| Autor: |
Mafalda Antunes-Ferreira, Silvia D’Ambrosi, Mohammad Arkani, Edward Post, Sjors G. J. G. In ‘t Veld, Jip Ramaker, Kenn Zwaan, Ece Demirel Kucukguzel, Laurine E. Wedekind, Arjan W. Griffioen, Mirjam Oude Egbrink, Marijke J. E. Kuijpers, Daan van den Broek, David P. Noske, Koen J. Hartemink, Siamack Sabrkhany, Idris Bahce, Nik Sol, Harm-Jan Bogaard, Danijela Koppers-Lalic, Myron G. Best, Thomas Wurdinger |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2045-2322 |
| DOI: |
10.1038/s41598-023-35818-w |
| Popis: |
Abstract Liquid 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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