Cross-species Comparison Reveals Therapeutic Vulnerabilities Halting Glioblastoma Progression

The growth of a tumor is tightly linked to the distribution of its cells along a continuum of activation states. Here, we systematically decode the activation state architecture (ASA) in a glioblastoma (GBM) patient cohort through comparison to adult murine neural stem cells. Modelling of these data forecast how tumor cells organize to sustain growth and identifies rate of activation as the main predictor of growth. Accordingly, patients with a higher quiescence fraction exhibit improved outcomes. Further, DNA methylation arrays enable ASA-related patient stratification. Comparison of healthy and malignant gene expression dynamics reveals dysregulation of the Wnt-antagonist SFRP1 at the quiescence to activation transition. SFRP1 overexpression renders GBM quiescent and increases overall survival of tumor-bearing mice. Surprisingly, it does so through reprogramming the tumor’s stem-like methylome into an astrocyte-like one. Our findings offer a framework for patient stratification, biomarker identification, and development of therapeutic avenues to halt GBM progression. Pre-print on bioRxiv Data confocal_raw.zip contains the max-projected stainings of the ROIs. The 3D confocal images that were used to segment the nuclei are not included due to their size, but can be made available on request. The voxel size is (1., 0.142, 0.142) um/pixel. confocal_segmentation.zip contains the nuclei segmentation that was obtained using mesmer and a custom 3D stitching approach. resolve_raw.zip contains the raw data as produced by Resolve Bioscience, i.e. raw 3D transcript counts and a 2D DAPI stain. resolve_registered.zip contains the spatial transcript counts after 3D registration, so their coordinate system is aligned to the confocal images and segmentations. segmentation_pipeline.zip contains the code that was used to process the data from raw images and transcript counts to the final segmented cells. segmentation_result.zip contains the final result of the segmentation, as well as the code that does the celltype assignment and neighbourhood enrichment. The code that was used to process and segment the spatial data can also be found on GitHub (anders-biostat/ResolveTools). Parameters The original transcripts are aligned with the Resolve DAPI images, and their voxels have size (0.3125, 0.138, 0.138) microns (zyx, respectively). Our confocal images have a voxel size of (1., 0.142, 0.142) microns (zyx, respectively).肿瘤的生长与其细胞沿激活状态连续谱的分布紧密相关。本研究通过与成年小鼠神经干细胞的比对，系统解析了胶质母细胞瘤（Glioblastoma, GBM）患者队列中的激活状态架构（Activation State Architecture, ASA）。基于上述数据构建的模型可预测肿瘤细胞如何组织以维持生长，并确定激活速率为肿瘤生长的核心预测因子。据此，静息细胞比例更高的患者预后更佳。此外，DNA甲基化芯片可实现与ASA相关的患者分层。通过比对健康与恶性组织的基因表达动态，研究发现Wnt拮抗剂SFRP1在静息态向激活态的转换过程中存在表达失调。SFRP1过表达可使GBM细胞进入静息态，并延长荷瘤小鼠的总生存期。令人意外的是，其作用机制是将肿瘤的干细胞样甲基化组重编程为星形胶质细胞样甲基化组。本研究结果为患者分层、生物标志物鉴定以及开发阻断GBM进展的治疗策略提供了理论框架。本研究预印本发布于bioRxiv平台。 数据 confocal_raw.zip 包含感兴趣区域（ROIs）的最大投影染色图像。由于体积过大，用于细胞核分割的3D共聚焦原始图像未包含在内，但可应要求提供。该数据集的体素尺寸为(1., 0.142, 0.142) 微米/像素。 confocal_segmentation.zip 包含使用mesmer工具与自定义3D拼接方法得到的细胞核分割结果。 resolve_raw.zip 包含Resolve Bioscience公司产出的原始数据，即原始3D转录本计数与2D DAPI染色图像。 resolve_registered.zip 包含经过3D配准后的空间转录本计数数据，其坐标系与共聚焦图像及分割结果保持一致。 segmentation_pipeline.zip 包含用于将原始图像与转录本计数数据处理为最终分割细胞的代码。 segmentation_result.zip 包含分割的最终结果，以及用于细胞类型注释与邻域富集分析的代码。 用于处理与分割空间数据的代码也可在GitHub（anders-biostat/ResolveTools）获取。 参数说明 原始转录本与Resolve DAPI图像完成配准，其体素尺寸为(0.3125, 0.138, 0.138) 微米（对应zyx轴）。 本研究使用的共聚焦图像体素尺寸为(1., 0.142, 0.142) 微米（对应zyx轴）。