Characterizing the mode—the way, manner or pattern—of evolution in tumours is important for clinical forecasting and optimizing cancer treatment. Sequencing studies have inferred various modes, including branching, punctuated and neutral evolution, but it is unclear why a particular pattern predominates in any given tumour. Here we propose that tumour architecture is key to explaining the variety of observed genetic patterns. We examine this hypothesis using spatially explicit population genetics models and demonstrate that, within biologically relevant parameter ranges, different spatial structures can generate four tumour evolutionary modes: rapid clonal expansion, progressive diversification, branching evolution and effectively almost neutral evolution. Quantitative indices for describing and classifying these evolutionary modes are presented. Using these indices, we show that our model predictions are consistent with empirical observations for cancer types with corresponding spatial structures. The manner of cell dispersal and the range of cell–cell interactions are found to be essential factors in accurately characterizing, forecasting and controlling tumour evolution.

The liver is a major metastatic target organ, and little is known about the role of immunity in controlling hepatic metastases. Here, we discovered that the concerted and nonredundant action of two innate lymphocyte subpopulations, conventional natural killer cells (cNKs) and tissue-resident type I innate lymphoid cells (trILC1s), is essential for antimetastatic defense. Using different preclinical models for liver metastasis, we found that trILC1 controls metastatic seeding, whereas cNKs restrain outgrowth. Whereas the killing capacity of trILC1s was not affected by the metastatic microenvironment, the phenotype and function of cNK cells were affected in a cancer type–specific fashion. Thus, individual cancer cell lines orchestrate the emergence of unique cNK subsets, which respond differently to tumor-derived factors. Our findings will contribute to the development of therapies for liver metastasis involving hepatic innate cells.

Characterizing the mode -the way, manner, or pattern -of evolution in tumours is important for clinical forecasting and optimizing cancer treatment. DNA sequencing studies have inferred various modes, including branching, punctuated and neutral evolution, but it is unclear why a particular pattern predominates in any given tumour [1]. Here we propose that differences in tumour architecture alone can explain the variety of observed patterns. We examine this hypothesis using spatially explicit population genetic models and demonstrate that, within biologically relevant parameter ranges, tumours are expected to exhibit diverse evolutionary modes including four archetypal "oncoevotypes": rapid clonal expansion (predicted in leukaemia); progressive diversification (in colorectal adenomas and early-stage colorectal carcinomas); branching evolution (in invasive glandular tumours); and almost neutral evolution (in certain non-glandular and poorly differentiated solid tumours). We thus provide a simple, mechanistic explanation for a wide range of empirical observations. Oncoevotypes are driven by differences in cell dispersal and cell-cell interactions, which we show are essential for accurately characterizing, forecasting and controlling tumour evolution.A tumour is a product of somatic evolution in which interacting processes of mutation, selection, genetic drift, and cell dispersal generate a patchwork of cell subpopulations (clones) with varying degrees of aggressiveness and treatment sensitivity [2]. A primary goal of modern cancer research is to characterize this evolutionary process, so as to enable precise, patient-specific prognostic forecasts and to optimize targeted therapy regimens.Much progress has been made in revealing the evolutionary features of particular cancers, yet these findings raise as many questions as they answer. Why do different tumour types exhibit different modes of evolution [1,3,4,5,6]? What conditions sustain the frequently observed pattern of branching evolution, in which several clones diverge and evolve in parallel [1,7]? And why do some pan-cancer analyses indicate that many tumours evolve neutrally [8], whereas others support extensive selection [9]?Factors proposed as contributing to intra-tumour evolution include microenvironmental heterogeneity, niche construction, and positive ecological interactions between clones [10, 2]. However, because such factors have not been well characterized across human cancer types, it remains unclear how they might relate to evolutionary modes.On the other hand, it is well established that tumours exhibit a wide range of architectures. In leukaemia, for example, mutated stem cells in semi-solid bone marrow produce cancer cells that mix and proliferate in the bloodstream (Figure 1a). Colorectal adenomas and early-stage colorectal carcinomas, by contrast, inherit 1

Preserving skeletal muscle function is essential to maintain life quality at high age. Calorie restriction (CR) potently extends health and lifespan, but is largely unachievable in humans, making “CR mimetics” of great interest. CR targets nutrient-sensing pathways centering on mTORC1. The mTORC1 inhibitor, rapamycin, is considered a potential CR mimetic and is proven to counteract age-related muscle loss. Therefore, we tested whether rapamycin acts via similar mechanisms as CR to slow muscle aging. Here we show that long-term CR and rapamycin unexpectedly display distinct gene expression profiles in geriatric mouse skeletal muscle, despite both benefiting aging muscles. Furthermore, CR improves muscle integrity in mice with nutrient-insensitive, sustained muscle mTORC1 activity and rapamycin provides additive benefits to CR in naturally aging mouse muscles. We conclude that rapamycin and CR exert distinct, compounding effects in aging skeletal muscle, thus opening the possibility of parallel interventions to counteract muscle aging.