- Home >
- Publications >
- Unveiling spatial heterogeneity in medulloblastoma: a multi-omics analysis of cellular state and geographical organization
Unveiling spatial heterogeneity in medulloblastoma: a multi-omics analysis of cellular state and geographical organization
Authors
Jiankang Li, Hailong Liu, Ziwei Wang, Jiao Zhang, Xuan Chen, Craig Daniels, Xiaochong Wu, Olivier Saulnier, Hiromichi Suzuki, Pasqualino De Antonellis, Alexandra Rasnitsyn, Winnie Ong, Evan Y Wang, Liam D Hendrikse, Yu Su, Yu Tian, Dongming Han, Ruohan Wang, Jialin Mo, Fei Liu, Kaiwen Deng, Dongyang Wang, Zhaoyang Feng, Yifei Jiang, Yanong Li, Yuting Ma, Zijia Liu, Meiyu Li, Peiyi Tian, Yanfeng Shi, Yong Jiang, Tao Yang, Shouwei Li, Jianfeng Liang, Jingchuan Wu, Ying Wang, Wanjing Zou, Yina Jiang, Lusheng Wang, Fang Chen, Xin Jin, Shuaicheng Li, Xiaoguang Qiu, Chunde Li, Ya Gao, Yujie Tang, Michael D Taylor, Tao Jiang
Abstract
Abstract
Background
Despite numerous studies on medulloblastoma (MB) cell heterogeneity, the spatial characteristics of cellular states remain unclear.
Methods
We analyze single-nucleus and spatial transcriptomes and chromatin accessibility from human MB spanning four subgroups, to identify malignant cell populations and describe the spatial evolutionary trajectories. The spatial CNVs patterns and niches were analyzed to investigate the cellular interactions.
Results
Three main malignant cell populations were identified, including progenitor-like, cycling and differentiated populations. Gene signatures of cell populations strongly correlate to clinical outcomes. These tumor cell populations are geographically organized as stem-like and mature regions, highlighting their spatially heterogeneous nature. Progenitor-like and cycling cells are mainly concentrated in stem-like regions, whereas various differentiated populations are primarily distributed in mature regions. By analyzing chromosomal alterations, we find that stem-like region typically harbors a single pattern of CNVs, reflecting high originality and uniformity, which is in stark contrast to mature region exhibiting multiple patterns with a broader range of biological functions. Projecting cellular state program onto spatial sections fully illustrates the evolution from stem-like region to various functional zones in mature region, which is correlated to microenvironmental components along the paths to maintain stemness or promote differentiation. Conclusions. This multi-omics database comprehensively facilitates the understanding of MB spatial evolutionary organization.
