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PTBP1 knockdown reprograms glioma stem cells into neuronal-like cells and suppresses tumorigenesis via the DUSP5-ERK1/2 signaling pathway.

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Paper

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The authors' code

Python · 38 lines · 1.8 KB · no license

  1. from util import *
  2. import csv
  4. def main():
  5. set_seed(1)
  6. device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
  7. test_dataset = SegmentationDataset('data/test_images', 'data/test_labels', transform_image=transforms.ToTensor())
  8. test_loader = DataLoader(test_dataset, batch_size=4, shuffle=False, num_workers=0)
  9. unlabeled = None
  10. if os.path.exists('data/unlabeled_images'):
  11. unlabeled = UnlabeledDataset('data/unlabeled_images', transform=transforms.ToTensor())
  12. weights = compute_class_weights(test_dataset).to(device)
  13. model = NestedUNet(in_ch=3, out_ch=3, deep_supervision=False).to(device)
  14. if os.path.exists('model.pth'):
  15. model.load_state_dict(torch.load('model.pth', map_location=device))
  16. else:
  17. print('Model file not found.'); return
  18. criterion = nn.CrossEntropyLoss(weight=weights)
  19. print("Testing on labeled test set...")
  20. test_model(model, test_loader, criterion, device)
  21. print("Saving visualized results...")
  22. if unlabeled:
  23. print("Processing unlabeled...")
  24. results = save_final_unlabeled_results_and_counts(model, unlabeled, device)
  25. csv_path = os.path.join('final_result_labeled', 'unlabeled_results.csv')
  26. with open(csv_path, 'w', newline='', encoding='utf-8') as f:
  27. writer = csv.writer(f)
  28. writer.writerow(['img_idx','cellA','cellB'])
  29. writer.writerows(results)
  30. print(f'Unlabeled CSV saved to {csv_path}')
  31. print("Computing macro recall...")
  32. names, recalls = compute_macro_recall_for_cells(model, test_dataset, device)
  33. plot_macro_recall_bar_chart(names, recalls, os.path.join('final_result_labeled','macro_recall_barplot.png'))
  34. print("Plotting ROC combined...")
  35. roc_per_sample_and_plot(model, test_dataset, device)
  37. if __name__ == '__main__':
  38. main()

test.py at commit c1d46ba, no license · at the source

Overview

Authors: Cunyu Li1, Manyu Chen2, Songyi Guo3, Yuhao Ma4, Suli Zhang1, Guanwei Li1, Jianqi Wu3, Tianqi Liu3, Yueyi Jin5, Xing Liu3,6, Hu Zhao7, Hongmei Liu8, Sijin Wu5,9, Hangjin Jiang10, Wen Cheng3, Anhua Wu3, Shuang Hao1
ORCID iDs: Manyu Chen, Songyi Guo, Guanwei Li, Tianqi Liu, Xing Liu, Hu Zhao, Sijin Wu, Hangjin Jiang, Shuang Hao
  1. College of Life and Health Sciences, Northeastern University, Shenyang, China
  2. Capital Medical University School of Basic Medicine & Chinese Institute for Brain Research, Beijing, China
  3. Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, China
  4. School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, China
  5. Academy of Pharmacy, Xi’an Jiaotong-Liverpool University, Suzhou, China
  6. Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, China
  7. Chinese Institute for Brain Research, Beijing, China
  8. Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China
  9. Engineering Research Center of RNA Medicine and Cell Therapy Technology, Ministry of Education, Suzhou, China (S.W.)
  10. Center for Data Science, Zhejiang University, Hangzhou, China
Institutions: Northeastern University (China); Capital Medical University (China); Chinese Institute for Brain Research (China); Sheng Jing Hospital (China); China Medical University (China); Zhejiang Gongshang University (China); Xi’an Jiaotong-Liverpool University (China); First Hospital of China Medical University (China); Southern University of Science and Technology (China); Zhejiang University (China)
Journal: Neuro-oncology, volume 28, issue 7, pages 1694-1710
Dates: received 18 August 2025; accepted 23 March 2026; published online 28 March 2026; in print July 2026
Type: Research article · Language: English
License: CC BY-NC
Identifiers: DOI 10.1093/neuonc/noag068 · PMID 41903206 · PMCID PMC13338330 · OpenAlex W7142334936
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), mouse (organism), other condition (population), cellular / molecular (subfield)
Methods: Statistics
Keywords: A2-PLGA/venetoclax, cell differentiation, glioma stem cells, neuronal-like cells, PTBP1
MeSH: Brain Neoplasms*, Glioma*, Heterogeneous-Nuclear Ribonucleoproteins*, MAP Kinase Signaling System*, Neoplastic Stem Cells*, Neurons*, Polypyrimidine Tract-Binding Protein*, Animals, Carcinogenesis, Cell Proliferation, Gene Expression Regulation, Neoplastic, Gene Knockdown Techniques, Humans, Mice, Tumor Cells, Cultured (* major topic)
Journal subjects: Basic and Translational Investigations
Topic: Protein Tyrosine Phosphatases (Molecular Biology, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: Experimental Technology Center; College of Life Science and Health; Northeastern University; National Natural Science Foundation of China (National Science Foundation of China) (81901163, 82371180, 82472833); Thousand Young Talents Program of China (QNQR-2021-02); Liaoning Xingliao Yingcai (XLYC1907141); SIP High-Quality Innovation Platform for Chronic Diseases (YZCXPT2022203); XJTLU Research Development Fund (RDF-23-01-100)
Citations: not cited yet (Europe PMC); 48 references in the paper

Abstract

Background: Glioblastoma (GBM), the most prevalent and aggressive primary brain tumor in adults, has a median survival of merely 14 months. Current therapeutic approaches, including maximal safe resection, radiotherapy, and temozolomide-based chemotherapy, have limited efficacy owing to resistance and the high rate of recurrence.

Methods: We analyzed H&E-stained specimens from 65 patients with glioma using deep learning-based morphological classification and analyzed a mouse model through tissue clearing and 3D imaging. Integrated transcriptomic and single-cell RNA-seq analyses identified PTBP1 as a morphology regulator. We validated the function of PTBP1 through lentiviral knockdown in vitro and in orthotopic models and performed structure-based drug screening against PTBP1 with experimental validation.

Results: We detected a clinically significant association between glioma cell morphology and patient survival times. Mechanistically, PTBP1, an RNA-binding protein abundantly expressed in glioma cells, regulated dual-specificity phosphatase 5 (DUSP5) expression post-transcriptionally and modulate ERK1/2 phosphorylation dynamics, thus reducing glioma stem cell proliferation and enhancing differentiation into neuronal-like cells to suppress tumor growth. Importantly, we developed a nanotherapeutic strategy using A2-PLGA/venetoclax; this strategy repurposes venetoclax, a known clinical drug for leukemia, as a PTBP1-targeting agent that effectively suppresses glioma progression in mouse models.

Conclusion: Our findings establish a novel PTBP1/DUSP5/ERK1/2 axis governing glioma stem cell proliferation and differentiation and identify the A2-PLGA/venetoclax nanoparticle as a mechanistically justified therapeutic candidate for glioblastoma.

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above.

YuhaoMa522/Glioma-CellCounter

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: c1d46ba47ae6cc7504607d9ecea422a9f942ef42, 22 July 2025
Languages: Python (3)
Size: 211 files, 3 scripts
Software Heritage: not archived
Found in: “Code Availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Matplotlib (1 file), NumPy (1 file), OpenCV (1 file), pandas (1 file), Pillow (1 file), PyTorch (1 file), scikit-learn (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
4 files
At the source: github.com/YuhaoMa522/Glioma-CellCounter

Code Availability

The code for analysis of tumor cell morphology in human glioma tissue is available at https://github.com/YuhaoMa522/Glioma-CellCounter.

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 3 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data Availability

The raw single-cell RNA-sequencing data of glioma clinical samples have been deposited in the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences under accession code HRA011504 and are accessible at https://ngdc.cncb.ac.cn/gsa-human/. Clinical data used in this study can be obtained by contacting the corresponding author.

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 17 authors, 5 keywords, 15 MeSH terms, 8 funders, 48 references.

Cite

This paper

Li, C., Chen, M., Guo, S., Ma, Y., Zhang, S., Li, G., Wu, J., Liu, T., Jin, Y., Liu, X., Zhao, H., Liu, H., Wu, S., Jiang, H., Cheng, W., Wu, A., & Hao, S. (2026). PTBP1 knockdown reprograms glioma stem cells into neuronal-like cells and suppresses tumorigenesis via the DUSP5-ERK1/2 signaling pathway. Neuro-oncology, 28(7), 1694-1710. https://doi.org/10.1093/neuonc/noag068

BibTeX

@article{li2026ptbp1,
author = {Li, Cunyu and Chen, Manyu and Guo, Songyi and Ma, Yuhao and Zhang, Suli and Li, Guanwei and Wu, Jianqi and Liu, Tianqi and Jin, Yueyi and Liu, Xing and Zhao, Hu and Liu, Hongmei and Wu, Sijin and Jiang, Hangjin and Cheng, Wen and Wu, Anhua and Hao, Shuang},
title = {{PTBP1 knockdown reprograms glioma stem cells into neuronal-like cells and suppresses tumorigenesis via the DUSP5-ERK1/2 signaling pathway}},
journal = {Neuro-oncology},
year = {2026},
month = jul,
volume = {28},
number = {7},
pages = {1694--1710},
publisher = {Oxford University Press},
issn = {1522-8517},
doi = {10.1093/neuonc/noag068},
url = {https://doi.org/10.1093/neuonc/noag068},
pmid = {41903206},
pmcid = {PMC13338330}
}

RIS

TY - JOUR
AU - Li, Cunyu
AU - Chen, Manyu
AU - Guo, Songyi
AU - Ma, Yuhao
AU - Zhang, Suli
AU - Li, Guanwei
AU - Wu, Jianqi
AU - Liu, Tianqi
AU - Jin, Yueyi
AU - Liu, Xing
AU - Zhao, Hu
AU - Liu, Hongmei
AU - Wu, Sijin
AU - Jiang, Hangjin
AU - Cheng, Wen
AU - Wu, Anhua
AU - Hao, Shuang
TI - PTBP1 knockdown reprograms glioma stem cells into neuronal-like cells and suppresses tumorigenesis via the DUSP5-ERK1/2 signaling pathway
T2 - Neuro-oncology
J2 - Neuro Oncol
PY - 2026
DA - 2026/07/01
VL - 28
IS - 7
SP - 1694
EP - 1710
SN - 1522-8517
PB - Oxford University Press
DO - 10.1093/neuonc/noag068
UR - https://doi.org/10.1093/neuonc/noag068
LA - en
ER -

CSL-JSON

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