Research Paper Volume 15, Issue 21 pp 12021—12067

Utility of G protein-coupled oestrogen receptor 1 as a biomarker for pan-cancer diagnosis, prognosis and immune infiltration: a comprehensive bioinformatics analysis

Yu-Chao Fan1, *, , Wen Wu3, *, , Xue-Feng Leng2, , Hong-Wei Zhang1, ,

  • 1 Department of Anesthesiology, Sichuan Cancer Center, Sichuan Cancer Hospital and Institute, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, China
  • 2 Division of Thoracic Surgery, Sichuan Cancer Center, Sichuan Cancer Hospital and Institute, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, China
  • 3 Department of Anesthesiology, Xichang People’s Hospital, Xichang, Sichuan, China
* Equal contribution and co-first authors

Received: January 15, 2023       Accepted: October 2, 2023       Published: November 2, 2023      

https://doi.org/10.18632/aging.205162
How to Cite

Copyright: © 2023 Fan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: The G protein-coupled oestrogen receptor (GPER) 1 mediates non-genomic oestrogen-related signalling and plays an important role in the regulation of cell growth and programmed cell death through multiple downstream pathways. Despite the increasing interest in the role of GPER1 in cancer development, no pan-cancer analysis has been available for GPER1.

Methods: In this study we performed a comprehensive analysis of the role of GPER1 in pan-cancer via Human Protein Atlas (HPA), The Cancer Genome Atlas (TCGA), University of California, Santa Cruz Xena (UCSC XENA), Genotype-Tissue Expression (GTEx), MethSurv, The University of Alabama at Birmingham CANcer data analysis Portal (UALCAN), cBioPortal, STRING and TISIDB detabases, followed by enrichment analysis using R software.

Results: GPER1 was widely expressed in tissues and organs and differed in expression from normal tissue in a variety of cancers. In diagnostic assessment, it’s Area Under the Curve (AUC) surpassed 0.9 in nine cancer types. Survival analysis showed that GPER1 was correlated with the prognosis of 11 cancer types. Moreover, GPER1 expression was associated with immune infiltration in multiple cancers.

Conclusions: In summary, GPER1 has good diagnostic or prognostic value across various malignancies. Together with its extensive correlation with immune components, the aforementioned results suggests that GPER1 shows promise in tumour diagnosis and prognosis, providing new ideas for precise and personalised anti-tumour strategies.

Abbreviations

GPER1: G protein-coupled oestrogen receptor 1; ACC: Adrenocortical carcinoma; BLCA: Bladder Urothelial Carcinoma; BRCA: Breast invasive carcinoma; CESC: Cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOL: Cholangiocarcinoma; COAD: Colon adenocarcinoma; DLBC: Lymphoid Neoplasm Diffuse Large B-cell Lymphoma; ESCA: Esophageal carcinoma; GBM: Glioblastoma multiforme; HNSC: Head and Neck squamous cell carcinoma; KICH: Kidney Chromophobe; KIRC: Kidney renal clear cell carcinoma; KIRP: Kidney renal papillary cell carcinoma; LAML: Acute Myeloid Leukemia; LGG: Brain Lower Grade Glioma; LIHC: Liver hepatocellular carcinoma; LUAD: Lung adenocarcinoma; LUSC: Lung squamous cell carcinoma; MESO: Mesothelioma; OS: Osteosarcoma; OV: Ovarian serous cystadenocarcinoma; OSCC: Oral Squamous Cell Carcinoma; PAAD: Pancreatic adenocarcinoma; PCPG: Pheochromocytoma and Paraganglioma; PRAD: Prostate adenocarcinoma; READ: Rectum adenocarcinoma; SARC: Sarcoma; SKCM: Skin Cutaneous Melanoma; STAD: Stomach adenocarcinoma; TGCT: Testicular Germ Cell Tumors; THCA: Thyroid carcinoma; THYM: Thymoma; UCSC XENA: University of California, Santa Cruz Xena; UCEC: Uterine Corpus Endometrial Carcinoma; UCS: Uterine Carcinosarcoma; UVM: Uveal Melanoma; The UALCAN: University of Alabama at Birmingham CANcer data analysis Portal; HPA: Human Protein Atlas; TCGA: The Cancer Genome Atlas; GTEx: Genotype-Tissue Expression; TILs: tumour-infiltrating lymphocytes; MHC: major histocompatibility complex; TME: tumour microenvironment; FPKM: Per Kilobase per Million; TPM: transcripts per million; ROC: Receiver Operator Characteristic; AUC: Area under Curve; YI: Youden’s index; K-M: Kaplan–Meier; BH: Benjamini-Hochberg; FDR: False Discovery Rate; OS: overall survival; DFS: disease-free survival; BP: biological process; MF: molecular function; CC: cellular component; DSS: disease-specific survival; HR: Hazard ratio; CI: Confidence Interval; GGI: Gene-Gene Interaction; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; DEGs: different expression genes; GSEA: Gene set enrichment analysis; PPI: Protein-Protein Interaction; ER: oestrogen receptors; MHC: major histocompatibility complex; TILs: tumor-infiltrating lymphocytes.