Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets

Myron G Best, Nik Sol, Sjors G J G In 't Veld, Adrienne Vancura, Mirte Muller, Anna-Larissa N Niemeijer, Aniko V Fejes, Lee-Ann Tjon Kon Fat, Anna E Huis In 't Veld, Cyra Leurs, Tessa Y Le Large, Laura L Meijer, Irsan E Kooi, François Rustenburg, Pepijn Schellen, Heleen Verschueren, Edward Post, Laurine E Wedekind, Jillian Bracht, Michelle EsenkbrinkLeon Wils, Francesca Favaro, Jilian D Schoonhoven, Jihane Tannous, Hanne Meijers-Heijboer, Geert Kazemier, Elisa Giovannetti, Jaap C Reijneveld, Sander Idema, Joep Killestein, Michal Heger, Saskia C de Jager, Rolf T Urbanus, Imo E Hoefer, Gerard Pasterkamp, Christine Mannhalter, Jose Gomez-Arroyo, Harm-Jan Bogaard, David P Noske, W Peter Vandertop, Daan van den Broek, Bauke Ylstra, R Jonas A Nilsson, Pieter Wesseling, Niki Karachaliou, Rafael Rosell, Elizabeth Lee-Lewandrowski, Kent B Lewandrowski, Bakhos A Tannous, Adrianus J de Langen, Egbert F Smit, Michel M van den Heuvel, Thomas Wurdinger, Sjors G.J.G. In ‘t Veld

Research output: Contribution to journalArticleAcademicpeer-review

181 Citations (Scopus)

Abstract

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 < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources.

Original languageEnglish
Pages (from-to)238-252.e9
JournalCancer cell
Volume32
Issue number2
DOIs
Publication statusPublished - 14 Aug 2017

Keywords

  • Adult
  • Aged
  • Aged, 80 and over
  • Algorithms
  • Artificial Intelligence
  • Biomarkers, Tumor
  • Blood Platelets/physiology
  • Carcinoma, Non-Small-Cell Lung/blood
  • Cohort Studies
  • Diagnosis, Computer-Assisted/methods
  • Female
  • Gene Expression Profiling
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Inflammation/blood
  • Lung Neoplasms/blood
  • Male
  • Middle Aged
  • NSCLC
  • RNA
  • Support Vector Machine
  • blood platelets
  • cancer diagnostics
  • liquid biopsies
  • particle-swarm optimization
  • self-learning algorithms
  • splicing
  • swarm intelligence
  • tumor-educated platelets

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