Endometriosis Clinical Trial
— niEndometriosiOfficial title:
Evaluation of Genetic Signature in Endometriosis Disease by Non Invasive Sampling
Verified date | February 2024 |
Source | Eurofins Genoma |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
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.
Status | Enrolling by invitation |
Enrollment | 150 |
Est. completion date | December 31, 2024 |
Est. primary completion date | July 31, 2024 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | Female |
Age group | 18 Years to 45 Years |
Eligibility | Inclusion Criteria: - Case population (CA), patients with endometriotic adnexal pathology - Control population (CO), patients with non-endometriotic adnexal pathology - Analytical control population (C-), patients with no gynecologic pathology, not undergoing surgery Exclusion Criteria: - Women with ages outside the inclusion range - Pregnant patient - Patient with a personal history of cancer - Patient infected with HIV |
Country | Name | City | State |
---|---|---|---|
Italy | Eurofins Genoma | Rome |
Lead Sponsor | Collaborator |
---|---|
Eurofins Genoma |
Italy,
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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 Serum Micro-RNA Expression. Diagnostics (Basel). 2022 Jan 12;12(1):175. doi: 10.3390/diagnostics12010175. — View Citation
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. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | 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 | |
Primary | 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 | |
Secondary | Tissue validation | Genetic profiling of miRNOME from saliva versus FFPE-tissues | 2 months | |
Secondary | Clinical validation | Correlation of miRNOME signature in saliva among cases, controls and analytical groups | 4 months | |
Secondary | Biomarkers identification | Identification of specific signature related to endometriosis, with at least 2 Log2fold change | 7 months |
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