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Issue 5, 2014
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Infrared imaging in breast cancer: automated tissue component recognition and spectral characterization of breast cancer cells as well as the tumor microenvironment

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Abstract

Current evaluation of histological sections of breast cancer samples remains unsatisfactory. The search for new predictive and prognostic factors is ongoing. Infrared spectroscopy and its potential to probe tissues and cells at the molecular level without requirement for contrast agents could be an attractive tool for clinical and diagnostic analysis of breast cancer. In this study, we report the successful application of FTIR (Fourier transform infrared) imaging for breast tissue component characterization. We show that specific FTIR spectral signatures can be assigned to the major tissue components of breast tumor samples. We demonstrate that a tissue component classifier can be built based on a spectral database of well-annotated tissues and successfully validated on independent breast samples. We also demonstrate that spectral features can reveal subtle differences within a tissue component, capturing for instance lymphocytic and stromal activation. By investigating in parallel lymph nodes, tonsils and wound healing tissues, we prove the uniqueness of the signature of both lymphocytic infiltrate and tumor microenvironment in the breast disease context. Finally, we demonstrate that the biochemical information reflected in the epithelial spectra might be clinically relevant for the grading purpose, suggesting potential to improve breast cancer management in the future.

Graphical abstract: Infrared imaging in breast cancer: automated tissue component recognition and spectral characterization of breast cancer cells as well as the tumor microenvironment

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Publication details

The article was received on 31 Jul 2013, accepted on 05 Dec 2013 and first published on 06 Dec 2013


Article type: Paper
DOI: 10.1039/C3AN01454A
Citation: Analyst, 2014,139, 1044-1056
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    Infrared imaging in breast cancer: automated tissue component recognition and spectral characterization of breast cancer cells as well as the tumor microenvironment

    A. Benard, C. Desmedt, M. Smolina, P. Szternfeld, M. Verdonck, G. Rouas, N. Kheddoumi, F. Rothé, D. Larsimont, C. Sotiriou and E. Goormaghtigh, Analyst, 2014, 139, 1044
    DOI: 10.1039/C3AN01454A

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