系统生物学
肿瘤微环境
肿瘤异质性
计算机科学
计算生物学
数据科学
肿瘤细胞
生物
癌症
癌症研究
遗传学
作者
Anna Fomitcheva Khartchenko,Aditya Kashyap,Tamar Geiger,Govind V. Kaigala
标识
DOI:10.1016/j.trecan.2022.07.008
摘要
Tumor cells present complex behaviors in their interactions with other cells. This intricate behavior is driving the need to develop new tools to understand these ecosystems. The surge of spatial technologies allows evaluation of the complexity of relationships between cells present in a tumor, giving insights about tumor heterogeneity and the tumor microenvironment while providing clinically relevant metrics for tumor classification. In this review, we describe key results obtained using spatial techniques, present recent advances in methods to uncover spatially relevant biological significance, and summarize their main characteristics. We expect spatial technologies to significantly broaden our understanding of tumor biology and to generate clinically relevant tools that will ultimately impact personalized medicine.
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