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Optimizing combination therapies with existing and future CML drugs.

Katouli AA, Komarova NL - PLoS ONE (2010)

Bottom Line: Small-molecule inhibitors imatinib, dasatinib and nilotinib have been developed to treat Chromic Myeloid Leukemia (CML).Many new compounds active against T315I mutants are now at different stages of development.Although our methodology is based on a stochastic model of CML microevolution, the algorithm itself does not require measurements of any parameters (such as mutation rates, or division/death rates of cells), and can be used by medical professionals without a mathematical background.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, University of California Irvine, Irvine, California, United States of America.

ABSTRACT
Small-molecule inhibitors imatinib, dasatinib and nilotinib have been developed to treat Chromic Myeloid Leukemia (CML). The existence of a triple-cross-resistant mutation, T315I, has been a challenging problem, which can be overcome by finding new inhibitors. Many new compounds active against T315I mutants are now at different stages of development. In this paper we develop an algorithm which can weigh different combination treatment protocols according to their cross-resistance properties, and find the protocols with the highest probability of treatment success. This algorithm also takes into account drug toxicity by minimizing the number of drugs used, and their concentration. Although our methodology is based on a stochastic model of CML microevolution, the algorithm itself does not require measurements of any parameters (such as mutation rates, or division/death rates of cells), and can be used by medical professionals without a mathematical background. For illustration, we apply this algorithm to the mutation data obtained in [1], [2].

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A mutation network for a three-drug treatment.The nodes correspond to different resistance phenotypes, and the arrows to mutation processes; mutation rates are marked next to the arrows. Singly-resistant mutations are denoted my solid lines, doubly-resistant mutations – by dashed lines and italic font, and the triply-resistant mutation by a thick line and bold font.
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pone-0012300-g001: A mutation network for a three-drug treatment.The nodes correspond to different resistance phenotypes, and the arrows to mutation processes; mutation rates are marked next to the arrows. Singly-resistant mutations are denoted my solid lines, doubly-resistant mutations – by dashed lines and italic font, and the triply-resistant mutation by a thick line and bold font.

Mentions: Stochastic dynamics occurs on a mutation diagram which specifies the mutation processes that create phenotypes resistant to various drugs, see figure 1. This network's nodes denote cancer cell phenotypes which have different characteristics with respect to their drug susceptibility. For example, if two drugs are used to treat the tumor, then potentially there could be at least four different cell types: those that are fully susceptible; we characterize those by the binary index s = 00; those resistant to drug 1 and susceptible to drug 2 (s = 10); those resistant to drug 2 and susceptible to drug 1 (s = 01), and those resistant to both drugs (or, fully-resistant), with s = 11. In general, if m drugs are applied in the course of the therapy, we have 2m combinatorial resistance types. The binary index s has m positions corresponding to the m drugs; “1” in a given position denotes resistance to the corresponding drug, while “0” means susceptibility.


Optimizing combination therapies with existing and future CML drugs.

Katouli AA, Komarova NL - PLoS ONE (2010)

A mutation network for a three-drug treatment.The nodes correspond to different resistance phenotypes, and the arrows to mutation processes; mutation rates are marked next to the arrows. Singly-resistant mutations are denoted my solid lines, doubly-resistant mutations – by dashed lines and italic font, and the triply-resistant mutation by a thick line and bold font.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2925944&req=5

pone-0012300-g001: A mutation network for a three-drug treatment.The nodes correspond to different resistance phenotypes, and the arrows to mutation processes; mutation rates are marked next to the arrows. Singly-resistant mutations are denoted my solid lines, doubly-resistant mutations – by dashed lines and italic font, and the triply-resistant mutation by a thick line and bold font.
Mentions: Stochastic dynamics occurs on a mutation diagram which specifies the mutation processes that create phenotypes resistant to various drugs, see figure 1. This network's nodes denote cancer cell phenotypes which have different characteristics with respect to their drug susceptibility. For example, if two drugs are used to treat the tumor, then potentially there could be at least four different cell types: those that are fully susceptible; we characterize those by the binary index s = 00; those resistant to drug 1 and susceptible to drug 2 (s = 10); those resistant to drug 2 and susceptible to drug 1 (s = 01), and those resistant to both drugs (or, fully-resistant), with s = 11. In general, if m drugs are applied in the course of the therapy, we have 2m combinatorial resistance types. The binary index s has m positions corresponding to the m drugs; “1” in a given position denotes resistance to the corresponding drug, while “0” means susceptibility.

Bottom Line: Small-molecule inhibitors imatinib, dasatinib and nilotinib have been developed to treat Chromic Myeloid Leukemia (CML).Many new compounds active against T315I mutants are now at different stages of development.Although our methodology is based on a stochastic model of CML microevolution, the algorithm itself does not require measurements of any parameters (such as mutation rates, or division/death rates of cells), and can be used by medical professionals without a mathematical background.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics, University of California Irvine, Irvine, California, United States of America.

ABSTRACT
Small-molecule inhibitors imatinib, dasatinib and nilotinib have been developed to treat Chromic Myeloid Leukemia (CML). The existence of a triple-cross-resistant mutation, T315I, has been a challenging problem, which can be overcome by finding new inhibitors. Many new compounds active against T315I mutants are now at different stages of development. In this paper we develop an algorithm which can weigh different combination treatment protocols according to their cross-resistance properties, and find the protocols with the highest probability of treatment success. This algorithm also takes into account drug toxicity by minimizing the number of drugs used, and their concentration. Although our methodology is based on a stochastic model of CML microevolution, the algorithm itself does not require measurements of any parameters (such as mutation rates, or division/death rates of cells), and can be used by medical professionals without a mathematical background. For illustration, we apply this algorithm to the mutation data obtained in [1], [2].

Show MeSH
Related in: MedlinePlus