Perturbation data for glioblastoma: radiotherapy, drugs and CRISPR胶质母细胞瘤扰动数据：放疗、药物与 CRISPR
Review pending待审阅 Version 0.1.0 · status: draft · last expert review: not yet reviewed版本 0.1.0 · 状态：初稿 · 最近专家审阅：尚未审阅
Research question研究问题
- What perturbation data exist for glioblastoma?胶质母细胞瘤有哪些扰动数据？
- Why do virtual cells need perturbation data?虚拟细胞为什么需要扰动数据？
Current understanding当前认识
Virtual cells learn how states respond to interventions, which requires perturbation data. For GBM the library contains in vivo Perturb-seq with radiotherapy in mouse models, drug-signature integration, organoid drug screens and one organoid temozolomide preprint; large-scale perturbation atlases are mostly non-GBM.虚拟细胞要学习状态对干预的反应，需要扰动数据。文献库中 GBM 相关的有：小鼠模型中结合放疗的体内 Perturb-seq、药物特征谱整合、类器官药物筛选，以及一项类器官替莫唑胺预印本；大规模扰动图谱大多非 GBM。
In vivo Perturb-seq (CRISPRi delivered intracranially in mouse GBM models) silenced drivers of tumor growth and genes that sensitise to radiotherapy, and showed radiotherapy rewires transcriptional responses to perturbations.体内 Perturb-seq（在小鼠 GBM 模型中颅内递送 CRISPRi）沉默了肿瘤生长驱动基因和放疗增敏基因，并显示放疗会重塑细胞对扰动的转录反应。 VC0070
Drug perturbations: scFOCAL uses LINCS L1000 signatures against GBM single-cell states; an automated personalised GBM organoid drug-screening platform; DELPHAI (preprint) models temozolomide responses in organoids.药物扰动：scFOCAL 将 LINCS L1000 特征谱与 GBM 单细胞状态比对；自动化个体化 GBM 类器官药物筛选平台；DELPHAI（预印本）建模类器官的替莫唑胺反应。 VC0132 VC0097 VC0129 · preprint · 预印本
Large general perturbation resources — genome-scale Perturb-seq in K562/RPE1 and Tahoe-100M (1,100 drugs across 50 cancer cell lines) — are the main training data for current models but are not GBM-focused.大型通用扰动资源——K562/RPE1 基因组规模 Perturb-seq 与 Tahoe-100M（50 种癌细胞系 × 1,100 种药物）——是当前模型的主要训练数据，但并非聚焦 GBM。 VC0040 VC0041 · preprint · 预印本 VC0042
Evidence map证据图谱
Primary studies & datasets原始研究与数据集
- VC0070 In vivo perturb-seq of cancer and microenvironment cells dissects oncologic drivers and radiotherapy responses in glioblastoma. — Liu SJ et al., Genome biology, 2024
- VC0132 Drug and single-cell gene expression integration identifies sensitive and resistant glioblastoma cell populations — Suter et al., Nature Communications, 2026
- VC0097 Automated and personalized glioblastoma tumor organoid drug screening platform exposes sensitivity to proteasome and HDAC inhibitors. — Jungwirth G et al., NPJ precision oncology, 2026
- VC0095 BRD2 bromodomain-mediated regulation of cell state plasticity modulates therapy response in glioblastoma. — Vadla R et al., Neuro-oncology, 2025
Related models & tools相关模型与工具
- VC0129 · preprint · 预印本 DELPHAI, AI Agent for Predicting Drug Response and Resistance — Peng et al., preprint, 2025
- VC0019 Predicting cellular responses to perturbation across diverse contexts with State. — Adduri AK et al., Cell, 2026
- VC0130 UniPert-G2CP bridges genetic and chemical screens from molecular representation to phenotype modeling — Li et al., Cell, 2026
Perturbation & validation evidence扰动与验证证据
- VC0040 Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq. — Replogle JM et al., Cell, 2022
- VC0042 Tahoe-100M: Mapping drug-induced molecular phenotypes at single-cell resolution. — Zhang J et al., Cell, 2026
- VC0048 Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines. — Ahlmann-Eltze C, Huber W, Anders S., Nature methods, 2025
11 library items cited on this page; 2 are preprints (not peer reviewed).本页引用文献库条目 11 条，其中预印本（未经同行评审）2 条。
What remains uncertain尚不确定之处
Whether glioma cell lines are included in Tahoe-100M, and how well cell-line results transfer to tumors, was not checked for this page.本页未核实 Tahoe-100M 是否包含胶质瘤细胞系，以及细胞系结果向肿瘤的可迁移性。 VC0042
Mouse in vivo perturbation results may not reflect human GBM.小鼠体内扰动结果未必反映人类 GBM。 VC0070
For research and education only. Not medical advice and not a recommendation of any diagnosis, treatment or product. Patients should consult their own physicians.仅供科研与教育参考，不构成医疗建议，也不构成对任何诊疗或产品的推荐。患者请咨询主治医生。