Biomarker Networks Might Help Reveal the Mechanism Behind Endometriosis

Protein-protein interactions and endometriosis-related genes are important components of biomarker networks, which have the potential to change the future of endometriosis research.

Key Points

Highlights:

• This study created disease interaction networks that include human protein-protein interactions (PPI) and genes that are known to cause endometriosis.
• The end goal was to identify biomarkers and interaction networks involved in endometriosis disease progression because it would help researchers understand the process by which the disease develops.

Importance:

• More efficient targeted therapies and treatments can be developed if researchers understand the mechanisms that promote endometriosis.

What’s done here?

• For seed gene selection, the researchers used Genotator and DisGeNET to identify genes related to endometriosis.
• The next step of the process was disease-gene network construction. PPIs were developed when the endometriosis-related genes were submitted to atBioNet, a network analysis tool. The SCAN algorithm was then utilized to find modules that are functional. This algorithm can also be used to assess the gene networks.
• The atBioNet Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis component was used to determine the roles of the endometriosis-related genes. KEGG pathways that were overrepresented were ranked using Fisher’s exact tests.
• Literature mining was conducted using the PubMed Database and select keywords. The search led researchers to various articles that were manually screened.  

Key results:

• There were 100 common input genes. Of these input genes, 96 genes were found in GenBank and could be actively mapped using network clustering to the six major subnetwork modules.
• The modules are as follows:
  • ModuleA – A significant majority of the pathways in this module are connected to cancer cell proliferation. This model also deals with:
    • cancer pathways
    • the cell cycle
    • oocyte meiosis
    • Wnt signaling pathway
    • adherens junctions.
  • Module B – This module is linked to the immune system and infectious diseases. This model also deals with:
    • Cytokine-cytokine receptor interaction
    • Mitogen-activated protein kinase signaling pathway
    • Janus kinase-signal transducer and activator of transcription signaling pathway
    • Intestinal immune network for immunoglobulin A production
    • Toll-like receptor signaling pathways
  • Module C – This module has pathways that deal primarily with immune and metastasis. This model also deals with:
    • Complement and coagulation cascades
    • Extracellular matrix receptor interactions
    • Focal adhesion
    • Proteasome and hematopoietic cell lineages corresponding with immune and metastasis
  • Module D – This module has enriched pathways that correspond to inflammatory processes. This includes:
    • Phagosome
    • Cell adhesion molecules
    • Antigen processing and presentation
    • Cytotoxicity mediated by natural killer cells
    • T cell receptor signaling pathways
    • Intestinal immune network for immunoglobulin A production
  • Module E – This last module deals with replication and repair. This includes:
    • DNA repair
    • Base excision repair
    • Nucleotide excision repair
    • Mismatch repair
    • Homologous recombination
  • The study identified known and currently unknown biomarkers.
    • 15 genes were previously reported as endometriosis biomarkers.
  • In conclusion, this study has identified numerous factors and mechanisms that could promote endometriosis disease progression.
  • The authors of the study recommend that further experimentation is conducted to better understand the functions and interactions associated with endometriosis genes in related modules.  

Limitations of the study:

• This study is mostly conducted using virtual tools. Further experimentation in humans is required to confirm the findings of the study.

Lay Summary

Scientists have yet to uncover the molecular mechanisms that promote endometriosis disease progression. Xiao et al. recently published a study in Experimental and Therapeutic Medicine where they hoped to shed new light on the pathogenesis of endometriosis. In their study titled “Protein‑protein interaction analysis to identify biomarker networks for endometriosis,” the authors built several disease interaction networks consisting of human protein-protein interactions (PPI) and endometriosis-related genes. The ultimate goal of the project was to identify potential biomarkers and interaction networks that are important for the development of endometriosis.

The experimental process consisted of a few critical steps. The first step was called a seed gene selection where researchers consulted tools like Genotator and DisGeNET to identify endometriosis-related genes. The next step was the disease-gene network construction where researchers used the genes above and atBioNet to develop PPIs. The third part of the process was pathway enrichment analysis where the researchers use the atBioNet Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis component to elucidate gene function. The last part of the process was a literature search. This search was completed using PubMed and a few choice keywords. The search yielded various publications, which the researchers studied.

There were 100 conventional input genes, and 96 of these genes could be mapped, using network clustering, to one of six network modules. The six network modules are A, which is primarily related with cancer proliferation; B, which is connected with the immune system and infectious diseases; C, which is primarily connected with immune and metastasis; D, which is coupled with inflammatory processes; and E, which is linked with replication and repair. The researchers discovered a variety of potential biomarkers, some that are known and some that are currently unknown. In short, this study successfully identified various probable factors and mechanisms that could contribute to the initiation and maturation of endometriosis.

Research Source: https://www.ncbi.nlm.nih.gov/pubmed/29201163