Lu Tang

Abstract The overlapping metabolic reprogramming of cancer and immune cells is a putative determinant of the antitumor immune response in cancer. Increased evidence suggests that cancer metabolism not only plays a crucial role in cancer signaling for sustaining tumorigenesis and survival, but also has wider implications in the regulation of antitumor immune response through both the release of metabolites and affecting the expression of immune molecules, such as lactate, PGE 2 , arginine, etc. Actually, this energetic interplay between tumor and immune cells leads to metabolic competition in the tumor ecosystem, limiting nutrient availability and leading to microenvironmental acidosis, which hinders immune cell function. More interestingly, metabolic reprogramming is also indispensable in the process of maintaining self and body homeostasis by various types of immune cells. At present, more and more studies pointed out that immune cell would undergo metabolic reprogramming during the process of proliferation, differentiation, and execution of effector functions, which is essential to the immune response. Herein, we discuss how metabolic reprogramming of cancer cells and immune cells regulate antitumor immune response and the possible approaches to targeting metabolic pathways in the context of anticancer immunotherapy. We also describe hypothetical combination treatments between immunotherapy and metabolic intervening that could be used to better unleash the potential of anticancer therapies.

Abstract Tumor microenvironment (TME) is the internal environment in which tumor cells survive, consisting of tumor cells, fibroblasts, endothelial cells, and immune cells, as well as non-cellular components, such as exosomes and cytokines. Exosomes are tiny extracellular vesicles (40-160nm) containing active substances, such as proteins, lipids and nucleic acids. Exosomes carry biologically active miRNAs to shuttle between tumor cells and TME, thereby affecting tumor development. Tumor-derived exosomal miRNAs induce matrix reprogramming in TME, creating a microenvironment that is conducive to tumor growth, metastasis, immune escape and chemotherapy resistance. In this review, we updated the role of exosomal miRNAs in the process of TME reshaping.

Multi-compartment models have been playing a central role in modelling infectious disease dynamics since the early 20th century. They are a class of mathematical models widely used for describing the mechanism of an evolving epidemic. Integrated with certain sampling schemes, such mechanistic models can be applied to analyse public health surveillance data, such as assessing the effectiveness of preventive measures (e.g. social distancing and quarantine) and forecasting disease spread patterns. This review begins with a nationwide macromechanistic model and related statistical analyses, including model specification, estimation, inference and prediction. Then, it presents a community-level micromodel that enables high-resolution analyses of regional surveillance data to provide current and future risk information useful for local government and residents to make decisions on reopenings of local business and personal travels. r software and scripts are provided whenever appropriate to illustrate the numerical detail of algorithms and calculations. The coronavirus disease 2019 pandemic surveillance data from the state of Michigan are used for the illustration throughout this paper.

Abstract Purpose: This study aims to provide comprehensive insights into longitudinal immune landscape in acute myeloid leukemia (AML) development and treatment, which may contribute to predict prognosis and guide clinical decisions. Experimental Design: Periphery blood samples from 79 patients with AML (at diagnosis or/and after chemotherapy or at relapse) and 24 healthy controls were prospectively collected. We performed phenotypic and functional analysis of various lymphocytes through multiparametric flow cytometry and investigated prognostic immune-related risk factors. Results: Immune defects in AML were reflected in T and natural killer (NK) cells, whereas B-cell function remained unaffected. Both CD8+ T and CD4+ T cells exhibited features of senescence and exhaustion at diagnosis. NK dysfunction was supported by excessive maturation and downregulation of NKG2D and NKP30. Diseased γδ T cells demonstrated a highly activated or even exhausted state through PD-1 upregulation and NKG2D downregulation. Effective therapeutic response following chemotherapy correlated with T and NK function restoration. Refractory and relapsed patients demonstrated even worse immune impairments, and selective immune signatures apparently correlated clinical outcomes and survival. PD-1 expression in CD8+ T cells was independently predictive of poor overall survival and event-free survival. Conclusions: T-cell senescence and exhaustion, together with impaired NK and γδ T-cell function, are dominant aspects involved in immune dysfunction in AML. Noninvasive immune testing of blood samples could be applied to predict therapeutic reactivity, high risk for relapse, and unfavorable prognosis.