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| Status |
Public on Oct 01, 2019 |
| Title |
Gene expression signature of endometrial samples from women with and without endometriosis. |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
Endometriosis is a benign gynecological disease characterized by the presence of endometrial-like cells outside the uterus. The prevalence of this disease reaches 10-15% in women of reproductive age which accounts for approximately 200 mln of women worldwide. The existing therapeutic approaches include medications and surgical options, but the risk of post-treatment recurrence of endometriosis remains high. There are currently no effective biomarkers of endometriosis in clinical practice and laparoscopy remains the gold standard for its diagnosis. However, laparoscopy is highly invasive procedure that frequently leads to complications and cannot be used as a routine screening test. In this study we profiled by RNA sequencing 52 endometrial pathological samples and 12 corresponding normal human tissues. We performed two-step differential gene expression analysis of endometrial samples and lesions of patients with endometriosis in comparison with normal reproductive tissues. Based on this analysis we generated a characteristic signature of five genes downregulated in endometriosis with respect to healthy endometrium. The 5-gene expression signature identified had significant predictive power (AUC>0.85) thus suggesting that the marker gene set identified can be used for a low invasive molecular diagnostic of endometriosis. Our data also suggest that the statistical method of five-fold cross validation of differential gene expression analysis procedure can be used for the ability to generate robust gene signatures using real-world clinical data.
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| Overall design |
Next generation sequencing of endometrial samples and lesions of patients with endometriosis in comparison with normal reproductive tissues (healthy endometrium, ovary and cervix)
Please note that the normal Ovary (GSM3415785, GSM3415786, GSM3415852, GSM3415878) Cervix (GSM3415783, GSM3415784, GSM3415872, GSM3415855) data is available in GSE120795.
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| Contributor(s) |
Yana A, Daniil N, Andrew G, Maria S, Maxim S, Anton B |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
| Submission date |
Aug 07, 2019 |
| Last update date |
Oct 01, 2019 |
| Contact name |
Daniil Nikitin |
| E-mail(s) |
danya.nikitin.orel@gmail.com
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| Phone |
89295743391
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| Organization name |
Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry
|
| Street address |
Miklucho-Maklaya
|
| City |
Moscow |
| ZIP/Postal code |
117198 |
| Country |
Russia |
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| Platforms (1) |
| GPL21290 |
Illumina HiSeq 3000 (Homo sapiens) |
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| Samples (58)
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| Relations |
| BioProject |
PRJNA559080 |
| SRA |
SRP217667 |
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