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 develo...
| Publicado en: | International Journal of Cancer Management Vol. 16; no. 1; pp. 1 - 12 |
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| Autores principales: | , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Medical Journals Commission of the Ministry of Health & Medical Education
Dec2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=174742622&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 174742622 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 25384422 L6AI jtl: International Journal of Cancer Management issn: 25384422 maglogo: N pubinfo: dt: Dec2023 vid: 16 iid: 1 pid: 66482 pub: Medical Journals Commission of the Ministry of Health & Medical Education artinfo: ui: 174742622 174742622 174742622 10.5812/ijcm-131281 174742622 ppf: 1 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Identification of Liver Cancer Driver Mutations from COSMIC Data. aug: au: Sethi, Amna Amin Shar, Nisar Ahmed affil: Department of Biomedical Engineering, NED University of Engineering & Technology, Karachi, Pakistan sug: subj: Liver Neoplasms Therapy Mutation Human Transcription Factors Biological Markers Epithelial Cells Death Alleles ab: 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 hepato-cellular 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. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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