journal article·2024-08Open access

Single‐Cell Chromatin Accessibility Analysis Reveals Subgroup‐Specific TF‐NTR Regulatory Circuits in Medulloblastoma

Xiaoyue Gao, Qiyuan Zhuang, Yun Li, Guochao Li, Zheng Huang, Shenzhi Chen, Shaoxing Sun, Hui Yang, Lan Jiang, Ying Mao

Advanced Science· Volume 11· Issue 30

Abstract

Abstract Medulloblastoma (MB) stands as one of the prevalent malignant brain tumors among pediatric patients. Despite its prevalence, the intricate interplay between the regulatory program driving malignancy in MB cells and their interactions with the microenvironment remains insufficiently understood. Leveraging the capabilities of single‐cell Assay for Transposase‐Accessible Chromatin sequencing (scATAC‐seq), the chromatin accessibility landscape is unveiled across 59,015 distinct MB cells. This expansive dataset encompasses cells belonging to discrete molecular subgroups, namely SHH, WNT, Group3, and Group4. Within these chromatin accessibility profiles, specific regulatory elements tied to individual subgroups are uncovered, shedding light on the distinct activities of transcription factors (TFs) that likely orchestrate the tumorigenesis process. Moreover, it is found that certain neurotransmitter receptors (NTRs) are subgroup‐specific and can predict MB subgroup classification when combined with their associated transcription factors. Notably, targeting essential NTRs within tumors influences both the in vitro sphere‐forming capability and the in vivo tumorigenic capacity of MB cells. These findings collectively provide fresh insights into comprehending the regulatory networks and cellular dynamics within MBs. Furthermore, the significance of the TF‐NTR regulatory circuits is underscored as prospective biomarkers and viable therapeutic targets.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Glioma Diagnosis and Treatment · Single-cell and spatial transcriptomics · Genomics and Chromatin Dynamics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

CAS Key Laboratory of Genome Sciences and Information Beijing Institute of Genomics Chinese Academy of Sciences and China National Center for Bioinformation Beijing 100101 China

University of Chinese Academy of Sciences Beijing 100049 China

Department of Neurosurgery Huashan Hospital Fudan University Shanghai 200040 China

National Center for Neurological Disorders Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration Neurosurgical Institute of Fudan University Shanghai Clinical Medical Center of Neurosurgery Huashan Hospital Fudan University Shanghai 200040 China

Sino‐Danish College University of Chinese Academy of Sciences Beijing 100049 China

State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Institute for Translational Brain Research Shanghai Medical College Fudan University Shanghai 200032 China

College of Future Technology College University of Chinese Academy of Sciences Beijing 100049 China

Funding

National Key Research and Development Program of China · National Natural Science Foundation of China

References (49)

Show source-provided references
1. 10.1038/s41571-019-0177-510.1038/s41571-019-0177-5 ↗
2. 10.1038/s41572-019-0063-610.1038/s41572-019-0063-6 ↗
3. 10.1038/nrneurol.2012.7810.1038/nrneurol.2012.78 ↗
4. 10.1200/JCO.2011.34.937310.1200/JCO.2011.34.9373 ↗
5. 10.1007/s00401-011-0922-z10.1007/s00401-011-0922-z ↗
6. 10.1038/nature2297310.1038/nature22973 ↗
7. 10.1016/j.ccell.2017.05.00510.1016/j.ccell.2017.05.005 ↗
8. 10.1038/nature1654610.1038/nature16546 ↗
9. 10.1093/neuonc/noab10610.1093/neuonc/noab106 ↗
10. 10.1016/j.ccell.2016.03.00210.1016/j.ccell.2016.03.002 ↗
11. 10.1016/j.celrep.2021.10947510.1016/j.celrep.2021.109475 ↗
12. 10.1016/j.ccell.2017.02.00910.1016/j.ccell.2017.02.009 ↗
13. 10.1038/s41586-019-1434-610.1038/s41586-019-1434-6 ↗
14. 10.1038/s41568-019-0223-810.1038/s41568-019-0223-8 ↗
15. 10.1093/neuonc/noac21110.1093/neuonc/noac211 ↗
16. 10.1093/neuonc/noab13510.1093/neuonc/noab135 ↗
17. 10.1038/s41586-019-1158-710.1038/s41586-019-1158-7 ↗
18. 10.1038/s41586-022-05215-w10.1038/s41586-022-05215-w ↗
19. 10.1038/s41586-022-05208-910.1038/s41586-022-05208-9 ↗
20. Corces M. R. · Science · 2018 · 362
21. 10.1038/nature1337910.1038/nature13379 ↗
22. 10.1038/s41467-020-14667-510.1038/s41467-020-14667-5 ↗
23. 10.1038/s41588-021-00790-610.1038/s41588-021-00790-6 ↗
24. 10.1200/JCO.2009.27.432410.1200/JCO.2009.27.4324 ↗
25. 10.1158/1078-0432.CCR-14-114410.1158/1078-0432.CCR-14-1144 ↗
26. 10.1038/nature1132710.1038/nature11327 ↗
27. 10.1016/j.molcel.2018.06.04410.1016/j.molcel.2018.06.044 ↗
28. 10.1038/s42003-021-02099-w10.1038/s42003-021-02099-w ↗
29. 10.1016/j.celrep.2020.03.07510.1016/j.celrep.2020.03.075 ↗
30. 10.1093/nar/gky86410.1093/nar/gky864 ↗
31. 10.1093/nar/gkaa19710.1093/nar/gkaa197 ↗
32. 10.1038/nmeth.440110.1038/nmeth.4401 ↗
33. 10.1016/j.molonc.2013.12.00910.1016/j.molonc.2013.12.009 ↗
34. 10.1007/s11033-014-3716-210.1007/s11033-014-3716-2 ↗
35. 10.1038/s41586-019-1564-x10.1038/s41586-019-1564-x ↗
36. 10.1038/s41586-019-1563-y10.1038/s41586-019-1563-y ↗
37. Sarropoulos I. · Science · 2021 · 373
38. 10.1038/nrg368210.1038/nrg3682 ↗
39. 10.1038/s41388-019-1006-010.1038/s41388-019-1006-0 ↗
40. 10.1002/jcp.2551810.1002/jcp.25518 ↗
41. 10.1016/j.bbcan.2011.04.00510.1016/j.bbcan.2011.04.005 ↗
42. 10.1158/0008-5472.CAN-16-014410.1158/0008-5472.CAN-16-0144 ↗
43. 10.1146/annurev.pathmechdis.3.121806.15151810.1146/annurev.pathmechdis.3.121806.151518 ↗
44. 10.1126/science.aax752610.1126/science.aax7526 ↗
45. 10.1038/nature0958710.1038/nature09587 ↗
46. 10.1016/j.devcel.2018.12.01710.1016/j.devcel.2018.12.017 ↗
47. 10.1016/j.cell.2019.12.02410.1016/j.cell.2019.12.024 ↗
48. 10.1016/j.cell.2018.05.03310.1016/j.cell.2018.05.033 ↗
49. 10.1038/s41591-019-0522-310.1038/s41591-019-0522-3 ↗