Literature DB >> 25697478

Anticipating designer drug-resistant cancer cells.

Mark L Frangione1, John H Lockhart1, Daniel T Morton1, Libia M Pava2, George Blanck3.   

Abstract

Successful use of anticancer designer drugs is likely to depend on simultaneous combinations of these drugs to minimize the development of resistant cancer cells. Considering the knowledge base of cancer signaling pathways, mechanisms of designer drug resistance should be anticipated, and early clinical trials could be designed to include arms that combine new drugs specifically with currently US Food and Drug Administration (FDA)-approved drugs expected to blunt alternative signaling pathways. In this review, we indicate examples of alternative signal pathways for recent anticancer drugs, and the use of original, Python-based software to systematically identify signaling pathways that could facilitate resistance to drugs targeting a particular protein. Pathway alternatives can be assessed at http://www.alternativesignalingpathways.com, developed with this review article.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 25697478     DOI: 10.1016/j.drudis.2015.02.005

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  5 in total

1.  TCGA: Increased oncoprotein coding region mutations correlate with a greater expression of apoptosis-effector genes and a positive outcome for stomach adenocarcinoma.

Authors:  John M Yavorski; George Blanck
Journal:  Cell Cycle       Date:  2016-06-29       Impact factor: 4.534

2.  Impact of SNPs on CpG Islands in the MYC and HRAS oncogenes and in a wide variety of tumor suppressor genes: A multi-cancer approach.

Authors:  Mohammad D Samy; John M Yavorski; James A Mauro; George Blanck
Journal:  Cell Cycle       Date:  2016-06-17       Impact factor: 4.534

3.  Identification of Sets of Cytoskeletal Related and Adhesion-related Coding Region Mutations in the TCGA Melanoma Dataset that Correlate with a Negative Outcome.

Authors:  John M Yavorski; Rebecca J Stoll; Mohammad D Samy; James A Mauro; George Blanck
Journal:  Curr Genomics       Date:  2017-06       Impact factor: 2.236

4.  Facilitating Anti-Cancer Combinatorial Drug Discovery by Targeting Epistatic Disease Genes.

Authors:  Yuan Quan; Meng-Yuan Liu; Ye-Mao Liu; Li-Da Zhu; Yu-Shan Wu; Zhi-Hui Luo; Xiu-Zhen Zhang; Shi-Zhong Xu; Qing-Yong Yang; Hong-Yu Zhang
Journal:  Molecules       Date:  2018-03-23       Impact factor: 4.411

5.  In vitro anti-proliferative effect of capecitabine (Xeloda) combined with mocetinostat (MGCD0103) in 4T1 breast cancer cell line by immunoblotting.

Authors:  Hacer Kaya Çakir; Onur Eroglu
Journal:  Iran J Basic Med Sci       Date:  2021-11       Impact factor: 2.699

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.