Transcript analysis of commercial prostate cancer risk stratification panels in hard-to-predict grade group 2-4 prostate cancers.
Transcript analysis of commercial prostate cancer risk stratification panels in hard-to-predict grade group 2-4 prostate cancers.
复制标题
对难以预测的 2-4 级前列腺癌商业前列腺癌风险分层组进行转录分析。
DOI：
10.1002/pros.24108
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Lehto TK
中科院分区：
文献类型：
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作者：
Lehto TK
研究背景：需要改进分级，以尽量减少2-4级（GG）前列腺癌的过度治疗。我们的目的是在信使RNA（mRNA）水平上确定商业板Decipher，Oncotype DX，Prolaris，和突变面板MSK‐IMPACT预测根治性前列腺切除术中GG 2-4前列腺癌患者的无转移和前列腺癌特异性死亡（PCSD）。（中位随访10.4年）。分析了76例术后转移或PCSD病例和84例临床基线风险相似但无进展的对照。使用NanoString技术分析索引病变mRNA转录物。使用面板基因集训练随机森林模型以预测临床终点，并测量曲线下面积（AUC）、灵敏度、特异性、约登指数和诊断所需数量（NND）。生存概率进行了评估与Kaplan-Meier estimate.ResultsAll基因集优于临床参数和预测无转移和前列腺癌特异性生存。然而，面板之间存在显著差异。在转移预测中，与其他组（AUC = 0.73-0.74）相比，Oncotype DX中的基因具有较差的性能（曲线下面积[AUC] = 0.65）。Decipher、MSK‐IMPACT和Prolaris显示出相似的NND（2.83-3.12），其中Oncotype DX具有最高的NND（4.79）。在PCSD预测中，Prolaris基因集的表现（AUC = 0.66）比MSK-IMPACT或Decipher（AUC = 0.72）差。肿瘤型DX的表现与其他组相似（AUC = 0.69，p> 0.05）。DX型的NND最低（2.79），其他组（4.22-5.66）。结论商业化基因组中基因的转录本分析在胃癌根治术后GG 2 - 4患者的生存预测中是可行的，并可能有助于临床决策。这些组之间存在显著差异，并且需要总体上更强的预测基因集。前瞻性研究是必要的活检材料。
BackgroundImproved prognostication is needed to minimize overtreatment in grade group (GG) 2–4 prostate cancer. Our aim was to determine, at messenger RNA (mRNA) level, the performance of the genes in the commercial panels Decipher, Oncotype DX, Prolaris, and mutational panel MSK‐IMPACT to predict metastasis‐free and prostate cancer‐specific death (PCSD) in patients with GG 2–4 prostate cancer at radical prostatectomy.MethodsThe retrospective cohort consisted of GG 2–4 patients treated with radical prostatectomy (median follow‐up 10.4 years). Seventy‐six cases with postoperative metastasis or PCSD and 84 controls with similar clinical baseline risk, but without progression, were analyzed. Index lesion mRNA transcripts were analyzed using NanoString technology. Random forest models were trained using panel gene sets to predict clinical endpoints and area under the curve (AUC), sensitivity, specificity, Youden index, and number needed to diagnose (NND) was measured. Survival probability was assessed with Kaplan–Meier estimator.ResultsAll gene sets outperformed clinical parameters and predicted metastasis‐free and prostate cancer‐specific survival. However, there were significant differences between the panels. In metastasis prediction, the genes in Oncotype DX had inferior performance (area under the curve [AUC] = 0.65) compared to other panels (AUC = 0.73–0.74). Decipher, MSK‐IMPACT and Prolaris showed similar NND (2.83–3.12) with Oncotype DX having highest NND (4.79). In PCSD prediction, the Prolaris gene set performed worse (AUC = 0.66) than MSK‐IMPACT or Decipher (AUC = 0.72). Oncotype DX performed similarly to other panels (AUC = 0.69,p> .05). Oncotype DX demonstrated lowest NND (2.79) compared to other panels (4.22–5.66).ConclusionTranscript analysis of genes included in commercial panels is feasible in survival prediction of GG 2‐4 patients after radical prostatectomy and may aid in clinical decision making. There were significant differences between the panels, and overall stronger predictive gene sets are needed. Prospective investigation is warranted in biopsy materials.