Advocating the need of a systems biology approach for personalised prognosis and treatment of B-CLL patients

The clinical course of B-CLL is heterogeneous. This heterogeneity leads to a clinical dilemma: can we identify those patients who will benefit from early treatment and predict the survival? In recent years, mathematical modelling has contributed significantly in understanding the complexity of diseases. In order to build a mathematical model for determining prognosis of B-CLL one has to identify, characterise and quantify key molecules involved in the disease. Here we discuss the need and role of mathematical modelling in predicting B-CLL disease pathogenesis and suggest a new systems biology approach for a personalised therapy of B-CLL patients

A dyad of lymphoblastic lysosomal cysteine proteases degrades the antileukemic drug L-asparaginase

l-Asparaginase is a key therapeutic agent for treatment of childhood acute lymphoblastic leukemia (ALL). There is wide individual variation in pharmacokinetics, and little is known about its metabolism. The mechanisms of therapeutic failure with l-asparaginase remain speculative. Here, we now report that 2 lysosomal cysteine proteases present in lymphoblasts are able to degrade l-asparaginase. Cathepsin B (CTSB), which is produced constitutively by normal and leukemic cells, degraded asparaginase produced by Escherichia coli (ASNase) and Erwinia chrysanthemi. Asparaginyl endopeptidase (AEP), which is overexpressed predominantly in high-risk subsets of ALL, specifically degraded ASNase. AEP thereby destroys ASNase activity and may also potentiate antigen processing, leading to allergic reactions. Using AEP-mediated cleavage sequences, we modeled the effects of the protease on ASNase and created a number of recombinant ASNase products. The N24 residue on the flexible active loop was identified as the primary AEP cleavage site. Sole modification at this site rendered ASNase resistant to AEP cleavage and suggested a key role for the flexible active loop in determining ASNase activity. We therefore propose what we believe to be a novel mechanism of drug resistance to ASNase. Our results may help to identify alternative therapeutic strategies with the potential of further improving outcome in childhood ALL

A precision medicine test predicts clinical response after idarubicin and cytarabine induction therapy in AML patients

Complete remission (CR) after induction therapy is the first treatment goal in acute myeloid leukemia (AML) patients and has prognostic impact. Our purpose is to determine the correlation between the observed CR/CRi rate after idarubicin (IDA) and cytarabine (CYT) 3 + 7 induction and the leukemic chemosensitivity measured by an ex vivo test of drug activity. Bone marrow samples from adult patients with newly diagnosed AML were included in this study. Whole bone marrow samples were incubated for 48 h in well plates containing IDA, CYT, or their combination. Pharmacological response parameters were estimated using population pharmacodynamic models. Patients attaining a CR/CRi with up to two induction cycles of 3 + 7 were classified as responders and the remaining as resistant. A total of 123 patients fulfilled the inclusion criteria and were evaluable for correlation analyses. The strongest clinical predictors were the area under the curve of the concentration response curves of CYT and IDA. The overall accuracy achieved using MaxSpSe criteria to define positivity was 81%, predicting better responder (93%) than non-responder patients (60%). The ex vivo test provides better yet similar information than cytogenetics, but can be provided before treatment representing a valuable in-time addition. After validation in an external cohort, this novel ex vivo test could be useful to select AML patients for 3 + 7 regimen vs. alternative schedules

Eradication of chronic myeloid leukemia stem cells: a novel mathematical model predicts no therapeutic benefit of adding G-CSF to imatinib

Imatinib mesylate induces complete cytogenetic responses in patients with chronic myeloid leukemia (CML), yet many patients have detectable BCR-ABL transcripts in peripheral blood even after prolonged therapy. Bone marrow studies have shown that this residual disease resides within the stem cell compartment. Quiescence of leukemic stem cells has been suggested as a mechanism conferring insensitivity to imatinib, and exposure to the Granulocyte-Colony Stimulating Factor (G-CSF), together with imatinib, has led to a significant reduction in leukemic stem cells in vitro. In this paper, we design a novel mathematical model of stem cell quiescence to investigate the treatment response to imatinib and G-CSF. We find that the addition of G-CSF to an imatinib treatment protocol leads to observable effects only if the majority of leukemic stem cells are quiescent; otherwise it does not modulate the leukemic cell burden. The latter scenario is in agreement with clinical findings in a pilot study administering imatinib continuously or intermittently, with or without G-CSF (GIMI trial). Furthermore, our model predicts that the addition of G-CSF leads to a higher risk of resistance since it increases the production of cycling leukemic stem cells. Although the pilot study did not include enough patients to draw any conclusion with statistical significance, there were more cases of progression in the experimental arms as compared to continuous imatinib. Our results suggest that the additional use of G-CSF may be detrimental to patients in the clinic

Translational Oncogenomics and Human Cancer Interactome Networks

An overview of translational, human oncogenomics, transcriptomics and cancer interactomic networks is presented together with basic concepts and potential, new applications to Oncology and Integrative Cancer Biology. Novel translational oncogenomics research is rapidly expanding through the application of advanced technology, research findings and computational tools/models to both pharmaceutical and clinical problems. A self-contained presentation is adopted that covers both fundamental concepts and the most recent biomedical, as well as clinical, applications. Sample analyses in recent clinical studies have shown that gene expression data can be employed to distinguish between tumor types as well as to predict outcomes. Potentially important applications of such results are individualized human cancer therapies or, in general, ‘personalized medicine’. Several cancer detection techniques are currently under development both in the direction of improved detection sensitivity and increased time resolution of cellular events, with the limits of single molecule detection and picosecond time resolution already reached. The urgency for the complete mapping of a human cancer interactome with the help of such novel, high-efficiency / low-cost and ultra-sensitive techniques is also pointed out

A precision medicine test predicts clinical response after idarubicin and cytarabine induction therapy in AML patients

Complete remission (CR) after induction therapy is the first treatment goal in acute myeloid leukemia (AML) patients and has prognostic impact. Our purpose is to determine the correlation between the observed CR/CRi rate after idarubicin (IDA) and cytarabine (CYT) 3 + 7 induction and the leukemic chemosensitivity measured by an ex vivo test of drug activity. Bone marrow samples from adult patients with newly diagnosed AML were included in this study. Whole bone marrow samples were incubated for 48 h in well plates containing IDA, CYT, or their combination. Pharmacological response parameters were estimated using population pharmacodynamic models. Patients attaining a CR/CRi with up to two induction cycles of 3 + 7 were classified as responders and the remaining as resistant. A total of 123 patients fulfilled the inclusion criteria and were evaluable for correlation analyses. The strongest clinical predictors were the area under the curve of the concentration response curves of CYT and IDA. The overall accuracy achieved using MaxSpSe criteria to define positivity was 81%, predicting better responder (93%) than non-responder patients (60%). The ex vivo test provides better yet similar information than cytogenetics, but can be provided before treatment representing a valuable in-time addition. After validation in an external cohort, this novel ex vivo test could be useful to select AML patients for 3 + 7 regimen vs. alternative schedules

Modeling and simulation applications with potential impact in drug development and patient care

Indiana University-Purdue University Indianapolis (IUPUI)Model-based drug development has become an essential element to potentially make drug development more productive by assessing the data using mathematical and statistical approaches to construct and utilize models to increase the understanding of the drug and disease. The modeling and simulation approach not only quantifies the exposure-response relationship, and the level of variability, but also identifies the potential contributors to the variability. I hypothesized that the modeling and simulation approach can: 1) leverage our understanding of pharmacokinetic-pharmacodynamic (PK-PD) relationship from pre-clinical system to human; 2) quantitatively capture the drug impact on patients; 3) evaluate clinical trial designs; and 4) identify potential contributors to drug toxicity and efficacy. The major findings for these studies included: 1) a translational PK modeling approach that predicted clozapine and norclozapine central nervous system exposures in humans relating these exposures to receptor binding kinetics at multiple receptors; 2) a population pharmacokinetic analysis of a study of sertraline in depressed elderly patients with Alzheimer’s disease that identified site specific differences in drug exposure contributing to the overall variability in sertraline exposure; 3) the utility of a longitudinal tumor dynamic model developed by the Food and Drug Administration for predicting survival in non-small cell lung cancer patients, including an exploration of the limitations of this approach; 4) a Monte Carlo clinical trial simulation approach that was used to evaluate a pre-defined oncology trial with a sparse drug concentration sampling schedule with the aim to quantify how well individual drug exposures, random variability, and the food effects of abiraterone and nilotinib were determined under these conditions; 5) a time to event analysis that facilitated the identification of candidate genes including polymorphisms associated with vincristine-induced neuropathy from several association analyses in childhood acute lymphoblastic leukemia (ALL) patients; and 6) a LASSO penalized regression model that predicted vincristine-induced neuropathy and relapse in ALL patients and provided the basis for a risk assessment of the population. Overall, results from this dissertation provide an improved understanding of treatment effect in patients with an assessment of PK/PD combined and with a risk evaluation of drug toxicity and efficacy