# Ovarian Cancer Detection with Blood- and Imaging-Based Biomarkers

> **NIH NIH R01** · UNIVERSITY OF ARIZONA · 2022 · $34,509

## Abstract

PROJECT SUMMARY
 This application is to support a predoctoral graduate student, Ms. Dominique Galvez, through a diversity
supplement to R01CA260399. Ms. Galvez will directly support and expand upon Specific Aim 2: Develop
endoscopic imaging and pathomics markers, advancing progress as well as expanding her training.
 A central problem in ovarian cancer is late diagnosis, which causes the 5-year survival rate to plummet
below 50%. Because ovarian cancer is so deadly, risk-reducing salpingo-oophorectomy (RRSO) is often
recommended for women at high risk; however, RRSO has fertility and health consequences. It is now
believed that ovarian high-grade serous carcinoma (HGSC) may begin in the fallopian tubes (FTs) as serous
tubal intraepithelial carcinoma (STIC). Our preliminary data indicate that there are significant changes in serum
protein biomarkers in HGSC cases 12-84 months prior to diagnosis. Further, we have also shown that changes
occur in multispectral fluorescence image markers of normal and cancerous ovaries and FTs, and that we can
build a thin falloposcope suitable for traversing the uterus and FT for imaging and cell collection.
 We will address the unmet clinical need for a minimally invasive test for STIC and early (stage I/II) ovarian
cancer. Currently, no methods enable the detection of ovarian HGSC with a lead time of more than 12 months.
Overall, our work will meet the need to detect aggressive cancers at the earliest possible stage. We will
combine blood screening for protein markers with a minimally invasive falloposcopy for optical imaging and FT
cell collection. Our procedure will be tested in a study of women at high risk undergoing bilateral salpingo-
oophorectomy with hysterectomy, which will enable us to obtain and compare test results to gold standard
histology. The specific aims are to:
 1) Develop and validate biomarkers that detect STIC and early epithelial ovarian cancer. We will improve
upon our existing cut-off based algorithm with newly-discovered markers as well develop a velocity-based
biomarker algorithm. The algorithm that detects disease 12-84 months prior to diagnosis will be confirmed in
an independent, blinded set of clinical blood samples.
 2) Develop endoscopic imaging and pathomics markers. We will improve our prototype falloposcope
system with higher resolution multispectral imaging and improved cell collection ability. We will develop
imaging and karyometric markers from the FT images and the cells collected, and perform a pilot in vivo study.
 3) Develop an actionable clinical strategy for early detection of epithelial ovarian cancer. A study will be
performed in women at high risk who are planning a RRSO. Those who test positive from our blood test will
have their tissue undergo a falloposcopy. Imaging and pathomics data will be used to develop a classifier,
which will be compared to gold standard histology findings of normal FT, STIC, or occult HGSC.

## Key facts

- **NIH application ID:** 10598251
- **Project number:** 3R01CA260399-01A1S1
- **Recipient organization:** UNIVERSITY OF ARIZONA
- **Principal Investigator:** Jennifer Kehlet Barton
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $34,509
- **Award type:** 3
- **Project period:** 2022-01-01 → 2026-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10598251

## Citation

> US National Institutes of Health, RePORTER application 10598251, Ovarian Cancer Detection with Blood- and Imaging-Based Biomarkers (3R01CA260399-01A1S1). Retrieved via AI Analytics 2026-06-03 from https://api.ai-analytics.org/grant/nih/10598251. Licensed CC0.

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