# Parsing the Interplay Between Biophysical and Biochemical Microenvironment Cues On Endometriosis Lesion Phenotypes Using Microphysiological Systems > **NIH NIH R01** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2022 · $303,245 ## Abstract Project Summary: Center for Engineering Endometriosis Care (CEEC) The high prevalence, diversity of morphological and symptomatic presentations, array of potential etiological explanations, and variable response to existing interventions suggest that different subgroups of endometriosis patients with mechanistic bases of disease may exist. These factors, combined with the weak links to genetic predisposition, make the entire spectrum of the human condition challenging to model in animals. The majority of endometriosis research approaches questions as "diseased" or "control", with stratification among clinical status of patients according to ASRM stages. The overarching goal the CEEC is to reframe the way the clinical and basic science researchers together approach the complex landscape of endometriosis: first, by creating a new framework for defining clinical cohorts, based on presumed distinct biological mechanisms among different patient groups, for corresponding basic science studies; and second, by developing and implementing new computational systems biology, tissue engineering, and organ-on-chip models designed to address specific scientific questions arising from the mechanistic groupings of patients. The average age of patients in published studies on endometriosis is above 30 - more than twice the age of onset for many patients. Endocrine, metabolic, and immune systems are, on average, very different in 16 and 32 year olds; the physiology of lesions very likely is, also. We know little about the interplay between systemic host factors and the drugs we now use to treat lesions on the physiology of the lesions. Why is the disease invasive in some patients, and not others? Here, we propose to classify patient cohorts into 4 distinct subgroups that differ by systemic physiology {ages 16-21 and ages 32-42) and lesion physiology {superficial only, persistent; or invasive +/- superficial). This scheme allows us to construct an engineering landscape of in vitro lesion microenvironments, according to the features of the lesion physical microenvironment and systemic microenvironment, and a corresponding parameter space in which the magnitudes of cues are varied. Three projects allow us to develop correlations between patient clinical phenotypes and in vitro models:: Project 1: Parsing Effects of Donor Source and Lesion Microenvironment on Lesion Phenotypes in Vitro Project 2: Dissecting macrophage signal integration and function in endometriosis Project 3: Correlates of a holistic in vivo cellular and molecular signature with clinical phenotypes These projects will draw from a Biospecimen Coordinating Core. At the completion of this work, we will have new tools, new insights into how existing hormone therapies work in patients, and hopefully a new language for communication between clinicians and basic scientists in the trenches of endometriosis research. We will also have a substantial impact on education of the next generation of endometriosis r... ## Key facts - **NIH application ID:** 10551985 - **Project number:** 1R01HD110335-01 - **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY - **Principal Investigator:** LINDA G GRIFFITH - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $303,245 - **Award type:** 1 - **Project period:** 2022-03-25 → 2026-02-28 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10551985 ## Citation > US National Institutes of Health, RePORTER application 10551985, Parsing the Interplay Between Biophysical and Biochemical Microenvironment Cues On Endometriosis Lesion Phenotypes Using Microphysiological Systems (1R01HD110335-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10551985. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*