Identifying therapeutic candidates for endometriosis through a transcriptomics-based drug repositioning approach Article Swipe
Tomiko Oskotsky
,
Arohee Bhoja
,
Daniel Bunis
,
Brian L. Le
,
Alice Tang
,
Idit Kosti
,
Christine Li
,
Sahar Houshdaran
,
Sushmita Sen
,
Júlia Vallvé-Juanico
,
Wanxin Wang
,
Erin Arthurs
,
Arpita Govil
,
Lauren Mahoney
,
Lindsey Lang
,
Brice Gaudillière
,
David K. Stevenson
,
Juan C. Irwin
,
Linda C. Giudice
,
Stacy L. McAllister
,
Marina Sirota
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.isci.2024.109388
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.isci.2024.109388
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.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.isci.2024.109388
- OA Status
- gold
- Cited By
- 10
- References
- 81
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392765049
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4392765049Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.isci.2024.109388Digital Object Identifier
- Title
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Identifying therapeutic candidates for endometriosis through a transcriptomics-based drug repositioning approachWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-03-01Full publication date if available
- Authors
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Tomiko Oskotsky, Arohee Bhoja, Daniel Bunis, Brian L. Le, Alice Tang, Idit Kosti, Christine Li, Sahar Houshdaran, Sushmita Sen, Júlia Vallvé-Juanico, Wanxin Wang, Erin Arthurs, Arpita Govil, Lauren Mahoney, Lindsey Lang, Brice Gaudillière, David K. Stevenson, Juan C. Irwin, Linda C. Giudice, Stacy L. McAllister, Marina SirotaList of authors in order
- Landing page
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https://doi.org/10.1016/j.isci.2024.109388Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1016/j.isci.2024.109388Direct OA link when available
- Concepts
-
Endometriosis, Drug repositioning, Medicine, Drug, Repurposing, Pharmacology, Internal medicine, Biology, EcologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 7, 2024: 3Per-year citation counts (last 5 years)
- References (count)
-
81Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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