Stochastic Dynamics of Leukemic Cells under an Intermittent Targeted Therapy

The evolutionary dynamics of cancerous cell populations in a model of Chronic Myeloid Leukemia (CML) is investigated in the presence of an intermittent targeted therapy. Cancer development and progression is modeled by simulating the stochastic evolution of initially healthy cells which can experience genetic mutations and modify their reproductive behavior, becoming leukemic clones. Front line therapy for the treatment of patients affected by CML is based on the administration of tyrosine kinase inhibitors, namely imatinib (Gleevec) or, more recently, dasatinib or nilotinib. Despite the fact that they represent the first example of a successful molecular targeted therapy, the development of resistance to these drugs is observed in a proportion of patients, especially those in advanced stages. In this study, we simulate an imatinib-like treatment of CML by modifying the fitness and the death rate of cancerous cells and describe the several scenarios in the evolutionary dynamics of white blood cells as a consequence of the efficacy of the different modeled therapies. The patient response to the therapy is investigated by simulating a drug administration following a continuous or pulsed time scheduling. A permanent disappearance of leukemic clones is achieved with a continuous therapy. This theoretical behavior is in a good agreement with that observed in previous clinical investigations. However, these findings demonstrate that an intermittent therapy could represent a valid alternative in patients with high risk of toxicity. A suitable tuned pulsed therapy can also reduce the probability of developing resistance

Intermittent targeted therapies and stochastic evolution in patients affected by chronic myeloid leukemia

Front line therapy for the treatment of patients affected by chronic myeloid leukemia (CML) is based on the administration of tyrosine kinase inhibitors, namely imatinib or, more recently, axitinib. Although imatinib is highly effective and represents an example of a successful molecular targeted therapy, the appearance of resistance is observed in a proportion of patients, especially those in advanced stages. In this work, we investigate the appearance of resistance in patients affected by CML, by modeling the evolutionary dynamics of cancerous cell populations in a simulated patient treated by an intermittent targeted therapy. We simulate, with the Monte Carlo method, the stochastic evolution of initially healthy cells to leukemic clones, due to genetic mutations and changes in their reproductive behavior. We first present the model and its validation with experimental data by considering a continuous therapy. Then, we investigate how fluctuations in the number of leukemic cells affect patient response to the therapy when the drug is administered with an intermittent time scheduling. Here we show that an intermittent therapy (IT) represents a valid choice in patients with high risk of toxicity, despite an associated delay to the complete restoration of healthy cells. Moreover, a suitably tuned IT can reduce the probability of developing resistance

The leukaemia stem cell: similarities, differences and clinical prospects in CML and AML

For two decades, leukaemia stem cells (LSCs) in chronic myeloid leukaemia (CML) and acute myeloid leukaemia (AML) have been advanced paradigms for the cancer stem cell field. In CML, the acquisition of the fusion tyrosine kinase BCR–ABL1 in a haematopoietic stem cell drives its transformation to become a LSC. In AML, LSCs can arise from multiple cell types through the activity of a number of oncogenic drivers and pre-leukaemic events, adding further layers of context and genetic and cellular heterogeneity to AML LSCs not observed in most cases of CML. Furthermore, LSCs from both AML and CML can be refractory to standard-of-care therapies and persist in patients, diversify clonally and serve as reservoirs to drive relapse, recurrence or progression to more aggressive forms. Despite these complexities, LSCs in both diseases share biological features, making them distinct from other CML or AML progenitor cells and from normal haematopoietic stem cells. These features may represent Achilles’ heels against which novel therapies can be developed. Here, we review many of the similarities and differences that exist between LSCs in CML and AML and examine the therapeutic strategies that could be used to eradicate them

Modeling Tumor Clonal Evolution for Drug Combinations Design

Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure toward drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review we discuss the promising opportunities that these interdisciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs.David H. Koch Cancer Research Fund (Grant P30-CA14051)National Cancer Institute (U.S.). Integrative Cancer Biology Program (Grant U54-CA112967)National Institute of General Medical Sciences (U.S.). Interdepartmental Biotechnology Training Program (5T32GM008334

Dynamical Models of Biology and Medicine

Mathematical and computational modeling approaches in biological and medical research are experiencing rapid growth globally. This Special Issue Book intends to scratch the surface of this exciting phenomenon. The subject areas covered involve general mathematical methods and their applications in biology and medicine, with an emphasis on work related to mathematical and computational modeling of the complex dynamics observed in biological and medical research. Fourteen rigorously reviewed papers were included in this Special Issue. These papers cover several timely topics relating to classical population biology, fundamental biology, and modern medicine. While the authors of these papers dealt with very different modeling questions, they were all motivated by specific applications in biology and medicine and employed innovative mathematical and computational methods to study the complex dynamics of their models. We hope that these papers detail case studies that will inspire many additional mathematical modeling efforts in biology and medicin

Stem and progenitor cell involvement in acute lymphoblastic leukemia

Leukemic stem cells (LSCs) share the capacity of self renewal and extensive proliferation with normal hematopoietic stem cells (HSCs), and are therefore obvious targets for therapy. As such, they need to be identified and characterized in order to elucidate what drives them, and what separates them from their normal counterparts. The focus of this thesis is on pre B cell Acute Lymphoblastic Leukemia (ALL), the most common form of cancer in children. We have investigated 2 distinct subtypes of ALL, characterized by the gene fusions ETV6-RUNX1 (found mainly in pediatric ALL, conferring a favorable prognosis) and BCR-ABL1 (producing two different onco-proteins, designated P190 and P210, both of which are associated with a poor prognosis in both children and adults). We show that ETV6-RUNX1 ALL are propagated by B-cell committed LSCs expressing the lymphoid marker CD19, leaving the normal HSC compartment intact. In BCR-ABL1-positive ALL we show an unexpected difference between the two forms of the fusion protein, such that the LSC in P190 BCR-ABL1 ALL, similar to ETV6-RUNX1 ALL, are B-cell committed progenitors, whereas P210 BCR-ABL1 ALL originates in a multipotent HSC, expressing the same phenotypical markers as the normal HSC, and with a retained, albeit severely reduced, capacity to produce a clonal myeloid progeny. Interestingly, the LSC still displays the B cell commitment marker CD19, as only CD19+ cells propagates the disease in immunocompromised mice. We cannot, however, exclude very rare, and/or very quiscent CD19-ve P210 LSCs. This represents a hitherto unanticipated distinct biological difference between P190 and P210 ALLs, possibly indicating different requirements for eradication. In the second paper we describe a method to prospectively purify a large part of the leukemic cells from bone marrow or peripheral blood from patients with ALL, for relevant comparisons across samples. We compared ALL cells harvested from bone marrow and peripheral blood from the same patient by gene expression profiling, and found a striking similarity between cells from the two locations, indicating that bone marrow derived biological cues necessary for normal pre B cells not seem to segregate ALL cells in a blood and a bone marrow compartment, and that cells thus can be harvested from either compartment for further gene expression analyses. Finally, in the discussion part of the two papers, are preliminary data from follow up studies discussed, where we find indications for the existence of distinct sets of LSCs within the same patient with ALL or chronic myeloid leukemia in lymphoid blast crisis, contrary to the generally held view of a homogeneous LSC population

Finding a targetable super-hub within the network of cancer cell persistency and adaptiveness: a clinician-scientist quantitative perspective for melanoma

In this perspective article, a clinically inspired phenotype-driven experimental approach is put forward to address the challenge of the adaptive response of solid cancers to small-molecule targeted therapies. A list of conditions is derived, including an experimental quantitative assessment of cell plasticity and an information theory-based detection of in vivo dependencies, for the discovery of post-transcriptional druggable mechanisms capable of preventing at multiple levels the emergence of plastic dedifferentiated slow-proliferating cells. The approach is illustrated by the author's own work in the example case of the adaptive response of BRAFV600-melanoma to BRAF inhibition. A bench-to-bedside and back to bench effort leads to a therapeutic strategy in which the inhibition of the baseline activity of the interferon-gamma-activated inhibitor of translation (GAIT) complex, incriminated in the expression insufficiency of the RNA-binding protein HuR in a minority of cells, results in the suppression of the plastic, intermittently slow-proliferating cells involved in the adaptive response. A similar approach is recommended for the validation of other classes of mechanisms that we seek to modulate to overcome this complex challenge of modern cancer therapy.Comment: 12 pages, 3 figure

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

Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation

Background Drug-induced drug resistance in cancer has been attributed to diverse biological mechanisms at the individual cell or cell population scale, relying on stochastically or epigenetically varying expression of phenotypes at the single cell level, and on the adaptability of tumours at the cell population level. Scope of review We focus on intra-tumour heterogeneity, namely between-cell variability within cancer cell populations, to account for drug resistance. To shed light on such heterogeneity, we review evolutionary mechanisms that encompass the great evolution that has designed multicellular organisms, as well as smaller windows of evolution on the time scale of human disease. We also present mathematical models used to predict drug resistance in cancer and optimal control methods that can circumvent it in combined therapeutic strategies. Major conclusions Plasticity in cancer cells, i.e., partial reversal to a stem-like status in individual cells and resulting adaptability of cancer cell populations, may be viewed as backward evolution making cancer cell populations resistant to drug insult. This reversible plasticity is captured by mathematical models that incorporate between-cell heterogeneity through continuous phenotypic variables. Such models have the benefit of being compatible with optimal control methods for the design of optimised therapeutic protocols involving combinations of cytotoxic and cytostatic treatments with epigenetic drugs and immunotherapies. General significance Gathering knowledge from cancer and evolutionary biology with physiologically based mathematical models of cell population dynamics should provide oncologists with a rationale to design optimised therapeutic strategies to circumvent drug resistance, that still remains a major pitfall of cancer therapeutics. This article is part of a Special Issue entitled “System Genetics” Guest Editor: Dr. Yudong Cai and Dr. Tao Huang

Integration Site and Clonal Expansion in Human Chronic Retroviral Infection and Gene Therapy

Retroviral vectors have been successfully used therapeutically to restore expression of genes in a range of single-gene diseases, including several primary immunodeficiency disorders. Although clinical trials have shown remarkable results, there have also been a number of severe adverse events involving malignant outgrowth of a transformed clonal population. This clonal expansion is influenced by the integration site profile of the viral integrase, the transgene expressed, and the effect of the viral promoters on the neighbouring host genome. Infection with the pathogenic human retrovirus HTLV-1 also causes clonal expansion of cells containing an integrated HTLV-1 provirus. Although the majority of HTLV-1-infected people remain asymptomatic, up to 5% develop an aggressive T cell malignancy. In this review we discuss recent findings on the role of the genomic integration site in determining the clonality and the potential for malignant transformation of cells carrying integrated HTLV-1 or gene therapy vectors, and how these results have contributed to the understanding of HTLV-1 pathogenesis and to improvements in gene therapy vector safety