Endometrial immune microenvironment dysfunction in endometriosis pathobiology

PROJECT SUMMARY Endometriosis, a debilitating chronic disease, affects around 10% of reproductive age women worldwide, severely impacting quality-of-life. Unfortunately, there is often a decade-long delay from first symptom onset to definitive diagnosis, underscoring the urgent need for improved earlier diagnostics. Evidence suggests that local

endometrial immune microenvironment (EIM) dysregulation may play a key factor in endometriosis pathobiology. Even though uterine NK (uNK) cells are the predominant cytolytic lymphocyte in the EIM, they have been surprisingly understudied in endometriosis. The objective of this proposal is to gain a better understanding of the

contribution of uNK cells to endometriosis and to identify non-invasive menstrual blood (MB) biomarkers that can be leveraged for diagnosis. I hypothesize that defective cytolysis of endometrial stromal cells by dysregulated uNK cells contributes to an abnormal tissue environment in endometriosis. The work in this proposal will be

completed at Stanford University School of Medicine in Dr. Gaudilliere’s laboratory (primary mentor) with guidance from an interdisciplinary mentoring team at UCSF (Dr. Giudice, Dr. Sirota) and Duke University (Dr. Coyne). A rigorous research training plan is proposed that harnesses cutting-edge high-dimensional single-cell

suspension and spatial immune profiling, sparse machine learning methods, and ex vivo assembloid modeling. Aim 1 (K99) will characterize the inhibitory/activating receptor repertoire and functional capacity of uNK cells of women with and without endometriosis (scRNAseq and mass cytometry). In addition, examining the spatial

organization of the EIM will provide crucial insight into microenvironmental interactions that underlie immune responses in healthy and diseased endometrium (imaging mass cytometry). This aim builds on my current expertise in human reproductive immunology and multi-parameter approaches and is a continuation of prior work

showing that uNK cells predominate in the EIM and exhibit a tissue-specific receptor profile. In Aim 2, an innovative MB immunoassay will be established on the mass cytometry platform (K99) by discerning the similarities and disparities between biopsy and MB-derived uNK cells. In the R00 phase, high-dimensional

predictive modeling will identify uNK cell features in MB that accurately classify endometriosis versus control. In Aim 3, through Dr. Coyne’s training (K99), endometrial assembloids derived from primary MB-derived endometrial cells will be established to replicate the EIM ex vivo. In the R00 phase, uNK cells will be incorporated

into this assembloid model to further investigate uNK-mediated mechanisms in abnormal endometrial tissue. In summary, the proposed studies will uncover fundamental uNK cell mechanisms that contribute to endometriosis pathobiology and establish a foundation for developing non-invasive diagnostics. The training, approach, and

results generated will offer a unique framework for future research on various uterine and reproductive disorders, aiding my career development and enabling me to become an independent academic translational scientist in reproductive immunology, bridging systems immunology, assembloid modelling, and computational biology.