研究早期癌症生物学的新兴策略
Emerging strategies to investigate the biology of early cancer
影响因子:66.80000
分区:医学1区 Top / 肿瘤学1区
发表日期:2024 Dec
作者:
Ran Zhou, Xiwen Tang, Yuan Wang
摘要
癌症或癌前病变的早期检测和干预具有改善患者生存的巨大希望。然而，在非癌组织环境中癌症起步的过程和正常的癌症的进展仍然很少。这部分是由于早期临床样本缺乏或研究早期癌症的模型。在这篇综述中，我们介绍了临床样品和模型系统，例如自毒小鼠以及类器官衍生或干细胞衍生的模型，可以纵向分析早期癌症的发展。我们还提出了新兴技术和计算工具，以增强我们对癌症开始和早期进展的理解，包括直接成像，谱系跟踪，单细胞和空间多摩学以及人工智能模型。这些模型和技术共同促进了对早期恶性转化级别较差的不良特征的更全面的理解，具有揭示主要驱动因素的巨大潜力，以及早期的生物标志物来开发癌症的发展。最后，我们讨论如何将这些新见解可能转化为基于机制的早期癌症检测和预防策略。
Abstract
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.