Highlights

Above

When collagen (green) forms thick aggregates (red) in breast tumors, it facilitates the migration of cancer cells throughout the body.

© A*STAR’s Institute of Molecular and Cell Biology (IMCB)

A collagen ‘highway’ for cancer

1 Feb 2021

The structure of collagen fibers may play a key role in the spread of breast cancer, with implications for clinical prognosis and treatment.

The US National Cancer Institute estimates that 12.9 percent of women will be diagnosed with breast cancer in their lifetime, making it a serious health issue for women across the globe. In particular, triple-negative breast cancers are the most aggressive of invasive cancers, for which prognosis is challenging and clinical outcomes are poor.

Previously, it was believed that collagen in breast tissue acted as a physical barrier preventing the spread of tumor cells from their original site. However, subsequent research found that collagen might also act as a ‘highway,’ facilitating tumor cell migration to remote locations. The knowledge gap was due to the limitations of staining techniques used to study the tumor microenvironment.

To better identify the role of collagen in tumor cell migration, researchers used a laser-based imaging technique called second harmonic generation (SHG) imaging to examine collagen fibers at a finer level of detail. Clinical samples were provided by Singapore General Hospital and the experiment is jointly designed by the hospital’s Division of Pathology.

“SHG is a multiphoton, laser-based, quantitative nonlinear optical imaging technique used to identify fibrillary collagen in fixed tissues,” explained Weimiao Yu, Head of the Computational & Molecular Pathology Lab at A*STAR’s Institute of Molecular and Cell Biology (IMCB), and a co-corresponding author on the study. “Due to its physical principles, SHG is highly sensitive to changes in collagen fibril and fiber structure, and also to the remodeling of connective tissue.”

Using two-photon excitation and SHG to scan breast cancer tissue microarrays, the research team was able to differentiate between aggregated thick collagen (ATC) and dispersed thin collagen (DTC) in the samples. Importantly, the fiber density of ATC and fiber length of DTC corresponded to clinicopathological features such as tumor size and whether the tumor was invasive or non-invasive, as well as the disease-free survival of patients with triple-negative breast cancer.

“Collagen structure, profiles and patterns within the tumor stromal microenvironment have diagnostic and prognostic value. It is an oversimplification to characterize collagen remodeling as a simple increase or decrease in total collagen content,” Yu said. He noted that the genetic mechanisms controlling the differences described in the study may require further investigation.

These findings may help clinicians plan better treatment regimens for their patients, Yu said. For example, less aggressive treatment plans could be implemented for patients that have collagen structures that indicate higher survival rates. The research outcomes have been licensed to A*STAR spin-off HistoIndex for commercialization and A*ccelerate for market development.

The A*STAR-affiliated researchers contributing to this research are from the Institute of Molecular and Cell Biology (IMCB), the Singapore Immunology Network (SIgN), and the Diagnostic Development Hub (DxD).

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References

Gole, L., Yeong, J., Lim, J.C.T., Ong, K.H., Han, H., et al. Quantitative stain-free imaging and digital profiling of collagen structure reveal diverse survival of triple negative breast cancer patients. Breast Cancer Res 22, 42 (2020) | article

About the Researcher

Weimiao Yu

Head, Computational & Molecular Pathology Lab

Institute of Molecular and Cell Biology
Weimiao Yu obtained his PhD degree from the National University of Singapore (NUS) in 2007, majoring in image processing and machine vision. He joined A*STAR’s Institute of Molecular and Cell Biology (IMCB) in 2007. Yu is currently heading the Computational & Molecular Pathology Lab (CMPL) to deepen and extend R&D collaborations with clinical and industry partners. His research interests are in computational biomedical image analysis and quantitative imaging informatics. To enhance the application of machine learning and AI in clinical diagnosis/prognosis, he co-founded a biotech company called A!maginostic Pte. Ltd. Researchers at a joint lab of excellence which Yu established between A!maginostic and IMCB conduct immunodiagnosis at the tissue level.

This article was made for A*STAR Research by Wildtype Media Group