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Combined Population Dynamics and Entropy Modelling Supports Patient Stratification in Chronic Myeloid Leukemia.

ABSTRACT: Modelling the parameters of multistep carcinogenesis is key for a better understanding of cancer progression, biomarker identification and the design of individualized therapies. Using chronic myeloid leukemia (CML) as a paradigm for hierarchical disease evolution we show that combined population dynamic modelling and CML patient biopsy genomic analysis enables patient stratification at unprecedented resolution. Linking CD34(+) similarity as a disease progression marker to patient-derived gene expression entropy separated established CML progression stages and uncovered additional heterogeneity within disease stages. Importantly, our patient data informed model enables quantitative approximation of individual patients' disease history within chronic phase (CP) and significantly separates "early" from "late" CP. Our findings provide a novel rationale for personalized and genome-informed disease progression risk assessment that is independent and complementary to conventional measures of CML disease burden and prognosis.

SUBMITTER: Brehme M

PROVIDER: S-EPMC4822142 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Combined Population Dynamics and Entropy Modelling Supports Patient Stratification in Chronic Myeloid Leukemia.

Brehme Marc M Koschmieder Steffen S Montazeri Maryam M Copland Mhairi M Oehler Vivian G VG Radich Jerald P JP Brümmendorf Tim H TH Schuppert Andreas A

Scientific reports 20160406

Modelling the parameters of multistep carcinogenesis is key for a better understanding of cancer progression, biomarker identification and the design of individualized therapies. Using chronic myeloid leukemia (CML) as a paradigm for hierarchical disease evolution we show that combined population dynamic modelling and CML patient biopsy genomic analysis enables patient stratification at unprecedented resolution. Linking CD34(+) similarity as a disease progression marker to patient-derived gene e ...[more]

PMID: 27048866

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Project description:The first treatment of chronic myeloid leukemia (CML) included spleen x-radiation and conventional drugs, mainly Busulfan and Hydroxyurea. This therapy improved the quality of life during the chronic phase of the disease, without preventing nor significantly delaying the progression towards advanced phases. The introduction of allogeneic stem cell transplantation (alloSCT) marked the first important breakthrough in the evolution of CML treatment, because about 50% of the eligible patients were cured. The second breakthrough was the introduction of human recombinant interferon-alfa, able to achieve a complete cytogenetic remission in 15% to 30% of patients, with a significant survival advantage over conventional chemotherapy. At the end of the last century, about 15 years ago, all these treatments were quickly replaced by a class of small molecules targeting the tyrosine kinases (TK), which were able to induce a major molecular remission in most of the patients, without remarkable side effects, and a very prolonged life-span. The first approved TK inhibitor (TKI) was Imatinib Mesylate (Glivec or Gleevec, Novartis). Rapidly, other TKIs were developed tested and commercialized, namely Dasatinib (Sprycel, Bristol-Myers Squibb), Nilotinib (Tasigna, Novartis), Bosutinib (Busulif, Pfizer) and Ponatinib (Iclusig, Ariad). Not all these compounds are available worldwide; some of them are approved only for second line treatment, and the high prices are a problem that can limit their use. A frequent update of treatment recommendations is necessary. The current treatment goals include not only the prevention of the transformation to the advanced phases and the prolongation of survival, but also a length of survival and of a quality of life comparable to that of non-leukemic individuals. In some patient the next ambitious step is to move towards a treatment-free remission. The CML therapy, the role of alloSCT and the promising experimental strategies are reviewed in the context of the new therapeutic goals.

Dataset Information

Combined Population Dynamics and Entropy Modelling Supports Patient Stratification in Chronic Myeloid Leukemia.

Publications

Combined Population Dynamics and Entropy Modelling Supports Patient Stratification in Chronic Myeloid Leukemia.

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