Endometriosis Gene Expression Heterogeneity and Biosignature: A Phylogenetic Analysis

  • Abu-Asab M
  • Zhang M
  • Amini D
  • et al.
N/ACitations
Citations of this article
30Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Endometriosis is a multifactorial disease with poorly understood etiology, and reflecting an evolutionary nature where genetic alterations accumulate throughout pathogenesis. Our objective was to characterize the heterogeneous pathological process using parsimony phylogenetics . Gene expression microarray data of ovarian endometriosis obtained from NCBI database were polarized and coded into derived (abnormal) and ancestral (normal) states. Such alterations are referred to as synapomorphies in a phylogenetic sense (or biomarkers). Subsequent gene linkage was modeled by Genomatix BiblioSphere Pathway software. A list of clonally shared derived (abnormal) expressions revealed the pattern of heterogeneity among specimens. In addition, it has identified disruptions within the major regulatory pathways including those involved in cell proliferation, steroidogenesis, angiogenesis, cytoskeletal organization and integrity, and tumorigenesis, as well as cell adhesion and migration. Furthermore, the analysis supported the potential central involvement of ESR2 in the initiation of endometriosis. The pathogenesis mapping showed that eutopic and ectopic lesions have different molecular biosignatures.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Abu-Asab, M., Zhang, M., Amini, D., Abu-Asab, N., & Amri, H. (2011). Endometriosis Gene Expression Heterogeneity and Biosignature: A Phylogenetic Analysis. Obstetrics and Gynecology International, 2011, 1–12. https://doi.org/10.1155/2011/719059

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 17

68%

Researcher 5

20%

Professor / Associate Prof. 2

8%

Lecturer / Post doc 1

4%

Readers' Discipline

Tooltip

Medicine and Dentistry 6

33%

Biochemistry, Genetics and Molecular Bi... 6

33%

Agricultural and Biological Sciences 4

22%

Computer Science 2

11%

Article Metrics

Tooltip
Social Media
Shares, Likes & Comments: 1

Save time finding and organizing research with Mendeley

Sign up for free