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改良的葡萄膜黑色素瘤拷贝数亚型,包括一个超高风险组。

Improved Uveal Melanoma Copy Number Subtypes Including an Ultra-High-Risk Group.

作者信息

Lalonde Emilie, Ewens Kathryn, Richards-Yutz Jennifer, Ebrahimzedeh Jessica, Terai Mizue, Gonsalves Carin F, Sato Takami, Shields Carol L, Ganguly Arupa

机构信息

Genetics Diagnostic Laboratory, Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania.

Department of Medical Oncology, Thomas Jefferson University, Philadelphia, Pennsylvania.

出版信息

Ophthalmol Sci. 2022 Jan 30;2(2):100121. doi: 10.1016/j.xops.2022.100121. eCollection 2022 Jun.

DOI:10.1016/j.xops.2022.100121
PMID:36249692
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9559896/
Abstract

PURPOSE

To evaluate the clinical relevance of low-frequency copy number aberrations (CNAs) in uveal melanoma (UM) and to discern residual genomic and clinical heterogeneity within established molecular subtypes based on genome-wide CNA profiling of 921 primary tumors.

DESIGN

Retrospective single-center case series.

PARTICIPANTS

Patients with primary UM referred for genetic testing between 2008 and 2016 (n = 921). The Cancer Genome Atlas cohort with clinical outcome data available (n = 70) was used to validate findings.

METHODS

Genome-wide CNAs were generated for primary tumors from 921 patients and for 19 metastatic UM (mUM) in the liver. Of the 921 patients, metastatic outcome was known for 678 patients with a median time to metastasis of 4.5 years. The primary tumors were processed on the Affymetrix arrays SNP-5.0 (n = 140), SNP-6.0 (n = 359), or CytoScanHD (n = 422), and the metastatic tumors on the CytoScanHD array (n = 19). Recurrent CNAs were identified, and the prognostic effect of individual CNAs and multiple CNA clustering strategies, including more specific molecular subgroups with rare CNAs, were evaluated.

MAIN OUTCOME MEASURES

CNA recurrence, and effect of CNAs and derived molecular subtypes on metastatic-free survival.

RESULTS

Genomic profiling revealed CNAs associated with risk of metastasis and demonstrated a strong association between chromosomal instability and patient prognosis. Using standard prognostic CNAs, 6 clusters were detected, and inclusion of chromosome 16q deletion revealed an additional cluster. Of these 7 genomic clusters, 5 patient groups showed distinct rates of metastasis, indicating that different genomic patterns can have similar patient outcomes. A small group of patients with a significantly higher rate of metastasis was characterized by monosomy 3, 8q amplification, and deletion of 1p or 16q. Although this ultra-high-risk group accounts for only 7% of this cohort, 88% demonstrated metastasis within 4 years, compared with 45% in the second-highest risk group.

CONCLUSIONS

These results suggest that 1p and 16q deletion should be incorporated in clinical assays to assess prognosis at diagnosis and to guide enrollment in clinical trials for adjuvant therapies.

摘要

目的

评估葡萄膜黑色素瘤(UM)中低频拷贝数变异(CNA)的临床相关性,并基于921例原发性肿瘤的全基因组CNA分析,识别既定分子亚型内残留的基因组和临床异质性。

设计

回顾性单中心病例系列研究。

参与者

2008年至2016年间转诊进行基因检测的原发性UM患者(n = 921)。使用有临床结局数据的癌症基因组图谱队列(n = 70)来验证研究结果。

方法

对921例患者的原发性肿瘤以及19例肝脏转移性UM(mUM)进行全基因组CNA检测。在921例患者中,678例患者有转移结局数据,转移的中位时间为4.5年。原发性肿瘤在Affymetrix SNP-5.0芯片(n = 140)、SNP-6.0芯片(n = 359)或CytoScanHD芯片(n = 422)上进行检测,转移性肿瘤在CytoScanHD芯片(n = 19)上进行检测。识别复发性CNA,并评估单个CNA以及多种CNA聚类策略(包括具有罕见CNA的更特异分子亚组)的预后效应。

主要观察指标

CNA复发情况,以及CNA和衍生的分子亚型对无转移生存期的影响。

结果

基因组分析揭示了与转移风险相关的CNA,并表明染色体不稳定性与患者预后之间存在密切关联。使用标准预后CNA,检测到6个聚类,纳入16号染色体q臂缺失后又发现了一个聚类。在这7个基因组聚类中,5个患者组显示出不同的转移率,这表明不同的基因组模式可能具有相似的患者结局。一小部分转移率显著较高的患者的特征为3号染色体单体、8号染色体q臂扩增以及1号或16号染色体p臂缺失。尽管这个超高风险组仅占该队列的7%,但88%的患者在4年内发生转移,而第二高风险组的这一比例为45%。

结论

这些结果表明,1号和16号染色体p臂缺失应纳入临床检测,以评估诊断时的预后,并指导辅助治疗临床试验的入组。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dca/9559896/fac1a27c5f01/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dca/9559896/7c80e765030b/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dca/9559896/4b337821455a/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dca/9559896/579a14614e0f/gr3ac.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dca/9559896/fac1a27c5f01/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dca/9559896/7c80e765030b/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dca/9559896/4b337821455a/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dca/9559896/579a14614e0f/gr3ac.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1dca/9559896/fac1a27c5f01/gr4.jpg

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