1. Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets
- Author
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Anna E. Huis In ‘t Veld, Michel M van den Heuvel, Pieter Wesseling, Niki Karachaliou, Nik Sol, Aniko V. Fejes, Adrianus J. de Langen, Michal Heger, Pepijn Schellen, Laura L. Meijer, Jilian D. Schoonhoven, Hanne Meijers-Heijboer, Sjors G J G In 't Veld, Bakhos A. Tannous, Irsan E. Kooi, Jose Gomez-Arroyo, Jillian Bracht, Rafael Rosell, Anna Larissa N. Niemeijer, Joep Killestein, Mirte Muller, Michelle Esenkbrink, Egbert F. Smit, Imo E. Hoefer, Jihane Tannous, Elizabeth Lee-Lewandrowski, Geert Kazemier, Heleen Verschueren, Francesca Favaro, Sander Idema, Bauke Ylstra, François Rustenburg, Rolf T. Urbanus, W. Peter Vandertop, Laurine E. Wedekind, Christine Mannhalter, Harm Jan Bogaard, Cyra E. Leurs, Adrienne Vancura, Lee Ann Tjon Kon Fat, Edward Post, Leon J Wils, Myron G. Best, Saskia C.A. de Jager, R. Jonas A. Nilsson, Jaap C. Reijneveld, Gerard Pasterkamp, Tessa Y S Le Large, Kent B. Lewandrowski, Elisa Giovannetti, Daan van den Broek, David P. Noske, Thomas Wurdinger, Neurosurgery, Neurology, Pulmonary medicine, ACS - Pulmonary hypertension & thrombosis, CCA - Imaging and biomarkers, Medical oncology laboratory, Surgery, AGEM - Re-generation and cancer of the digestive system, Human genetics, Amsterdam Neuroscience - Neuroinfection & -inflammation, Pathology, Amsterdam Neuroscience - Systems & Network Neuroscience, Amsterdam Neuroscience - Brain Imaging, Amsterdam Reproduction & Development (AR&D), Graduate School, and AGEM - Amsterdam Gastroenterology Endocrinology Metabolism
- Subjects
Male ,0301 basic medicine ,Cancer Research ,Lung Neoplasms ,Support Vector Machine ,blood platelets ,Blood Platelets/physiology ,NSCLC ,Carcinoma, Non-Small-Cell Lung/blood ,Swarm intelligence ,Cohort Studies ,liquid biopsies ,Carcinoma, Non-Small-Cell Lung ,Diagnosis ,80 and over ,Computer-Assisted/methods ,Platelet ,Diagnosis, Computer-Assisted ,particle-swarm optimization ,Aged, 80 and over ,Tumor ,cancer diagnostics ,Non-Small-Cell Lung/blood ,swarm intelligence ,High-Throughput Nucleotide Sequencing ,Middle Aged ,3. Good health ,Diagnosis, Computer-Assisted/methods ,Oncology ,self-learning algorithms ,Biomarker (medicine) ,Female ,Non small cell ,Algorithms ,Rare cancers Radboud Institute for Health Sciences [Radboudumc 9] ,Blood Platelets ,Adult ,Inflammation/blood ,Rare cancers Radboud Institute for Molecular Life Sciences [Radboudumc 9] ,Article ,Lung Neoplasms/blood ,splicing ,03 medical and health sciences ,Artificial Intelligence ,Biomarkers, Tumor ,medicine ,Humans ,Lung cancer ,Aged ,Inflammation ,Cancer och onkologi ,business.industry ,Gene Expression Profiling ,Carcinoma ,Cancer ,Cell Biology ,medicine.disease ,tumor-educated platelets ,030104 developmental biology ,Cancer and Oncology ,Immunology ,Cancer research ,RNA ,business ,Biomarkers - Abstract
Summary Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92–0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83–0.95; p, Graphical Abstract, Highlights • Tumor-educated platelet (TEP) RNA profiles allow for blood-based cancer diagnostics • Inflammatory conditions only minimally confound TEP-based cancer detection • Swarm intelligence algorithms enable efficient selection of biomarker gene panels • TEP gene panels enable support vector machine-based classification of lung cancer, Best et al. use particle-swarm optimization algorithms and RNA-seq of tumor-educated platelets from patients to generate RNA sets capable of identifying patients with non-small-cell lung cancer, including those having early stage, from individuals without cancer, including those having inflammatory conditions.
- Published
- 2017
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