Detecting Prostate Cancer Using Pattern Recognition Neural Networks With Flow Cytometry-Based Immunophenotyping in At-Risk Men.

IF 3.4 Q2 MEDICINE, RESEARCH & EXPERIMENTAL Biomarker Insights Pub Date : 2020-04-17 eCollection Date: 2020-01-01 DOI:10.1177/1177271920913320
George A Dominguez, Alexander T Polo, John Roop, Anthony J Campisi, Robert A Somer, Adam D Perzin, Dmitry I Gabrilovich, Amit Kumar
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Abstract

Current screening methods for prostate cancer (PCa) result in a large number of false positives making it difficult for clinicians to assess disease status, thus warranting advancements in screening and early detection methods. The goal of this study was to design a liquid biopsy test that uses flow cytometry-based immunophenotyping and artificial neural network (ANN) analysis to detect PCa. Numerous myeloid and lymphoid cell populations, including myeloid-derived suppressor cells, were measured from 156 patients with PCa, 123 with benign prostatic hyperplasia (BPH), and 99 male healthy donor (HD) controls. Using pattern recognition neural network (PRNN) analysis, a type of ANN, PCa detection compared against HD resulted in 96.6% sensitivity, 87.5% specificity, and an area under the curve (AUC) value of 0.97. Detecting patients with higher risk disease (⩾Gleason 7) against lower risk disease (BPH/Gleason 6) resulted in 92.0% sensitivity, 42.7% specificity, and an AUC of 0.72. This study suggests that analyzing flow cytometry immunophenotyping data with PRNNs may prove to be a useful tool to improve PCa detection and reduce the number of unnecessary prostate biopsies performed each year.

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使用模式识别神经网络和基于流式细胞术的免疫表型在高危男性中检测前列腺癌。
目前的前列腺癌(PCa)筛查方法导致大量假阳性,使临床医生难以评估疾病状态,因此需要在筛查和早期检测方法方面取得进展。本研究的目的是设计一种液体活检测试,使用基于流式细胞术的免疫表型和人工神经网络(ANN)分析来检测PCa。对156例PCa患者、123例良性前列腺增生(BPH)患者和99例男性健康供体(HD)对照进行了大量髓系和淋巴细胞群(包括髓系来源的抑制细胞)检测。采用模式识别神经网络(PRNN)分析,与HD相比,PCa检测的灵敏度为96.6%,特异性为87.5%,曲线下面积(AUC)值为0.97。检测高风险疾病(小于或等于Gleason 7)的患者与低风险疾病(BPH/Gleason 6)的对比,导致92.0%的敏感性,42.7%的特异性,AUC为0.72。这项研究表明,用prnn分析流式细胞术免疫表型数据可能是一种有用的工具,可以提高前列腺癌的检测水平,减少每年不必要的前列腺活检次数。
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来源期刊
Biomarker Insights
Biomarker Insights MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
6.00
自引率
0.00%
发文量
26
审稿时长
8 weeks
期刊介绍: An open access, peer reviewed electronic journal that covers all aspects of biomarker research and clinical applications.
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