Enhancing oral squamous cell carcinoma prediction: the prognostic power of the worst pattern of invasion and the limited impact of molecular resection margins

Author:

Hurník Pavel,Režnarová Jana,Chyra Zuzana,Motyka Oldřich,Putnová Barbora Moldovan,Čermáková Zuzana,Blažek Tomáš,Fománek Martin,Gaykalova Daria,Buchtová Marcela,Ševčíková Tereza,Štembírek Jan

Abstract

ObjectiveOral squamous cell carcinoma (OSCC) originates from the mucosal lining of the oral cavity. Almost half of newly diagnosed cases are classified as advanced stage IV disease, which makes resection difficult. In this study, we investigated the pathological features and mutation profiles of tumor margins in OSCC.MethodsWe performed hierarchical clustering of principal components to identify distinct patterns of tumor growth and their association with patient prognosis. We also used next-generation sequencing to analyze somatic mutations in tumor and marginal tissue samples.ResultsOur analyses uncovered that the grade of worst pattern of invasion (WPOI) is strongly associated with depth of invasion and patient survival in multivariable analysis. Mutations were primarily detected in the DNA isolated from tumors, but several mutations were also identified in marginal tissue. In total, we uncovered 29 mutated genes, mainly tumor suppressor genes involved in DNA repair including BRCA genes; however none of these mutations significantly correlated with a higher chance of relapse in our medium-size cohort. Some resection margins that appeared histologically normal harbored tumorigenic mutations in TP53 and CDKN2A genes.ConclusionEven histologically normal margins may contain molecular alterations that are not detectable by conventional histopathological methods, but NCCN classification system still outperforms other methods in the prediction of the probability of disease relapse.

Publisher

Frontiers Media SA

Subject

Cancer Research,Oncology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3