Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data

The occurrence of cancer is closely related to the deregulation of certain pathways. Based on pathway deregulation scores (PDS) inferred by the Pathifier algorithm, we analyzed transcriptomic data of 13 different cancer types in The Cancer Genome Atlas database to identify cancer-specific deregulate...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Cong Pian, Mengyuan He, Yuanyuan Chen
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	pan-cancer pathway deregulation scores cancer-specific deregulated pathways prognostic pathways prognostic model Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/6d69bc5043f24b26bd802e97581c2b38
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:6d69bc5043f24b26bd802e97581c2b38
record_format	dspace
spelling	oai:doaj.org-article:6d69bc5043f24b26bd802e97581c2b382021-11-25T16:48:19ZPathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data10.3390/biomedicines91115022227-9059https://doaj.org/article/6d69bc5043f24b26bd802e97581c2b382021-10-01T00:00:00Zhttps://www.mdpi.com/2227-9059/9/11/1502https://doaj.org/toc/2227-9059The occurrence of cancer is closely related to the deregulation of certain pathways. Based on pathway deregulation scores (PDS) inferred by the Pathifier algorithm, we analyzed transcriptomic data of 13 different cancer types in The Cancer Genome Atlas database to identify cancer-specific deregulated pathways and prognostic pathways. The results showed that the individual-specific pathway deregulation scores can clearly distinguish different cancer types and their tumor-adjacent tissues. In addition, the cancer-specific deregulated pathways and prognostic pathways of different cancer types had high heterogeneity, and the identified cancer prognostic pathways have been reported to be closely related to the corresponding cancers. Furthermore, we also found that cancers with more deregulation pathways tend to be malignant and have worse prognoses. Finally, a Cox proportional Hazards model was constructed based on the prognostic pathways; this model successfully predicted survival and prognosis based on data from cancer samples. In addition, the performance of the breast cancer prognostic model was validated with an independent data set in the METABRIC database. Therefore, the prognostic pathways we identified have the potential to become targets for the treatment of cancer.Cong PianMengyuan HeYuanyuan ChenMDPI AGarticlepan-cancerpathway deregulation scorescancer-specific deregulated pathwaysprognostic pathwaysprognostic modelBiology (General)QH301-705.5ENBiomedicines, Vol 9, Iss 1502, p 1502 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	pan-cancer pathway deregulation scores cancer-specific deregulated pathways prognostic pathways prognostic model Biology (General) QH301-705.5
spellingShingle	pan-cancer pathway deregulation scores cancer-specific deregulated pathways prognostic pathways prognostic model Biology (General) QH301-705.5 Cong Pian Mengyuan He Yuanyuan Chen Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data
description	The occurrence of cancer is closely related to the deregulation of certain pathways. Based on pathway deregulation scores (PDS) inferred by the Pathifier algorithm, we analyzed transcriptomic data of 13 different cancer types in The Cancer Genome Atlas database to identify cancer-specific deregulated pathways and prognostic pathways. The results showed that the individual-specific pathway deregulation scores can clearly distinguish different cancer types and their tumor-adjacent tissues. In addition, the cancer-specific deregulated pathways and prognostic pathways of different cancer types had high heterogeneity, and the identified cancer prognostic pathways have been reported to be closely related to the corresponding cancers. Furthermore, we also found that cancers with more deregulation pathways tend to be malignant and have worse prognoses. Finally, a Cox proportional Hazards model was constructed based on the prognostic pathways; this model successfully predicted survival and prognosis based on data from cancer samples. In addition, the performance of the breast cancer prognostic model was validated with an independent data set in the METABRIC database. Therefore, the prognostic pathways we identified have the potential to become targets for the treatment of cancer.
format	article
author	Cong Pian Mengyuan He Yuanyuan Chen
author_facet	Cong Pian Mengyuan He Yuanyuan Chen
author_sort	Cong Pian
title	Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data
title_short	Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data
title_full	Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data
title_fullStr	Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data
title_full_unstemmed	Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data
title_sort	pathway-based personalized analysis of pan-cancer transcriptomic data
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/6d69bc5043f24b26bd802e97581c2b38
work_keys_str_mv	AT congpian pathwaybasedpersonalizedanalysisofpancancertranscriptomicdata AT mengyuanhe pathwaybasedpersonalizedanalysisofpancancertranscriptomicdata AT yuanyuanchen pathwaybasedpersonalizedanalysisofpancancertranscriptomicdata
_version_	1718412960415612928

Pathway-Based Personalized Analysis of Pan-Cancer Transcriptomic Data

Ejemplares similares