ProstaTrend—一种用于预测侵袭性前列腺癌的多变量 RNA 表达评分。

ProstaTrend-A Multivariable Prognostic RNA Expression Score for Aggressive Prostate Cancer.

机构信息

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany; Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany; Institute of Clinical Immunology, Faculty of Medicine, University of Leipzig, Leipzig, Germany.

出版信息

Eur Urol. 2020 Sep;78(3):452-459. doi: 10.1016/j.eururo.2020.06.001. Epub 2020 Jul 4.

DOI:10.1016/j.eururo.2020.06.001

PMID:32631745

Abstract

BACKGROUND

Prostate cancer (PCa) is the most prevalent solid cancer among men in Western Countries. The clinical behavior of localized PCa is highly variable. Some cancers are aggressive leading to death, while others can even be monitored safely. Hence, there is a high clinical need for precise biomarkers for identification of aggressive disease in addition to established clinical parameters.

OBJECTIVE

To develop an RNA expression-based score for the prediction of PCa prognosis that facilitates clinical decision making.

DESIGN, SETTING, AND PARTICIPANTS: We assessed 233 tissue specimens of PCa patients with long-term follow-up data from fresh-frozen radical prostatectomies (RPs), from formalin-fixed and paraffin-embedded RP specimens and biopsies by transcriptome-wide next-generation sequencing and customized expression microarrays.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We applied Cox proportional hazard models to the cohorts from different platforms and specimen types. Evidence from these models was combined by fixed-effect meta-analysis to identify genes predictive of the time to death of disease (DoD). Genes were combined by a weighted median approach into a prognostic score called ProstaTrend and transferred for the prediction of biochemical recurrence (BCR) after RP in an independent cohort of The Cancer Genome Atlas (TCGA).

RESULTS AND LIMITATIONS

ProstaTrend comprising ∼1400 genes was significantly associated with DoD in the training cohort of PCa patients treated by RP (leave-one-out cross-validation, Cox regression: p=2e-09) and with BCR in the TCGA validation cohort (Cox regression: p=3e-06). The prognostic impact persisted after multivariable Cox regression analysis adjusting for Gleason grading group (GG) ≥3 and resection status (p=0.001; DoD, training cohort) and for GG≥3, pathological stage ≥T3, and resection state (p=0.037; BCR, validation cohort).

CONCLUSIONS

ProstaTrend is a transcriptome-based score that predicts DoD and BCR in cohorts of PCa patients treated with RP.

PATIENT SUMMARY

ProstaTrend provides molecular patient risk stratification after radical prostatectomy.

摘要

背景

前列腺癌（PCa）是西方国家男性中最常见的实体癌。局限性 PCa 的临床行为变化很大。一些癌症具有侵袭性，导致死亡，而另一些癌症甚至可以安全监测。因此，除了现有的临床参数外，还需要精确的生物标志物来识别侵袭性疾病。

目的

开发一种基于 RNA 表达的评分系统，用于预测 PCa 预后，以辅助临床决策。

设计、地点和参与者：我们评估了来自不同平台和标本类型的 233 例 PCa 患者的组织标本，这些患者接受了根治性前列腺切除术（RP），并进行了长期随访，包括新鲜冷冻 RP 标本和福尔马林固定石蜡包埋 RP 标本和活检。

结果测量和统计分析

我们应用 Cox 比例风险模型对来自不同平台和标本类型的队列进行分析。通过固定效应荟萃分析对这些模型的证据进行了组合，以确定预测疾病死亡时间（DoD）的基因。通过加权中位数方法将基因组合成一个名为 ProstaTrend 的预后评分，并将其转移到癌症基因组图谱（TCGA）的 RP 后生化复发（BCR）的独立队列中进行预测。

结果和局限性

ProstaTrend 由约 1400 个基因组成，在接受 RP 治疗的 PCa 患者的训练队列中与 DoD 显著相关（留一法交叉验证，Cox 回归：p=2e-09），并在 TCGA 验证队列中与 BCR 相关（Cox 回归：p=3e-06）。在多变量 Cox 回归分析中，调整了 Gleason 分级组（GG）≥3 和切除状态（p=0.001；DoD，训练队列）以及 GG≥3、病理分期≥T3 和切除状态（p=0.037；BCR，验证队列）后，预后影响仍然存在。