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Endometriosis is a disease that affects 10-15% of the general population and 50% of infertile women. It is characterized by the presence of endometrial tissue outside the uterine cavity. Endometriosis can lead to infertility by interfering through endocrine and mechanical alterations on the function of the ovaries, fallopian tubes, and uterus. The aim of the study is to define the differential expression of a cluster of RNAs tissue driven for the identification of an RNA profile in saliva, specific for endometriosis. This study focuses on the expression of genes involved in the control and regulation of apoptosis, cell survival, metabolism, cell adhesion and invasion, angiogenesis, inflammation, and estrogen receptor expression levels.
Retrospective selection based on anamnestic criteria of: 50 patients with diagnosed endometriotic adnexal pathology (case, CA), 50 patients with non-endometriotic adnexal pathology (control, CO) and 50 patients with no gynecological pathology, not undergoing surgery (analytical control).
The study involves collecting a saliva sample from all patients involved in the study, and performing a biopsy from both patients with endometriotic adnexal pathology (CA) and patients with non-endometriotic adnexal pathology (CO).
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| case | Patients with endometriotic adnexal pathology |
| |
| control | Patients with non endometriotic adnexal pathology |
| |
| analytical control | Patients with no gynecological pathology, not undergoing surgery |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Observational study | Other | Observational study in different tissues in identifing new genetic markers related to endometriosis disease |
|
| Measure | Description | Time Frame |
|---|---|---|
| Next Generation Sequencing technical validation | Assessing the quality of Next Generation Sequencing via the FASTQC tool. Following benchmarks will be considered: 1.1 Per base sequence quality [Phred score: positive real number, the higher the better] 1.2 Total number of sequenced reads [integer: positiver integer number, the higher the better] | 1 month |
| Wet lab kit validation | Assessing the quality of the kit by mapping the reads against public miRNA databases. Following benchmark will be considered: Total reads mapped [integer] | 1 month |
| Measure | Description | Time Frame |
|---|---|---|
| Tissue validation | Genetic profiling of miRNOME from saliva versus FFPE-tissues | 2 months |
| Clinical validation | Correlation of miRNOME signature in saliva among cases, controls and analytical groups |
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Inclusion Criteria:
Exclusion Criteria:
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Groups of study:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Eurofins Genoma | Rome | 00138 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 36411203 | Background | Dabi Y, Suisse S, Puchar A, Delbos L, Poilblanc M, Descamps P, Haury J, Golfier F, Jornea L, Bouteiller D, Touboul C, Darai E, Bendifallah S. Endometriosis-associated infertility diagnosis based on saliva microRNA signatures. Reprod Biomed Online. 2023 Jan;46(1):138-149. doi: 10.1016/j.rbmo.2022.09.019. Epub 2022 Sep 27. | |
| 35887388 |
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| ID | Term |
|---|---|
| D004715 | Endometriosis |
| ID | Term |
|---|---|
| D005831 | Genital Diseases, Female |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
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| ID | Term |
|---|---|
| D019370 | Observation |
| ID | Term |
|---|---|
| D008722 | Methods |
| D008919 | Investigative Techniques |
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tissue biopsy and saliva
| 4 months |
| Biomarkers identification | Identification of specific signature related to endometriosis, with at least 2 Log2fold change | 7 months |
| Bendifallah S, Dabi Y, Suisse S, Jornea L, Bouteiller D, Touboul C, Puchar A, Darai E. A Bioinformatics Approach to MicroRNA-Sequencing Analysis Based on Human Saliva Samples of Patients with Endometriosis. Int J Mol Sci. 2022 Jul 21;23(14):8045. doi: 10.3390/ijms23148045. |
| 35160066 | Background | Bendifallah S, Suisse S, Puchar A, Delbos L, Poilblanc M, Descamps P, Golfier F, Jornea L, Bouteiller D, Touboul C, Dabi Y, Darai E. Salivary MicroRNA Signature for Diagnosis of Endometriosis. J Clin Med. 2022 Jan 26;11(3):612. doi: 10.3390/jcm11030612. |
| 35260677 | Background | Bendifallah S, Dabi Y, Suisse S, Jornea L, Bouteiller D, Touboul C, Puchar A, Darai E. MicroRNome analysis generates a blood-based signature for endometriosis. Sci Rep. 2022 Mar 8;12(1):4051. doi: 10.1038/s41598-022-07771-7. |
| 35054341 | Background | Dabi Y, Suisse S, Jornea L, Bouteiller D, Touboul C, Puchar A, Darai E, Bendifallah S. Clues for Improving the Pathophysiology Knowledge for Endometriosis Using Plasma Micro-RNA Expression. Diagnostics (Basel). 2022 Jan 12;12(1):175. doi: 10.3390/diagnostics12010175. |
| 35022502 | Background | Bendifallah S, Puchar A, Suisse S, Delbos L, Poilblanc M, Descamps P, Golfier F, Touboul C, Dabi Y, Darai E. Machine learning algorithms as new screening approach for patients with endometriosis. Sci Rep. 2022 Jan 12;12(1):639. doi: 10.1038/s41598-021-04637-2. |
| D000091662 | Genital Diseases |