Characterization of cancer-associated adipocytes by Raman spectroscopy and trajectory inference

Abstract Cancer-associated adipocytes (CAAs) have emerged as pivotal players in various cancers, particularly in such as breast cancer, significantly influencing their progression and therapy resistance. Understanding the adipocytes/cancer cells crosstalk is crucial for effective treatment strategies. Raman spectroscopy, a label-free optical technique, offers potential for characterizing biological samples by providing chemical-specific information. In this study, we used Raman spectroscopy and Trajectory Inference methods, specifically the Partition-based graph abstraction algorithm, to investigate the interactions between 3T3-L1 differentiated adipocytes and MDA-MB-231 breast cancer cells in a 2D co-culture model. We demonstrate the existence of subpopulations of adipocytes and the molecular changes associated with CAAs phenotype. This work contributes to understanding the role of CAAs in breast cancer progression and may guide the development of targeted therapies disrupting this interaction.

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Publication Details

Journal
PhotoniX
Published
2024-10-23
DOI
https://doi.org/10.1186/s43074-024-00146-3
Citations
5
Primary Topic
Spectroscopy Techniques in Biomedical and Chemical Research
Type
article
Field-Weighted Citation Impact
3.31

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article

Characterization of cancer-associated adipocytes by Raman spectroscopy and trajectory inference

Nicolas Goffin, Charlotte Vaysse, Olivier Piot, Inês Miguel et al.
5 citations
PhotoniX
Spectroscopy Techniques in Biomedical and Chemical Research
3.31
article

Characterization of cancer-associated adipocytes by Raman spectroscopy and trajectory inference

Nicolas Goffin, Charlotte Vaysse, Olivier Piot, Inês Miguel, Émilie Buache, Nathalie Lalun, Landry Blanc, Cyril Gobinet, Catherine Muller, M.O. Fernandes
article en
5 citations

Abstract

Abstract Cancer-associated adipocytes (CAAs) have emerged as pivotal players in various cancers, particularly in such as breast cancer, significantly influencing their progression and therapy resistance. Understanding the adipocytes/cancer cells crosstalk is crucial for effective treatment strategies. Raman spectroscopy, a label-free optical technique, offers potential for characterizing biological samples by providing chemical-specific information. In this study, we used Raman spectroscopy and Trajectory Inference methods, specifically the Partition-based graph abstraction algorithm, to investigate the interactions between 3T3-L1 differentiated adipocytes and MDA-MB-231 breast cancer cells in a 2D co-culture model. We demonstrate the existence of subpopulations of adipocytes and the molecular changes associated with CAAs phenotype. This work contributes to understanding the role of CAAs in breast cancer progression and may guide the development of targeted therapies disrupting this interaction.

PhotoniXVol. 5(1)
Centre National de la Recherche Scientifique (FR), Université Toulouse III - Paul Sabatier (FR), Inserm (FR), Université Fédérale de Toulouse Midi-Pyrénées (FR), Institut universitaire du cancer de Toulouse Oncopole (FR), Institut de Pharmacologie et de Biologie Structurale (FR), Biostatistique et processus spatiaux (FR), Pathologies Pulmonaires et Plasticité Cellulaire, BioSpectroscopie Translationnelle, Université de Reims Champagne-Ardenne (FR)
Alliance Nationale pour les Sciences de la Vie et de la Santé, European Commission
Good health and well-being
Openalex Percentile: Top 8%
Spectroscopy Techniques in Biomedical and Chemical Research
3.31
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