Carranza Francisco G, Diaz Fernando C, Ninova Maria, Velazquez-Villarreal Enrique
Department of Integrative Translational Sciences, City of Hope, Beckman Research Institute, Duarte, CA, United States.
Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, United States.
Front Oncol. 2024 Dec 3;14:1513821. doi: 10.3389/fonc.2024.1513821. eCollection 2024.
Over the past century, colorectal cancer (CRC) has become one of the most devastating cancers impacting the human population. To gain a deeper understanding of the molecular mechanisms driving this solid tumor, researchers have increasingly turned their attention to the tumor microenvironment (TME). Spatial transcriptomics and proteomics have emerged as a particularly powerful technology for deciphering the complexity of CRC tumors, given that the TME and its spatial organization are critical determinants of disease progression and treatment response. Spatial transcriptomics enables high-resolution mapping of the whole transcriptome. While spatial proteomics maps protein expression and function across tissue sections. Together, they provide a detailed view of the molecular landscape and cellular interactions within the TME. In this review, we delve into recent advances in spatial biology technologies applied to CRC research, highlighting both the methodologies and the challenges associated with their use, such as the substantial tissue heterogeneity characteristic of CRC. We also discuss the limitations of current approaches and the need for novel computational tools to manage and interpret these complex datasets. To conclude, we emphasize the importance of further developing and integrating spatial transcriptomics into CRC precision medicine strategies to enhance therapeutic targeting and improve patient outcomes.
在过去的一个世纪里,结直肠癌(CRC)已成为影响人类的最具毁灭性的癌症之一。为了更深入地了解驱动这种实体瘤的分子机制,研究人员越来越多地将注意力转向肿瘤微环境(TME)。鉴于TME及其空间组织是疾病进展和治疗反应的关键决定因素,空间转录组学和蛋白质组学已成为一种特别强大的技术,用于解读CRC肿瘤的复杂性。空间转录组学能够对整个转录组进行高分辨率绘图。而空间蛋白质组学则可绘制跨组织切片的蛋白质表达和功能图谱。它们共同提供了TME内分子景观和细胞相互作用的详细视图。在这篇综述中,我们深入探讨了应用于CRC研究的空间生物学技术的最新进展,强调了方法以及使用这些技术所面临的挑战,例如CRC特有的显著组织异质性。我们还讨论了当前方法的局限性以及对新型计算工具来管理和解释这些复杂数据集的需求。最后,我们强调进一步开发并将空间转录组学整合到CRC精准医学策略中以增强治疗靶向性和改善患者预后的重要性。