ReviewProstate cancer and prostatic diseases2018
Prostate cancer diagnosis and characterization with mass spectrometry imaging.
Review in Prostate cancer and prostatic diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 26 citations in OpenAlex.
- Review
- In Search of Ideal Solutions for Cancer Diagnosis: From Conventional Methods to Protein Biomarkers in Liquid Biopsy.Proteomes · 2025Review
- Lipidomics, Microbiota, and IntestinalInternational journal of molecular sciences · 2025Review
- Integrative analysis of the SOX family-related prognostic signature and immunological infiltration in prostate cancer.Translational cancer research · 2023Article
- Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images.Journal of the American Society for Mass Spectrometry · 2023Article
- The foundations and development of lipidomics.Journal of lipid research · 2022Review
- Multiplatform Metabolomics Studies of Human Cancers With NMR and Mass Spectrometry Imaging.Frontiers in molecular biosciences · 2022Article
- Review
- Removal of optimal cutting temperature (O.C.T.) compound from embedded tissue for MALDI imaging of lipids.Analytical and bioanalytical chemistry · 2021Article
- Prostate Cancer Progression: as a Matter of Fats.Frontiers in oncology · 2021Review
- Anticancer Drug Affects Metabolomic Profiles in Multicellular Spheroids: Studies Using Mass Spectrometry Imaging Combined with Machine Learning.Analytical chemistry · 2019Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundProstate cancer (PCa), the most common cancer and second leading cause of cancer death in American men, presents the clinical challenge of distinguishing between indolent and aggressive tumors for proper treatment. PCa presents significant alterations in metabolic pathways that can potentially be measured using techniques like mass spectrometry (MS) or MS imaging (MSI) and used to characterize PCa aggressiveness. MS quantifies metabolomic, proteomic, and lipidomic profiles of biological systems that can be further visualized for their spatial distributions through MSI.
methodsPubMed was queried for all publications relating to MS and MSI in human PCa from April 2007 to April 2017. With the goal of reviewing the utility of MSI in diagnosis and prognostication of human PCa, MSI articles that reported investigations of PCa-specific metabolites or metabolites indicating PCa aggressiveness were selected for inclusion. Articles were included that covered MS and MSI principles, limitations, and applications in PCa.
resultsWe identified nine key studies on MSI in intact human prostate tissue specimens that determined metabolites which could either differentiate between benign and malignant prostate tissue or indicate PCa aggressiveness. These MSI-detected biomarkers show promise in reliably identifying PCa and determining disease aggressiveness.
conclusionsMSI represents an innovative technique with the ability to interrogate cancer biomarkers in relation to tissue pathologies and investigate tumor aggressiveness. We propose MSI as a powerful adjuvant histopathology imaging tool for prostate tissue evaluations, where clinical translation of this ex vivo technique could make possible the use of MSI for personalized medicine in diagnosis and prognosis of PCa. Moreover, the knowledge provided from this technique can majorly contribute to the understanding of molecular pathogenesis of PCa and other malignant diseases.
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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.