多基因风险评分预测treatment-naïve转移性去势抵抗性前列腺癌的临床结局。

IF 3.4 Q2 ONCOLOGY
Muhammad Zaki Hidayatullah Fadlullah, David Nix, Cameron Herberts, Corinne Maurice-Dror, Alexander W Wyatt, Bogdana Schmidt, Brayden Fairbourn, Aik-Choon Tan, Liang Wang, Manish Kohli
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引用次数: 0

摘要

背景:确定多基因拷贝数变异(MG-CNV)风险评分在treatment-naïve转移性去势抵抗性前列腺癌(mCRPC)患者转移组织和血浆生物标本中的表现,以预测临床结果。方法:从dbGaP、cbiopportal和一个机构mCRPC队列公开获取的队列中获得mCRPC组织和血浆无细胞DNA (cfDNA)生物标本测序结果,通过独立队列中AR、MYC、COL22A1、PIK3CA、PIK3CB、NOTCH1的增加和TMPRSS2、NCOR1、ZBTB16、TP53、NKX3-1的损失,建立MG-CNV风险评分,以确定一线雄激素受体途径抑制剂(arpi)的总生存期(OS)、无进展生存期(PFS)。每个队列的风险评分范围被分为“高风险”组和“低风险”组,并确定与OS/PFS的关联。单因素和多因素Cox比例风险回归应用于生存分析(P)结果:在所有队列的1137例转移性组织-血浆生物标本中,699/1137例为未经治疗的mCRPC(235/699例转移性组织;464/699血浆- cfdna)和311/1137组织- cfdna配对。在多变量分析中,来自转移组织或cfDNA的MG-CNV风险评分与OS有统计学意义相关,评分高与生存期短相关,风险比(HR) 2.65 (CI: 1.99- 3.51;P = 1.35-11),与低风险评分患者的14个月相比,PFS较短(中位PFS为7.8个月)。结论:在转移组织或cfDNA中获得的treatment-naïve mCRPC状态的分子风险评分可预测临床生存结果,并为设计基于生物标志物的富集临床试验提供了基于肿瘤生物学的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-gene risk score for prediction of clinical outcomes in treatment-naïve metastatic castrate-resistant prostate cancer.

Background: To determine the performance of a multi-gene copy number variation (MG-CNV) risk score in metastatic tissue and plasma biospecimens from treatment-naïve metastatic castration-resistant prostate cancer (mCRPC) patients for prediction of clinical outcomes.

Methods: The mCRPC tissue and plasma cell-free DNA (cfDNA) biospecimen sequencing results obtained from publicly accessed cohorts in dbGaP, cBioPortal, and an institutional mCRPC cohort were used to develop a MG-CNV risk score derived from gains in AR, MYC, COL22A1, PIK3CA, PIK3CB, NOTCH1 and losses in TMPRSS2, NCOR1, ZBTB16, TP53, NKX3-1 in independent cohorts for determining overall survival (OS), progression-free survival (PFS) to first-line androgen receptor pathway inhibitors (ARPIs). The range of the risk scores for each cohort was dichotomized into "high-risk" and "low-risk" groups and association with OS/PFS determined. Univariate and multivariable Cox proportional hazards regressions were applied for survival analyses (P < .05 for statistical significance).

Results: Of 1137 metastatic tissue-plasma biospecimens across all cohorts, 699/1137 were treatment-naive mCRPC (235/699 metastatic tissue; 464/699 plasma-cfDNA), and 311/1137 were matched tissue-cfDNA pairs. In multivariable analysis, the MG-CNV risk score derived from metastatic tissue or in cfDNA was statistically significantly associated with OS with high score associated with short survival (hazard ratio = 2.65, confidence interval = 1.99 to 3.51; P = 1.35-11) and shorter PFS to ARPIs (median PFS of 7.8 months) compared with 14 months in patients with low-risk score.

Conclusions: A molecular risk score in treatment-naïve mCRPC state obtained either in metastatic tissue or cfDNA predicts clinical survival outcomes and offers a tumor biology-based tool to design biomarker-based enrichment clinical trials.

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来源期刊
JNCI Cancer Spectrum
JNCI Cancer Spectrum Medicine-Oncology
CiteScore
7.70
自引率
0.00%
发文量
80
审稿时长
18 weeks
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