# SERS diagnostics platform for liquid bioapsy analysis of tumor-associated exosomes

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2020 · $564,554

## Abstract

Project Summary/Abstract
For ovarian cancer (OvCa), only 27% of women diagnosed at advanced stages survive 5 years, yet more than
90% of patients survive when diagnosed at an earlier stage. Therefore, there is an urgent need for new non-
invasive technologies capable of rapidly diagnosing ovarian cancers (OvCa) in early stage. Fortuitously, all
cells (and tumor cells to a greater extent) expel nanoscale vesicles that are directly reflective of the biological
state of their parent cells. A subset of circulating EVs known as exosomes are composed of biomolecules
spanning the range of lipids, proteins, genes, and more, and hold great potential for the diagnosis and
prognosis of cancer. Yet current methods for phenotyping biofluids according to detection of tumor-associated
exosomes (TEXs) are not meeting clinical standards and fail to precisely capture particle to particle
heterogeneity. We propose to develop a new nanoplasmonics-based technology for sensitive detection of
cancer-related exosome bio-signatures enabled by multiplexed surface-enhanced Raman spectroscopy, that
we call ExoSERS. Our approach encompasses three aims devised to realize the ExoSERS platform. Aim 1
outlines development of a new class of Raman-active ligands to serve as the molecular barcodes. This aim
encompasses the design and synthesis of polyyne-based ligands designed to confer Raman spectroscopic
encoding and also initiate a silane coating to form a protecting shell around a nanoplasmonic core. Aim 2
describes the synthesis and optimization of nanoplasmonic core-shell structures that will be well-suited to
binding EVs. An inner gold core structure yields plasmonic enhancement, while the outer silica shell permits
long-term stability and a convenient surface for covalent decoration with exosome and cancer-specific surface
marker targeting agents. Aim 3 comprises validation of the platform’s feasibility to profile human OvCa patient
plasma, including machine learning approaches to type cancers using the barcoded approach. Endpoints of
platform characterization will be statistical validation of exosome detection efficiency, minimal sample volume
needed, ease of utilization, and low cost. Several quantitative milestones have been proposed to gauge our
progress and provide deliverables to the larger diagnostic and circulating biomarker communities.

## Key facts

- **NIH application ID:** 9973569
- **Project number:** 1R01CA241666-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** Randy Carney
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $564,554
- **Award type:** 1
- **Project period:** 2020-04-15 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9973569

## Citation

> US National Institutes of Health, RePORTER application 9973569, SERS diagnostics platform for liquid bioapsy analysis of tumor-associated exosomes (1R01CA241666-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9973569. Licensed CC0.

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