Meta-Analysis

. 2022 Mar 15;3(3):100542.

doi: 10.1016/j.xcrm.2022.100542.

A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes

Sally Mortlock¹, Rosario I Corona², Pik Fang Kho^{3

4}, Paul Pharoah^{5

6}, Ji-Heui Seo⁷, Matthew L Freedman^{7

8}, Simon A Gayther⁹, Matthew T Siedhoff¹⁰, Peter A W Rogers¹¹, Ronald Leuchter¹², Christine S Walsh¹³, Ilana Cass¹², Beth Y Karlan¹⁴, B J Rimel¹²; Ovarian Cancer Association Consortium, International Endometriosis Genetics Consortium; Grant W Montgomery¹, Kate Lawrenson^{2

9

12}, Siddhartha P Kar^{15

16}

Affiliations

¹ The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.
² Women's Cancer Research Program at Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
³ Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
⁴ School of Biomedical Science, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia.
⁵ Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, CB1 8RN Cambridge, UK.
⁶ Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, CB1 8RN Cambridge, UK.
⁷ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
⁸ Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA.
⁹ Center for Bioinformatics and Functional Genomics, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
¹⁰ Division of Minimally Invasive Gynecologic Surgery, Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
¹¹ University of Melbourne Department of Obstetrics and Gynaecology, and Gynaecology Research Centre, Royal Women's Hospital, Parkville, VIC 3052, Australia.
¹² Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
¹³ Department of Obstetrics and Gynecology, University of Colorado, Aurora, CO, USA.
¹⁴ Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
¹⁵ Medical Research Council Integrative Epidemiology Unit, University of Bristol, BS8 2BN Bristol, UK.
¹⁶ Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN Bristol, UK.

PMID: 35492879
PMCID: PMC9040176
DOI: 10.1016/j.xcrm.2022.100542

Meta-Analysis

A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes

Sally Mortlock et al. Cell Rep Med. 2022.

. 2022 Mar 15;3(3):100542.

doi: 10.1016/j.xcrm.2022.100542.

Authors

Affiliations

¹ The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.
² Women's Cancer Research Program at Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
³ Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
⁴ School of Biomedical Science, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia.
⁵ Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, CB1 8RN Cambridge, UK.
⁶ Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, CB1 8RN Cambridge, UK.
⁷ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
⁸ Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA.
⁹ Center for Bioinformatics and Functional Genomics, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
¹⁰ Division of Minimally Invasive Gynecologic Surgery, Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
¹¹ University of Melbourne Department of Obstetrics and Gynaecology, and Gynaecology Research Centre, Royal Women's Hospital, Parkville, VIC 3052, Australia.
¹² Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
¹³ Department of Obstetrics and Gynecology, University of Colorado, Aurora, CO, USA.
¹⁴ Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
¹⁵ Medical Research Council Integrative Epidemiology Unit, University of Bristol, BS8 2BN Bristol, UK.
¹⁶ Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN Bristol, UK.

PMID: 35492879
PMCID: PMC9040176
DOI: 10.1016/j.xcrm.2022.100542

Abstract

Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses, we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (r_g) between endometriosis and clear cell (r_g = 0.71), endometrioid (r_g = 0.48), and high-grade serous (r_g = 0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identified 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases.

Keywords: Mendelian randomization; endometriosis; epithelial ovarian cancer; genetic association; genetic correlation; genetic risk; histotype; meta-analysis.

PubMed Disclaimer

Conflict of interest statement

M.L.F. reports other support from Nuscan Diagnostics outside the scope of the submitted work. C.W. reports research funding support from Merck, is a member of the Immunogen advisory board (1/2022), and has been a member of the Genentech advisory board (8/2020). The remaining authors declare no competing interests.

Figures

**Figure 1**
Functional annotation of SNPs associated with risk of endometriosis and epithelial ovarian cancer (A) Histogram of number of non-redundant SNPs for all epithelial ovarian cancer (EOC) histological subtypes that overlap n biofeatures. Inset: histogram of number of non-redundant SNPs for all histological subtypes that overlap at least one biofeature. (B) Proportion of loci shared between endometriosis and each EOC histotype containing SNPs that overlap at least one biofeature. (C) A promoter SNP at the *VEZT/FGD6* locus overlaps 10 biofeatures and intersects with an active open region of chromatin that lies in a bidirectional promoter associated with these two genes. Biofeatures are shown as peaks on the ATAC-seq and H3K27ac ChIP-seq tracks for primary tissues and cell lines. Endo, endometriosis; FT, fallopian tube; Stroma, endometriosis-associated stroma; CCOC, clear cell ovarian cancer; CL, cell lines; ENOC, endometrioid ovarian cancer; HGSOC, high-grade serous ovarian cancer; MOC, mucinous ovarian cancer; PT, primary tissues. Specimens are primary tissues unless otherwise indicated. The gray shaded area highlights peaks overlapping rs6538618. Boxplots show the association between rs6538618 genotypes and expression of *VEZT* and *FGD6* in endometrium.

See this image and copyright information in PMC

References

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A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes

Affiliations

A multi-level investigation of the genetic relationship between endometriosis and ovarian cancer histotypes

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical

Molecular Biology Databases