Exploration of the core protein network under endometriosis symptomatology using a computational approach.
cell signaling
endometrium
female infertility
systems biology
text-mining
Journal
Frontiers in endocrinology
ISSN: 1664-2392
Titre abrégé: Front Endocrinol (Lausanne)
Pays: Switzerland
ID NLM: 101555782
Informations de publication
Date de publication:
2022
2022
Historique:
received:
09
02
2022
accepted:
17
08
2022
entrez:
19
9
2022
pubmed:
20
9
2022
medline:
21
9
2022
Statut:
epublish
Résumé
Endometriosis is defined by implantation and invasive growth of endometrial tissue in extra-uterine locations causing heterogeneous symptoms, and a unique clinical picture for each patient. Understanding the complex biological mechanisms underlying these symptoms and the protein networks involved may be useful for early diagnosis and identification of pharmacological targets. In the present study, we combined three approaches (i) a text-mining analysis to perform a systematic search of proteins over existing literature, (ii) a functional enrichment analysis to identify the biological pathways in which proteins are most involved, and (iii) a protein-protein interaction (PPI) network to identify which proteins modulate the most strongly the symptomatology of endometriosis. Two hundred seventy-eight proteins associated with endometriosis symptomatology in the scientific literature were extracted. Thirty-five proteins were selected according to degree and betweenness scores criteria. The most enriched biological pathways associated with these symptoms were (i) Interleukin-4 and Interleukin-13 signaling (p = 1.11 x 10 Our study identified some key proteins with the ability to modulate endometriosis symptomatology. Our findings indicate that both pro- and anti-inflammatory biological pathways may play important roles in the symptomatology of endometriosis. This approach represents a genuine systemic method that may complement traditional experimental studies. The current data can be used to identify promising biomarkers for early diagnosis and potential therapeutic targets.
Sections du résumé
Background
Endometriosis is defined by implantation and invasive growth of endometrial tissue in extra-uterine locations causing heterogeneous symptoms, and a unique clinical picture for each patient. Understanding the complex biological mechanisms underlying these symptoms and the protein networks involved may be useful for early diagnosis and identification of pharmacological targets.
Methods
In the present study, we combined three approaches (i) a text-mining analysis to perform a systematic search of proteins over existing literature, (ii) a functional enrichment analysis to identify the biological pathways in which proteins are most involved, and (iii) a protein-protein interaction (PPI) network to identify which proteins modulate the most strongly the symptomatology of endometriosis.
Results
Two hundred seventy-eight proteins associated with endometriosis symptomatology in the scientific literature were extracted. Thirty-five proteins were selected according to degree and betweenness scores criteria. The most enriched biological pathways associated with these symptoms were (i) Interleukin-4 and Interleukin-13 signaling (p = 1.11 x 10
Conclusion
Our study identified some key proteins with the ability to modulate endometriosis symptomatology. Our findings indicate that both pro- and anti-inflammatory biological pathways may play important roles in the symptomatology of endometriosis. This approach represents a genuine systemic method that may complement traditional experimental studies. The current data can be used to identify promising biomarkers for early diagnosis and potential therapeutic targets.
Identifiants
pubmed: 36120440
doi: 10.3389/fendo.2022.869053
pmc: PMC9478376
doi:
Substances chimiques
Interleukin-13
0
Interleukin-10
130068-27-8
Interleukin-4
207137-56-2
Types de publication
Journal Article
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
869053Informations de copyright
Copyright © 2022 El Idrissi, Fruchart, Belarbi, Lamer, Dubois-Deruy, Lemdani, N’Guessan, Guinhouya and Zitouni.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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