Identification of Melanoma Subsets Based on DNA Methylation Sites and Construction of a Prognosis Evaluation Model

Author:

Tengda Li123ORCID,Cheng Qian4ORCID,Yi Sun5ORCID

Affiliation:

1. School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou 325035, Zhejiang, China

2. Key Laboratory of Laboratory Medicine, Ministry of Education, Wenzhou Medical University, Wenzhou 325035, Zhejiang, China

3. Zhejiang Provincial Key Laboratory for Medical Genetics, School of Laboratory Medicine and Life Science, Wenzhou Medical College, Wenzhou 325035, China

4. Department of Laboratory Medicine, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China

5. Department of Laboratory Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China

Abstract

Background. Melanoma is a lethal skin malignant tumor, and its formation or development is regulated by various genetic and epigenetic molecules. Although there are traditional methods provided for the doctors to evaluate the patients’ prognosis or make the diagnosis, the novel method based on epigenetic markers is still needed to make the early diagnosis. Results. We identified 256 melanoma-independent prognosis-related methylation sites ( P  < 0.0001) and divided patients into seven methylation subgroups. Methylation levels and survival time in the C2 subgroup were lower than that of other clusters ( P  < 0.05). We established the predicted model of prognosis risk for melanoma using the significantly changed methylation sites in C2. The model efficiently divided patients into high- and low-risk groups (area under the receiver operating characteristic curve, 0.833). Risk scores and patient survival time were negatively correlated (rs = −0.325, P  < 0.0001). Genes corresponding to the independent prognosis-associated methylation sites were enriched in cancer- and immunology-related pathways. We identified 35 hub genes. DOK2, GBP4, PSMB9, and NLRC5 were significantly changed according to methylation subgroups, survival, tumor stages, and T categories and were positively correlated, which was validated in the testing group ( P  < 0.05). The levels of DOK2, GBP4, PSMB9, and NLRC5 had an opposite trend to their methylation sites in patients with poor prognosis. Conclusions. We identified seven DNA methylation subtypes and constructed a highly effective prognosis risk assessment model. The transcript levels of key genes corresponding to the independent prognosis-related methylation sites were significantly changed in patients according to prognosis and positively correlated with each other, indicating they may collaboratively promote melanoma formation. These findings further our understanding of the mechanism of melanoma and provide new targets for diagnosis and treatment.

Funder

Wenzhou Medical University

Publisher

Hindawi Limited

Subject

Oncology

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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