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Critical illness, such as severe COVID-19, is heterogenous in presentation and treatment response. However, it remains possible that clinical course may be influenced by dynamic and/or random events such that similar patients subject to similar injuries may yet follow different trajectories. We deployed a mechanistic mathematical model of COVID-19 to determine the range of possible clinical courses after SARS-CoV-2 infection, which may follow from specific changes in viral properties, immune properties, treatment modality and random external factors such as initial viral load. We find that treatment efficacy and baseline patient or viral features are not the sole determinant of outcome. We found patients with enhanced innate or adaptive immune responses can experience poor viral control, resolution of infection or non-infectious inflammatory injury depending on treatment efficacy and initial viral load. Hypoxemia may result from poor viral control or ongoing inflammation despite effective viral control. Adaptive immune responses may be inhibited by very early effective therapy, resulting in viral load rebound after cessation of therapy. Our model suggests individual disease course may be influenced by the interaction between external and patient-intrinsic factors. These data have implications for the reproducibility of clinical trial cohorts and timing of optimal treatment. [ABSTRACT FROM AUTHOR]

Effective anti‐cancer immune responses require activation of one or more naïve T cells. If the correct naïve T cell encounters its cognate antigen presented by an antigen presenting cell, then the T cell can activate and proliferate. Here, mathematical modeling is used to explore the possibility that immune activation in lymph nodes is a rate‐limiting step in anti‐cancer immunity and can affect response rates to immune checkpoint therapy. The model provides a mechanistic framework for optimizing cancer immunotherapy and developing testable solutions to unleash anti‐tumor immune responses for more patients with cancer. The results show that antigen production rate and trafficking of naïve T cells into the lymph nodes are key parameters and that treatments designed to enhance tumor antigen production can improve immune checkpoint therapies. The model underscores the potential of radiation therapy in augmenting tumor immunogenicity and neoantigen production for improved ICB therapy, while emphasizing the need for careful consideration in cases where antigen levels are already sufficient to avoid compromising the immune response. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) is a serious health challenge, causing more deaths worldwide than cancer. The vascular endothelium, which forms the inner lining of blood vessels, plays a central role in maintaining vascular integrity and homeostasis and is in direct contact with the blood flow. Research over the past century has shown that mechanical perturbations of the vascular wall contribute to the formation and progression of atherosclerosis. While the straight part of the artery is exposed to sustained laminar flow and physiological high shear stress, flow near branch points or in curved vessels can exhibit 'disturbed' flow. Clinical studies as well as carefully controlled in vitro analyses have confirmed that these regions of disturbed flow, which can include low shear stress, recirculation, oscillation, or lateral flow, are preferential sites of atherosclerotic lesion formation. Because of their critical role in blood flow homeostasis, vascular endothelial cells (ECs) have mechanosensory mechanisms that allow them to react rapidly to changes in mechanical forces, and to execute context-specific adaptive responses to modulate EC functions. This review summarizes the current understanding of endothelial mechanobiology, which can guide the identification of new therapeutic targets to slow or reverse the progression of atherosclerosis. [ABSTRACT FROM AUTHOR]

Implementation of effective cancer treatment strategies requires consideration of how the spatiotemporal heterogeneities within the tumor microenvironment (TME) influence tumor progression and treatment response. Here, we developed a multi-scale three-dimensional mathematical model of the TME to simulate tumor growth and angiogenesis and then employed the model to evaluate an array of single and combination therapy approaches. Treatments included maximum tolerated dose or metronomic (i.e., frequent low doses) scheduling of anti-cancer drugs combined with anti-angiogenic therapy. The results show that metronomic therapy normalizes the tumor vasculature to improve drug delivery, modulates cancer metabolism, decreases interstitial fluid pressure and decreases cancer cell invasion. Further, we find that combining an anti-cancer drug with anti-angiogenic treatment enhances tumor killing and reduces drug accumulation in normal tissues. We also show that combined anti-angiogenic and anti-cancer drugs can decrease cancer invasiveness and normalize the cancer metabolic microenvironment leading to reduced hypoxia and hypoglycemia. Our model simulations suggest that vessel normalization combined with metronomic cytotoxic therapy has beneficial effects by enhancing tumor killing and limiting normal tissue toxicity. Author summary: Effective treatment of solid tumors with injected drugs requires that sufficient exposure of cancer cells to the cytotoxic drugs. However, non-uniform and poorly functioning blood vessels make this difficult. The amount of drug that reaches a given cancer cells depends on many factors, including the drug chemistry, its lifetime in the blood circulation, its ability to cross the blood vessel wall and enter the tissue, and the schedule of the injections. We present a mathematical model of tumor growth, angiogenesis, metabolism and drug transport that examines how these processes affect the response to treatment. We find that low dose, high frequency (metronomic) therapy normalizes the tumor vasculature to improve drug delivery and that combining an anti-cancer drug with a drug that specifically enhances vascular function increases tumor killing and reduces drug accumulation in normal tissues. Our model simulations suggest that vessel normalization combined with metronomic cytotoxic therapy has beneficial effects by enhancing tumor killing and limiting normal tissue toxicity. [ABSTRACT FROM AUTHOR]

Simple Summary: We examined the expression of SDF1α and its cognate receptor CXCR4 in human prostate cancer (PCa) lesions and the impact of CXCR4 inhibition alone and in combination with single-dose irradiation in orthotopic PCa models in mice. Both SDF1α and CXCR4 were highly expressed in primary and bone metastatic human PCa samples. Inhibiting CXCR4 activity in PCa cells abrogated SDF1α-induced invasion but did not sensitize them to irradiation in vitro. In orthotopic primary and bone metastatic PCa models, treatment with the CXCR4 antagonist AMD3100 alone was ineffective, but when added to radiotherapy, it significantly inhibited metastatic tumor growth. The mechanisms of AMD3100 included normalization of bone metastatic PCa vasculature. These results support testing SDF1α/CXCR4 inhibitors with radiotherapy in metastatic PCa patients. Radiotherapy (RT) is a standard treatment for patients with advanced prostate cancer (PCa). Previous preclinical studies showed that SDF1α/CXCR4 axis could mediate PCa metastasis (most often to the bones) and cancer resistance to RT. We found high levels of expression for both SDF1α and its receptor CXCR4 in primary and metastatic PCa tissue samples. In vitro analyses using PCa cells revealed an important role of CXCR4 in cell invasion but not radiotolerance. Pharmacologic inhibition of CXCR4 using AMD3100 showed no efficacy in orthotopic primary and bone metastatic PCa models. However, when combined with RT, AMD3100 potentiated the effect of local single-dose RT (12 Gy) in both models. Moreover, CXCR4 inhibition also reduced lymph node metastasis from primary PCa. Notably, CXCR4 inhibition promoted the normalization of bone metastatic PCa vasculature and reduced tissue hypoxia. In conclusion, the SDF1α/CXCR4 axis is a potential therapeutic target in metastatic PCa patients treated with RT. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 vaccines are effective at limiting disease severity, but effectiveness is lower among patients with cancer or immunosuppression. Effectiveness wanes with time and varies by vaccine type. Moreover, previously prescribed vaccines were based on the ancestral SARS-CoV-2 spike-protein that emerging variants may evade. Here, we describe a mechanistic mathematical model for vaccination-induced immunity. We validate it with available clinical data and use it to simulate the effectiveness of vaccines against viral variants with lower antigenicity, increased virulence, or enhanced cell binding for various vaccine platforms. The analysis includes the omicron variant as well as hypothetical future variants with even greater immune evasion of vaccine-induced antibodies and addresses the potential benefits of the new bivalent vaccines. We further account for concurrent cancer or underlying immunosuppression. The model confirms enhanced immunogenicity following booster vaccination in immunosuppressed patients but predicts ongoing booster requirements for these individuals to maintain protection. We further studied the impact of variants on immunosuppressed individuals as a function of the interval between multiple booster doses. Our model suggests possible strategies for future vaccinations and suggests tailored strategies for high-risk groups. [ABSTRACT FROM AUTHOR]