Computational modeling reveals key factors driving treatment-free remission in chronic myeloid leukemia patients.

Patients with chronic myeloid leukemia (CML) who receive tyrosine kinase inhibitors (TKIs) have been known to achieve treatment-free remission (TFR) upon discontinuing treatment. However, the underlying mechanisms of this phenomenon remain incompletely understood. This study aims to elucidate the mechanism of TFR in CML patients, focusing on the feedback interaction between leukemia stem cells and the bone marrow microenvironment. We have developed a mathematical model to explore the interplay between leukemia stem cells and the bone marrow microenvironment, allowing for the simulation of CML progression dynamics. Our proposed model reveals a dichotomous response following TKI discontinuation, with two distinct patient groups emerging: one prone to early molecular relapse and the other capable of achieving long-term TFR after treatment cessation. This finding aligns with clinical observations and underscores the essential role of feedback interaction between leukemic cells and the tumor microenvironment in sustaining TFR. Notably, we have shown that the ratio of leukemia cells in peripheral blood (PBLC) and the tumor microenvironment (TME) index can be a valuable predictive tool for identifying patients likely to achieve TFR after discontinuing treatment. This study provides fresh insights into the mechanism of TFR in CML patients and underscores the significance of microenvironmental control in achieving TFR.

Evolutionary analysis of replicator dynamics about anti-cancer combination therapy.

The emergence and growth of drug-resistant cancer cell subpopulations during anti-cancer treatment is a major challenge for cancer therapies. Combination therapies are usually applied for overcoming drug resistance. In the present paper, we explored the evolution outcome of tumor cell populations under different combination schedules of chemotherapy and p53 vaccine, by construction of replicator dynamical model for sensitive cells, chemotherapy-resistant cells and p53 vaccine-resistant cells. The local asymptotic stability analysis of the evolutionary stable points revealed that cancer population could evolve to the population with single subpopulation, or coexistence of sensitive cells and p53 vaccine-resistant cells, or coexistence of chemotherapy-resistant cells and p53 vaccine-resistant cells under different monotherapy or combination schedules. The design of adaptive therapy schedules that maintain the subpopulations under control is also demonstrated by sequential and periodic application of combination treatment strategies based on the evolutionary velocity and evolutionary absorbing regions. Applying a new replicator dynamical model, we further explored the supportive effects of sensitive cancer cells on targeted therapy-resistant cells revealed in mice experiments. It was shown that the supportive effects of sensitive cells could drive the evolution of cell population from sensitive cells to coexistence of sensitive cells and one type of targeted therapy-resistant cells.

Modeling tumour heterogeneity of PD-L1 expression in tumour progression and adaptive therapy.

Although PD-1/PD-L1 inhibitors show potent and durable anti-tumour effects in some refractory tumours, the response rate in overall patients is unsatisfactory, which in part due to the inherent heterogeneity of PD-L1. In order to establish an approach for predicting and estimating the dynamic alternation of PD-L1 heterogeneity during cancer progression and treatment, this study establishes a comprehensive modelling and computational framework based on a mathematical model of cancer cell evolution in the tumour-immune microenvironment, and in combination with epigenetic data and overall survival data of clinical patients from The Cancer Genome Atlas. Through PD-L1 heterogeneous virtual patients obtained by the computational framework, we explore the adaptive therapy of administering anti-PD-L1 according to the dynamic of PD-L1 state among cancer cells. Our results show that in contrast to the continuous maximum tolerated dose treatment, adaptive therapy is more effective for PD-L1 positive patients, in that it prolongs the survival of patients by administration of drugs at lower dosage.

Predicting the HIV/AIDS epidemic and measuring the effect of AIDS Conquering Project in Guangxi Zhuang Autonomous Region.

To control the HIV/AIDS epidemics in Guangxi Zhuang Autonomous Region in China, Guangxi government launched the 5-year Guangxi AIDS Conquering Project (GACP, Phase I: 2010-2014, Phase II: 2015-2020). In the project, three measures are implemented, such as great improvements of the coverage of HIV/AIDS education, promotion of HIV voluntary counseling and testing, and enhancement of antiretroviral treatment. In this paper, we explore the effects of the three measures of GACP by construction of a Susceptible-Infected-Diagnosed-Treated population compartments model and via evaluation of the basic reproduction number derived from the model. A computational framework is developed for estimating the model parameters based on the HIV surveillance data, with application of the Markov-Chain Monte-Carlo method and Nonlinear Least Squares method. By estimating the new infections and evaluating the basic reproduction number, we find that the implementation of the three measures of GACP has a significant effect on controlling the rise of HIV/AIDS cases and the epidemic trend. Compared with HIV voluntary counseling and testing, strengthening HIV/AIDS education and expanding the coverage of antiretroviral treatment show a greater impact on HIV/AIDS epidemic control, which provides a reference project for other provinces with a similar epidemic situation in Guangxi Zhuang Autonomous Region. At the same time, our research fills the current research gap for the evaluation of large-scale AIDS prevention and control projects in developing areas.

Modeling the effect of gut microbiome on therapeutic efficacy of immune checkpoint inhibitors against cancer.

Immune checkpoint inhibitors have been shown to be highly successful against some solid metastatic malignancies, but only for a subset of patients who show durable clinical responses. The overall patient response rate is limited due to the interpatient heterogeneity. Preclinical and clinical studies have recently shown that the therapeutic responses can be improved through the modulation of gut microbiome. However, the underlying mechanisms are not fully understood. In this paper, we explored the effect of favorable and unfavorable gut bacteria on the therapeutic efficacy of anti-PD-1 against cancer by modeling the tumor-immune-gut microbiome interactions, and further examined the predictive markers of responders and non-responders to anti-PD-1. The dynamics of the gut bacteria was fitted to the clinical data of melanoma patients, and virtual patients data were generated based on the clinical patient survival data. Our simulation results show that low initial growth rate and low level of favorable bacteria at the initiation of anti-PD-1 therapy are predictive of non-responders, while high level of favorable bacteria at the initiation of anti-PD-1 therapy is predictive of responders. Simulation results also confirmed that it is possible to promote patients' response rate to anti-PD-1 by manipulating the gut bacteria composition of non-responders, whereby achieving long-term progression-free survival.

miR-194-5p negatively regulates the proliferation and differentiation of rabbit skeletal muscle satellite cells.

Skeletal muscle satellite cells (SMSCs), also known as a multipotential stem cell population, play a crucial role during muscle growth and regeneration. In recent years, numerous miRNAs have been associated with the proliferation and differentiation of SMSCs in a number of mammalian species; however, the regulatory mechanisms of miR-194-5p in rabbit SMSCs still remain scarce. In this study, miR-194-5p was first observed to be highly expressed in the rabbit leg muscle. Furthermore, both the mimics and inhibitor of miR-194-5p were used to explore its role in the proliferation and differentiation of rabbit SMSCs cultured in vitro. Results from both EdU and CCK8 assays showed that miR-194-5p inhibited the proliferation of SMSCs. Meanwhile, Mef2c was identified as a target gene of miR-194-5p based on the dual-luciferase reporter assay results. In addition, upregulation of miR-194-5p decreased the expression levels of Mef2c and MyoG during rabbit SMSCs differentiation on Days 3 and 7 of in vitro culture. Taken together, these data demonstrated that miR-194-5p negatively regulates the proliferation and differentiation of rabbit SMSCs by targeting Mef2c.

Extracellular Vesicles Derived from Human Umbilical Cord Mesenchymal Stromal Cells Protect Cardiac Cells Against Hypoxia/Reoxygenation Injury by Inhibiting Endoplasmic Reticulum Stress via Activation of the PI3K/Akt Pathway.

Endoplasmic reticulum (ER) stress is implicated in the pathogenesis of many diseases, including myocardial ischemia/reperfusion injury. We hypothesized that human umbilical cord mesenchymal stromal cells derived extracellular vesicles (HuMSC-EVs) could protect cardiac cells against hyperactive ER stress induced by hypoxia/reoxygenation (H/R) injury. The H/R model was generated using the H9c2 cultured cardiac cell line. HuMSC-EVs were extracted using a commercially available exosome isolation reagent. Levels of apoptosis-related signaling molecules and the degree of ER stress were assessed by western blot. The role of the PI3K/Akt pathway was investigated using signaling inhibitors. Lactate dehydrogenase leakage and 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) analysis were used for evaluating the therapeutic effects of HuMSC-EVs in vitro. The results showed that ER stress and the rate of apoptosis were increased in the context of H/R injury. Treatment with HuMSC-EVs inhibited ER stress and increased survival in H9c2 cells exposed to H/R. Mechanistically, the PI3K/Akt pathway was activated by treatment with HuMSC-EVs after H/R. Inhibition of the PI3K/Akt pathway by a specific inhibitor, LY294002, partially reduced the protective effect of HuMSC-EVs. Our findings suggest that HuMSC-EVs could alleviate ER stress-induced apoptosis during H/R via activation of the PI3K/Akt pathway.

TNF-α inhibitor reduces drug-resistance to anti-PD-1: A mathematical model.

Drug resistance is a primary obstacle in cancer treatment. In many patients who at first respond well to treatment, relapse occurs later on. Various mechanisms have been explored to explain drug resistance in specific cancers and for specific drugs. In this paper, we consider resistance to anti-PD-1, a drug that enhances the activity of anti-cancer T cells. Based on results in experimental melanoma, it is shown, by a mathematical model, that resistances to anti-PD-1 can be significantly reduced by combining it with anti-TNF-α. The model is used to simulate the efficacy of the combined therapy with different range of doses, different initial tumor volume, and different schedules. In particular, it is shown that under a course of treatment with 3-week cycles where each drug is injected in the first day of either week 1 or week 2, injecting anti-TNF-α one week after anti-PD-1 is the most effective schedule in reducing tumor volume.

How to schedule VEGF and PD-1 inhibitors in combination cancer therapy?

BACKGROUND: One of the questions in the design of cancer clinical trials with combination of two drugs is in which order to administer the drugs. This is an important question, especially in the case where one agent may interfere with the effectiveness of the other agent. RESULTS: In the present paper we develop a mathematical model to address this scheduling question in a specific case where one of the drugs is anti-VEGF, which is known to affect the perfusion of other drugs. As a second drug we take anti-PD-1. Both drugs are known to increase the activation of anticancer T cells. Our simulations show that in the case where anti-VEGF reduces the perfusion, a non-overlapping schedule is significantly more effective than a simultaneous injection of the two drugs, and it is somewhat more beneficial to inject anti-PD-1 first. CONCLUSION: The method and results of the paper can be extended to other combinations, and they could play an important role in the design of clinical trials with combination therapy, where scheduling strategies may significantly affect the outcome.

Mathematical modeling in scheduling cancer treatment with combination of VEGF inhibitor and chemotherapy drugs.

The present paper considers a treatment of cancer with a combination of anti-VEGF (bevacizumab) and a chemotherapy drug (docetaxel). Since anti-VEGF reduces the perfusion of chemotherapy drugs, the question arises whether it is more effective to administer the two drugs at the same time, or non-overlapping, in order to reduce tumor volume more effectively. To address this question we develop a mathematical model and use it to simulate different schedules. We find that the treatment of cancer would be far more effective if the two drugs are given non-overlappingly, with the chemotherapy drug at day 0 and anti-VEGF at day 7 in cycles of 21 days.

A stochastic model that explains axonal organelle pileups induced by a reduction of molecular motors.

Nerve cells are critically dependent on the transport of intracellular cargoes, which are moved by motor proteins along microtubule tracks. Impairments in this movement are thought to explain the focal accumulations of axonal cargoes and axonal swellings observed in many neurodegenerative diseases. In some cases, these diseases are caused by mutations that impair motor protein function, and genetic depletion of functional molecular motors has been shown to lead to cargo accumulations in axons. The evolution of these accumulations has been compared to the formation of traffic jams on a highway, but this idea remains largely untested. In this paper, we investigated the underlying mechanism of local axonal cargo accumulation induced by a global reduction of functional molecular motors in axons. We hypothesized that (i) a reduction in motor number leads to a reduction in the number of active motors on each cargo which in turn leads to less persistent movement, more frequent stops and thus shorter runs; (ii) as cargoes stop more frequently, they impede the passage of other cargoes, leading to local 'traffic jams'; and (iii) collisions between moving and stopping cargoes can push stopping cargoes further away from their microtubule tracks, preventing them from reattaching and leading to the evolution of local cargo accumulations. We used a lattice-based stochastic model to test whether this mechanism can lead to the cargo accumulation patterns observed in experiments. Simulation results of the model support the hypothesis and identify key questions that must be tested experimentally.

Role of white-tailed deer in geographic spread of the black-legged tick Ixodes scapularis : Analysis of a spatially nonlocal model.

yme disease is transmitted via blacklegged ticks, the spatial spread of which is believed to be primarily via transport on white-tailed deer. In this paper, we develop a mathematical model to describe the spatial spread of blacklegged ticks due to deer dispersal. The model turns out to be a system of differential equations with a spatially non-local term accounting for the phenomenon that a questing female adult tick that attaches to a deer at one location may later drop to the ground, fully fed, at another location having been transported by the deer. We first justify the well-posedness of the model and analyze the stability of its steady states. We then explore the existence of traveling wave fronts connecting the extinction equilibrium with the positive equilibrium for the system. We derive an algebraic equation that determines a critical value c* which is at least a lower bound for the wave speed in the sense that, if c

Modeling combination therapy for breast cancer with BET and immune checkpoint inhibitors.

CTLA-4 is an immune checkpoint expressed on active anticancer T cells. When it combines with its ligand B7 on dendritic cells, it inhibits the activity of the T cells. The Bromo- and Extra-Terminal (BET) protein family includes proteins that regulate the expression of key oncogenes and antiapoptotic proteins. BET inhibitor (BETi) has been shown to reduce the expression of MYC by suppressing its transcription factors and to down-regulate the hypoxic transcriptome response to VEGF-A. This paper develops a mathematical model of the treatment of cancer by combination therapy of BETi and CTLA-4 inhibitor. The model shows that the two drugs are positively correlated in the sense that the tumor volume decreases as the dose of each of the drugs is increased. The model also considers the effect of the combined therapy on levels of myeloid-derived suppressor cells (MDSCs) and the overexpression of TNF-α, which may predict gastrointestinal side effects of the combination.

Combination therapy for cancer with oncolytic virus and checkpoint inhibitor: A mathematical model.

Oncolytic virus (OV) is a replication competent virus that selectively invades cancer cells; as these cells die under the viral burden, the released virus particles proceed to infect other cancer cells. Oncolytic viruses are designed to also be able to stimulate the anticancer immune response. Thus, one may represent an OV by two parameters: its replication potential and its immunogenicity. In this paper we consider a combination therapy with OV and a checkpoint inhibitor, anti-PD-1. We evaluate the efficacy of the combination therapy in terms of the tumor volume at some later time, for example, 6 months from initial treatment. Since T cells kill not only virus-free cancer cells but also virus-infected cancer cells, the following question arises: Does increasing the amount of the checkpoint inhibitor always improve the efficacy? We address this question, by a mathematical model consisting of a system of partial differential equations. We use the model to construct, by simulations, an efficacy map in terms of the doses of the checkpoint inhibitor and the OV injection. We show that there are regions in the map where an increase in the checkpoint inhibitor actually decreases the efficacy of the treatment. We also construct efficacy maps with checkpoint inhibitor vs. the replication potential of the virus that show the same antagonism, namely, an increase in the checkpoint inhibitor may actually decrease the efficacy. These results have implications for clinical trials.

Human umbilical cord mesenchymal stem cells alleviate interstitial fibrosis and cardiac dysfunction in a dilated cardiomyopathy rat model by inhibiting TNF­α and TGF­ß1/ERK1/2 signaling pathways.

Dilated cardiomyopathy (DCM) is a disease of the heart characterized by pathological remodeling, including patchy interstitial fibrosis and degeneration of cardiomyocytes. In the present study, the beneficial role of human umbilical cord­derived mesenchymal stem cells (HuMSCs) derived from Wharton's jelly was evaluated in the myosin­induced rat model of DCM. Male Lewis rats (aged 8­weeks) were injected with porcine myosin to induce DCM. Cultured HuMSCs (1x106 cells/rat) were intravenously injected 28 days after myosin injection and the effects on myocardial fibrosis and the underlying signaling pathways were investigated and compared with vehicle­injected and negative control rats. Myosin injections in rats (vehicle group and experimental group) for 28 days led to severe fibrosis and significant deterioration of cardiac function indicative of DCM. HuMSC treatment reduced fibrosis as determined by Masson's staining of collagen deposits, as well as quantification of molecular markers of myocardial fibrosis such as collagen I/III, profibrotic factors transforming growth factor­ß1 (TGF­ß1), tumor necrosis factor­α (TNF­α), and connective tissue growth factor (CTGF). HuMSC treatment restored cardiac function as observed using echocardiography. In addition, western blot analysis indicated that HuMSC injections in DCM rats inhibited the expression of TNF­α, extracellular­signal regulated kinase 1/2 (ERK1/2) and TGF­ß1, which is a master switch for inducing myocardial fibrosis. These findings suggested that HuMSC injections attenuated myocardial fibrosis and dysfunction in a rat model of DCM, likely by inhibiting TNF­α and the TGF­ß1/ERK1/2 fibrosis pathways. Therefore, HuMSC treatment may represent a potential therapeutic method for treatment of DCM.

Combination therapy for melanoma with BRAF/MEK inhibitor and immune checkpoint inhibitor: a mathematical model.

BACKGROUND: The B-raf gene is mutated in up to 66% of human malignant melanomas, and its protein product, BRAF kinase, is a key part of RAS-RAF-MEK-ERK (MAPK) pathway of cancer cell proliferation. BRAF-targeted therapy induces significant responses in the majority of patients, and the combination BRAF/MEK inhibitor enhances clinical efficacy, but the response to BRAF inhibitor and to BRAF/MEK inhibitor is short lived. On the other hand, treatment of melanoma with an immune checkpoint inhibitor, such as anti-PD-1, has lower response rate but the response is much more durable, lasting for years. For this reason, it was suggested that combination of BRAF/MEK and PD-1 inhibitors will significantly improve overall survival time. RESULTS: This paper develops a mathematical model to address the question of the correlation between BRAF/MEK inhibitor and PD-1 inhibitor in melanoma therapy. The model includes dendritic and cancer cells, CD 4+ and CD 8+ T cells, MDSC cells, interleukins IL-12, IL-2, IL-6, IL-10 and TGF- ß, PD-1 and PD-L1, and the two drugs: BRAF/MEK inhibitor (with concentration γ B ) and PD-1 inhibitor (with concentration γ A ). The model is represented by a system of partial differential equations, and is used to develop an efficacy map for the combined concentrations (γ B ,γ A ). It is shown that the two drugs are positively correlated if γ B and γ A are at low doses, that is, the growth of the tumor volume decreases if either γ B or γ A is increased. On the other hand, the two drugs are antagonistic at some high doses, that is, there are zones of (γ B ,γ A ) where an increase in one of the two drugs will increase the tumor volume growth, rather than decrease it. CONCLUSIONS: It will be important to identify, by animal experiments or by early clinical trials, the zones of (γ B ,γ A ) where antagonism occurs, in order to avoid these zones in more advanced clinical trials.

Tetracycline-controllable artificial microRNA-HOTAIR + EZH2 suppressed the progression of bladder cancer cells.

Previous studies have suggested that EZH2 is up-regulated in bladder cancer tissues and identified it as a biomarker for poor prognosis. However, the biological functions of EZH2 in bladder cancer cells remain unknown. In this research, we discovered that EZH2 expression is irrelevant to the TNM stage and poor prognosis of bladder cancer patients. But suppression of EZH2 can slowdown the progression of bladder cancer cells. Moreover, we used the technology of synthetic biology to construct the tetracycline-controllable artificial microRNA-HOTAIR + EZH2, which can decrease the expression of HOTAIR and EZH2 in a doxycycline dosage-dependent manner. And we also found that HOTAIR expression was positively correlated with EZH2 expression. Tetracycline-controllable artificial microRNA-HOTAIR + EZH2 can inhibit the proliferation and migration of bladder cancer cells. Meanwhile, the apoptosis rate of bladder cancer cells was increased. Taken together, our research showed the cancer-promoting effects of EZH2 and created a novel method to rescue the development of bladder cancer cells.

Combination therapy of cancer with cancer vaccine and immune checkpoint inhibitors: A mathematical model.

In this paper we consider a combination therapy of cancer. One drug is a vaccine which activates dendritic cells so that they induce more T cells to infiltrate the tumor. The other drug is a checkpoint inhibitor, which enables the T cells to remain active against the cancer cells. The two drugs are positively correlated in the sense that an increase in the amount of each drug results in a reduction in the tumor volume. We consider the question whether a treatment with combination of the two drugs at certain levels is preferable to a treatment by one of the drugs alone at 'roughly' twice the dosage level; if that is the case, then we say that there is a positive 'synergy' for this combination of dosages. To address this question, we develop a mathematical model using a system of partial differential equations. The variables include dendritic and cancer cells, CD4+ and CD8+ T cells, IL-12 and IL-2, GM-CSF produced by the vaccine, and a T cell checkpoint inhibitor associated with PD-1. We use the model to explore the efficacy of the two drugs, separately and in combination, and compare the simulations with data from mouse experiments. We next introduce the concept of synergy between the drugs and develop a synergy map which suggests in what proportion to administer the drugs in order to achieve the maximum reduction of tumor volume under the constraint of maximum tolerated dose.

Human umbilical cord mesenchymal stem cells alleviate acute myocarditis by modulating endoplasmic reticulum stress and extracellular signal regulated 1/2-mediated apoptosis.

Acute myocarditis is a non-ischemic inflammatory disease of the myocardium, and there is currently no standard treatment. Mesenchymal stem cells (MSCs) can alleviate myosin­induced myocarditis; however, the mechanism has not been clearly elucidated. In the present study, the authors investigated the ability of human umbilical cordMSCs (HuMSCs) to attenuate myocardial injury and dysfunction during the acute phase of experimental myocarditis. Male Lewis rats (aged 8 weeks) were injected with porcine myosin to induce myocarditis. Cultured HuMSCs (1x106 cells/rat) were intravenously injected 10 days following myosin injection. A total of 3 weeks following injection, this resulted in severe inflammation and significant deterioration of cardiac function. HuMSC transplantation attenuated infiltration of inflammatory cells and adverse cardiac remodeling, as well as reduced cardiomyocyte apoptosis. Furthermore, it was identified that HuMSC transplantation suppressed endoplasmic reticulum stress and extracellular signal­regulated kinase (ERK)1/2 signaling in experimental autoimmune myocarditis (EAM). The reduced number of TUNEL­positive apoptotic cells in myocardial sections from HuMSC­treated EAM rats compared with control demonstrates HuMSCs' anti­apoptotic function. Based on these data, the author suggested that treatment with HuMSCs inhibits myocardial apoptosis in EAM rats, ultimately protecting them from myocardial damage. The conclusion demonstrated that HuMSC transplantation attenuates myocardial injury and dysfunction in a rat model of acute myocarditis, potentially via regulation of ER stress, ERK1/2 signaling and induction of cardiomyocyte apoptosis.

Exosomal microRNA concentrations in colorectal cancer: A mathematical model.

Colorectal cancer (CRC) is the second leading cause of cancer related deaths in the United States. Early detection increases survival very significantly. Indeed, five year survival for people diagnosed at stage I-II is 90%, while for those diagnosed at stage IV it is only 13%. The gold standard for early detection is colonoscopy, but this procedure is limited due to its invasive nature and its high cost. Hence there is a need to identify non-invasive biomarkers for CRC. Exosomal miRs secreted by cancer cells and overexpressed in the blood have been suggested as biomarkers for cancer. In particular, exosomal miRs 21, 23a, 92a and 1246 are overexpressed in CRC, and thus have the potential to be used as serum biomarkers for early detection of the disease. The present paper develops for the first time a mathematical model for early stage of CRC which includes the effect of these miRs on the growth of the cancer. The model is represented by a system of partial differential equations. Simulations of the model show a relationship between the growth of the tumor diameter and the total mass of these miRs under some of the common mutations which occur in CRC, namely, KRAS, PI3K, APC, p53 and SMAD mutations. The model may serve as a step toward establishing miRs 21, 23a, 92a and 1246 as reliable blood biomarkers for CRC as more experimental results and clinical data become available.