Mathematical model predicts response to chemotherapy in advanced non-resectable non-small cell lung cancer patients treated with platinum-based doublet

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.

Optimal treatment strategy of cancers with intratumor heterogeneity

Intratumor heterogeneity hinders the success of anti-cancer treatment due to the interaction between different types of cells. To recapitulate the communication of different types of cells, we developed a mathematical model to study the dynamic interaction between normal, drug-sensitive and drug-resistant cells in response to cancer treatment. Based on the proposed model, we first study the analytical conclusions, namely the nonnegativity and boundedness of solutions, and the existence and stability of steady states. Furthermore, to investigate the optimal treatment that minimizes both the cancer cells count and the total dose of drugs, we apply the Pontryagin's maximum(or minimum) principle (PMP) to explore the combination therapy strategy with either quadratic control or linear control functionals. We establish the existence and uniqueness of the quadratic control problem, and apply the forward-backward sweep method (FBSM) to solve the optimal control problems and obtain the optimal therapy scheme.

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.

A model for the intrinsic limit of cancer therapy: Duality of treatment-induced cell death and treatment-induced stemness

Intratumor cellular heterogeneity and non-genetic cell plasticity in tumors pose a recently recognized challenge to cancer treatment. Because of the dispersion of initial cell states within a clonal tumor cell population, a perturbation imparted by a cytocidal drug only kills a fraction of cells. Due to dynamic instability of cellular states the cells not killed are pushed by the treatment into a variety of functional states, including a "stem-like state" that confers resistance to treatment and regenerative capacity. This immanent stress-induced stemness competes against cell death in response to the same perturbation and may explain the near-inevitable recurrence after any treatment. This double-edged-sword mechanism of treatment complements the selection of preexisting resistant cells in explaining post-treatment progression. Unlike selection, the induction of a resistant state has not been systematically analyzed as an immanent cause of relapse. Here, we present a generic elementary model and analytical examination of this intrinsic limitation to therapy. We show how the relative proclivity towards cell death versus transition into a stem-like state, as a function of drug dose, establishes either a window of opportunity for containing tumors or the inevitability of progression following therapy. The model considers measurable cell behaviors independent of specific molecular pathways and provides a new theoretical framework for optimizing therapy dosing and scheduling as cancer treatment paradigms move from "maximal tolerated dose," which may promote therapy induced-stemness, to repeated "minimally effective doses" (as in adaptive therapies), which contain the tumor and avoid therapy-induced progression.

Salvianolic Acid B Suppresses Non-Small-Cell Lung Cancer Metastasis through PKM2-Independent Metabolic Reprogramming

Objective

Salvianolic acid B (Sal B) has been demonstrated to be a potential chemoprevention agent for several cancers. Herein, we investigated the pharmacological function of Sal B on non-small-cell lung cancer (NSCLC) metastasis.

Methods

Two NSCLC cell lines (NCI-H2030 and NCI-H1650) were disposed of by 200 μM Sal B or 10 μM PKM2 agonist TEPP-46. Wound healing and transwell experiments were implemented for analyzing migratory and invasive capacities. Epithelial-to-mesenchymal transition (EMT) markers β-catenin and E-cadherin were measured via western blotting. Cellular bioenergetics were evaluated with glucose uptake, lactate production, enolase activity, cellular ATP levels, as well as seahorse-based oxygen consumption rate (OCR), extracellular acidification rate (ECAR) analysis. Metabolic reprogramming markers PKM2, LDHA, and GLUT1 were detected via western blotting and immunofluorescence.

Results

The results showed that Sal B disposal weakened the migration and invasion of NCI-H2030 and NCI-H1650 cells and inactivated the EMT process according to downregulation of β-catenin and upregulation of E-cadherin. Sal B-treated NSCLC cells displayed decreased glucose uptake, lactate production, enolase activity, cellular ATP levels, OCR, and ECAR, indicating a reduction in metabolic reprogramming. Additionally, Sal B downregulated the expression of PKM2, LDHA, and GLUT1. TEPP-46 may reverse the inhibitory effect of Sal B on metastasis as well as metabolic reprogramming.

Conclusion

Our findings provide evidence that Sal B enables to weaken NSCLC metastasis through PKM2-independent metabolic reprogramming, which sheds light on the promising therapeutic usage of Sal B in treating NSCLC.

Normalizing tumor microenvironment with nanomedicine and metronomic therapy to improve immunotherapy

Nanomedicine offered hope for improving the treatment of cancer but the survival benefits of the clinically approved nanomedicines are modest in many cases when compared to conventional chemotherapy. Metronomic therapy, defined as the frequent, low dose administration of chemotherapeutics – is being tested in clinical trials as an alternative to the conventional maximum tolerated dose (MTD) chemotherapy schedule. Although metronomic chemotherapy has not been clinically approved yet, it has shown better survival than MTD in many preclinical studies. When beneficial, metronomic therapy seems to be associated with normalization of the tumor microenvironment including improvements in tumor perfusion, tissue oxygenation and drug delivery as well as activation of the immune system. Recent preclinical studies suggest that nanomedicines can cause similar changes in the tumor microenvironment. Here, by employing a mathematical framework, we show that both approaches can serve as normalization strategies to enhance treatment. Furthermore, employing murine breast and fibrosarcoma tumor models as well as ultrasound shear wave elastography and contrast-enhanced ultrasound, we provide evidence that the approved nanomedicine Doxil can induce normalization in a dose-dependent manner by improving tumor perfusion as a result of tissue softening. Finally, we show that pretreatment with a normalizing dose of Doxil can improve the efficacy of immune checkpoint inhibition.

What do cellular responses to acidity tell us about cancer?

The notion that invasive cancer is a product of somatic evolution is a well-established theory that can be modelled mathematically and demonstrated empirically from therapeutic responses. Somatic evolution is by no means deterministic, and ample opportunities exist to steer its trajectory towards cancer cell extinction. One such strategy is to alter the chemical microenvironment shared between host and cancer cells in a way that no longer favours the latter. Ever since the first description of the Warburg effect, acidosis has been recognised as a key chemical signature of the tumour microenvironment. Recent findings have suggested that responses to acidosis, arising through a process of selection and adaptation, give cancer cells a competitive advantage over the host. A surge of research efforts has attempted to understand the basis of this advantage and seek ways of exploiting it therapeutically. Here, we review key findings and place these in the context of a mathematical framework. Looking ahead, we highlight areas relating to cellular adaptation, selection, and heterogeneity that merit more research efforts in order to close in on the goal of exploiting tumour acidity in future therapies.