Suppr超能文献

在早期临床试验中发现和评估蛋白质生物标志物作为晚期癌症患者健康状况的特征

Discovery and Evaluation of Protein Biomarkers as a Signature of Wellness in Late-Stage Cancer Patients in Early Phase Clinical Trials.

作者信息

Geary Bethany, Peat Erin, Dransfield Sarah, Cook Natalie, Thistlethwaite Fiona, Graham Donna, Carter Louise, Hughes Andrew, Krebs Matthew G, Whetton Anthony D

机构信息

Stoller Biomarker Discovery Centre, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9NQ, UK.

Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK.

出版信息

Cancers (Basel). 2021 May 18;13(10):2443. doi: 10.3390/cancers13102443.

Abstract

TARGET (tumour characterisation to guide experimental targeted therapy) is a cancer precision medicine programme focused on molecular characterisation of patients entering early phase clinical trials. Performance status (PS) measures a patient's ability to perform a variety of activities. However, the quality of present algorithms to assess PS is limited and based on qualitative clinician assessment. Plasma samples from patients enrolled into TARGET were analysed using the mass spectrometry (MS) technique: sequential window acquisition of all theoretical fragment ion spectra (SWATH)-MS. SWATH-MS was used on a discovery cohort of 55 patients to differentiate patients into either a good or poor prognosis by creation of a Wellness Score (WS) that showed stronger prediction of overall survival ( = 0.000551) compared to PS ( = 0.001). WS was then tested against a validation cohort of 77 patients showing significant ( = 0.000451) prediction of overall survival. WS in both sets had receiver operating characteristic curve area under the curve (AUC) values of 0.76 ( = 0.002) and 0.67 ( = 0.011): AUC of PS was 0.70 ( = 0.117) and 0.55 ( = 0.548). These signatures can now be evaluated further in larger patient populations to assess their utility in a clinical setting.

摘要

TARGET(肿瘤特征描述以指导实验性靶向治疗)是一项癌症精准医疗计划,专注于对进入早期临床试验的患者进行分子特征描述。体能状态(PS)衡量患者进行各种活动的能力。然而,目前评估PS的算法质量有限,且基于临床医生的定性评估。使用质谱(MS)技术,即所有理论碎片离子谱的顺序窗口采集(SWATH)-MS,对纳入TARGET的患者的血浆样本进行分析。SWATH-MS应用于一个由55名患者组成的发现队列,通过创建健康评分(WS)将患者分为预后良好或不良,与PS相比(P = 0.001),WS对总生存期的预测更强(P = 0.000551)。然后,在一个由77名患者组成的验证队列中对WS进行测试,结果显示其对总生存期有显著(P = 0.000451)预测能力。两组中的WS的曲线下面积(AUC)值分别为0.76(P = 0.002)和0.67(P = 0.011);PS的AUC分别为0.70(P = 0.117)和0.55(P = 0.548)。现在可以在更大的患者群体中进一步评估这些特征,以评估它们在临床环境中的效用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e1d/8157875/546419c3c385/cancers-13-02443-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验