Menu
×
West Ashley Library
9 a.m. – 7 p.m.
Phone: (843) 766-6635
Folly Beach Library
Closed
Phone: (843) 588-2001
Edgar Allan Poe/Sullivan's Island Library
Closed for renovations
Phone: (843) 883-3914
Wando Mount Pleasant Library
9 a.m. – 8 p.m.
Phone: (843) 805-6888
Village Library
9 a.m. – 6 p.m.
Phone: (843) 884-9741
St. Paul's/Hollywood Library
9 a.m. – 8 p.m.
Phone: (843) 889-3300
Otranto Road Library
9 a.m. – 8 p.m.
Phone: (843) 572-4094
Mt. Pleasant Library
9 a.m. – 8 p.m.
Phone: (843) 849-6161
McClellanville Library
9 a.m. - 6 p.m.
Phone: (843) 887-3699
Keith Summey North Charleston Library
9 a.m. – 8 p.m.
Phone: (843) 744-2489
John's Island Library
9 a.m. – 8 p.m.
Phone: (843) 559-1945
Hurd/St. Andrews Library
9 a.m. – 8 p.m.
Phone: (843) 766-2546
Miss Jane's Building (Edisto Library Temporary Location)
9 a.m. – 6 p.m.
Phone: (843) 869-2355
Dorchester Road Library
9 a.m. – 8 p.m.
Phone: (843) 552-6466
John L. Dart Library
9 a.m. – 7 p.m.
Phone: (843) 722-7550
Baxter-Patrick James Island
9 a.m. – 8 p.m.
Phone: (843) 795-6679
Main Library
9 a.m. – 8 p.m.
Phone: (843) 805-6930
Bees Ferry West Ashley Library
9 a.m. – 8 p.m.
Phone: (843) 805-6892
Mobile Library
9 a.m. - 5 p.m.
Phone: (843) 805-6909
Today's Hours
West Ashley Library
9 a.m. – 7 p.m.
Phone: (843) 766-6635
Folly Beach Library
Closed
Phone: (843) 588-2001
Edgar Allan Poe/Sullivan's Island Library
Closed for renovations
Phone: (843) 883-3914
Wando Mount Pleasant Library
9 a.m. – 8 p.m.
Phone: (843) 805-6888
Village Library
9 a.m. – 6 p.m.
Phone: (843) 884-9741
St. Paul's/Hollywood Library
9 a.m. – 8 p.m.
Phone: (843) 889-3300
Otranto Road Library
9 a.m. – 8 p.m.
Phone: (843) 572-4094
Mt. Pleasant Library
9 a.m. – 8 p.m.
Phone: (843) 849-6161
McClellanville Library
9 a.m. - 6 p.m.
Phone: (843) 887-3699
Keith Summey North Charleston Library
9 a.m. – 8 p.m.
Phone: (843) 744-2489
John's Island Library
9 a.m. – 8 p.m.
Phone: (843) 559-1945
Hurd/St. Andrews Library
9 a.m. – 8 p.m.
Phone: (843) 766-2546
Miss Jane's Building (Edisto Library Temporary Location)
9 a.m. – 6 p.m.
Phone: (843) 869-2355
Dorchester Road Library
9 a.m. – 8 p.m.
Phone: (843) 552-6466
John L. Dart Library
9 a.m. – 7 p.m.
Phone: (843) 722-7550
Baxter-Patrick James Island
9 a.m. – 8 p.m.
Phone: (843) 795-6679
Main Library
9 a.m. – 8 p.m.
Phone: (843) 805-6930
Bees Ferry West Ashley Library
9 a.m. – 8 p.m.
Phone: (843) 805-6892
Mobile Library
9 a.m. - 5 p.m.
Phone: (843) 805-6909
Patron Login
menu
Item request has been placed!
×
Item request cannot be made.
×
![loading](/sites/all/modules/hf_eds/images/loading.gif)
Phenotype-based probabilistic analysis of heterogeneous responses to cancer drugs and their combination efficacy.
Item request has been placed!
×
Item request cannot be made.
×
![loading](/sites/all/modules/hf_eds/images/loading.gif)
- Author(s): Comandante-Lou, Natacha; Khaliq, Mehwish; Venkat, Divya; Manikkam, Mohan; Fallahi-Sichani, Mohammad
- Source:
PLoS Computational Biology; 2/21/2020, Vol. 16 Issue 2, p1-27, 27p, 5 Graphs- Subject Terms:
- Source:
- Additional Information
- Abstract: Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish the efficacy of cancer drugs. Efficacious combination therapies are thus needed to block drug-tolerant cells via minimizing the impact of heterogeneity. Probabilistic models such as Bliss independence have been developed to evaluate drug interactions and their combination efficacy based on probabilities of specific actions mediated by drugs individually and in combination. In practice, however, these models are often applied to conventional dose-response curves in which a normalized parameter with a value between zero and one, generally referred to as fraction of cells affected (f
a ), is used to evaluate the efficacy of drugs and their combined interactions. We use basic probability theory, computer simulations, time-lapse live cell microscopy, and single-cell analysis to show that fa metrics may bias our assessment of drug efficacy and combination effectiveness. This bias may be corrected when dynamic probabilities of drug-induced phenotypic events, i.e. induction of cell death and inhibition of division, at a single-cell level are used as metrics to assess drug efficacy. Probabilistic phenotype metrics offer the following three benefits. First, in contrast to the commonly used fa metrics, they directly represent probabilities of drug action in a cell population. Therefore, they deconvolve differential degrees of drug effect on tumor cell killing versus inhibition of cell division, which may not be correlated for many drugs. Second, they increase the sensitivity of short-term drug response assays to cell-to-cell heterogeneities and the presence of drug-tolerant subpopulations. Third, their probabilistic nature allows them to be used directly in unbiased evaluation of synergistic efficacy in drug combinations using probabilistic models such as Bliss independence. Altogether, we envision that probabilistic analysis of single-cell phenotypes complements currently available assays via improving our understanding of heterogeneity in drug response, thereby facilitating the discovery of more efficacious combination therapies to block drug-tolerant cells. Author summary: Resistance to therapy due to tumor cell heterogeneity poses a major challenge to the use of cancer drugs. Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish therapeutic efficacy, even in populations of cells that are scored as highly sensitive based on drug potency. Overcoming such heterogeneity and blocking subpopulations of drug-tolerant cells motivate efforts toward identifying efficacious combination therapies. The success of these efforts depends on our ability to distinguish how heterogeneous populations of cells respond to individual drugs, and how these responses are influenced by combined drug interactions. In this paper, we propose mathematical and experimental frameworks to evaluate time-dependent drug interactions based on probabilistic metrics that quantify drug-induced tumor cell killing or inhibition of division at a single-cell level. These metrics can reveal heterogeneous drug responses and their changes with time and drug combinations. Thus, they have important implications for designing efficacious combination therapies, especially those designed to block or overcome drug-tolerant subpopulations of cancer cells. [ABSTRACT FROM AUTHOR] - Abstract: Copyright of PLoS Computational Biology is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
Contact CCPL
Copyright 2022 Charleston County Public Library Powered By EBSCO Stacks 3.3.0 [350.3] | Staff Login
No Comments.