Systematic Pan-Cancer Analysis of KLRB1 with Prognostic Value and Immunological Activity across Human Tumors

Abstract

Introduction: KLRB1 is a gene encoding CD161 expressed in NK cells and some T cell subsets. At present, KLRB1 is believed to affect tumorigenesis and development by regulating the cytotoxicity of NK cells in several cancers. However, there is a lack of systematic reviews of KLRB1 in a variety of malignancies.

Objectives: Hence, our research is aimed at providing a relatively comprehensive understanding of the role of KLRB1 in different types of cancer, paving the way for further research on the molecular mechanism and immunotherapy potential of KLRB1.

Methods: In this study, we used relevant public databases, including TCGA (The Cancer Genome Atlas), GEO (Gene Expression Omnibus), CCLE (Cancer Cell Line Encyclopedia), GTEx (Genotype Tissue-Expression), and HPA (Human Protein Atlas), to perform a pan-cancer analysis of KLRB1 across 33 types of cancer. We explored the potential molecular mechanism of KLRB1 in clinical prognosis and tumor immunity from the aspects of gene expression, survival status, clinical phenotype, immune infiltration, immunotherapy response, and chemotherapeutic drug sensitivity.

Results: KLRB1 was downregulated in 13 cancers while upregulated in kidney cancer. Patients with high expression of KLRB1 have a better prognosis in most types of cancer. Moreover, the KLRB1 expression level is related to TMB and MSI and related to various immune signatures of tumor. The expression of KLRB1 can affect tumor immune cell infiltration. KLRB1 expression level can also affect the sensitivity of chemotherapy drugs.

Conclusions: KLRB1 may be a prognostic and immunological biomarker across tumors. At the same time, KLRB1 expression can reflect the sensitivity of cancer patients to chemotherapy drugs. KLRB1 may become a new target for immunotherapy.

Figure 1

Expression of KLRB1 in normal and tumor tissues. (a) KLRB1 expression across 31 regular tissues and (b) 21 tumor cell lines. (c) Differences in KLRB1 expression between normal and tumor tissues in 33 tumor types from TCGA. p values are based on the Wilcoxon rank-sum test. (d) Significant difference of KLRB1 expression between normal and tumor tissues in 11 tumors based on GEO datasets. p values are based on the Wilcoxon rank-sum test. ^∗p < 0.05, ^∗∗p < 0.01, and ^∗∗∗p < 0.001. (e) Immunohistochemistry images. The expression of KLRB1 protein in tumor tissues is significantly lower than that in normal tissues across 6 types of cancer.

Figure 2

The relationship between KLRB1 expression and patient prognosis. (a) Univariate Cox regression of KLRB1 expression for overall survival (OS) in 33 cancers. (b) Univariate Cox regression of KLRB1 expression for disease-specific survival (DSS) in 33 cancers. (c) The Kaplan–Meier curves of OS in the low- and high-expression KLRB1 groups. (d) The Kaplan–Meier curves of DSS in the low- and high-expression KLRB1 groups.

Figure 3

Relationship between KLRB1 expression and clinical phenotypes in different cancers. Association between KLRB1 expression and (a) age and (b) stage.

Figure 4

The relationship between KLRB1 expression and the TMB and MSI and MMR gene expression. (a) Relationship between KLRB1 and TMB (red curve of the radar chart indicates the correlation coefficient, and blue numbers indicate the range). (b) Relationship between KLRB1 and MSI (blue curve of the radar chart indicates the correlation coefficient, and green numbers indicate the range). (c) Relationship between KLRB1 expression and MMR genes (for each pair, top left triangle represents the p value, and bottom right triangle indicates the correlation coefficient). ^∗p < 0.05, ^∗∗p < 0.01, and ^∗∗∗p < 0.001.

Figure 5

Differences in KLRB1 expression are associated with differences in distribution of immune cell infiltration. (a) The relationship between KLRB1 expression and the degree of immune cell infiltration in different cancers (evaluated using the CIBERSORT method). For each small grid, the upper left triangle represents the p value, and the lower right triangle represents the correlation coefficient. Distribution infiltration of (b) CD8+ T and CD4+ T cells, (c) B cells, and (d) macrophages (using marker genes' expression analysis) stratified by KLRB1 high- and low-expression groups. ^∗p < 0.05, ^∗∗p < 0.01, and ^∗∗∗p < 0.001.

Figure 6

The relationship between KLRB1 and immune-related genes. (a) KLRB1 expression is associated with various immune signatures, among the 33 cancer types in TCGA, including immunocytolytic activity (CYT), HLA, interferon (IFN), and TILs. (b) The heat map of coexpression between KLRB1 and immune-related genes. For each small grid, the upper left triangle represents the p value, and the lower right triangle represents the correlation coefficient. ^∗p < 0.05, ^∗∗p < 0.01, and ^∗∗∗p < 0.001.

Figure 7

KLRB1 can be used as a potential indicator of response to immunotherapy. (a) Enriched Gene Ontology (GO) biological function of KLRB1 across various cancers. (b) Enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of KLRB1 across various cancers. Comparison of the correlation between KLRB1 expression, TMB, and glycolytic activity and (c) the immune score and (d) cytolytic activity. (e) Correlation between KLRB1 and the expression of checkpoint genes in 33 cancers. (f) The distribution of the expression level of checkpoint genes stratified by high and low KLRB1 expression for 33 cancers. ^∗p < 0.05, ^∗∗p < 0.01, and ^∗∗∗p < 0.001.

Figure 8

The correlation between KLRB1 expression and chemotherapeutic drug sensitivity. (a) Correlation between KLRB1 expression and cisplatin sensitivity. (b) Correlation between KLRB1 expression and doxorubicin sensitivity.