Applying Mathematical Models to Study the Role of the Immune System in Chronic Myelogenous Leukemia

Although tyrosine kinase inhibitors (TKIs) such as imatinib have transformed chronic myelogenous leukemia (CML) into a chronic condition, these therapies are not curative in the majority of cases. Most patients must continue TKI therapy indefinitely, a requirement that is both expensive and that compromises a patient's quality of life. While TKIs are known to reduce leukemic cells' proliferative capacity and to induce apoptosis, their effects on leukemic stem cells, the immune system, and the microenvironment are not fully understood. A more complete understanding of their global therapeutic effects would help us to identify any limitations of TKI monotherapy and to address these issues through novel combination therapies. Mathematical models are a complementary tool to experimental and clinical data that can provide valuable insights into the underlying mechanisms of TKI therapy. Previous modeling efforts have focused on CML patients who show biphasic and triphasic exponential declines in BCR-ABL ratio during therapy. However, our patient data indicates that many patients treated with TKIs show fluctuations in BCR-ABL ratio yet are able to achieve durable remissions. To investigate these fluctuations, we construct a mathematical model that integrates CML with a patient's autologous immune response to the disease. In our model, we define an immune window, which is an intermediate range of leukemic concentrations that lead to an effective immune response against CML. While small leukemic concentrations provide insufficient stimulus, large leukemic concentrations actively suppress a patient's immune system, thus limiting it's ability to respond. Our patient data and modeling results suggest that at diagnosis, a patient's high leukemic concentration is able to suppress their immune system. TKI therapy drives the leukemic population into the immune window, allowing the patient's immune cells to expand and eventually mount an efficient response against the residual CML. This response drives the leukemic population below the immune window, causing the immune population to contract and allowing the leukemia to partially recover. The leukemia eventually reenters the immune window, thus stimulating a sequence of weaker immune responses as the two populations approach equilibrium. We hypothesize that a patient's autologous immune response to CML may explain the fluctuations in BCR-ABL ratio that are regularly seen during TKI therapy. These fluctuations may serve as a signature of a patient's individual immune response to CML. By applying our modeling framework to patient data, we are able to construct an immune profile that can then be used to propose patient-specific combination therapies aimed at further reducing a patient's leukemic burden. Our characterization of a patient's anti-leukemia immune response may be especially valuable in the study of drug resistance, treatment cessation, and combination therapy.

THE ROLE OF THE MECHANICAL ENVIRONMENT ON CANCER CELL TRANSMIGRATION AND MRNA LOCALIZATION

Most cancer-related deaths are due to metastasis formation, the ability of cancer cells to break away from the primary tumor site, transmigrate through the endothelium, and form secondary tumors in distant areas. Many studies have identified links between the mechanical properties of the cellular microenvironment and the behavior of cancer cells. Cells may experience heterogeneous microenvironments of varying stiffness during tumor progression, transmigration, and invasion into the basement membrane. In addition to mechanical factors, the localization of RNAs to lamellipodial regions has been proposed to play an important part in metastasis. This dissertation provides a quantitative evaluation of the biophysical effects on cancer cell transmigration and RNA localization. In the first part of this dissertation, we sought to compare cancer cell and leukocyte transmigration and investigate the impact of matrix stiffness on transmigration process. We found that cancer cell transmigration includes an additional step, ‘incorporation’, into the endothelial cell (EC) monolayer. During this phase, cancer cells physically displace ECs and spread into the monolayer. Furthermore, the effects of subendothelial matrix stiffness and endothelial activation on cancer cell incorporation are cell-specific, a notable difference from the process by which leukocytes transmigrate. Collectively, our results provide mechanistic insights into tumor cell extravasation and demonstrate that incorporation into the endothelium is one of the earliest steps. In the next part of this work, we investigated how matrix stiffness impacts RNA localization and its relevance to cancer metastasis. In migrating cells, the tumor suppressor protein, adenomatous polyposis coli (APC) targets RNAs to cellular protrusions. We observed that increasing stiffness promotes the peripheral localization of these APC-dependent RNAs and that cellular contractility plays a role in regulating this pathway. We next investigated the mechanism underlying the effect of substrate stiffness and cellular contractility. We found that contractility drives localization of RNAs to protrusions through modulation of detyrosinated microtubules, a network of modified microtubules that associate with, and are required for localization of APC-dependent RNAs. These results raise the possibility that as the matrix environment becomes stiffer during tumor progression, it promotes the localization of RNAs and ultimately induces a metastatic phenotype.

The role of the Indian Ocean sector and sea surface salinity for prediction of the coupled Indo-Pacific system

The purpose of this dissertation is to evaluate the potential downstream influence of the Indian Ocean (IO) on El Niño/Southern Oscillation (ENSO) forecasts through the oceanic pathway of the Indonesian Throughflow (ITF), atmospheric teleconnections between the IO and Pacific, and assimilation of IO observations. Also the impact of sea surface salinity (SSS) in the Indo-Pacific region is assessed to try to address known problems with operational coupled model precipitation forecasts. The ITF normally drains warm fresh water from the Pacific reducing the mixed layer depths (MLD). A shallower MLD amplifies large-scale oceanic Kelvin/Rossby waves thus giving ~10% larger response and more realistic ENSO sea surface temperature (SST) variability compared to observed when the ITF is open. In order to isolate the impact of the IO sector atmospheric teleconnections to ENSO, experiments are contrasted that selectively couple/decouple the interannual forcing in the IO. The interannual variability of IO SST forcing is responsible for 3 month lagged widespread downwelling in the Pacific, assisted by off-equatorial curl, leading to warmer NINO3 SST anomaly and improved ENSO validation (significant from 3-9 months). Isolating the impact of observations in the IO sector using regional assimilation identifies large-scale warming in the IO that acts to intensify the easterlies of the Walker circulation and increases pervasive upwelling across the Pacific, cooling the eastern Pacific, and improving ENSO validation (r ~ 0.05, RMS~0.08C). Lastly, the positive impact of more accurate fresh water forcing is demonstrated to address inadequate precipitation forecasts in operational coupled models. Aquarius SSS assimilation improves the mixed layer density and enhances mixing, setting off upwelling that eventually cools the eastern Pacific after 6 months, counteracting the pervasive warming of most coupled models and significantly improving ENSO validation from 5-11 months. In summary, the ITF oceanic pathway, the atmospheric teleconnection, the impact of observations in the IO, and improved Indo-Pacific SSS are all responsible for ENSO forecast improvements, and so each aspect of this study contributes to a better overall understanding of ENSO. Therefore, the upstream influence of the IO should be thought of as integral to the functioning of ENSO phenomenon.