Xiao Kefeng, Guo Jinan, Zhang Xuhui, Feng Xiaoyan, Zhang Heqiu, Cheng Zhiqiang, Johnson Heather, Persson Jenny L, Chen Lingwu
Department of Urology, Jinan University School of Medicine and Shenzhen People's Hospital, No. 1017, Dongmen Road North, Luo Hu District, Shenzhen, 518020, China.
Department of Bio-Diagnosis, Institute of Basic Medical Sciences, 27, Taiping Road, Beijing, 100850, China.
Tumour Biol. 2016 Aug;37(8):10115-22. doi: 10.1007/s13277-015-4619-0. Epub 2016 Jan 28.
Currently, no ideal prostate cancer (PCa) diagnostic or prognostic test is available due to the lack of biomarkers with high sensitivity and specificity. There is an unmet medical need to develop combinations of multiple biomarkers which may have higher accuracy in detection of PCa and stratification of aggressive and indolent cancer patients. The aim of this study was to test two biomarker gene panels in distinguishing PCa from benign prostate and high-risk, aggressive PCa from low-risk, indolent PCa, respectively. We identified a five-gene panel that can be used to distinguish PCa from benign prostate. The messenger RNA (mRNA) expression signature of the five genes was determined in 144 PCa and benign prostate specimens from prostatectomy. We showed that the five-gene panel distinguished PCa from benign prostate with sensitivity of 96.59 %, specificity of 92.86 %, and area under the curve (AUC) of 0.992 (p < 0.0001). The five-gene panel was further validated in a 137 specimen cohort and showed sensitivity of 84.62 %, specificity of 91.84 %, and AUC of 0.942 (p < 0.0001). To define subtypes of PCa for treatment guidance, we examined mRNA expression signature of an eight-gene panel in 87 PCa specimens from prostatectomy. The signature of the eight-gene panel was able to distinguish aggressive PCa (Gleason score >6) from indolent PCa (Gleason score ≤6) with sensitivity of 90.28 %, specificity of 80.00 %, and AUC of 0.967 (p < 0.0001). This panel was further validated in a 158 specimen cohort and showed significant difference between aggressive PCa and indolent PCa with sensitivity of 92.57 %, specificity of 70.00 %, and AUC of 0.962 (p < 0.0001). Our findings in assessing multiple biomarkers in combination may provide new tools to detect PCa and distinguish aggressive and indolent PCa for precision and personalized treatment. The two biomarker panels may be used in clinical settings for accurate PCa diagnosis and patient risk stratification for biomarker-guided treatment.
目前，由于缺乏具有高敏感性和特异性的生物标志物，尚无理想的前列腺癌（PCa）诊断或预后检测方法。开发多种生物标志物的组合存在未满足的医学需求，这些组合在检测PCa以及区分侵袭性和惰性癌症患者方面可能具有更高的准确性。本研究的目的是分别测试两个生物标志物基因panel，以区分PCa与良性前列腺组织，以及区分高危、侵袭性PCa与低危、惰性PCa。我们鉴定出一个可用于区分PCa与良性前列腺组织的五基因panel。在144例前列腺切除术后的PCa和良性前列腺组织标本中测定了这五个基因的信使核糖核酸（mRNA）表达特征。我们发现，该五基因panel区分PCa与良性前列腺组织的敏感性为96.59%，特异性为92.86%，曲线下面积（AUC）为0.992（p<0.0001）。该五基因panel在一个137例标本的队列中进一步验证，敏感性为84.62%，特异性为91.84%，AUC为0.942（p<0.0001）。为了确定PCa的亚型以指导治疗，我们在87例前列腺切除术后的PCa标本中检测了一个八基因panel的mRNA表达特征。该八基因panel的特征能够区分侵袭性PCa（Gleason评分>6）与惰性PCa（Gleason评分≤6），敏感性为90.28%，特异性为80.00%，AUC为0.967（p<0.0001）。该panel在一个158例标本的队列中进一步验证，侵袭性PCa与惰性PCa之间存在显著差异，敏感性为92.57%，特异性为70.00%，AUC为0.962（p<0.0001）。我们关于联合评估多种生物标志物的研究结果可能为检测PCa以及区分侵袭性和惰性PCa以实现精准和个性化治疗提供新工具。这两个生物标志物panel可用于临床环境中进行准确的PCa诊断和基于生物标志物指导治疗的患者风险分层。
