Energy & Environmental Science最新文献

Despite tremendous progress in the past decade, the complex and heterogeneous nature of cancer complicates efforts to identify new therapies and therapeutic combinations that achieve durable responses in most patients. Further advances in cancer therapy will rely, in part, on the development of targeted therapeutics matched with the genetic and molecular characteristics of cancer. The Cancer Dependency Map (DepMap) is a large-scale data repository and research platform, aiming to systematically reveal the landscape of cancer vulnerabilities in thousands of genetically and molecularly annotated cancer models. DepMap is used routinely by cancer researchers and translational scientists and has facilitated the identification of several novel and selective therapeutic strategies for multiple cancer types that are being tested in the clinic. However, it is also clear that the current version of DepMap is not yet comprehensive. In this Perspective, we review (1) the impact and current uses of DepMap, (2) the opportunities to enhance DepMap to overcome its current limitations, and (3) the ongoing efforts to further improve and expand DepMap.

Immunotherapy has become a key new pillar of cancer treatment, and this has sparked interest in understanding mechanisms of cancer immune evasion. It has long been appreciated that cancers are constituted by heterogeneous populations of tumour cells. This feature is often fuelled by specialized cells that have molecular programs resembling tissue stem cells. Although these cancer stem cells (CSCs) have capacity for unlimited self-renewal and differentiation, it is increasingly evident that some CSCs are capable of achieving remarkable immune resistance. Given that most immunotherapy regiments have overlooked CSC-specific immune-evasive mechanisms, many current treatment strategies often lead to cancer relapse. This Review focuses on advancements in understanding how CSCs in solid tumours achieve their unique immune-evasive properties, enabling them to drive tumour regrowth. Moreover, as cancers often arise from tissue stem cells that acquired oncogenic mutations, we discuss how tissue stem cells undergoing malignant transformation activate intrinsic immune-evasive mechanisms and establish close interactions with suppressive immune cells to escape immune surveillance. In addition, we summarize how in advanced disease stages, CSCs often hijack features of normal stem cells to resist antitumour immunity. Finally, we provide insights in how to design a new generation of cancer immunotherapies to ensure elimination of CSCs.

Tumorigenesis embodies the formation of a heterotypic tumour microenvironment (TME) that, among its many functions, enables the evasion of T cell-mediated immune responses. Remarkably, most TME cell types, including cancer cells, fibroblasts, myeloid cells, vascular endothelial cells and pericytes, can be stimulated to deploy immunoregulatory programmes. These programmes involve regulatory inducers (signals-in) and functional effectors (signals-out) that impair CD8⁺ and CD4⁺ T cell activity through cytokines, growth factors, immune checkpoints and metabolites. Some signals target specific cell types, whereas others, such as transforming growth factor-β (TGFβ) and prostaglandin E₂ (PGE₂), exert broad, pleiotropic effects; as signals-in, they trigger immunosuppressive programmes in most TME cell types, and as signals-out, they directly inhibit T cells and also modulate other cells to reinforce immunosuppression. This functional diversity and redundancy pose a challenge for therapeutic targeting of the immune-evasive TME. Fundamentally, the commonality of regulatory programmes aimed at abrogating T cell activity, along with paracrine signalling between cells of the TME, suggests that many normal cell types are hard-wired with latent functions that can be triggered to prevent inappropriate immune attack. This intrinsic capability is evidently co-opted throughout the TME, enabling tumours to evade immune destruction.

Early detection and intervention of cancer or precancerous lesions hold great promise to improve patient survival. However, the processes of cancer initiation and the normal–precancer–cancer progression within a non-cancerous tissue context remain poorly understood. This is, in part, due to the scarcity of early-stage clinical samples or suitable models to study early cancer. In this Review, we introduce clinical samples and model systems, such as autochthonous mice and organoid-derived or stem cell-derived models that allow longitudinal analysis of early cancer development. We also present the emerging techniques and computational tools that enhance our understanding of cancer initiation and early progression, including direct imaging, lineage tracing, single-cell and spatial multi-omics, and artificial intelligence models. Together, these models and techniques facilitate a more comprehensive understanding of the poorly characterized early malignant transformation cascade, holding great potential to unveil key drivers and early biomarkers for cancer development. Finally, we discuss how these new insights can potentially be translated into mechanism-based strategies for early cancer detection and prevention.

Multiple myeloma is an incurable plasma cell malignancy that evolves over decades through the selection and malignant transformation of monoclonal plasma cells. The evolution from precursor states to symptomatic disease is characterized by an increasing complexity of genomic alterations within the plasma cells and a remodelling of the microenvironment towards an immunosuppressive state. Notably, in patients with advanced disease, similar mechanisms of tumour escape and immune dysfunction mediate resistance to modern T cell-based therapies, such as T cell-engaging bispecific antibodies and chimeric antigen receptor (CAR)-T cells. Thus, an increasing number of clinical trials are assessing the efficiency and safety of these therapies in individuals with newly diagnosed multiple myeloma and high-risk smoldering multiple myeloma. In this Review, we summarize the current knowledge about tumour intrinsic and extrinsic processes underlying progression from precursor states to symptomatic myeloma and discuss the rationale for early interception including the use of T cell-redirecting therapies.

In the past decade, remarkable progress in cancer medicine has been achieved by the development of treatments that target DNA sequence variants. However, a purely genetic approach to treatment selection is hampered by the fact that diverse cell states can emerge from the same genotype. In multicellular organisms, cell-state heterogeneity is driven by epigenetic processes that regulate DNA-based functions such as transcription; disruption of these processes is a hallmark of cancer that enables the emergence of defective cell states. Advances in single-cell technologies have unlocked our ability to quantify the epigenomic heterogeneity of tumours and understand its mechanisms, thereby transforming our appreciation of how epigenomic changes drive cancer evolution. This Review explores the idea that epigenomic heterogeneity and plasticity act as a reservoir of cell states and therefore as a source of tumour evolution. Best practices to quantify epigenomic heterogeneity and explore its various causes and consequences are discussed, including epigenomic reprogramming, stochastic changes and lasting memory. The design of new therapeutic approaches to restrict epigenomic heterogeneity, with the long-term objective of limiting cancer development and progression, is also addressed.