# NIH grant: GapScore: A Functional Biomarker for Predicting Therapy Response in BRCA-Deficient Tumors (1R41CA314549-01) — retained record

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source: [us-gov-api](https://highsignal.app/data/us-gov-api) (us-gov-api:nih-reporter)  published 2026-09-11 00:00 ingested 2026-09-14 02:42

[original source ↗](https://reporter.nih.gov/project-details/1R41CA314549-01)

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NIH grant 1R41CA314549-01: GapScore: A Functional Biomarker for Predicting Therapy Response in BRCA-Deficient Tumors
Institute: {'code': 'CA', 'abbreviation': 'NCI', 'name': 'National Cancer Institute', 'admin_org_id': '12500008', 'admin_funding_url': ''}. PI: Jenna  Whalen. Award: $406500.
Start: 2026-09-11T00:00:00.
ABSTRACT
The objective of this proposal is to clinically translate a novel biomarker assay, GapScore, which measures
single-stranded DNA (ssDNA) gaps—the fundamental lesions driving sensitivity to therapy in BRCA-deficient
cancers. Traditionally, chemosensitivity in BRCA-mutant tumors has been attributed to defects in homologous
recombination (HR) repair and fork protection (FP). However, our findings reveal that BRCA-deficient cells also
harbor profound replication gap suppression defects, resulting in persistent ssDNA gaps that directly correlate
with therapy response. Unlike existing biomarkers such as HRD status or RAD51 foci, GapScore directly
quantifies this inherent vulnerability and is compatible with routine clinical pathology workflows. In Specific Aim
1, we will adapt and retrain our AI-based image analysis pipeline, previously validated in xenografts, to handle
the heterogeneity of human tumors. This will enable precise segmentation of FFPE patient samples into viable,
necrotic, stromal, fibrotic, vascular, and adipose regions, ensuring accurate quantification of ssDNA gaps in
relevant tumor areas. In Specific Aim 2, we will evaluate GapScore as a predictive biomarker by applying it to
a retrospective cohort of breast and ovarian tumors with linked patient outcome data, treatment responses,
BRCA mutation status, and traditional biomarker annotations (HRD and RAD51). We will benchmark GapScore’s
performance against these clinical standards to determine whether it offers superior predictive accuracy. This
research has the potential to redefine cancer diagnostics by providing the first clinically actionable biomarker
rooted in the true biology of therapy response. Successful completion of these aims will support a Phase II STTR
application. Ultimately, we will seek to establish GapScore as a functional biomarker for patient stratification in
BRCA-associated breast and ovarian cancers and lay the foundation for prospective clinical trials aimed at
improving treatment precision and outcomes.
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