Summary
Endometriosis is a complex disease that on average, involves a ten-year gap between symptom onset and
diagnosis. Moreover, due to the current surgical nature of endometriosis diagnosis (laparoscopy), research
studies involving confirmed cases are both difficult to obtain and costly to recruit for. Laparoscopic surgery
(recovery times 2-6 weeks) followed by histological confirmation is considered the gold standard for diagnosis.
However, even with surgical intervention, 50% of patients have recurrence, underlining the fact that
endometriosis shows periodic states of activation, regardless of surgical or therapeutic intervention.
Consequently, a non-invasive, reliable biomarker test for endometriosis is a significant unmet medical need.
A non-invasive diagnostic for endometriosis would motivate earlier detection of disease and could fundamentally
change a patient’s prognosis by preventing disease progression. Menstrual fluid is a rich source of reproductive
tissue that can be utilized for disease diagnosis. Next Gen Jane are developing a menstrual effluent competent
collection tool, the Smart Tampon System (STS) which addresses issues of non-invasive sample accessibility
and ease of sample transport to a laboratory.
Toward development of a reliable biomarker for endometriosis, our preliminary data with the STS device
indicates we can detect multiple RNA species in menstrual effluent, some of which have been previously
discovered in other related studies. We believe that the STS provides unparalleled ease of access to menstrual
effluent and markedly improves sample handling efficiencies. These factors alongside the demonstrated utility
of the STS as a sample for RNASeq (amongst other studies) differentiates this proposal from other non-invasive
approaches to detection of endometriosis.
Our goal is to develop a non-invasive ”yes/no” diagnostic test for endometriosis by examining the genomic
signatures of endometrial tissue shed into a tampon during menstruation. In order to further identify and evaluate
the performance of genomic markers in menstrual fluid, we will enroll 72 patients with a negative or positive
surgical confirmation of endometriosis in order to: Firstly, confirm previously identified biomarkers from pilot data
that evaluates diagnosis of disease. Secondly, we will use statistical classification of RNASeq data to examine
~300 pre- and post- laparoscopy matched patient samples to confirm sensitivity and specificity of miRNA and
mRNA biomarkers in concert with patient survey data.
