A Computational Framework to Characterize the Cancer Drug Induced Effect on Aging Using Transcriptomic Data

Cancer treatments such as chemotherapies may change or accelerate aging trajectories in cancer patients. Emerging evidence has shown that “omics” data can be used to study molecular changes of the aging process. Here, we integrated the drug-induced and normal aging transcriptomic data to computation...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhao, Yueshan, Wang, Yue, Yang, Da, Suh, Kangho, Zhang, Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Pharmacology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9277350/
https://www.ncbi.nlm.nih.gov/pubmed/35847024
http://dx.doi.org/10.3389/fphar.2022.906429
_version_ 1784745960953348096
author Zhao, Yueshan
Wang, Yue
Yang, Da
Suh, Kangho
Zhang, Min
author_facet Zhao, Yueshan
Wang, Yue
Yang, Da
Suh, Kangho
Zhang, Min
author_sort Zhao, Yueshan
collection PubMed
description Cancer treatments such as chemotherapies may change or accelerate aging trajectories in cancer patients. Emerging evidence has shown that “omics” data can be used to study molecular changes of the aging process. Here, we integrated the drug-induced and normal aging transcriptomic data to computationally characterize the potential cancer drug-induced aging process in patients. Our analyses demonstrated that the aging-associated gene expression in the GTEx dataset can recapitulate the well-established aging hallmarks. We next characterized the drug-induced transcriptomic changes of 28 FDA approved cancer drugs in brain, kidney, muscle, and adipose tissues. Further drug-aging interaction analysis identified 34 potential drug regulated aging events. Those events include aging accelerating effects of vandetanib (Caprelsa®) and dasatinib (Sprycel®) in brain and muscle, respectively. Our result also demonstrated aging protective effect of vorinostat (Zolinza®), everolimus (Afinitor®), and bosutinib (Bosulif®) in brain.
format Online
Article
Text
id pubmed-9277350
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-92773502022-07-14 A Computational Framework to Characterize the Cancer Drug Induced Effect on Aging Using Transcriptomic Data Zhao, Yueshan Wang, Yue Yang, Da Suh, Kangho Zhang, Min Front Pharmacol Pharmacology Cancer treatments such as chemotherapies may change or accelerate aging trajectories in cancer patients. Emerging evidence has shown that “omics” data can be used to study molecular changes of the aging process. Here, we integrated the drug-induced and normal aging transcriptomic data to computationally characterize the potential cancer drug-induced aging process in patients. Our analyses demonstrated that the aging-associated gene expression in the GTEx dataset can recapitulate the well-established aging hallmarks. We next characterized the drug-induced transcriptomic changes of 28 FDA approved cancer drugs in brain, kidney, muscle, and adipose tissues. Further drug-aging interaction analysis identified 34 potential drug regulated aging events. Those events include aging accelerating effects of vandetanib (Caprelsa®) and dasatinib (Sprycel®) in brain and muscle, respectively. Our result also demonstrated aging protective effect of vorinostat (Zolinza®), everolimus (Afinitor®), and bosutinib (Bosulif®) in brain. Frontiers Media S.A. 2022-06-29 /pmc/articles/PMC9277350/ /pubmed/35847024 http://dx.doi.org/10.3389/fphar.2022.906429 Text en Copyright © 2022 Zhao, Wang, Yang, Suh and Zhang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Zhao, Yueshan
Wang, Yue
Yang, Da
Suh, Kangho
Zhang, Min
A Computational Framework to Characterize the Cancer Drug Induced Effect on Aging Using Transcriptomic Data
title A Computational Framework to Characterize the Cancer Drug Induced Effect on Aging Using Transcriptomic Data
title_full A Computational Framework to Characterize the Cancer Drug Induced Effect on Aging Using Transcriptomic Data
title_fullStr A Computational Framework to Characterize the Cancer Drug Induced Effect on Aging Using Transcriptomic Data
title_full_unstemmed A Computational Framework to Characterize the Cancer Drug Induced Effect on Aging Using Transcriptomic Data
title_short A Computational Framework to Characterize the Cancer Drug Induced Effect on Aging Using Transcriptomic Data
title_sort computational framework to characterize the cancer drug induced effect on aging using transcriptomic data
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9277350/
https://www.ncbi.nlm.nih.gov/pubmed/35847024
http://dx.doi.org/10.3389/fphar.2022.906429
work_keys_str_mv AT zhaoyueshan acomputationalframeworktocharacterizethecancerdruginducedeffectonagingusingtranscriptomicdata
AT wangyue acomputationalframeworktocharacterizethecancerdruginducedeffectonagingusingtranscriptomicdata
AT yangda acomputationalframeworktocharacterizethecancerdruginducedeffectonagingusingtranscriptomicdata
AT suhkangho acomputationalframeworktocharacterizethecancerdruginducedeffectonagingusingtranscriptomicdata
AT zhangmin acomputationalframeworktocharacterizethecancerdruginducedeffectonagingusingtranscriptomicdata
AT zhaoyueshan computationalframeworktocharacterizethecancerdruginducedeffectonagingusingtranscriptomicdata
AT wangyue computationalframeworktocharacterizethecancerdruginducedeffectonagingusingtranscriptomicdata
AT yangda computationalframeworktocharacterizethecancerdruginducedeffectonagingusingtranscriptomicdata
AT suhkangho computationalframeworktocharacterizethecancerdruginducedeffectonagingusingtranscriptomicdata
AT zhangmin computationalframeworktocharacterizethecancerdruginducedeffectonagingusingtranscriptomicdata

Ejemplares similares