文章：

研究早期癌症生物学的新策略

Emerging strategies to investigate the biology of early cancer

原文发布日期：2024-10-21

DOI: 10.1038/s41568-024-00754-y

类型: Review Article

开放获取: 否

英文摘要：

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.

摘要翻译： 

癌症或癌前病变的早期发现与干预对提升患者生存率具有重要意义。然而，在非癌组织环境中，癌症的发生以及正常-癌前-癌变的进展过程仍不甚明确。这部分源于早期临床样本或适用于早期癌症研究模型的稀缺。本综述介绍了临床样本与模型系统（如原位小鼠模型、类器官衍生模型及干细胞衍生模型），这些模型支持对早期癌症发展进行纵向分析。我们同时介绍了新兴技术与计算工具，包括直接成像、谱系追踪、单细胞与空间多组学、人工智能模型等，这些技术深化了我们对癌症发生及早期进展的认识。这些模型与技术共同促进了对尚未明确的早期恶性转化级联反应的更全面理解，为揭示癌症发展的关键驱动因素和早期生物标志物带来巨大潜力。最后，我们探讨了如何将这些新见解转化为基于机制的早期癌症检测与预防策略。

原文链接：

Emerging strategies to investigate the biology of early cancer