Your browser doesn't support javascript.
loading
A bioinformatic analysis of the inhibin-betaglycan-endoglin/CD105 network reveals prognostic value in multiple solid tumors.
Listik, Eduardo; Horst, Ben; Choi, Alex Seok; Lee, Nam Y; Gyorffy, Balázs; Mythreye, Karthikeyan.
Afiliação
  • Listik E; Department of Pathology, Division of Molecular and Cellular Pathology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • Horst B; Department of Pathology, Division of Molecular and Cellular Pathology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • Choi AS; Department of Chemistry and Biochemistry, University of South Carolina, Columbia, South Carolina, United States of America.
  • Lee NY; Department of Pathology, Division of Molecular and Cellular Pathology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
  • Gyorffy B; Division of Pharmacology, Chemistry and Biochemistry, College of Medicine, University of Arizona, Tucson, Arizona, United States of America.
  • Mythreye K; TTK Cancer Biomarker Research Group, Institute of Enzymology, and Semmelweis University Department of Bioinformatics and 2nd Department of Pediatrics, Budapest, Hungary.
PLoS One ; 16(4): e0249558, 2021.
Article em En | MEDLINE | ID: mdl-33819300
ABSTRACT
Inhibins and activins are dimeric ligands belonging to the TGFß superfamily with emergent roles in cancer. Inhibins contain an α-subunit (INHA) and a ß-subunit (either INHBA or INHBB), while activins are mainly homodimers of either ßA (INHBA) or ßB (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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteoglicanas / Biomarcadores Tumorais / Receptores de Fatores de Crescimento Transformadores beta / Biologia Computacional / Redes Reguladoras de Genes / Endoglina / Inibinas / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteoglicanas / Biomarcadores Tumorais / Receptores de Fatores de Crescimento Transformadores beta / Biologia Computacional / Redes Reguladoras de Genes / Endoglina / Inibinas / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article