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A Molecular Signature Predictive of Indolent Prostate Cancer

机译:惰性前列腺癌的分子特征预测。

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摘要

Many newly diagnosed prostate cancers present as low Gleason score tumors that require no treatment intervention. Distinguishing the many indolent tumors from the minority of lethal ones remains a major clinical challenge. We now show that low Gleason score prostate tumors can be distinguished as indolent and aggressive subgroups on the basis of their expression of genes associated with aging and senescence. Using gene set enrichment analysis, we identified a 19-gene signature enriched in indolent prostate tumors. We then further classified this signature with a decision tree learning model to identify three genes—FGFR1, PMP22, and CDKN1A—that together accurately predicted outcome of low Gleason score tumors. Validation of this three-gene panel on independent cohorts confirmed its independent prognostic value as well as its ability to improve prognosis with currently used clinical nomograms. Furthermore, protein expression of this three-gene panel in biopsy samples distinguished Gleason 6 patients who failed surveillance over a 10-year period. We propose that this signature may be incorporated into prognostic assays for monitoring patients on active surveillance to facilitate appropriate courses of treatment.
机译:许多新诊断的前列腺癌表现为格里森评分低的肿瘤,不需要治疗干预。将许多惰性肿瘤与少数致死性肿瘤区分开来仍然是主要的临床挑战。我们现在显示,低格里森评分前列腺癌可根据其与衰老和衰老相关的基因表达来区分为惰性和侵袭性亚组。使用基因集富集分析,我们确定了惰性前列腺肿瘤中富集的19基因签名。然后,我们使用决策树学习模型进一步对该签名进行分类,以识别三个基因-FGFR1,PMP22和CDKN1A,它们一起可以准确预测低格里森评分肿瘤的预后。对这三个基因组的独立队列进行验证,证实了其独立的预后价值以及利用目前使用的临床诺模图改善预后的能力。此外,在活检样本中此三基因检测组的蛋白质表达可区分格里森6例患者,这些患者在10年内未能通过监测。我们建议可以将此签名合并到预后分析中,以便在主动监视下监视患者,以促进适当的治疗过程。

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