# FemKube, the human female reproductive tract-on-a-chip, as a platform for studying high grade serous ovarian cancer and developing novel cancer chemotherapeutics

> **NIH NIH F30** · UNIVERSITY OF ILLINOIS AT CHICAGO · 2020 · $50,520

## Abstract

PROJECT SUMMARY/ABSTRACT
 High grade serous ovarian cancer (HGSOC), the most lethal gynecologic malignancy, is typically
diagnosed after distant metastasis has occurred, and chemoresistance renders current treatments short-lived.
Two major knowledge gaps exist in the field: we lack an understanding of early lesions and development of
new anticancer drugs. HGSOC has been difficult to research and model due to debate over the most common
cell of origin, which is now accepted to be the fallopian tube epithelium (FTE), and because the menstrual
cycle plays a role in HGSOC development. No models of the disease previously existed, which incorporate
both the fallopian tube and an ovary capable of recapitulating the human menstrual cycle. FemKube, the first
female reproductive tract-on-a-chip, was created through a multi-institutional collaboration between the
University of Illinois, Northwestern, and Draper Labs to support primary human fallopian tube tissues and
murine ovaries, which are engineered to drive a physiologically accurate 28-day human menstrual cycle, in the
setting of microfluidic flow. We will leverage this innovative technology to address both issues in the field by
utilizing it to investigate early oncogenic events in the fallopian tube and to enhance the preclinical
development of a promising new class of natural product chemotherapeutics, Phyllanthusmins (PHYs).
 Our collaborative team has demonstrated the ability of FemKube to support growth of human fallopian
tissues for the length of an accurately reproduced menstrual cycle. It is hypothesized that the FTE is damaged
by secreted factors produced by the ovary during the follicular phase (first half of the menstrual cycle that
encompasses follicle maturation), which is restored under the influence of progestins secreted from the corpus
luteum (what remains of the follicle after ovulation) in the late luteal phase (second half of the menstrual cycle).
Our first aim is to investigate how the cycling ovary impacts HGSOC initiation in the FTE by mapping DNA
damage, proliferation, and apoptosis. We will use inhibitors of menstrual cycle hormones and nascent
oncogenic mediators, such as known DNA mutators, inflammatory and growth factors, reactive oxygen species
neutralizers and tumor suppressors, to mechanistically study HGSOC initiation in the FemKube system.
 Our second aim seeks to incorporate our ability to culture primary human tissues in the FemKube
system into the preclinical drug development pipeline. With the help our collaborators at the Ohio State
University, we have developed a promising class of compounds derived from natural products, PHYs, with
nanomolar potency on HGSOC cell lines in vitro. We will confirm PHY's apoptotic and anticancer abilities in
vitro. We will demonstrate their efficacy on tumors ex vivo in the FemKube system and benchmark our findings
against gold standard in vivo chemotherapeutic assays in mice. Overall, the introduction of FemKube
technology will an...

## Key facts

- **NIH application ID:** 9928905
- **Project number:** 5F30CA217079-04
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT CHICAGO
- **Principal Investigator:** Alexandria Young
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $50,520
- **Award type:** 5
- **Project period:** 2017-05-16 → 2021-05-15

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9928905

## Citation

> US National Institutes of Health, RePORTER application 9928905, FemKube, the human female reproductive tract-on-a-chip, as a platform for studying high grade serous ovarian cancer and developing novel cancer chemotherapeutics (5F30CA217079-04). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/9928905. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*
