口腔癌队列的基因组和人乳头瘤病毒分析确定TP53是总生存的预测因子。

Cancers of the head & neck Pub Date : 2019-12-05 eCollection Date: 2019-01-01 DOI:10.1186/s41199-019-0045-0
Neil Mundi, Stephenie D Prokopec, Farhad Ghasemi, Andrew Warner, Krupal Patel, Danielle MacNeil, Christopher Howlett, William Stecho, Paul Plantinga, Nicole Pinto, Kara M Ruicci, Mohammed Imran Khan, Myung Woul Han, John Yoo, Kevin Fung, Axel Sahovaler, David A Palma, Eric Winquist, Joe S Mymryk, John W Barrett, Paul C Boutros, Anthony C Nichols
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引用次数: 11

摘要

背景:通过癌症基因组图谱计划已经报道了头颈癌的基因组图谱。我们试图确定高危人乳头瘤病毒(HPV)或频繁突变基因是否与口腔癌队列中的生存相关。方法:收集患者人口学资料及最终病理资料。使用定制的Illumina靶向测序板分析肿瘤DNA。采用qPCR检测5种高危型HPV。统计分析用于确定患者预后与突变状态之间的关联。结果:高危型HPV占7%;HPV状态与生存无关。在TP53、TERT启动子和PIK3CA中发现了突变。多变量分析显示,TP53突变与较差的总生存率显著相关(p = 0.03)。结论:TP53突变与较差的患者生存有关。扩大我们的样本量可以确定进一步的预测结果,以直接定制癌症治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Genomic and human papillomavirus profiling of an oral cancer cohort identifies TP53 as a predictor of overall survival.

Genomic and human papillomavirus profiling of an oral cancer cohort identifies TP53 as a predictor of overall survival.

Genomic and human papillomavirus profiling of an oral cancer cohort identifies TP53 as a predictor of overall survival.

Background: The genomic landscape of head and neck cancer has been reported through The Cancer Genome Atlas project. We attempt to determine if high-risk human papillomavirus (HPV) or frequently mutated genes are correlated with survival in an oral cancer cohort.

Methods: Patient demographic data along with data from final pathology was collected. Tumor DNA was analyzed using a custom Illumina targeted sequencing panel. Five high-risk HPV types were tested by qPCR. Statistical analyses were used to identify associations between patient outcome and mutational status.

Results: High-risk HPV types were identified in 7% of cases; HPV status was not associated with survival. Mutations were identified in TP53, TERT promoter, & PIK3CA. Mutations in TP53 were significantly associated with poorer overall survival on multi-variate analysis (p = 0.03).

Conclusions: Mutations in TP53 were associated with poor patient survival. Expanding our sample size may identify further predictors of outcome to direct customized cancer care.

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