# Quantitative proteomic profiling of extracellular vesicles from menstrualeffluent for the discovery of non-invasive diagnostic biomarkers of endometriosis

> **NIH NIH R43** · XOSOMIX LLC · 2022 · $309,897

## Abstract

Abstract:
Endometriosis is a disease caused by the extension of endometrial glands and stroma outside the uterine cavity.
Approximately 10% of reproductive age women, more than 4 million in the United States alone, are affected by
endometriosis; the true prevalence is expected to be much higher due to the high rate of undiagnosed cases.
Significant physical, psychological, and economic suffering has been documented in patients suffering from
endometriosis. In spite of the tremendous interest and unmet need, there is no FDA-approved non-invasive
diagnostic tool or biomarker for endometriosis. One of the key reasons is the lack of understanding of the
correlation between clinical symptoms, histological manifestations, and underlying dysfunction resulting in
disease. In addition, endometriosis is often associated with a range of other disorders, creating a high biomarker
noise. Extracellular vesicles (EV) are secreted by all cells and are thought to mediate intercellular as well as
inter-organ communication and are known to communicate the specific disease state. EVs have been
hypothesized to play a role in the pathogenesis and diagnosis of endometriosis. In disease, EV content is known
to be altered to reflect the disease type in a highly specific way. We seek to overcome the low signal, high noise
hurdle of endometriosis biomarker discovery by 1) focusing on EVs, the cellular messengers of the disease,
present in menstrual effluent 2) using state of the art, highly sensitive, quantitative proteomic technique, and 3)
using cohort/panel of biomarkers. Our improvement in proteomic technique alone results in 10-fold more
significant quantitative differences. In combination, they present a very significant conceptual, technical, and
instrumentation leap over past studies. We will perform the multiplexed quantitative proteomics using isobaric
tandem mass tags (TMT) on menstrual effluent EVs from surgically confirmed endometriosis patients and
compare them to controls with endometriosis like symptoms including chronic pelvic pain, but with no
endometriosis being detected at the surgery. It will provide us a patient specific, high-quality database of
proteomic content of exosomes secreted in menstrual effluent and identify functional signaling networks on them,
to lay down the foundation for the exploration of EVs from menstrual effluent. The goal of this grant is to identify
the cohort/panel of biomarkers of endometriosis on menstrual effluent EVs, that can be taken to assay
development and clinical validation in phase II.

## Key facts

- **NIH application ID:** 10547052
- **Project number:** 1R43HD109099-01A1
- **Recipient organization:** XOSOMIX LLC
- **Principal Investigator:** Pranav Sharma
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $309,897
- **Award type:** 1
- **Project period:** 2022-09-19 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10547052

## Citation

> US National Institutes of Health, RePORTER application 10547052, Quantitative proteomic profiling of extracellular vesicles from menstrualeffluent for the discovery of non-invasive diagnostic biomarkers of endometriosis (1R43HD109099-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10547052. Licensed CC0.

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