Model discovery approach enables noninvasive measurement of intra-tumoral fluid transport in dynamic MRI.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to noninvasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that our method will contribute to the better understanding of cancer progression and therapeutic response.

Structural and practical identifiability of contrast transport models for DCE-MRI.

Contrast transport models are widely used to quantify blood flow and transport in dynamic contrast-enhanced magnetic resonance imaging. These models analyze the time course of the contrast agent concentration, providing diagnostic and prognostic value for many biological systems. Thus, ensuring accuracy and repeatability of the model parameter estimation is a fundamental concern. In this work, we analyze the structural and practical identifiability of a class of nested compartment models pervasively used in analysis of MRI data. We combine artificial and real data to study the role of noise in model parameter estimation. We observe that although all the models are structurally identifiable, practical identifiability strongly depends on the data characteristics. We analyze the impact of increasing data noise on parameter identifiability and show how the latter can be recovered with increased data quality. To complete the analysis, we show that the results do not depend on specific tissue characteristics or the type of enhancement patterns of contrast agent signal.

Targeting Wnt signaling for improved glioma immunotherapy.

Introduction: Despite aggressive standard-of-care therapy, including surgery, radiation, and chemotherapy, glioblastoma recurrence is almost inevitable and uniformly lethal. Activation of glioma-intrinsic Wnt/ß-catenin signaling is associated with a poor prognosis and the proliferation of glioma stem-like cells, leading to malignant transformation and tumor progression. Impressive results in a subset of cancers have been obtained using immunotherapies including anti-CTLA4, anti-PD-1, and anti-PD-L1 or chimeric antigen receptor (CAR) T cell therapies. However, the heterogeneity of tumors, low mutational burden, single antigen targeting, and associated antigen escape contribute to non-responsiveness and potential tumor recurrence despite these therapeutic efforts. In the current study, we determined the effects of the small molecule, highly specific Wnt/CBP (CREB Binding Protein)/ß-catenin antagonist ICG-001, on glioma tumor cells and the tumor microenvironment (TME)-including its effect on immune cell infiltration, blood vessel decompression, and metabolic changes. Methods: Using multiple glioma patient-derived xenografts cell lines and murine tumors (GL261, K-Luc), we demonstrated in vitro cytostatic effects and a switch from proliferation to differentiation after treatment with ICG-001. Results: In these glioma cell lines, we further demonstrated that ICG-001 downregulated the CBP/ß-catenin target gene Survivin/BIRC5-a hallmark of Wnt/CBP/ß-catenin inhibition. We found that in a syngeneic mouse model of glioma (K-luc), ICG-001 treatment enhanced tumor infiltration by CD3+ and CD8+ cells with increased expression of the vascular endothelial marker CD31 (PECAM-1). We also observed differential gene expression and induced immune cell infiltration in tumors pretreated with ICG-001 and then treated with CAR T cells as compared with single treatment groups or when ICG-001 treatment was administered after CAR T cell therapy. Discussion: We conclude that specific Wnt/CBP/ß-catenin antagonism results in pleotropic changes in the glioma TME, including glioma stem cell differentiation, modulation of the stroma, and immune cell activation and recruitment, thereby suggesting a possible role for enhancing immunotherapy in glioma patients.

Neuroprotective potential of intranasally delivered L-myc immortalized human neural stem cells in female rats after a controlled cortical impact injury.

Efficacious stem cell-based therapies for traumatic brain injury (TBI) depend on successful delivery, migration, and engraftment of stem cells to induce neuroprotection. L-myc expressing human neural stem cells (LMNSC008) demonstrate an inherent tropism to injury sites after intranasal (IN) administration. We hypothesize that IN delivered LMNSC008 cells migrate to primary and secondary injury sites and modulate biomarkers associated with neuroprotection and tissue regeneration. To test this hypothesis, immunocompetent adult female rats received either controlled cortical impact injury or sham surgery. LMNSC008 cells or a vehicle were administered IN on postoperative days 7, 9, 11, 13, 15, and 17. The distribution and migration of eGFP-expressing LMNSC008 cells were quantified over 1 mm-thick optically cleared (CLARITY) coronal brain sections from TBI and SHAM controls. NSC migration was observed along white matter tracts projecting toward the hippocampus and regions of TBI. ELISA and Nanostring assays revealed a shift in tissue gene expression in LMNSC008 treated rats relative to controls. LMNSC008 treatment reduced expression of genes and pathways involved in inflammatory response, microglial function, and various cytokines and receptors. Our proof-of-concept studies, although preliminary, support the rationale of using intranasal delivery of LMNSC008 cells for functional studies in preclinical models of TBI and provide support for potential translatability in TBI patients.

Model discovery approach enables non-invasive measurement of intra-tumoral fluid transport in dynamic MRI.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to non-invasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that it will contribute to the better understanding of cancer progression and therapeutic response.

Neuroprotective potential of intranasally delivered L-myc immortalized human neural stem cells in female rats after a controlled cortical impact injury.

Efficacious stem cell-based therapies for traumatic brain injury (TBI) depend on successful delivery, migration, and engraftment of stem cells to induce neuroprotection. L-myc expressing human neural stem cells (LMNSC008) demonstrate an inherent tropism to injury sites after intranasal (IN) administration. We hypothesize that IN delivered LMNSC008 cells migrate to primary and secondary injury sites and modulate biomarkers associated with neuroprotection and tissue regeneration. To test this, immunocompetent adult female rats received a controlled cortical impact injury (CCI) or sham surgery. LMNSC008 cells or a vehicle (VEH) were administered IN on postoperative days 7, 9, 11, 13, 15, and 17. The distribution and migration of eGFP-expressing LMNSC008 cells were quantified over 1 mm-thick optically cleared (CLARITY) coronal brain sections from TBI and SHAM controls. NSC migration was observed along white matter tracts projecting toward the hippocampus and regions of TBI. ELISA and Nanostring assays revealed a shift in tissue gene expression in LMNSC008 treated rats relative to controls. LMNSC008 treatment reduced expression of genes and pathways involved in inflammatory response, microglial function, and various cytokines and receptors. The data demonstrate a robust proof-of-concept for LMNSC008 therapy for TBI and provides a strong rationale for IN delivery for translation in TBI patients.

Small molecule targeting of transcription-replication conflict for selective chemotherapy.

Targeting transcription replication conflicts, a major source of endogenous DNA double-stranded breaks and genomic instability could have important anticancer therapeutic implications. Proliferating cell nuclear antigen (PCNA) is critical to DNA replication and repair processes. Through a rational drug design approach, we identified a small molecule PCNA inhibitor, AOH1996, which selectively kills cancer cells. AOH1996 enhances the interaction between PCNA and the largest subunit of RNA polymerase II, RPB1, and dissociates PCNA from actively transcribed chromatin regions, while inducing DNA double-stranded breaks in a transcription-dependent manner. Attenuation of RPB1 interaction with PCNA, by a point mutation in RPB1's PCNA-binding region, confers resistance to AOH1996. Orally administrable and metabolically stable, AOH1996 suppresses tumor growth as a monotherapy or as a combination treatment but causes no discernable side effects. Inhibitors of transcription replication conflict resolution may provide a new and unique therapeutic avenue for exploiting this cancer-selective vulnerability.

Data driven model discovery and interpretation for CAR T-cell killing using sparse identification and latent variables.

In the development of cell-based cancer therapies, quantitative mathematical models of cellular interactions are instrumental in understanding treatment efficacy. Efforts to validate and interpret mathematical models of cancer cell growth and death hinge first on proposing a precise mathematical model, then analyzing experimental data in the context of the chosen model. In this work, we present the first application of the sparse identification of non-linear dynamics (SINDy) algorithm to a real biological system in order discover cell-cell interaction dynamics in in vitro experimental data, using chimeric antigen receptor (CAR) T-cells and patient-derived glioblastoma cells. By combining the techniques of latent variable analysis and SINDy, we infer key aspects of the interaction dynamics of CAR T-cell populations and cancer. Importantly, we show how the model terms can be interpreted biologically in relation to different CAR T-cell functional responses, single or double CAR T-cell-cancer cell binding models, and density-dependent growth dynamics in either of the CAR T-cell or cancer cell populations. We show how this data-driven model-discovery based approach provides unique insight into CAR T-cell dynamics when compared to an established model-first approach. These results demonstrate the potential for SINDy to improve the implementation and efficacy of CAR T-cell therapy in the clinic through an improved understanding of CAR T-cell dynamics.

Structural and practical identifiability of contrast transport models for DCE-MRI.

Compartment models are widely used to quantify blood flow and transport in dynamic contrast-enhanced magnetic resonance imaging. These models analyze the time course of the contrast agent concentration, providing diagnostic and prognostic value for many biological systems. Thus, ensuring accuracy and repeatability of the model parameter estimation is a fundamental concern. In this work, we analyze the structural and practical identifiability of a class of nested compartment models pervasively used in analysis of MRI data. We combine artificial and real data to study the role of noise in model parameter estimation. We observe that although all the models are structurally identifiable, practical identifiability strongly depends on the data characteristics. We analyze the impact of increasing data noise on parameter identifiability and show how the latter can be recovered with increased data quality. To complete the analysis, we show that the results do not depend on specific tissue characteristics or the type of enhancement patterns of contrast agent signal.

Stem Cell-based therapies for COVID-19-related acute respiratory distress syndrome.

As the number of confirmed cases and resulting death toll of the COVID-19 pandemic continue to increase around the globe - especially with the emergence of new mutations of the SARS-CoV-2 virus in addition to the known alpha, beta, gamma, delta and omicron variants - tremendous efforts continue to be dedicated to the development of interventive therapeutics to mitigate infective symptoms or post-viral sequelae in individuals for which vaccines are not accessible, viable or effective in the prevention of illness. Many of these investigations aim to target the associated acute respiratory distress syndrome, or ARDS, which induces damage to lung epithelia and other physiologic systems and is associated with progression in severe cases. Recently, stem cell-based therapies have demonstrated preliminary efficacy against ARDS based on a number of preclinical and preliminary human safety studies, and based on promising outcomes are now being evaluated in phase II clinical trials for ARDS. A number of candidate stem cell therapies have been found to exhibit low immunogenicity, coupled with inherent tropism to injury sites. In recent studies, these have demonstrated the ability to modulate suppression of pro-inflammatory cytokine signals such as those characterizing COVID-19-associated ARDS. Present translational studies are aiming to optimize the safety, efficacy and delivery to fully validate stem cell-based strategies targeting COVID-19 associated ARDS for viable clinical application.

Mathematical modeling of therapeutic neural stem cell migration in mouse brain with and without brain tumors.

Neural stem cells (NSCs) offer a potential solution to treating brain tumors. This is because NSCs can circumvent the blood-brain barrier and migrate to areas of damage in the central nervous system, including tumors, stroke, and wound injuries. However, for successful clinical application of NSC treatment, a sufficient number of viable cells must reach the diseased or damaged area(s) in the brain, and evidence suggests that it may be affected by the paths the NSCs take through the brain, as well as the locations of tumors. To study the NSC migration in brain, we develop a mathematical model of therapeutic NSC migration towards brain tumor, that provides a low cost platform to investigate NSC treatment efficacy. Our model is an extension of the model developed in Rockne et al. (PLoS ONE 13, e0199967, 2018) that considers NSC migration in non-tumor bearing naive mouse brain. Here we modify the model in Rockne et al. in three ways: (i) we consider three-dimensional mouse brain geometry, (ii) we add chemotaxis to model the tumor-tropic nature of NSCs into tumor sites, and (iii) we model stochasticity of migration speed and chemosensitivity. The proposed model is used to study migration patterns of NSCs to sites of tumors for different injection strategies, in particular, intranasal and intracerebral delivery. We observe that intracerebral injection results in more NSCs arriving at the tumor site(s), but the relative fraction of NSCs depends on the location of injection relative to the target site(s). On the other hand, intranasal injection results in fewer NSCs at the tumor site, but yields a more even distribution of NSCs within and around the target tumor site(s).

Dose-dependent thresholds of dexamethasone destabilize CAR T-cell treatment efficacy.

Chimeric antigen receptor (CAR) T-cell therapy is potentially an effective targeted immunotherapy for glioblastoma, yet there is presently little known about the efficacy of CAR T-cell treatment when combined with the widely used anti-inflammatory and immunosuppressant glucocorticoid, dexamethasone. Here we present a mathematical model-based analysis of three patient-derived glioblastoma cell lines treated in vitro with CAR T-cells and dexamethasone. Advanced in vitro experimental cell killing assay technologies allow for highly resolved temporal dynamics of tumor cells treated with CAR T-cells and dexamethasone, making this a valuable model system for studying the rich dynamics of nonlinear biological processes with translational applications. We model the system as a nonautonomous, two-species predator-prey interaction of tumor cells and CAR T-cells, with explicit time-dependence in the clearance rate of dexamethasone. Using time as a bifurcation parameter, we show that (1) dexamethasone destabilizes coexistence equilibria between CAR T-cells and tumor cells in a dose-dependent manner and (2) as dexamethasone is cleared from the system, a stable coexistence equilibrium returns in the form of a Hopf bifurcation. With the model fit to experimental data, we demonstrate that high concentrations of dexamethasone antagonizes CAR T-cell efficacy by exhausting, or reducing the activity of CAR T-cells, and by promoting tumor cell growth. Finally, we identify a critical threshold in the ratio of CAR T-cell death to CAR T-cell proliferation rates that predicts eventual treatment success or failure that may be used to guide the dose and timing of CAR T-cell therapy in the presence of dexamethasone in patients.

Multiple Treatment Cycles of Neural Stem Cell Delivered Oncolytic Adenovirus for the Treatment of Glioblastoma.

Tumor tropic neural stem cells (NSCs) can improve the anti-tumor efficacy of oncovirotherapy agents by protecting them from rapid clearance by the immune system and delivering them to multiple distant tumor sites. We recently completed a first-in-human trial assessing the safety of a single intracerebral dose of NSC-delivered CRAd-Survivin-pk7 (NSC.CRAd-S-pk7) combined with radiation and chemotherapy in newly diagnosed high-grade glioma patients. The maximum feasible dose was determined to be 150 million NSC.CRAd-Sp-k7 (1.875 × 1011 viral particles). Higher doses were not assessed due to volume limitations for intracerebral administration and the inability to further concentrate the study agent. It is possible that therapeutic efficacy could be maximized by administering even higher doses. Here, we report IND-enabling studies in which an improvement in treatment efficacy is achieved in immunocompetent mice by administering multiple treatment cycles intracerebrally. The results imply that pre-existing immunity does not preclude therapeutic benefits attainable by administering multiple rounds of an oncolytic adenovirus directly into the brain.

Delivery strategies for cell-based therapies in the brain: overcoming multiple barriers.

Cell-based therapies to the brain are promising for the treatment of multiple brain disorders including neurodegeneration and cancers. In order to access the brain parenchyma, there are multiple physiological barriers that must be overcome depending on the route of delivery. Specifically, the blood-brain barrier has been a major difficulty in drug delivery for decades, and it still presents a challenge for the delivery of therapeutic cells. Other barriers, including the blood-cerebrospinal fluid barrier and lymphatic-brain barrier, are less explored, but may offer specific challenges or opportunities for therapeutic delivery. Here we discuss the barriers to the brain and the strategies currently in place to deliver cell-based therapies, including engineered T cells, dendritic cells, and stem cells, to treat diseases. With a particular focus on cancers, we also highlight the current ongoing clinical trials that use cell-based therapies to treat disease, many of which show promise at treating some of the deadliest illnesses.

Intranasally Administered L-Myc-Immortalized Human Neural Stem Cells Migrate to Primary and Distal Sites of Damage after Cortical Impact and Enhance Spatial Learning.

As the success of stem cell-based therapies is contingent on efficient cell delivery to damaged areas, neural stem cells (NSCs) have promising therapeutic potential because they inherently migrate to sites of central nervous system (CNS) damage. To explore the possibility of NSC-based therapy after traumatic brain injury (TBI), isoflurane-anesthetized adult male rats received a controlled cortical impact (CCI) of moderate severity (2.8 mm deformation at 4 m/s) or sham injury (i.e., no cortical impact). Beginning 1-week post-injury, the rats were immunosuppressed and 1 × 106 human NSCs (LM-NS008.GFP.fLuc) or vehicle (VEH) (2% human serum albumen) were administered intranasally (IN) on post-operative days 7, 9, 11, 13, 15, and 17. To evaluate the spatial distributions of the LM-NSC008 cells, half of the rats were euthanized on day 25, one day after completion of the cognitive task, and the other half were euthanized on day 46. 1 mm thick brain sections were optically cleared (CLARITY), and volumes were imaged by confocal microscopy. In addition, LM-NSC008 cell migration to the TBI site by immunohistochemistry for human-specific Nestin was observed at day 39. Acquisition of spatial learning was assessed in a well-established Morris water maze task on six successive days beginning on post-injury day 18. IN administration of LM-NSC008 cells after TBI (TBI + NSC) significantly facilitated spatial learning relative to TBI + VEH rats (p < 0.05) and had no effect on sham + NSC rats. Overall, these data indicate that IN-administered LM-NSC008 cells migrate to sites of TBI damage and that their presence correlates with cognitive improvement. Future studies will expand on these preliminary findings by evaluating other LM-NSC008 cell dosing paradigms and evaluating mechanisms by which LM-NSC008 cells contribute to cognitive recovery.

Repeatability of tumor perfusion kinetics from dynamic contrast-enhanced MRI in glioblastoma.

BACKGROUND: Dynamic contrast-enhanced MRI (DCE-MRI) parameters have been shown to be biomarkers for treatment response in glioblastoma (GBM). However, variations in analysis and measurement methodology complicate determination of biological changes measured via DCE. The aim of this study is to quantify DCE-MRI variations attributable to analysis methodology and image quality in GBM patients. METHODS: The Extended Tofts model (eTM) and Leaky Tracer Kinetic Model (LTKM), with manually and automatically segmented vascular input functions (VIFs), were used to calculate perfusion kinetic parameters from 29 GBM patients with double-baseline DCE-MRI data. DCE-MRI images were acquired 2-5 days apart with no change in treatment. Repeatability of kinetic parameters was quantified with Bland-Altman and percent repeatability coefficient (%RC) analysis. RESULTS: The perfusion parameter with the least RC was the plasma volume fraction (v p ), with a %RC of 53%. The extra-cellular extra-vascular volume fraction (v e ) %RC was 82% and 81%, for extended Tofts-Kety Model (eTM) and LTKM respectively. The %RC of the volume transfer rate constant (K trans ) was 72% for the eTM, and 82% for the LTKM, respectively. Using an automatic VIF resulted in smaller %RCs for all model parameters, as compared to manual VIF. CONCLUSIONS: As much as 72% change in K trans (eTM, autoVIF) can be attributable to non-biological changes in the 2-5 days between double-baseline imaging. Poor K trans repeatability may result from inferior temporal resolution and short image acquisition time. This variation suggests DCE-MRI repeatability studies should be performed institutionally, using an automatic VIF method and following quantitative imaging biomarkers alliance guidelines.

Chlorotoxin-directed CAR T cells for specific and effective targeting of glioblastoma.

Although chimeric antigen receptor (CAR) T cells have demonstrated signs of antitumor activity against glioblastoma (GBM), tumor heterogeneity remains a critical challenge. To achieve broader and more effective GBM targeting, we developed a peptide-bearing CAR exploiting the GBM-binding potential of chlorotoxin (CLTX). We find that CLTX peptide binds a great proportion of tumors and constituent tumor cells. CAR T cells using CLTX as the targeting domain (CLTX-CAR T cells) mediate potent anti-GBM activity and efficiently target tumors lacking expression of other GBM-associated antigens. Treatment with CLTX-CAR T cells resulted in tumor regression in orthotopic xenograft GBM tumor models. CLTX-CAR T cells do not exhibit observable off-target effector activity against normal cells or after adoptive transfer into mice. Effective targeting by CLTX-CAR T cells requires cell surface expression of matrix metalloproteinase-2. Our results pioneer a peptide toxin in CAR design, expanding the repertoire of tumor-selective CAR T cells with the potential to reduce antigen escape.

Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data.

Chimeric antigen receptor (CAR) T-cell therapy has shown promise in the treatment of haematological cancers and is currently being investigated for solid tumours, including high-grade glioma brain tumours. There is a desperate need to quantitatively study the factors that contribute to the efficacy of CAR T-cell therapy in solid tumours. In this work, we use a mathematical model of predator-prey dynamics to explore the kinetics of CAR T-cell killing in glioma: the Chimeric Antigen Receptor T-cell treatment Response in GliOma (CARRGO) model. The model includes rates of cancer cell proliferation, CAR T-cell killing, proliferation, exhaustion, and persistence. We use patient-derived and engineered cancer cell lines with an in vitro real-time cell analyser to parametrize the CARRGO model. We observe that CAR T-cell dose correlates inversely with the killing rate and correlates directly with the net rate of proliferation and exhaustion. This suggests that at a lower dose of CAR T-cells, individual T-cells kill more cancer cells but become more exhausted when compared with higher doses. Furthermore, the exhaustion rate was observed to increase significantly with tumour growth rate and was dependent on level of antigen expression. The CARRGO model highlights nonlinear dynamics involved in CAR T-cell therapy and provides novel insights into the kinetics of CAR T-cell killing. The model suggests that CAR T-cell treatment may be tailored to individual tumour characteristics including tumour growth rate and antigen level to maximize therapeutic benefit.

Quantitative Evaluation of Intraventricular Delivery of Therapeutic Neural Stem Cells to Orthotopic Glioma.

Neural stem cells (NSCs) are inherently tumor-tropic, which allows them to migrate through normal tissue and selectively localize to invasive tumor sites in the brain. We have engineered a clonal, immortalized allogeneic NSC line (HB1.F3.CD21; CD-NSCs) that maintains its stem-like properties, a normal karyotype and is HLA Class II negative. It is genetically and functionally stable over time and multiple passages, and has demonstrated safety in phase I glioma trials. These properties enable the production of an "off-the-shelf" therapy that can be readily available for patient treatment. There are multiple factors contributing to stem cell tumor-tropism, and much remains to be elucidated. The route of NSC delivery and the distribution of NSCs at tumor sites are key factors in the development of effective cell-based therapies. Stem cells can be engineered to deliver and/or produce many different therapeutic agents, including prodrug activating enzymes (which locally convert systemically administered prodrugs to active chemotherapeutic agents); oncolytic viruses; tumor-targeted antibodies; therapeutic nanoparticles; and extracellular vesicles that contain therapeutic oligonucleotides. By targeting these therapeutics selectively to tumor foci, we aim to minimize toxicity to normal tissues and maximize therapeutic benefits. In this manuscript, we demonstrate that NSCs administered via intracerebral/ventricular (IVEN) routes can migrate efficiently toward single or multiple tumor foci. IVEN delivery will enable repeat administrations for patients through an Ommaya reservoir, potentially resulting in improved therapeutic outcomes. In our preclinical studies using various glioma lines, we have quantified NSC migration and distribution in mouse brains and have found robust migration of our clinically relevant HB1.F3.CD21 NSC line toward invasive tumor foci, irrespective of their origin. These results establish proof-of-concept and demonstrate the potential of developing a multitude of therapeutic options using modified NSCs.

Long-term stability and computational analysis of migration patterns of L-MYC immortalized neural stem cells in the brain.

BACKGROUND: Preclinical studies indicate that neural stem cells (NSCs) can limit or reverse central nervous system (CNS) damage through delivery of therapeutic agents for cell regeneration. Clinical translation of cell-based therapies raises concerns about long-term stability, differentiation and fate, and absence of tumorigenicity of these cells, as well as manufacturing time required to produce therapeutic cells in quantities sufficient for clinical use. Allogeneic NSC lines are in growing demand due to challenges inherent in using autologous stem cells, including production costs that limit availability to patients. METHODS/PRINCIPAL FINDINGS: We demonstrate the long-term stability of L-MYC immortalized human NSCs (LM-NSC008) cells in vivo, including engraftment, migration, and absence of tumorigenicity in mouse brains for up to nine months. We also examined the distributions of engrafted LM-NSC008 cells within brain, and present computational techniques to analyze NSC migration characteristics in relation to intrinsic brain structures. CONCLUSIONS/SIGNIFICANCE: This computational analysis of NSC distributions following implantation provides proof-of-concept for the development of computational models that can be used clinically to predict NSC migration paths in patients. Previously, models of preferential migration of malignant tumor cells along white matter tracts have been used to predict their final distributions. We suggest that quantitative measures of tissue orientation and white matter tracts determined from MR images can be used in a diffusion tensor imaging tractography-like approach to describe the most likely migration routes and final distributions of NSCs administered in a clinical setting. Such a model could be very useful in choosing the optimal anatomical locations for NSC administration to patients to achieve maximum therapeutic effects.