Integrative Pan-Cancer Analysis Confirmed that FCGR3A is a Candidate Biomarker Associated With Tumor Immunity

Abstract

Background: Fc gamma receptor 3A (FCGR3A) encodes a receptor for the Fc portion of immunoglobulin G, which plays a significant role in the immune response. However, the role of FCGR3A in cancers remains unclear. This study aimed to visualize the prognostic landscape of FCGR3A in pan-cancer and investigate the relationship between FCGR3A expression and tumor microenvironment. Method: Based on the TCGA database, GTEx database, and GDSC database, we analyzed the expression of FCGR3A in pan-cancers and adjacent normal tissues and its relationship with prognosis, immune cells infiltration, immune-related genes, DNA mismatch repair (MMR) genes, DNA methylation, and drugs sensitivity. The gene alteration frequency of FCGR3A was acquired on the cBioportal website. Moreover, we constructed PPI networks, performed GO and KEGG analysis to illustrate the function, and signaling pathways of FCGR3A-related genes, and conducted gene set enrichment analysis (GSEA) of FCGR3A to further explore its potential biological functions. Result: The differential analysis results of the publicly available databases showed that FCGR3A was generally highly expressed in pan-cancer. Survival analysis revealed that FCGR3A predominated as a risk prognostic factor in most cancers. Additionally, the expression of FCGR3A was confirmed to be associated with several immune cells infiltration, multiple immune checkpoint genes, and DNA mismatch repair genes expression in generalized carcinoma. We also identified a negative correlation between FCGR3A and DNA methylation levels. Through GO/KEGG and GESA, we found that FCGR3A was involved in many pathologic and physiological processes, and was most closely related to tumor immune-related pathways. Drug sensitivity analysis showed that higher FCGR3A expression predicts a low IC50 value for the vast majority of drugs. Conclusions: FCGR3A may be an immune-oncogenic molecule that correlates with tumor immune infiltration levels and affects drug sensitivity, thus it can be served as a promising biomarker for cancer detection, prognosis, therapeutic design, and follow-up.

Keywords: FCGR3A; drug sensitivity; immune infiltration; pan-cancer analysis; prognosis; tumor biomarker; tumor microenvironment.

FIGURE 1

Expression level of FCGR3A gene in pan-cancer. (A) FCGR3A expression levels in tumors containing 20 TCGA tissues and paired adjacent non-cancerous tissues; (B) FCGR3A expression difference in 27 tumors integrating data of normal tissues in GTEx database and data of tumor tissues in TCGA database; (C) Based on the CPTAC dataset, the expression level of FCGR3A protein in normal and primary tumor tissues was analyzed. *p < 0.05; **p < 0.01; ***p < 0.001.

FIGURE 2

Comparison of FCGR3A gene expression between normal and tumor tissues (left) and immunohistochemistry images in normal (middle) and tumor (right) tissues. (A) Skin; (B) Testis; (C) Lung. *p < 0.05; **p < 0.01; ***p < 0.001.

FIGURE 3

The association between FCGR3A expression levels and prognosis and tumor pathological stage. (A) Overall survival (OS); (B) Disease specific survival (DSS); (C) Progression-free survival (PFS); (D) Differential expression of FCGR3A in different stages.

FIGURE 4

Correlation analysis of FCGR3A expression with immune cells infiltration. (A) The scatter plot showed a correlation between FCGR3A and the levels of infiltration of six major immune cells in CESC, COAD, KIRP, and UCEC; (B) Heat map showed the relationship between FCGR3A expression and 25 immune cell markers. CESC, cervical squamous cell carcinoma and endocervical adenocarcinoma; COAD, colon adenocarcinoma; KIRP, kidney renal papillary cell carcinoma; UCEC, uterine corpus endometrial carcinoma. *p < 0.05; **p < 0.01; ***p < 0.001.

FIGURE 5

Correlation analysis of FCGR3A expression with immune-related genes. (A) immunosuppressive related genes; (B) chemokine genes. *p < 0.05; **p < 0.01; ***p < 0.001.

FIGURE 6

Mutation characteristics of FCGR3A in different TCGA tumors and its relationship with DNA mismatch repair genes (MMRs). (A) Alteration frequency of FCGR3A mutation types in different tumors; (B) Heat maps showed the association of APOC1 expression with expression levels of four MMRs genes in various cancers. *p < 0.05; **p < 0.01; ***p < 0.001.

FIGURE 7

Correlation between FCGR3A expression and gene promoter methylation. (A) Bladder urothelial carcinoma (BLCA); (B) Breast invasive carcinoma (BRCA); (C) Cholangiocarcinoma (CHOL); (D) Colon adenocarcinoma (COAD); (E) Esophageal carcinoma (ESCA); (F) Head and neck squamous cell carcinoma (HNSC); (G) Kidney renal clear cell carcinoma (KIRC); (H) liver hepatocellular carcinoma (LIHC); (I) Lung adenocarcinoma (LUAD); (J) Lung squamous cell carcinoma (LUSC); (K) Pancreatic adenocarcinoma (PAAD); (L) Prostate adenocarcinoma (PRAD).

FIGURE 8

Protein-protein interaction (PPI) network, gene ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of FCGR3A-related genes. (A,B) PPI network; (C) GO analyses; (D) KEGG analysis.

FIGURE 9

The 5 most relevant signaling pathways of FCGR3A’s GSEA in the GO dataset. (A) Glioblastoma multiforme (GBM); (B) Kidney renal clear cell carcinoma (KIRC); (C) brain lower grade glioma (LGG); (D) Prostate adenocarcinoma (PRAD); (E) Skin cutaneous melanoma (SKCM); (F) Thyroid carcinoma (THCA); (G) Thymoma (THYM); (H) Uveal melanoma (UVM).

FIGURE 10

Relationship between FCGR3A expression and drug sensitivity. (A) The top six negatively correlated. (B) The only six positively correlated. (C) The difference of drug sensitivity of six commonly used anticancer drugs (5-fluorouracil, Camptothecin, Etoposide, Doxorubicin, Gemcitabine, and Methotrexate) in high and low FCGR3A expression groups was shown in the forms of boxplot charts. *p < 0.05; **p < 0.01; ***p < 0.001.