Cited by 589Reproductive System and PregnancyEstrogen and related hormone effectsEndometrial and Cervical Cancer Treatments

Molecular Phenotyping of Human Endometrium Distinguishes Menstrual Cycle Phases and Underlying Biological Processes in Normo-Ovulatory Women

Talbi, S., Hamilton, A. E., Vo, K. C., Tulac, S., Overgaard, M. T., Dosiou, C., Le Shay, N., Nezhat, C. N. +4 more·2006·Endocrinology

Abstract

Histological evaluation of endometrium has been the gold standard for clinical diagnosis and management of women with endometrial disorders. However, several recent studies have questioned the accuracy and utility of such evaluation, mainly because of significant intra- and interobserver variations in histological interpretation. To examine the possibility that biochemical or molecular signatures of endometrium may prove to be more useful, we have investigated whole-genome molecular phenotyping (54,600 genes and expressed sequence tags) of this tissue sampled across the cycle in 28 normo-ovulatory women, using high-density oligonucleotide microarrays. Unsupervised principal component analysis of all samples revealed that samples self-cluster into four groups consistent with histological phenotypes of proliferative (PE), early-secretory (ESE), mid-secretory (MSE), and late-secretory (LSE) endometrium. Independent hierarchical clustering analysis revealed equivalent results, with two major dendrogram branches corresponding to PE/ESE and MSE/LSE and sub-branching into the four respective phases with heterogeneity among samples within each sub-branch. K-means clustering of genes revealed four major patterns of gene expression (high in PE, high in ESE, high in MSE, and high in LSE), and gene ontology analysis of these clusters demonstrated cycle-phase-specific biological processes and molecular functions. Six samples with ambiguous histology were identically assignable to a cycle phase by both principal component analysis and hierarchical clustering. Additionally, pairwise comparisons of relative gene expression across the cycle revealed genes/families that clearly distinguish the transitions of PE→ESE, ESE→MSE, and MSE→LSE, including receptomes and signaling pathways. Select genes were validated by quantitative RT-PCR. Overall, the results demonstrate that endometrial samples obtained by two different sampling techniques (biopsy and curetting hysterectomy specimens) from subjects who are as normal as possible in a human study and including those with unknown histology, can be classified by their molecular signatures and correspond to known phases of the menstrual cycle with identical results using two independent analytical methods. Also, the results enable global identification of biological processes and molecular mechanisms that occur dynamically in the endometrium in the changing steroid hormone milieu across the menstrual cycle in normo-ovulatory women. The results underscore the potential of gene expression profiling for developing molecular diagnostics of endometrial normalcy and abnormalities and identifying molecular targets for therapeutic purposes in endometrial disorders.

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Crossref · 10.1210/en.2005-1076

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  • Whole genome profiling of normal endometrium revealed tremendous molecular variation between samples taken from the proliferative, early-secretory, midsecretory, and late-secretory phases of the menstrual cycle.

    “Whole genome profiling of normal endometrium revealed tremendous molecular variation between samples taken from the proliferative, early-secretory, midsecretory, and late-secretory phases of the menstrual cycle [109]”

    From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [109]

  • The endometrium evidences remarkable sex steroid-driven cyclic variation and regenerative capacity.

    “First, the endometrium evidences remarkable sex steroid-driven cyclic variation and regenerative capacity.”

    From Update on biomarkers for the detection of endometriosis (2015) · cites this paper as [109]

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References 93 · Cited by 589

Authors
Talbi, S., Hamilton, A. E., Vo, K. C., Tulac, S., Overgaard, M. T., Dosiou, C., Le Shay, N., Nezhat, C. N., Kempson, R., Lessey, B. A., Nayak, N. R., & Giudice, L. C.
Affiliations
  • University of California, San Francisco (US)
  • Stanford Medicine (US)
  • Stanford University (US)
  • Prisma Health (US)
Corresponding author
Giudice, L. C.
Venue
Endocrinology
Published
2006-03-01
Volume
147
Issue
3
Pages
1097-1121
ISSN
  • 0013-7227 (ISSN-L)
  • 1945-7170
OpenAlex
W2164002837
Cited by
589
References
93
Citations by year
2026: 11 · 2025: 15 · 2024: 21 · 2023: 32 · 2022: 26 · 2021: 28 · 2020: 32 · 2019: 26 · 2018: 32 · 2017: 31 · 2016: 25 · 2015: 32 · 2014: 37 · 2013: 29 · 2012: 33
FWCI
8.90
Type
journal article
Language
en
Open access
closed
Locations
  • Endocrinology (publishedVersion)
  • PubMed (publishedVersion)
  • VBN Forskningsportal (Aalborg Universitet) (submittedVersion)
Funders
  • National Institutes of Health (5k12hd043452-05)
  • University of North Carolina at Chapel Hill
  • University of California, San Francisco
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD 043452-03, HD 31398-09, U54HD031398)
Topics
  • Life Sciences › Immunology and Microbiology › Immunology › Reproductive System and Pregnancy
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Estrogen and related hormone effects
  • Health Sciences › Medicine › Obstetrics and Gynecology › Endometrial and Cervical Cancer Treatments
Keywords
endometrium, menstrual cycle phases, gene expression profiling, endometrial receptivity, luteal phase, proliferative phase, molecular phenotyping, endometrial histology, Gene Ontology, endometrial pathology, molecular diagnosis
MeSH terms
Adult, Algorithms, Biopsy, Endometrium, Female, Gene Expression Regulation, Multigene Family, Humans, Menstrual Cycle, Middle Aged, Models, Biological, Ovulation, Phenotype, Steroids, Uterine Diseases, Uterus, Signal Transduction, Down-Regulation, Up-Regulation, Cluster Analysis, Genome, Endometrial Neoplasms, Reverse Transcriptase Polymerase Chain Reaction, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Principal Component Analysis

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