Journal Article Systematic Review Epublish 2 citations
PubMed: 36120440 DOI: 10.3389/fendo.2022.869053
Exploration of the core protein network under endometriosis symptomatology using a computational approach.
Front Endocrinol (Lausanne) 13:869053
Authors: Fatima El Idrissi, Mathilde Fruchart, Karim Belarbi, Antoine Lamer, Emilie Dubois-Deruy, Mohamed Lemdani, Assi L N'Guessan, Benjamin C Guinhouya, Djamel Zitouni
Affiliations
- Univ. Lille, UFR 3S, Faculté Ingénierie et Management de la Santé, Lille, France. Univ. Lille, UFR 3S, Faculté de Pharmacie, Lille, France.
- Univ. Lille, UFR 3S, Faculté Ingénierie et Management de la Santé, Lille, France.
- Univ. Lille, CHU Lille, ULR 2694 - METRICS, Lille, France.
- Univ. Lille, UFR 3S, Faculté de Pharmacie, Lille, France.
- Univ. Lille, Inserm, CHU-Lille, Lille Neuroscience & Cognition, Lille, France.
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167 - RID-AGE - Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France.
- Univ. Lille, UMR CNRS 8524, Laboratoire Paul Painlevé, Villeneuve d'Ascq, Cedex, France.
Abstract
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), (ii) Signaling by Interleukins (p = 1.11 x 10), (iii) Cytokine signaling in Immune system (p = 1.11 x 10), and (iv) Interleukin-10 signaling (p = 5.66 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.
MeSH
Endometriosis, Early Diagnosis, Endometrium, Infertility, Female, Systems Biology, Signs And Symptoms, Signal Transduction, Diagnosis