Department of Neurosurgery, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
Cancer Center Amsterdam, Amsterdam, The Netherlands.
Sci Rep. 2023 Jun 8;13(1):9359. doi: 10.1038/s41598-023-35818-w.
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.
液体活检方法为早期和微创癌症检测提供了一种很有前途的技术。肿瘤教育血小板(TEP)已成为检测各种癌症类型的很有前途的液体活检生物源。在这项研究中,我们使用先前建立的血栓测序协议处理和分析了从 466 名非小细胞肺癌(NSCLC)患者和 410 名无症状个体(对照)中收集的 TEP。我们开发了一种新的粒子群优化机器学习算法,该算法能够选择 881 个 RNA 生物标志物组(AUC 为 0.88)。在此,我们在一个独立的样本队列(n=558)中提出并验证了两种血液样本测试方法:一种具有高灵敏度(检测到 95%的 NSCLC),另一种具有高特异性(检测到 94%的对照)。我们的数据解释了 TEP 衍生的剪接 RNA 如何作为微创临床血液测试的生物标志物,补充现有的成像测试,并协助肺癌患者的检测和管理。