从COSMIC数据中鉴定肝癌驱动突变

IF 0.4 Q4 ONCOLOGY
Amna Amin Sethi, N. Shar
{"title":"从COSMIC数据中鉴定肝癌驱动突变","authors":"Amna Amin Sethi, N. Shar","doi":"10.5812/ijcm-131281","DOIUrl":null,"url":null,"abstract":"Background: Liver cancer accounts for more than 700,000 deaths each year making it the third leading cause of cancer-related deaths worldwide. Late diagnosis of the disease is the reason behind most deaths. Driver mutations are genetic alterations in tumor cells, which are responsible for the development of liver cancer; therefore, the identification of genetic biomarkers is necessary for the prediction and early diagnosis of liver cancer. Objectives: The main objective of this study is to identify pathogenic alleles that may act as potential biomarkers for the prediction of liver cancer. It also identifies the role of novel genes in liver cancer that are not known to cause the disease. Methods: The mutation data of non-coding variants were downloaded from the catalogue of somatic mutations in cancer (COSMIC) databases. Different bioinformatics tools were, then, used to retrieve mutations in liver cancer. The genetic alterations in hepatocellular carcinoma (HCC) were analyzed. Results: The present study successfully identified pathogenic alleles (consistent mutations) along with a set of novel genes that might be involved in the development of liver cancer. It identified non-coding mutations near human genes and transcription factor binding sites of HepG2 cells. This study also identified mutations near the genes that are involved in the Ras/MAFK signaling pathway of the Hepatitis B virus. Conclusions: The pathogenic alleles identified in this study may provide targeted therapy for the treatment of liver cancer. The identification of novel genes may help to understand the progression of liver cancer at the molecular level. The identified driver mutations may act as potential biomarkers and therapeutic targets for early prediction and treatment of liver cancer.","PeriodicalId":44764,"journal":{"name":"International Journal of Cancer Management","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of Liver Cancer Driver Mutations from COSMIC Data\",\"authors\":\"Amna Amin Sethi, N. Shar\",\"doi\":\"10.5812/ijcm-131281\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Liver cancer accounts for more than 700,000 deaths each year making it the third leading cause of cancer-related deaths worldwide. Late diagnosis of the disease is the reason behind most deaths. Driver mutations are genetic alterations in tumor cells, which are responsible for the development of liver cancer; therefore, the identification of genetic biomarkers is necessary for the prediction and early diagnosis of liver cancer. Objectives: The main objective of this study is to identify pathogenic alleles that may act as potential biomarkers for the prediction of liver cancer. It also identifies the role of novel genes in liver cancer that are not known to cause the disease. Methods: The mutation data of non-coding variants were downloaded from the catalogue of somatic mutations in cancer (COSMIC) databases. Different bioinformatics tools were, then, used to retrieve mutations in liver cancer. The genetic alterations in hepatocellular carcinoma (HCC) were analyzed. Results: The present study successfully identified pathogenic alleles (consistent mutations) along with a set of novel genes that might be involved in the development of liver cancer. It identified non-coding mutations near human genes and transcription factor binding sites of HepG2 cells. This study also identified mutations near the genes that are involved in the Ras/MAFK signaling pathway of the Hepatitis B virus. Conclusions: The pathogenic alleles identified in this study may provide targeted therapy for the treatment of liver cancer. The identification of novel genes may help to understand the progression of liver cancer at the molecular level. The identified driver mutations may act as potential biomarkers and therapeutic targets for early prediction and treatment of liver cancer.\",\"PeriodicalId\":44764,\"journal\":{\"name\":\"International Journal of Cancer Management\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2023-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Cancer Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5812/ijcm-131281\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Cancer Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5812/ijcm-131281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

背景:肝癌每年导致70多万人死亡,使其成为全球癌症相关死亡的第三大原因。这种疾病的晚期诊断是大多数死亡的原因。驱动突变是肿瘤细胞的基因改变,是导致肝癌发生的原因;因此,基因生物标志物的鉴定对于肝癌的预测和早期诊断是必要的。目的:本研究的主要目的是鉴定可能作为预测肝癌潜在生物标志物的致病等位基因。它还确定了在肝癌中未知的新基因的作用。方法:从COSMIC数据库下载非编码变异的突变数据。然后,不同的生物信息学工具被用来检索肝癌的突变。分析肝细胞癌(HCC)的基因改变。结果:本研究成功地鉴定了致病等位基因(一致突变)以及一组可能参与肝癌发展的新基因。在HepG2细胞的人类基因和转录因子结合位点附近发现了非编码突变。本研究还发现了乙肝病毒Ras/MAFK信号通路基因附近的突变。结论:本研究发现的致病等位基因可能为肝癌的治疗提供靶向治疗。新基因的鉴定可能有助于从分子水平上了解肝癌的进展。发现的驱动突变可能作为肝癌早期预测和治疗的潜在生物标志物和治疗靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of Liver Cancer Driver Mutations from COSMIC Data
Background: Liver cancer accounts for more than 700,000 deaths each year making it the third leading cause of cancer-related deaths worldwide. Late diagnosis of the disease is the reason behind most deaths. Driver mutations are genetic alterations in tumor cells, which are responsible for the development of liver cancer; therefore, the identification of genetic biomarkers is necessary for the prediction and early diagnosis of liver cancer. Objectives: The main objective of this study is to identify pathogenic alleles that may act as potential biomarkers for the prediction of liver cancer. It also identifies the role of novel genes in liver cancer that are not known to cause the disease. Methods: The mutation data of non-coding variants were downloaded from the catalogue of somatic mutations in cancer (COSMIC) databases. Different bioinformatics tools were, then, used to retrieve mutations in liver cancer. The genetic alterations in hepatocellular carcinoma (HCC) were analyzed. Results: The present study successfully identified pathogenic alleles (consistent mutations) along with a set of novel genes that might be involved in the development of liver cancer. It identified non-coding mutations near human genes and transcription factor binding sites of HepG2 cells. This study also identified mutations near the genes that are involved in the Ras/MAFK signaling pathway of the Hepatitis B virus. Conclusions: The pathogenic alleles identified in this study may provide targeted therapy for the treatment of liver cancer. The identification of novel genes may help to understand the progression of liver cancer at the molecular level. The identified driver mutations may act as potential biomarkers and therapeutic targets for early prediction and treatment of liver cancer.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
1.10
自引率
0.00%
发文量
67
期刊介绍: International Journal of Cancer Management (IJCM) publishes peer-reviewed original studies and reviews on cancer etiology, epidemiology and risk factors, novel approach to cancer management including prevention, diagnosis, surgery, radiotherapy, medical oncology, and issues regarding cancer survivorship and palliative care. The scope spans the spectrum of cancer research from the laboratory to the clinic, with special emphasis on translational cancer research that bridge the laboratory and clinic. We also consider original case reports that expand clinical cancer knowledge and convey important best practice messages.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信