Converging deep learning and human-observed tumor-adipocyte interaction as a biomarker in colorectal cancer

By proving the substantial overlap between human-observed SARIFA and DL-based TAF as morphologic biomarkers, we demonstrate that linking DL-based image features to independently developed histopathologic biomarkers is a promising tool in the identification of clinically and biologically meaningful biomarkers. Adipocyte-tumor-cell interactions seem to be crucial in CRC, which should be considered as biomarkers for further investigations.

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Publication Details

Journal
Communications Medicine
Published
2024-08-15
DOI
https://doi.org/10.1038/s43856-024-00589-6
Citations
12
Primary Topic
Cancer, Lipids, and Metabolism
Type
article
Field-Weighted Citation Impact
3.42

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article

Converging deep learning and human-observed tumor-adipocyte interaction as a biomarker in colorectal cancer

David F. Steiner, Hannah S. Muti, Bruno Märkl, Vincenzo L’Imperio et al.
12 citations
Communications Medicine
Cancer, Lipids, and Metabolism
3.42
article

Converging deep learning and human-observed tumor-adipocyte interaction as a biomarker in colorectal cancer

David F. Steiner, Hannah S. Muti, Bruno Märkl, Vincenzo L’Imperio, Kurt Zatloukal, Nic G. Reitsam, Markus Plass, Bianca Grosser, Jakob Nikolas Kather, Ellery Wulczyn, Veselin Grozdanov, Heimo Müller
article en
12 citations

Abstract

By proving the substantial overlap between human-observed SARIFA and DL-based TAF as morphologic biomarkers, we demonstrate that linking DL-based image features to independently developed histopathologic biomarkers is a promising tool in the identification of clinically and biologically meaningful biomarkers. Adipocyte-tumor-cell interactions seem to be crucial in CRC, which should be considered as biomarkers for further investigations.

Communications MedicineVol. 4(1)
Google (United States) (US), University of Leeds (GB), University of Augsburg (DE), Universität Ulm (DE), Medical University of Graz (AT), Heidelberg University (DE), Cancer Research UK (GB), University Hospital Heidelberg (DE), Fresenius (Germany) (DE), National Center for Tumor Diseases (DE), Istituti di Ricovero e Cura a Carattere Scientifico (IT), University Hospital Carl Gustav Carus (DE), University of Milano-Bicocca (IT), Technische Universität Dresden (DE)
National Institute for Health and Care Research, Department of Health and Social Care, European Commission, Deutscher Akademischer Austauschdienst, Bundesministerium für Bildung und Forschung, Bundesministerium für Gesundheit, Deutsche Krebshilfe, Gemeinsame Bundesausschuss, HORIZON EUROPE Framework Programme, Leeds Biomedical Research Centre
Openalex Percentile: Top 7%
Cancer, Lipids, and Metabolism
3.42
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