Identifying GPSM Family Members as Potential Biomarkers in Breast Cancer: A Comprehensive Bioinformatics Analysis

• Published in: Biomedicines 2021-09, Vol.9 (9), p.1144
• Main Authors: Dang, Huy-Hoang, Ta, Hoang Dang Khoa, Nguyen, Truc T. T., Anuraga, Gangga, Wang, Chih-Yang, Lee, Kuen-Haur, Le, Nguyen Quoc Khanh
• Format: Article
• Language: English
• Subjects: Bioinformatics; biomarker; Biomarkers; Breast cancer; Cell cycle; Cell division; Cell surface; Datasets; functional enrichment analysis; G protein-coupled receptors; G-protein signaling modulator; Gene expression; Genomics; Immunomodulation; Immunotherapy; Infiltration; Medical prognosis; Metastases; Ontology; Protein expression; Proteins; Survival analysis; Tumors
• ISSN: 2227-9059; 2227-9059
• DOI: 10.3390/biomedicines9091144

G-protein signaling modulators (GPSMs) are a class of proteins involved in the regulation of G protein-coupled receptors, the most abundant family of cell-surface receptors that are crucial in the development of various tumors, including breast cancer. This study aims to identify the potential therapeutic and prognostic roles of GPSMs in breast cancer. Oncomine and UALCAN databases were queried to determine GPSM expression levels in breast cancer tissues compared to normal samples. Survival analysis was conducted to reveal the prognostic significance of GPSMs in individuals with breast cancer. Functional enrichment analysis was performed using cBioPortal and MetaCore platforms. Finally, the association between GPSMs and immune infiltration cells in breast cancer was identified using the TIMER server. The experimental results then showed that all GPSM family members were significantly differentially expressed in breast cancer according to Oncomine and UALCAN data. Their expression levels were also associated with advanced tumor stages, and GPSM2 was found to be related to worse distant metastasis-free survival in patients with breast cancer. Functional enrichment analysis indicated that GPSMs were largely involved in cell division and cell cycle pathways. Finally, GPSM3 expression was correlated with the infiltration of several immune cells. Members of the GPSM class were differentially expressed in breast cancer. In conclusion, expression of GPSM2 was linked with worse distant metastasis-free outcomes, and hence could potentially serve as a prognostic biomarker. Furthermore, GPSM3 has potential to be a possible target for immunotherapy for breast cancer.