ArticleScientific reports2020
Infrared Spectroscopic Imaging Visualizes a Prognostic Extracellular Matrix-Related Signature in Breast Cancer.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Proteomic landscape of decellularized breast carcinomas identifies C-type lectin domain family 3 member A as a driver of cancer aggressiveness.NPJ breast cancer · 2025Article
- Machine learning-assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues.Journal of biomedical optics · 2024Article
- Machine learning assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues.bioRxiv : the preprint server for biology · 2024Article
- Modeling the extracellular matrix in cell migration and morphogenesis: a guide for the curious biologist.Frontiers in cell and developmental biology · 2024Review
- Metasurface-Enhanced Mid-Infrared Spectrochemical Imaging of Tissues.Advanced materials (Deerfield Beach, Fla.) · 2023Article
- Fourier Transform Infrared Spectroscopy in Oral Cancer Diagnosis.International journal of molecular sciences · 2021Review
- Vibrational Spectroscopy for Identification of Metabolites in Biologic Samples.Molecules (Basel, Switzerland) · 2020Review
- Infrared Spectroscopic Analysis in the Differentiation of Epithelial Misplacement From Adenocarcinoma in Sigmoid Colonic Adenomatous Polyps.Clinical pathology (Thousand Oaks, Ventura County, Calif.)Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
Abstract
Molecular analysis techniques such as gene expression analysis and proteomics have contributed greatly to our understanding of cancer heterogeneity. In prior studies, gene expression analysis was shown to stratify patient outcome on the basis of tumor-microenvironment associated genes. A specific gene expression profile, referred to as ECM3 (Extracellular Matrix Cluster 3), indicated poorer survival in patients with grade III tumors. In this work, we aimed to visualize the downstream effects of this gene expression profile onto the tissue, thus providing a spatial context to altered gene expression profiles. Using infrared spectroscopic imaging, we identified spectral patterns specific to the ECM3 gene expression profile, achieving a high spectral classification performance of 0.87 as measured by the area under the curve of the receiver operating characteristic curve. On a patient level, we correctly identified 20 out of 22 ECM3 group patients and 19 out of 20 non-ECM3 group patients by using this spectroscopic imaging-based classifier. By comparing pixels that were identified as ECM3 or non-ECM3 with H&E and IHC images, we were also able to observe an association between tissue morphology and the gene expression clusters, showing the ability of our method to capture broad outcome associated features from infrared images.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.