Prediction of colorectal cancer driver genes from patients’ genome data

Colorectal cancer refers to the cancer that occurs in the colon and rectum. It has been established as the third most common cancer and the forth one in causing worldwide mortality. Cancer caused by the mutation of several genes that usually involved in the regulation of cell proliferation, growth a...

Full description

Bibliographic Details
Main Authors:	Muhammad-Iqmal Abdullah, Nor Azlan Nor Muhammad
Format:	Article
Language:	English
Published:	Penebit Universiti Kebangsaan Malaysia 2018
Online Access:	http://journalarticle.ukm.my/12932/ http://journalarticle.ukm.my/12932/ http://journalarticle.ukm.my/12932/1/20%20Muhammad-Iqmal%20Abdullah.pdf

id	ukm-12932
recordtype	eprints
spelling	ukm-129322019-05-15T11:10:38Z http://journalarticle.ukm.my/12932/ Prediction of colorectal cancer driver genes from patients’ genome data Muhammad-Iqmal Abdullah, Nor Azlan Nor Muhammad, Colorectal cancer refers to the cancer that occurs in the colon and rectum. It has been established as the third most common cancer and the forth one in causing worldwide mortality. Cancer caused by the mutation of several genes that usually involved in the regulation of cell proliferation, growth and cell death. The mutation that leads to abnormal function of genes, either in enabling the genes to gain or loss of function was termed as driver mutation and the genes with driver mutation ability was termed as driver genes. The identification of driver genes provides insight on mechanistic process of cancer development where this information can be used to further understand their mode of action for causing dysregulation in signaling pathways. In this study, two bioinformatic tools, i.e. CGI and iCAGES were used to predict potential driver genes from the genome of eight colorectal cancer patients with annotated variants datasets. 44 unique driver genes and 21 pathways have been identified; such as p53 signaling, PI3K-AKT, Endocrine resistance, MAPK and cell cycle pathways. The identification of these pathways can lead to the identification of potential drugs targeting these pathways. Penebit Universiti Kebangsaan Malaysia 2018-12 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/12932/1/20%20Muhammad-Iqmal%20Abdullah.pdf Muhammad-Iqmal Abdullah, and Nor Azlan Nor Muhammad, (2018) Prediction of colorectal cancer driver genes from patients’ genome data. Sains Malaysiana, 47 (12). pp. 3095-3105. ISSN 0126-6039 http://www.ukm.my/jsm/malay_journals/jilid47bil12_2018/KandunganJilid47Bil12_2018.html
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	Colorectal cancer refers to the cancer that occurs in the colon and rectum. It has been established as the third most common cancer and the forth one in causing worldwide mortality. Cancer caused by the mutation of several genes that usually involved in the regulation of cell proliferation, growth and cell death. The mutation that leads to abnormal function of genes, either in enabling the genes to gain or loss of function was termed as driver mutation and the genes with driver mutation ability was termed as driver genes. The identification of driver genes provides insight on mechanistic process of cancer development where this information can be used to further understand their mode of action for causing dysregulation in signaling pathways. In this study, two bioinformatic tools, i.e. CGI and iCAGES were used to predict potential driver genes from the genome of eight colorectal cancer patients with annotated variants datasets. 44 unique driver genes and 21 pathways have been identified; such as p53 signaling, PI3K-AKT, Endocrine resistance, MAPK and cell cycle pathways. The identification of these pathways can lead to the identification of potential drugs targeting these pathways.
format	Article
author	Muhammad-Iqmal Abdullah, Nor Azlan Nor Muhammad,
spellingShingle	Muhammad-Iqmal Abdullah, Nor Azlan Nor Muhammad, Prediction of colorectal cancer driver genes from patients’ genome data
author_facet	Muhammad-Iqmal Abdullah, Nor Azlan Nor Muhammad,
author_sort	Muhammad-Iqmal Abdullah,
title	Prediction of colorectal cancer driver genes from patients’ genome data
title_short	Prediction of colorectal cancer driver genes from patients’ genome data
title_full	Prediction of colorectal cancer driver genes from patients’ genome data
title_fullStr	Prediction of colorectal cancer driver genes from patients’ genome data
title_full_unstemmed	Prediction of colorectal cancer driver genes from patients’ genome data
title_sort	prediction of colorectal cancer driver genes from patients’ genome data
publisher	Penebit Universiti Kebangsaan Malaysia
publishDate	2018
url	http://journalarticle.ukm.my/12932/ http://journalarticle.ukm.my/12932/ http://journalarticle.ukm.my/12932/1/20%20Muhammad-Iqmal%20Abdullah.pdf
first_indexed	2023-09-18T20:03:43Z
last_indexed	2023-09-18T20:03:43Z
_version_	1777407018445832192

Prediction of colorectal cancer driver genes from patients’ genome data

Similar Items