Identification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis

Abstract Breast cancer is the most common cancer in women both in the developed and less developed countries, and it imposes a considerable threat to human health. Therefore, in order to develop effective targeted therapies against Breast cancer, a deep understanding of its underlying molecular mech...

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Autores principales:	Utkarsh Raj, Imlimaong Aier, Rahul Semwal, Pritish Kumar Varadwaj
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ef319c78b07349a1a3fd543560ce1d2c
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spelling	oai:doaj.org-article:ef319c78b07349a1a3fd543560ce1d2c2021-12-02T12:31:52ZIdentification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis10.1038/s41598-017-03534-x2045-2322https://doaj.org/article/ef319c78b07349a1a3fd543560ce1d2c2017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-03534-xhttps://doaj.org/toc/2045-2322Abstract Breast cancer is the most common cancer in women both in the developed and less developed countries, and it imposes a considerable threat to human health. Therefore, in order to develop effective targeted therapies against Breast cancer, a deep understanding of its underlying molecular mechanisms is required. The application of deep transcriptional sequencing has been found to be reported to provide an efficient genomic assay to delve into the insights of the diseases and may prove to be useful in the study of Breast cancer. In this study, ChIP-Seq data for normal samples and Breast cancer were compared, and differential peaks identified, based upon fold enrichment (with P-values obtained via t-tests). The Protein–protein interaction (PPI) network analysis was carried out, following which the highly connected genes were screened and studied, and the most promising ones were selected. Biological pathway involved in the process were then identified. Our findings regarding potential Breast cancer-related genes enhances the understanding of the disease and provides prognostic information in addition to standard tumor prognostic factors for future research.Utkarsh RajImlimaong AierRahul SemwalPritish Kumar VaradwajNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Utkarsh Raj Imlimaong Aier Rahul Semwal Pritish Kumar Varadwaj Identification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis
description	Abstract Breast cancer is the most common cancer in women both in the developed and less developed countries, and it imposes a considerable threat to human health. Therefore, in order to develop effective targeted therapies against Breast cancer, a deep understanding of its underlying molecular mechanisms is required. The application of deep transcriptional sequencing has been found to be reported to provide an efficient genomic assay to delve into the insights of the diseases and may prove to be useful in the study of Breast cancer. In this study, ChIP-Seq data for normal samples and Breast cancer were compared, and differential peaks identified, based upon fold enrichment (with P-values obtained via t-tests). The Protein–protein interaction (PPI) network analysis was carried out, following which the highly connected genes were screened and studied, and the most promising ones were selected. Biological pathway involved in the process were then identified. Our findings regarding potential Breast cancer-related genes enhances the understanding of the disease and provides prognostic information in addition to standard tumor prognostic factors for future research.
format	article
author	Utkarsh Raj Imlimaong Aier Rahul Semwal Pritish Kumar Varadwaj
author_facet	Utkarsh Raj Imlimaong Aier Rahul Semwal Pritish Kumar Varadwaj
author_sort	Utkarsh Raj
title	Identification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis
title_short	Identification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis
title_full	Identification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis
title_fullStr	Identification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis
title_full_unstemmed	Identification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis
title_sort	identification of novel dysregulated key genes in breast cancer through high throughput chip-seq data analysis
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/ef319c78b07349a1a3fd543560ce1d2c
work_keys_str_mv	AT utkarshraj identificationofnoveldysregulatedkeygenesinbreastcancerthroughhighthroughputchipseqdataanalysis AT imlimaongaier identificationofnoveldysregulatedkeygenesinbreastcancerthroughhighthroughputchipseqdataanalysis AT rahulsemwal identificationofnoveldysregulatedkeygenesinbreastcancerthroughhighthroughputchipseqdataanalysis AT pritishkumarvaradwaj identificationofnoveldysregulatedkeygenesinbreastcancerthroughhighthroughputchipseqdataanalysis
_version_	1718394252024610816

Identification of novel dysregulated key genes in Breast cancer through high throughput ChIP-Seq data analysis

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