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A bioinformatic analysis of the inhibin-betaglycan-endoglin/CD105 network reveals prognostic value in multiple solid tumors.
- Source :
-
PloS one [PLoS One] 2021 Apr 05; Vol. 16 (4), pp. e0249558. Date of Electronic Publication: 2021 Apr 05 (Print Publication: 2021). - Publication Year :
- 2021
-
Abstract
- Inhibins and activins are dimeric ligands belonging to the TGFβ superfamily with emergent roles in cancer. Inhibins contain an α-subunit (INHA) and a β-subunit (either INHBA or INHBB), while activins are mainly homodimers of either βA (INHBA) or βB (INHBB) subunits. Inhibins are biomarkers in a subset of cancers and utilize the coreceptors betaglycan (TGFBR3) and endoglin (ENG) for physiological or pathological outcomes. Given the array of prior reports on inhibin, activin and the coreceptors in cancer, this study aims to provide a comprehensive analysis, assessing their functional prognostic potential in cancer using a bioinformatics approach. We identify cancer cell lines and cancer types most dependent and impacted, which included p53 mutated breast and ovarian cancers and lung adenocarcinomas. Moreover, INHA itself was dependent on TGFBR3 and ENG/CD105 in multiple cancer types. INHA, INHBA, TGFBR3, and ENG also predicted patients' response to anthracycline and taxane therapy in luminal A breast cancers. We also obtained a gene signature model that could accurately classify 96.7% of the cases based on outcomes. Lastly, we cross-compared gene correlations revealing INHA dependency to TGFBR3 or ENG influencing different pathways themselves. These results suggest that inhibins are particularly important in a subset of cancers depending on the coreceptor TGFBR3 and ENG and are of substantial prognostic value, thereby warranting further investigation.<br />Competing Interests: NO authors have competing interests.
- Subjects :
- Biomarkers, Tumor genetics
Endoglin genetics
Humans
Inhibins genetics
Neoplasms genetics
Neoplasms metabolism
Prognosis
Proteoglycans genetics
Receptors, Transforming Growth Factor beta genetics
Survival Rate
Biomarkers, Tumor metabolism
Computational Biology methods
Endoglin metabolism
Gene Regulatory Networks
Inhibins metabolism
Neoplasms pathology
Proteoglycans metabolism
Receptors, Transforming Growth Factor beta metabolism
Subjects
Details
- Language :
- English
- ISSN :
- 1932-6203
- Volume :
- 16
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- PloS one
- Publication Type :
- Academic Journal
- Accession number :
- 33819300
- Full Text :
- https://doi.org/10.1371/journal.pone.0249558