ArticleProceedings of the National Academy of Sciences of the United States of America2014
Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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Who cites it
58 citing papers in PubMed.
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- Supervised topological data analysis for MALDI mass spectrometry imaging applications.BMC bioinformatics · 2023Article
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- Correlative Chemical Imaging and Spatial Chemometrics Delineate Alzheimer Plaque Heterogeneity at High Spatial Resolution.JACS Au · 2023Article
- MSIr: Automatic Registration Service for Mass Spectrometry Imaging and Histology.Analytical chemistry · 2023Article
- Classification of Pancreatic Ductal Adenocarcinoma Using MALDI Mass Spectrometry Imaging Combined with Neural Networks.Cancers · 2023Article
- Untangling Alzheimer's disease with spatial multi-omics: a brief review.Frontiers in aging neuroscience · 2023Review
- DiviK: divisive intelligent K-means for hands-free unsupervised clustering in big biological data.BMC bioinformatics · 2022Article
- Emerging Computational Methods in Mass Spectrometry Imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Review
- Evaluation of Proteomic and Lipidomic Changes inInternational journal of molecular sciences · 2022Article
- Mass spectrometry imaging to explore molecular heterogeneity in cell culture.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- High Resolution Ambient MS Imaging of Biological Samples by Desorption Electro-Flow Focussing Ionization.Analytical chemistry · 2022Article
- Automated Cancer Diagnostics via Analysis of Optical and Chemical Images by Deep and Shallow Learning.Metabolites · 2022Article
- Metabonomics study of the effects of single copy mutant KRAS in the presence or absence of WT allele using human HCT116 isogenic cell lines.Metabolomics : Official journal of the Metabolomic Society · 2021Article
- The effect of sample age on the metabolic information extracted from formalin-fixed and paraffin embedded tissue samples using desorption electrospray ionization mass spectrometry imaging.Journal of mass spectrometry and advances in the clinical lab · 2021Article
- A Mass Spectrometry Imaging Based Approach for Prognosis Prediction in UICC Stage I/II Colon Cancer.Cancers · 2021Article
- Peak learning of mass spectrometry imaging data using artificial neural networks.Nature communications · 2021Article
- An integrated mass spectrometry imaging and digital pathology workflow for objective detection of colorectal tumours by unique atomic signatures.Chemical science · 2021Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mass spectrometry imaging (MSI) provides the opportunity to investigate tumor biology from an entirely novel biochemical perspective and could lead to the identification of a new pool of cancer biomarkers. Effective clinical translation of histology-driven MSI in systems oncology requires precise colocalization of morphological and biochemical features as well as advanced methods for data treatment and interrogation. Currently proposed MSI workflows are subject to several limitations, including nonoptimized raw data preprocessing, imprecise image coregistration, and limited pattern recognition capabilities. Here we outline a comprehensive strategy for histology-driven MSI, using desorption electrospray ionization that covers (i) optimized data preprocessing for improved information recovery; (ii) precise image coregistration; and (iii) efficient extraction of tissue-specific molecular ion signatures for enhanced biochemical distinction of different tissue types. The proposed workflow has been used to investigate region-specific lipid signatures in colorectal cancer tissue. Unique lipid patterns were observed using this approach according to tissue type, and a tissue recognition system using multivariate molecular ion patterns allowed highly accurate (>98%) identification of pixels according to morphology (cancer, healthy mucosa, smooth muscle, and microvasculature). This strategy offers unique insights into tumor microenvironmental biochemistry and should facilitate compilation of a large-scale tissue morphology-specific MSI spectral database with which to pursue next-generation, fully automated histological approaches.
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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.