Goetze Sandra, Schüffler Peter, Athanasiou Alcibiade, Koetemann Anika, Poyet Cedric, Fankhauser Christian Daniel, Wild Peter J, Schiess Ralph, Wollscheid Bernd
Department of Health Sciences and Technology, Institute of Translational Medicine, Swiss Federal Institute of Technology, ETH Zurich, 8093, Zurich, Switzerland.
Swiss Institute of Bioinformatics (SIB), 1015, Lausanne, Switzerland.
Clin Proteomics. 2022 Apr 27;19(1):9. doi: 10.1186/s12014-022-09349-x.
Non-invasive liquid biopsies could complement current pathological nomograms for risk stratification of prostate cancer patients. Development and testing of potential liquid biopsy markers is time, resource, and cost-intensive. For most protein targets, no antibodies or ELISAs for efficient clinical cohort pre-evaluation are currently available. We reasoned that mass spectrometry-based prescreening would enable the cost-effective and rational preselection of candidates for subsequent clinical-grade ELISA development.
Using Mass Spectrometry-GUided Immunoassay DEvelopment (MS-GUIDE), we screened 48 literature-derived biomarker candidates for their potential utility in risk stratification scoring of prostate cancer patients. Parallel reaction monitoring was used to evaluate these 48 potential protein markers in a highly multiplexed fashion in a medium-sized patient cohort of 78 patients with ground-truth prostatectomy and clinical follow-up information. Clinical-grade ELISAs were then developed for two of these candidate proteins and used for significance testing in a larger, independent patient cohort of 263 patients.
Machine learning-based analysis of the parallel reaction monitoring data of the liquid biopsies prequalified fibronectin and vitronectin as candidate biomarkers. We evaluated their predictive value for prostate cancer biochemical recurrence scoring in an independent validation cohort of 263 prostate cancer patients using clinical-grade ELISAs. The results of our prostate cancer risk stratification test were statistically significantly 10% better than results of the current gold standards PSA alone, PSA plus prostatectomy biopsy Gleason score, or the National Comprehensive Cancer Network score in prediction of recurrence.
Using MS-GUIDE we identified fibronectin and vitronectin as candidate biomarkers for prostate cancer risk stratification.
非侵入性液体活检可为当前前列腺癌患者风险分层的病理列线图提供补充。潜在液体活检标志物的开发和测试需要耗费大量时间、资源和成本。对于大多数蛋白质靶点，目前尚无用于高效临床队列预评估的抗体或酶联免疫吸附测定（ELISA）。我们推断基于质谱的预筛选能够以具有成本效益且合理的方式预先选择候选物，以用于后续临床级ELISA的开发。
我们使用质谱引导的免疫测定开发（MS-GUIDE），筛选了48个从文献中获取的生物标志物候选物，评估它们在前列腺癌患者风险分层评分中的潜在效用。在一个包含78例接受根治性前列腺切除术且有临床随访信息的中型患者队列中，采用平行反应监测以高度多重的方式评估这48种潜在蛋白质标志物。随后针对其中两种候选蛋白开发了临床级ELISA，并在一个由263例患者组成的更大的独立患者队列中进行显著性检验。
基于机器学习对液体活检的平行反应监测数据进行分析，初步鉴定纤连蛋白和玻连蛋白为候选生物标志物。我们使用临床级ELISA在一个由263例前列腺癌患者组成的独立验证队列中评估了它们对前列腺癌生化复发评分的预测价值。在预测复发方面，我们的前列腺癌风险分层测试结果在统计学上比目前单独使用前列腺特异性抗原（PSA）、PSA加前列腺切除活检Gleason评分或美国国立综合癌症网络（National Comprehensive Cancer Network）评分等金标准的结果显著高出10%。
通过MS-GUIDE，我们鉴定出纤连蛋白和玻连蛋白为前列腺癌风险分层的候选生物标志物。
