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

> **NIH CA R01** · UNIVERSITY OF ARIZONA · 2026 · $738,514

## Abstract

A central problem in ovarian cancer is late diagnosis, which causes the 5-year survival rate to plummet
below 50%. Ovarian cancer symptoms are vague and nonspecific, and current screening is generally not
effective. 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), and that precancerous changes are detectable before metastasis to the
ovary and peritoneal cavity occurs. 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. Our initial
target population is women at high risk for ovarian cancer who wish to delay or avoid RRSO. 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-disco

## Key facts

- **NIH application ID:** 11257652
- **Project number:** 5R01CA260399-05
- **Recipient organization:** UNIVERSITY OF ARIZONA
- **Principal Investigator:** Jennifer Kehlet Barton; David A. Fishman; Anna E. Lokshin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** CA
- **Fiscal year:** 2026
- **Award amount:** $738,514
- **Award type:** 5
- **Project period:** 2022-01-01T00:00:00 → 2026-12-31T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11257652

## Citation

> US National Institutes of Health, RePORTER application 11257652, Ovarian Cancer Detection with Blood- and Imaging-Based Biomarkers (5R01CA260399-05). Retrieved via AI Analytics 2026-05-18 from https://api.ai-analytics.org/grant/nih/11257652. Licensed CC0.

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