Tumor-educated platelet blood tests for Non-Small Cell Lung Cancer detection and management

Author:

Antunes-Ferreira Mafalda,D’Ambrosi Silvia,Arkani Mohammad,Post Edward,In ‘t Veld Sjors G. J. G.,Ramaker Jip,Zwaan Kenn,Kucukguzel Ece Demirel,Wedekind Laurine E.,Griffioen Arjan W.,Oude Egbrink Mirjam,Kuijpers Marijke J. E.,van den Broek Daan,Noske David P.,Hartemink Koen J.,Sabrkhany Siamack,Bahce Idris,Sol Nik,Bogaard Harm-Jan,Koppers-Lalic Danijela,Best Myron G.,Wurdinger Thomas

Abstract

AbstractLiquid biopsy approaches offer a promising technology for early and minimally invasive cancer detection. Tumor-educated platelets (TEPs) have emerged as a promising liquid biopsy biosource for the detection of various cancer types. In this study, we processed and analyzed the TEPs collected from 466 Non-small Cell Lung Carcinoma (NSCLC) patients and 410 asymptomatic individuals (controls) using the previously established thromboSeq protocol. We developed a novel particle-swarm optimization machine learning algorithm which enabled the selection of an 881 RNA biomarker panel (AUC 0.88). Herein we propose and validate in an independent cohort of samples (n = 558) two approaches for blood samples testing: one with high sensitivity (95% NSCLC detected) and another with high specificity (94% controls detected). Our data explain how TEP-derived spliced RNAs may serve as a biomarker for minimally-invasive clinical blood tests, complement existing imaging tests, and assist the detection and management of lung cancer patients.

Funder

Horizon 2020

Stichting STOPhersentumoren.nl

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Artificial intelligence and machine learning in hemostasis and thrombosis;Bleeding, Thrombosis and Vascular Biology;2024-01-31

2. Graph Convolutional Networks based Non-Small Cell Lung Cancer Identification using RNA-seq Data from Blood Samples;2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology;2023-12-07

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