Your browser doesn't support javascript.
loading
Identifying therapeutic candidates for endometriosis through a transcriptomics-based drug repositioning approach.
Oskotsky, Tomiko T; Bhoja, Arohee; Bunis, Daniel; Le, Brian L; Tang, Alice S; Kosti, Idit; Li, Christine; Houshdaran, Sahar; Sen, Sushmita; Vallvé-Juanico, Júlia; Wang, Wanxin; Arthurs, Erin; Govil, Arpita; Mahoney, Lauren; Lang, Lindsey; Gaudilliere, Brice; Stevenson, David K; Irwin, Juan C; Giudice, Linda C; McAllister, Stacy L; Sirota, Marina.
Afiliación
  • Oskotsky TT; Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA.
  • Bhoja A; Department of Pediatrics, UCSF, San Francisco, CA, USA.
  • Bunis D; Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA.
  • Le BL; Carnegie Mellon University, Pittsburgh, PA, USA.
  • Tang AS; Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA.
  • Kosti I; Department of Pediatrics, UCSF, San Francisco, CA, USA.
  • Li C; Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA.
  • Houshdaran S; Department of Pediatrics, UCSF, San Francisco, CA, USA.
  • Sen S; Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA.
  • Vallvé-Juanico J; Department of Pediatrics, UCSF, San Francisco, CA, USA.
  • Wang W; Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA.
  • Arthurs E; Department of Pediatrics, UCSF, San Francisco, CA, USA.
  • Govil A; Bakar Computational Health Sciences Institute, UCSF, San Francisco, CA, USA.
  • Mahoney L; Department of Obstetrics, Gynecology and Reproductive Sciences, UCSF, San Francisco, CA, USA.
  • Lang L; Department of Obstetrics, Gynecology and Reproductive Sciences, UCSF, San Francisco, CA, USA.
  • Gaudilliere B; Department of Obstetrics, Gynecology and Reproductive Sciences, UCSF, San Francisco, CA, USA.
  • Stevenson DK; Department of Obstetrics, Gynecology and Reproductive Sciences, UCSF, San Francisco, CA, USA.
  • Irwin JC; Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, USA.
  • Giudice LC; Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, USA.
  • McAllister SL; Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, USA.
  • Sirota M; Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, USA.
iScience ; 27(4): 109388, 2024 Apr 19.
Article en En | MEDLINE | ID: mdl-38510116
ABSTRACT
Existing medical treatments for endometriosis-related pain are often ineffective, underscoring the need for new therapeutic strategies. In this study, we applied a computational drug repurposing pipeline to stratified and unstratified disease signatures based on endometrial gene expression data to identify potential therapeutics from existing drugs, based on expression reversal. Of 3,131 unique genes differentially expressed by at least one of six endometriosis signatures, only 308 (9.8%) were in common; however, 221 out of 299 drugs identified, (73.9%) were shared. We selected fenoprofen, an uncommonly prescribed NSAID that was the top therapeutic candidate for further investigation. When testing fenoprofen in an established rat model of endometriosis, fenoprofen successfully alleviated endometriosis-associated vaginal hyperalgesia, a surrogate marker for endometriosis-related pain. These findings validate fenoprofen as a therapeutic that could be utilized more frequently for endometriosis and suggest the utility of the aforementioned computational drug repurposing approach for endometriosis.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: IScience Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: IScience Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos