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与早期乳腺癌骨转移和非骨转移相关的基因组拷贝数失衡。

Genomic copy number imbalances associated with bone and non-bone metastasis of early-stage breast cancer.

机构信息

Department of Pediatrics, Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA,

出版信息

Breast Cancer Res Treat. 2014 Jan;143(1):189-201. doi: 10.1007/s10549-013-2796-3. Epub 2013 Dec 4.

Abstract

The aim of this study is to identify and validate copy number aberrations in early-stage primary breast tumors associated with bone or non-bone metastasis. Whole-genome molecular inversion probe arrays were used to evaluate copy number imbalances (CNIs) in breast tumors from 960 early-stage patients with information about site of metastasis. The CoxBoost algorithm was used to select metastasis site-related CNIs and to fit a Cox proportional hazards model. Gains at 1q41 and 1q42.12 and losses at 1p13.3, 8p22, and Xp11.3 were significantly associated with bone metastasis. Gains at 2p11.2, 3q21.3-22.2, 3q27.1, 10q23.1, and 14q13.2-3 and loss at 7q21.11 were associated with non-bone metastasis. To examine the joint effect of CNIs and clinical predictors, patients were stratified into three risk groups (low, intermediate, and high) based on the sum of predicted linear hazard ratios. For bone metastasis, the hazard (95 % confidence interval) for the low-risk group was 0.32 (0.11-0.92) compared to the intermediate-risk group and 2.99 (1.74-5.11) for the high-risk group. For non-bone metastasis, the hazard for the low-risk group was 0.34 (0.17-0.66) and 2.33 (1.59-3.43) for the high-risk group. The prognostic value of loss at 8p22 for bone metastasis and gains at 10q23.1 for non-bone metastasis, and gain at 11q13.5 for both bone and non-bone metastases were externally validated in 335 breast tumors pooled from four independent cohorts. Distinct CNIs are independently associated with bone and non-bone metastasis for early-stage breast cancer patients across cohorts. These data warrant consideration for tailoring surveillance and management of metastasis risk.

摘要

本研究旨在鉴定和验证与骨或非骨转移相关的早期原发性乳腺癌肿瘤的拷贝数异常。使用全基因组分子倒置探针阵列评估 960 例早期乳腺癌患者肿瘤的拷贝数失衡(CNI),这些患者具有转移部位的信息。使用 CoxBoost 算法选择与转移部位相关的 CNI 并拟合 Cox 比例风险模型。1q41 和 1q42.12 的增益以及 1p13.3、8p22 和 Xp11.3 的缺失与骨转移显著相关。2p11.2、3q21.3-22.2、3q27.1、10q23.1 和 14q13.2-3 的增益以及 7q21.11 的缺失与非骨转移相关。为了检查 CNI 和临床预测因子的联合效应,根据预测线性风险比之和,将患者分为低、中、高三个风险组。对于骨转移,低风险组的危险度(95%置信区间)为 0.32(0.11-0.92),与中风险组相比,高风险组为 2.99(1.74-5.11)。对于非骨转移,低风险组的危险度为 0.34(0.17-0.66),高风险组为 2.33(1.59-3.43)。在四个独立队列中汇集的 335 个乳腺癌肿瘤中,对 8p22 缺失与骨转移、10q23.1 增益与非骨转移以及 11q13.5 与骨和非骨转移的相关性进行了外部验证。在不同的队列中,不同的 CNI 与早期乳腺癌患者的骨转移和非骨转移独立相关。这些数据为调整监测和转移风险管理提供了依据。

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