Cardiovascular diseases have become the leading cause of human death. Aging is an independent risk factor for cardiovascular diseases. Cardiac aging is associated with maladaptation of cellular metabolism, dysfunction (or senescence) of cardiomyocytes, a decrease in angiogenesis, and an increase in tissue scarring (fibrosis). These events eventually lead to cardiac remodeling and failure. Senescent cardiomyocytes show the hallmarks of DNA damage, endoplasmic reticulum stress, mitochondria dysfunction, contractile dysfunction, hypertrophic growth, and senescence-associated secreting phenotype (SASP). Metabolism within cardiomyocytes is essential not only to fuel the pump function of the heart but also to maintain the functional homeostasis and participate in the senescence of cardiomyocytes. The senescence of cardiomyocyte is also regulated by the non-myocytes (endothelial cells, fibroblasts, and immune cells) in the local microenvironment. On the other hand, the senescent cardiomyocytes alter their phenotypes and subsequently affect the non-myocytes in the local microenvironment and contribute to cardiac aging and pathological remodeling. In this review, we first summarized the hallmarks of the senescence of cardiomyocytes. Then, we discussed the metabolic switch within senescent cardiomyocytes and provided a discussion of the cellular communications between dysfunctional cardiomyocytes and non-myocytes in the local microenvironment. We also addressed the functions of metabolic regulators within non-myocytes in modulating myocardial microenvironment. Finally, we pointed out some interesting and important questions that are needed to be addressed by further studies.

Cancer-associated fibroblasts (CAFs) are the predominant components of the tumor microenvironment (TME) and influence cancer hallmarks, but without systematic investigation on their ubiquitous characteristics across different cancer types. Here, we perform pan-cancer analysis on 226 samples across 10 solid cancer types to profile the TME at single-cell resolution, illustrating the commonalities/plasticity of heterogenous CAFs. Activation trajectory of the major CAF types is divided into three states, exhibiting distinct interactions with other cell components, and relating to prognosis of immunotherapy. Moreover, minor CAF components represent the alternative origin from other TME components (e.g., endothelia and macrophages). Particularly, the ubiquitous presentation of endothelial-to-mesenchymal transition CAF, which may interact with proximal SPP1+ tumor-associated macrophages, is implicated in endothelial-to-mesenchymal transition and survival stratifications. Our study comprehensively profiles the shared characteristics and dynamics of CAFs, and highlight their heterogeneity and plasticity across different cancer types. Browser of integrated pan-cancer single-cell information is available at https://gist-fgl.github.io/sc-caf-atlas/.

No abstract

The advent of single-cell RNA sequencing (scRNA-seq) has provided insight into the tumour immune microenvironment (TIME). This review focuses on the application of scRNA-seq in investigation of the TIME. Over time, scRNA-seq methods have evolved, and components of the TIME have been deciphered with high resolution. In this review, we first introduced the principle of scRNA-seq and compared different sequencing approaches. Novel cell types in the TIME, a continuous transitional state, and mutual intercommunication among TIME components present potential targets for prognosis prediction and treatment in cancer. Thus, we concluded novel cell clusters of cancer-associated fibroblasts (CAFs), T cells, tumour-associated macrophages (TAMs) and dendritic cells (DCs) discovered after the application of scRNA-seq in TIME. We also proposed the development of TAMs and exhausted T cells, as well as the possible targets to interrupt the process. In addition, the therapeutic interventions based on cellular interactions in TIME were also summarized. For decades, quantification of the TIME components has been adopted in clinical practice to predict patient survival and response to therapy and is expected to play an important role in the precise treatment of cancer. Summarizing the current findings, we believe that advances in technology and wide application of single-cell analysis can lead to the discovery of novel perspectives on cancer therapy, which can subsequently be implemented in the clinic. Finally, we propose some future directions in the field of TIME studies that can be aided by scRNA-seq technology.

RPF has estrogen-like effect on lipid metabolism in liver and adipose tissue.