# A novel multimodal ECM analysis platform for tumor characterization combining morphological and spectrochemical tissue imaging approaches.

> **NIH NIH R61** · UNIVERSITY OF WISCONSIN-MADISON · 2024 · $197,983

## Abstract

PROJECT SUMMARY
The tumor microenvironment (TME) in essentially all epithelial cancers is associated with significant biochemical
and structural changes in the extracellular matrix (ECM). Many tumors including those of the breast, pancreas
and ovary are characterized by profound changes in the collagen architecture. ECM changes (~micron scale)
are below the resolution of conventional imaging modalities but analysis of this structure is critical for
understanding carcinogenesis and metastasis. We have used the collagen-specific modality of Second Harmonic
Generation (SHG) optical microscopy to discriminate cancer specimens from normal tissues based on changes
in supramolecular structure, fibril structure, and fiber morphology, where we have focused on high grade serous
ovarian cancer (HGSOC). However, SHG cannot identify the specific molecular alterations, which could provide
critical information on disease etiology, prognosis, and response to therapy. Now we will develop a novel method
that combines spatially registered SHG and surface enhanced mid-infrared spectral imaging (SE-MIRSI)
correlating morphometric and chemometric information to elucidate tumor-promoting ECM alterations. The latter
spatially probes specific molecular signatures from vibrational spectroscopy and provides increased sensitivity
using nanophotonic substrates, allowing rapid and large-area chemical imaging of whole tissue sections.
Specifically, SE-MIRSI can quantitatively identify specific changes in isoform distribution, posttranslational
modifications and altered crosslinking of the collagen fibers. Spatial registration of SHG and SE-MIRSI then will
provide a comprehensive, ultrasensitive, label free, non-destructive, high-resolution structural and biochemical
imaging platform to investigate the role of ECM alterations in promoting tumor carcinogenesis and metastasis.
Here, we will develop a multivariate data processing workflow that identifies the specific signatures of collagen
and other ECM components from the two modalities establishing the basis of an accurate classifier. We will
validate the multimodal characterizations on HSGOC tissue samples. At the end of this project, we will have
developed a multimodal imaging platform that will uniquely identify collagen and other ECM biochemical
alterations in the TME. We will establish performance measures based on imaging speed and throughput,
sensitivity and classification accuracy. These structural and biochemical analyses will provide new insight into
carcinogenesis and disease progression in several carcinomas. We propose these Aims:
Aim 1. Identify specific structural and biochemical signatures of in vitro ECM models through the combined use
of SHG and SE-MIRSI.
Aim 2. Validate spatially registered SHG/SE-MIRSI method on high grade serous ovarian cancer and identify
specific associated structural morphology and biochemical signatures.

## Key facts

- **NIH application ID:** 10894280
- **Project number:** 5R61CA281795-02
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** Paul J Campagnola
- **Activity code:** R61 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $197,983
- **Award type:** 5
- **Project period:** 2023-08-01 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10894280

## Citation

> US National Institutes of Health, RePORTER application 10894280, A novel multimodal ECM analysis platform for tumor characterization combining morphological and spectrochemical tissue imaging approaches. (5R61CA281795-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10894280. Licensed CC0.

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