Biology subjects

Curtin, L.

Publications and source records attributed to Curtin, L..

11 recordsLinked to original sources

bioRxiv2024

Virtual Clinical Trials of BMP4 Differentiation Therapy: Digital Twins to Aid Glioblastoma Trial Design

Glioma stem cells (GSCs) are considered a major driver of glioblastoma (GBM) progression and are highly resistant to standard cytotoxic treatments. BMP4 has been shown to drive differentiation of GSCs, increase sensitivity to radiotherapy, slow growth and increase survival times in animal models. To assess the potential of BMP4 as a differentiation therapy, we develop a mathematical model that describes the growth of a GBM tumor via a hierarchy of GSCs, progenitor cells and terminally differentiated cells. We parametrize our model using experimental data from twelve patient-derived GSC lines, on which we measured response to radiotherapy and population growth with and without exposure to BMP4. Cell lines were typically more sensitive to radiotherapy after two days of BMP4 treatment but population growth can either increase or decrease after seven days of exposure to BMP4. To identify key parameters that drive successful treatment we perform global sensitivity analysis which identifies key parameters for BMP4 efficacy including proliferation rate and self-renewal sensitivity of GSCs. We then compare two treatment schedules: a single dose of BMP4 at resection and continuous delivery of BMP4 from resection till the end of radiotherapy. Due to the short half-life of BMP4 and its synergy with radiotherapy, continuous delivery of BMP4 during radiotherapy is more effective than a single dose prior to radiotherapy. We then perform a series of virtual clinical trials, stratified by tumor proliferation rate and GSC self-renewal sensitivity, which allows us to estimate the probability of observing a successful early-phase clinical trial for various virtual patient cohorts. We find that trials that selected the subset of patients with more proliferative GBMs were more likely to lead to significant improvements in survival. SignificanceTargeting glioma stem cells with BMP4 provides a novel opportunity to shift the complex cellular ecosystem of gliomas to enhance treatment efficacy. Mathematical modelling can facilitate optimal patient tumor feature selection when designing successful clinical trials.

cancer biology↗

bioRxiv2024

Cerebral Microvascular Density, Permeability of the Blood-Brain Barrier, and Neuroinflammatory Responses Indicate Early Aging Characteristics in a Marfan Syndrome Mouse Model

Marfan Syndrome (MFS) is a connective tissue disorder due to mutations in fibrillin-1 (Fbn1), where a Fbn1 missense mutation (Fbn1C1039G/+) can result in systemic increases in the bioavailability and signaling of transforming growth factor-{beta} (TGF-{beta}). In a well-established mouse model of MFS (Fbn1C1041G/+), pre-mature aging of the aortic wall and the progression of aortic root aneurysm are observed by 6-months-of-age. TGF-{beta} signaling has been implicated in cerebrovascular dysfunction, loss of blood-brain barrier (BBB) integrity, and age-related neuroinflammation. We have reported that pre-mature vascular aging in MFS mice could extend to cerebrovasculature, where peak blood flow velocity in the posterior cerebral artery (PCA) of 6-month-old (6M) MFS mice was reduced, similarly to 12-month-old (12M) control mice. Case studies of MFS patients have documented neurovascular manifestations, including intracranial aneurysms, stroke, arterial tortuosity, as well as headaches and migraines, with reported incidence of pain and chronic fatigue. Despite these significant clinical observations, investigation into cerebrovascular dysfunction and neuropathology in MFS remains limited. Using 6M-control (C57BL/6) and 6M-MFS (Fbn1C1041G/+) and healthy 12M-control male and female mice, we test the hypothesis that abnormal Fbn1 protein expression is associated with altered cerebral microvascular density, BBB permeability, and neuroinflammation in the PCA-perfused hippocampus, all indicative of a pre-mature aging brain phenotype. Using Glut1 staining, 6M-MFS mice and 12M-CTRL similarly present decreased microvascular density in the dentate gyrus (DG), cornu ammonis 1 (CA1), and cornu ammonis 3 (CA3) regions of the hippocampus. 6M-MFS mice exhibit increased BBB permeability in the DG, CA1, and CA3 as evident by Immunoglobulin G (IgG) staining, which was more comparable to 12M-CTRL mice. 6M-MFS mice show a higher number of microglia in the hippocampus compared to age-matched control mice, a pattern resembling that of 12M-CTRL mice. This study represents the first known investigation into neuropathology in a mouse model of MFS and indicates that the pathophysiology underlying MFS leads to a systemic pre-mature aging phenotype. This study is crucial for identifying and understanding MFS-associated neurovascular and neurological abnormalities, underscoring the need for research aimed at improving the quality of life and managing pre-mature aging symptoms in MFS and related connective tissue disorders.

neuroscience↗

bioRxiv2022

Glioblastoma states are defined by cohabitating cellular populations with progression-, imaging- and sex-distinct patterns

Background: Magnetic Resonance Imaging (MRI) is the mainstay for neurosurgical oncology but not for informing us about glioma biology. An obstacle to developing MR-based glioma biomarkers is the absence of rigorous correlation between MRI features and glioma biology as assessed in multi-regional biopsies, within and across patients. Methods: We directly addressed this obstacle by collating a unique cohort of 202 MRI-localized biopsies from 58 patients. We define a low-dimensional transcriptional pseudotime continuum along which heterogeneous high-grade glioma (HGG) samples organize both within and across patients. Results: We observe three polarized transcriptional tissue states: infiltrated brain, immune/inflammatory, and proliferative associated with patterns of cohabitation of cellular subpopulations. The states and deconvolved populations show correlation with enhancement status on T1Gd MRI. Moreover, discrete MRI habitats, regions sharing common imaging features, defined as combinations of high or low signal intensity across multiparametric MRI revealed 14 MRI habitats. We order the MRI habitats according to the average pseudotime on the transcriptional continuum. We find that MRI habitats with low pseudotime (associated with early tumor development and diffusely invaded brain tissue) localized at the periphery of the tumor whilst high pseudotime either proliferative or immune/inflammatory states were towards the core of the lesion. We find that composition of MRI habitats is impacted by MGMT status. Conclusion: This suggests that ongoing aggregation of MRI-localized biopsies may augment our projection of biology onto MRI habitats to support the noninvasive identification of cellular ecologies within and across each patient's tumor.

cancer biology↗

bioRxiv2021

Partial loss of succinate dehydrogenase reduces high red cell distribution width and promotes healthy survival in chronically hypoxic mice

Increased red cell distribution width (RDW), which measures erythrocyte size variability (anisocytosis), has been linked to early mortality in many diseases and normal aged population through unknown mechanisms. Hypoxia has been proposed to increase both RDW and mortality. However, experimental evidence, especially in animal models, is lacking. Here, we show that chronic hypobaric hypoxia (~10% O2) increases erythrocyte numbers, hemoglobin and RDW, while reducing longevity in male mice. Compound heterozygous knockout (chKO) mutations in succinate dehydrogenase (Sdh; mitochondrial complex II) genes Sdhb, Sdhc and Sdhd reduce high RDW and immature reticulocyte fraction, and increase healthy lifespan in chronic hypoxia. Hemoglobin and erythrocyte numbers in hypoxia do not show statistically significant differences between Sdh chKO and WT mice. These results identify a mitochondrial mechanism regulating both RDW and organismal adaptation to chronic hypoxia, and suggest SDH as a potential therapeutic target to reduce high RDW-associated clinical mortality.

physiology↗

bioRxiv2021

Morphological Metrics of Magnetic Resonance Imaging of Glioblastoma as Biomarkers of Prognosis

Morphological characteristics have been linked to outcomes across a variety of cancers. Lacunarity is a quantitative morphological measure of how shapes fill space while fractal dimension is a morphological measure of the complexity of pixel arrangement. Glioblastoma is the most aggressive primary brain tumor with a short expected survival given the current standard-of-care treatment. Due to the sensitive location of the tumor, there is a heavy reliance on imaging to assess the state of the disease in the clinic. In this project, we computed lacunarity and fractal dimension values for glioblastoma-induced abnormalities on gadolinium-enhanced T1-weighted magnetic resonance imaging (T1Gd MRI) as well as T2-weighted (T2) and fluid-attenuated inversion recovery (FLAIR) MRIs. In our patient cohort (n=402), we aim to connect these morphological metrics calculated on pretreatment MRI with the survival of patients with GBM. We calculated lacunarity and fractal dimension across all MRI slices on necrotic regions (n=390) and abnormalities on T1Gd MRI (n=402), as well as on enhancing abnormalities present on T2/FLAIR MRI (n=257). We also explored the relationship between these metrics and age at diagnosis, as well as abnormality volume. We found statistically significant relationships to outcome across all three imaging subtypes, with the shape of T2/FLAIR abnormalities showing the strongest relationship with overall survival. The link between morphological and survival metrics could be driven by underlying biological phenomena, tumor location or microenvironmental factors that should be further explored.

bioinformatics↗

bioRxiv2020

Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations

Glioblastomas (GBMs) are the most aggressive primary brain tumours and have no known cure. Each individual tumour comprises multiple sub-populations of genetically-distinct cells that may respond differently to targeted therapies and may contribute to disappointing clinical trial results. Image-localized biopsy techniques allow multiple biopsies to be taken during surgery and provide information that identifies regions where particular sub-populations occur within an individual GBM, thus providing insight into their regional genetic variability. These sub-populations may also interact with one another through a competitive or cooperative nature; it is important to ascertain the nature of these interactions, as they may have implications for responses to targeted therapies. We combine genetic information from biopsies with a mechanistic model of interacting GBM sub-populations to characterise the nature of interactions between two commonly occurring GBM sub-populations, those with EGFR and PDGFRA genes amplified. We study population levels found across image-localized biopsy data from a cohort of 25 patients and compare this to model outputs under competitive, cooperative and neutral interaction assumptions. We explore other factors affecting the observed simulated sub-populations, such as selection advantages and phylogenetic ordering of mutations, which may also contribute to the levels of EGFR and PDGFRA amplified populations observed in biopsy data.

cancer biology↗

bioRxiv2020

A Mechanistic Investigation into Ischemia-Driven Distal Recurrence of Glioblastoma

Glioblastoma (GBM) is the most aggressive primary brain tumor with a short median survival. Tumor recurrence is a clinical expectation of this disease and usually occurs along the resection cavity wall. However, previous clinical observations have suggested that in cases of ischemia following surgery, tumors are more likely to recur distally. Through the use of a previously established mechanistic model of GBM, the Proliferation Invasion Hypoxia Necrosis Angiogenesis (PIHNA) model, we explore the phenotypic drivers of this observed behavior. We have extended the PIHNA model to include a new nutrient-based vascular efficiency term that encodes the ability of local vasculature to provide nutrients to the simulated tumor. The extended model suggests sensitivity to a hypoxic microenvironment and the inherent migration and proliferation rates of the tumor cells are key factors that drive distal recurrence.

cancer biology↗

bioRxiv2019

Investigating the Role of Hypoxia-Induced Migration in Glioblastoma Growth Rates

We analyze the wave-speed of the Proliferation Invasion Hypoxia Necrosis Angiogenesis (PIHNA) model that was previously created and applied to simulate the growth and spread of glioblastoma (GBM), a particularly aggressive primary brain tumor. We extend the PIHNA model by allowing for different hypoxic and normoxic cell migration rates and study the impact of these differences on the wave-speed dynamics. Through this analysis, we find key variables that drive the outward growth of the simulated GBM. We find a minimum tumor wave-speed for the model; this depends on the migration and proliferation rates of the normoxic cells and is achieved under certain conditions on the migration rates of the normoxic and hypoxic cells. If the hypoxic cell migration rate is greater than the normoxic cell migration rate above a threshold, the wave-speed increases above the predicted minimum. This increase in wave-speed is explored through an eigenvalue and eigenvector analysis of the linearized PIHNA model, which yields an expression for this threshold. The PIHNA model suggests that an inherently faster-diffusing hypoxic cell population can drive the outward growth of a GBM as a whole, and that this effect is more prominent for faster proliferating tumors that recover relatively slowly from a hypoxic phenotype.

cancer biology↗

bioRxiv2019

Modeling the Role of Hypoxia in Glioblastoma Growth and Recurrence Patterns

A typical feature of glioblastoma (GBM) growth is local recurrence after surgery. However, some GBMs recur distally. It has been noted that GBM patients with perioperative ischemia are more likely to have distal recurrence and that GBM cells migrate faster under hypoxic conditions. We apply the Proliferation Invasion Hypoxia Necrosis Angiogenesis (PIHNA) model to examine the effect of faster hypoxic cell migration on simulated GBM growth. Results suggest that a highly migratory hypoxic cell population drives the growth of the whole tumor and leads to distant recurrence, as do higher normoxic tumor cell migration and low cellular proliferation rates.

cancer biology↗

bioRxiv2018

Connecting Patterns of Tumor Growth with Sex Differences in Extreme Survivorship for Primary Glioblastoma Patients

BackgroundSex is recognized as a significant determinant of outcome among glioblastoma patients, but the relative prognostic importance of glioblastoma features has not been thoroughly explored for sex differences.\n\nMethodsCombining multi-modal MR images, biomathematical models, and patient clinical information, this investigation assesses which pretreatment variables have a sex-specific impact on the survival of glioblastoma patients. Pretreatment MR images of 494 glioblastoma patients (299 males and 195 females) were segmented to quantify tumor volumes. Cox proportional hazard (CPH) models and Students t-tests were used to assess which variables were associated with survival outcomes.\n\nResultsAmong males, tumor (T1Gd) radius was a predictor of overall survival (HR=1.027, p=0.044). Among females, higher tumor cell net invasion rate was a significant detriment to overall survival (HR=1.011, p<0.001). Female extreme survivors had significantly smaller tumors (T1Gd) (p=0.010 t-test), but tumor size was not correlated with female overall survival (p=0.955 CPH). Both male and female extreme survivors had significantly lower tumor cell net proliferation rates than other patients (M p=0.004, F p=0.001, t-test). Additionally, extent of resection, tumor laterality, and IDH1 mutation status were also found to have sex-specific effects on overall survival.\n\nConclusionDespite similar distributions of the MR imaging parameters between males and females, there was a sex-specific difference in how these parameters related to outcomes, which emphasizes the importance of considering sex as a biological factor when determining patient prognosis and treatment approach.

cancer biology↗

bioRxiv2017

Combining radiomics and mathematical modeling to elucidate mechanisms of resistance to immune checkpoint blockade in non-small cell lung cancer

Immune therapies have shown promise in a number of cancers, and clinical trials using the anti-PD-L1/PD-1 checkpoint inhibitor in lung cancer have been successful for a number of patients. However, some patients either do not respond to the treatment or have cancer recurrence after an initial response. It is not clear which patients might fall into these categories or what mechanisms are responsible for treatment failure. To explore the different underlying biological mechanisms of resistance, we created a spatially explicit mathematical model with a modular framework. This construction enables different potential mechanisms to be turned on and off in order to adjust specific tumor and tissue interactions to match a specific patient's disease. In parallel, we developed a software suite to identify significant computed tomography (CT) imaging features correlated with outcome using data from an anti-PDL-1 checkpoint inhibitor clinical trial for lung cancer and a tool that extracts these features from both patient CT images and \"virtual CT\" images created from the cellular density profile of the model. The combination of our two toolkits provides a framework that feeds patient data through an iterative pipeline to identify predictive imaging features associated with outcome, whilst at the same time proposing hypotheses about the underlying resistance mechanisms.

cancer biology↗