ArticleMolecular oncology2021
imPlatelet classifier: image-converted RNA biomarker profiles enable blood-based cancer diagnostics.
Article in Molecular oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Precision medicine in diagnosis, prognosis, and disease monitoring of bone and soft tissue sarcomas using liquid biopsy: a systematic review.Archives of orthopaedic and trauma surgery · 2025Pooled it
- Platelet-derived mitochondrial transfer in cancer metastasis: mechanisms, functional consequences, and translational opportunities.Clinical & experimental metastasis · 2026Review
- Exploring platelet-covered and naked circulating tumor cells - a single-cell transcriptomic perspective.Journal of translational medicine · 2026Article
- Large-Scale Quantitative Morphometry of Platelet α-Granules via SIM Super-Resolution Microscopy for Cancer Liquid Biopsy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Integrative analysis of tumor-educated platelets for stage-specific diagnosis, prognosis, and therapy in ovarian cancer.Discover oncology · 2026Article
- Tumor-educated platelet RNA as a diagnostic biomarker for ground-glass opacity-related lung adenocarcinoma.Translational lung cancer research · 2025Article
- Article
- Impact of clinical factors on accuracy of ovarian cancer detection via platelet RNA profiling.Blood advances · 2025Article
- The role of platelets in cancer: from their influence on tumor progression to their potential use in liquid biopsy.Biomarker research · 2025Review
- Case Report: Blood single-cell analysis of a IVB high-grade serous ovarian cancer patient presenting a favorable prognosis.Frontiers in oncology · 2025Article
- Clinical utility of various liquid biopsy samples for the early detection of ovarian cancer: a comprehensive review.Frontiers in oncology · 2025Review
- Improving platelet-RNA-based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification.Molecular oncology · 2024Article
- Clinical application of liquid biopsy in colorectal cancer: detection, prediction, and treatment monitoring.Molecular cancer · 2024Review
- Roles of Tumor-Educated Platelets (TEPs) in the biology of Non-Small Cell Lung Cancer (NSCLC): A systematic review. "Re-discovering the neglected biosources of the liquid biopsy family".The journal of liquid biopsy · 2024Review
- Bleeding and Thrombosis in Multiple Myeloma: Platelets as Key Players during Cell Interactions and Potential Use as Drug Delivery Systems.International journal of molecular sciences · 2023Review
- Article
- Tumor-Educated Platelets as a Promising Biomarker for Blood-Based Detection of Renal Cell Carcinoma.Frontiers in oncology · 2022Article
- Article
- Transcriptomic landscape of blood platelets in healthy donors.Scientific reports · 2021Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia of Genes and Genomes was also implemented to improve accuracy. Images obtained from samples can then be compared against standard images for specific cancers to determine a diagnosis. We tested imPlatelet on a cohort of 401 non-small cell lung cancer patients, 62 sarcoma patients, and 28 ovarian cancer patients. imPlatelet provided excellent discrimination between lung cancer cases and healthy controls, with accuracy equal to 1 in the independent dataset. When discriminating between noncancer cases and sarcoma or ovarian cancer patients, accuracy equaled 0.91 or 0.95, respectively, in the independent datasets. According to our knowledge, this is the first study implementing an image-based deep-learning approach combined with biological knowledge to classify human samples. The performance of imPlatelet considerably exceeds previously published methods and our own alternative attempts of sample discrimination. We show that the deep-learning image-based classifier accurately identifies cancer, even when a limited number of samples are available.
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