.005.

Figure 6

The correlation of CD44 with the functional state in cancers. The interactive bubble chart presents the correlation of CD44 with the functional state in 17 cancers (A). The correlation of CD44 with functional state in LUAD (B), GBM (C). LUAD lung adenocarcinoma, GBM glioblastoma multiforme. ∗∗∗P < 0.001.

Figure 7

GO functional terms (A) and KEGG pathway analysis (B) of CD44 in various cancer types in the high- and low-risk cancer groups. GO Gene ontology, KEGG Kyoto Encyclopedia of Genes and Genomes.