Our publications

Our work has been published in peer-reviewed international scientific journals. As the publications have appeared in international journals in English, we make them available in their original language.
Validation of the Salivary miRNA Signature of Endometriosis — Interim Data
Bendifallah S., Dabi Y., Suisse S., et al. | June 2023
The discovery of a saliva-based micro–ribonucleic acid (miRNA) signature for endometriosis in 2022 opened up new perspectives for early and noninvasive diagnosis of the disease. The 109-miRNA saliva signature is the product of miRNA bio- markers and AI modeling. We designed a multicenter study to provide external validation of its diagnostic accuracy. We present here an interim analysis.
Value of non-coding RNAs to assess lymph node status in cervical cancer
Dabi Y., Favier A., Razakamanantsoa L., et al. I May 2023
Cervical cancer (CC) is the fourth cancer in women and is the leading cause of cancer death in 42 countries. Lymph node metastasis is a determinant prognostic factor, as underlined in the latest FIGO classification. However, assessment of lymph node status remains difficult, despite the progress of imaging such as PET- CT and MRI.
Saliva microRNA signature to diagnose endometriosis: A cost-effectiveness evaluation of the Endotest®
Ferrier C., Bendifallah S., Suisse S., Dabi Y., Touboul C., Puchar A., Zarca K. et Durand Zaleski I. | November 2022
Objective: To evaluate a saliva diagnostic test (Endotest®) for endometriosis compared with the conventional algorithm. Design: A cost-effectiveness analysis with a decision-tree model based on literature data. Setting: France. Population: Women with chronic pelvic pain.
Endometriosis-associated infertility diagnosis based on saliva microRNA signatures
Dabi Y., Suisse S., Puchar A., Delbos L., Poilblanc M., Descamps P., Haury J., Golfier F., Jornea L., Bouteiller D., Touboul C., Daraï E. et Bendifallah S. I October 2022
Research question: Can a saliva-based miRNA signature for endometriosis-associated infertility be designed and validated by analysing the human miRNome? Design: The prospective ENDOmiARN study (NCT04728152) included 200 saliva samples obtained between January 2021 and June 2021 from women with pelvic pain suggestive of endometriosis.
A Bioinformatics Approach to MicroRNA‐Sequencing Analysis Based on Human Saliva Samples of Patients with Endometriosis
Bendifallah S., Dabi Y., Suisse S., Delbos L., Poilblanc M., Descamps P., Golfier F., Jornea L., Bouteiller D., Touboul C., Puchar A. et Daraï E. I July 2022
Endometriosis, defined by the presence of endometrium-like tissue outside the uterus, affects 2–10% of the female population, i.e., around 190 million women, worldwide. The aim of the prospective ENDO-miRNA study was to develop a bioinformatics approach for microRNA- sequencing analysis of 200 saliva samples for miRNAome expression and to test its diagnostic accuracy for endometriosis.
Endometriosis Associated-miRNome Analysis of Blood Samples: A Prospective Study
Bendifallah S., Dabi Y., Suisse S., Delbos L., Poilblanc M., Descamps P., Golfier F., Jornea L., Bouteiller D., Touboul C., Puchar A. et Daraï E. I May 2022
The aim of our study was to describe the bioinformatics approach to analyze miRNome with Next Generation Sequencing (NGS) of 200 plasma samples from patients with and without endometriosis. Patients were prospectively included in the ENDO-miRNA study that selected patients with pelvic pain suggestive of endometriosis.
MicroRNome analysis generates a blood-based signature for endometriosis
Bendifallah S., Suisse S., Dabi Y., et al. I March 2022
Endometriosis, characterized by endometrial-like tissue outside the uterus, is thought to affect 2–10% of women of reproductive age: representing about 190 million women worldwide. Numerous studies have evaluated the diagnostic value of blood biomarkers but with disappointing results. Thus, the gold standard for diagnosing endometriosis remains laparoscopy. We performed a prospective trial, the ENDO-miRNA study, using both Artificial Intelligence (AI) and Machine Learning (ML),…
Salivary MicroRNA Signature for Diagnosis of Endometriosis
Bendifallah S., Suisse S., Puchar A., et al. I January 2022
Background: Endometriosis diagnosis constitutes a considerable economic burden for the healthcare system with diagnostic tools often inconclusive with insufficient accuracy. We sought to analyze the human miRNAome to define a saliva-based diagnostic miRNA signature for endometriosis.
Clues for Improving the Pathophysiology Knowledge for Endometriosis Using Serum Micro-RNA Expression
Dabi Y., Suisse S., Jornea L., et al. I January 2022
The pathophysiology of endometriosis remains poorly understood. The aim of the present study was to investigate functions and pathways associated with the various miRNAs differentially expressed in patients with endometriosis. Plasma samples of the 200 patients from the prospective « ENDO-miRNA » study were analyzed and all known human miRNAs were sequenced.
Machine learning algorithms as new screening approach for patients with endometriosis
Bendifallah S., Suisse S., Puchar A., et al. I January 2022
Endometriosis—a systemic and chronic condition occurring in women of childbearing age—is a highly enigmatic disease with unresolved questions. While multiple biomarkers, genomic analysis, questionnaires, and imaging techniques have been advocated as screening and triage tests for endometriosis to replace diagnostic laparoscopy, none have been implemented routinely in clinical practice.

Stay connected

Sign up to be notified of the latest news and publications.