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LTF promotes central nervous system leukemia progression via neutrophil serine proteases.

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Paper

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The authors' code

R · 40 lines · 1.1 KB · no license

  1. # if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")
  2. # BiocManager::install(c("clusterProfiler", "org.Hs.eg.db", "AnnotationDbi", "GO.db"))
  3. # Gene symbols associated with GO terms were retrieved using AnnotationDbi v1.64.1, clusterProfiler v4.10.0, org.Hs.eg.db v3.18.0, and GO.db v3.18.0. GO annotations were based on GOALL mappings.
  4. library(clusterProfiler)
  5. library(org.Hs.eg.db)
  6. library(AnnotationDbi)
  7. library(GO.db)
  8. get_go_gene_symbols <- function(go_ids,
  9. OrgDb = org.Hs.eg.db,
  10. keytype = "GOALL") {
  11. valid_go <- keys(GO.db, keytype = "GOID")
  12. invalid_go <- setdiff(go_ids, valid_go)
  13. if (length(invalid_go) > 0) {
  14. warning("The following GO IDs were not found in GO.db:",
  15. paste(invalid_go, collapse = ", "))
  16. }
  17. go_ids <- intersect(go_ids, valid_go)
  18. if (length(go_ids) == 0) {
  19. return(data.frame())
  20. }
  21. gene_df <- AnnotationDbi::select(
  22. OrgDb,
  23. keys = go_ids,
  24. keytype = keytype,
  25. columns = c("SYMBOL", "ENTREZID", "GOALL", "ONTOLOGYALL")
  26. )
  27. return(gene_df)
  28. }
  29. result <- get_go_gene_symbols("GO:0001817")

GO_Gene_Search.R at commit 04b1472, no license · at the source

Overview

Authors: Yiran Zhang1,2, Huasong Yu1,2, Zhongxiang Jiao1,2, Ming Yang1,2, Wenshan Zhang1,2, Chaoqun Wang1,2,3, Hexiao Zhang1,2, Wei Wang1,2, Minghe Zhang1,2, Xiaoyue Li1,2, Lin Song1,2, Bo Jiang1,2, Junyuan Qi1,2, Yinghui Li1,2, Yingdai Gao1,2
  1. State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
  2. Tianjin Institutes of Health Science, Tianjin, China
  3. Department of Pharmacy, Children’s Hospital of Soochow University, Suzhou, Jiangsu, China
Journal: Frontiers in pharmacology, volume 17, article 1813396
Dates: received 18 February 2026; accepted 24 April 2026; published online 1 July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.3389/fphar.2026.1813396 · PMID 42460014 · PMCID PMC13368923 · OpenAlex W7166889068
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: mouse (organism)
Methods: Connectivity, Statistics, Smoothing, state filtering, decompositions, Machine learning, Evoked potentials
Keywords: acute myeloid leukemia, central nervous system leukemia, lactoferrin, neutrophil serine proteases, brensocatib
Topic: Acute Myeloid Leukemia Research (Hematology, Medicine), according to OpenAlex
Citations: not cited yet (Europe PMC); 47 references in the paper

Abstract

Introduction: Central nervous system (CNS) infiltration is a severe complication of acute myeloid leukemia (AML), often leading to relapse and poor prognosis. The underlying mechanisms remain poorly understood, limiting the development of effective targeted therapies. Conventional chemotherapy agents capable of crossing the blood-brain barrier (BBB) carry significant toxicity and fail to eliminate leukemia stem cells.

Methods: Using multiple clinical cohorts, we established prognostic prediction model for AML. Using knockdown and overexpression experiments in a mouse leukemia CNS infiltration model, the role of risk factor gene in CNS infiltration was evaluated, along with the attenuating effect of its downstream proteins drug inhibition on leukemia CNS infiltration.

Results: We identify Lactoferrin (LTF) as a risk factor associated with poor AML prognosis using a machine learning–based prognostic model. Through LTF knockdown and overexpression in a mouse leukemia model, we demonstrate its pivotal role in CNS invasion. Mechanistically, neutrophil serine proteases (NSPs) act as downstream effectors of LTF, and pharmacological inhibition with Brensocatib effectively blocks AML cell entry into the brain.

Discussion: Our findings establish LTF as a mediator of CNS infiltration in AML and highlight NSP inhibition as a promising therapeutic strategy.

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

Repository

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

HuasongYu/GO_Gene_Search

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 04b1472336011128baba16c42ac63c2d253d6864, 22 April 2026
Languages: R (1)
Size: 2 files, 1 script
Software Heritage: not archived
Found in: the text, “RNA-seq data processing”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: clusterProfiler (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
2 files

The paper's code and data availability statement is in the Data section.

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;
  • 1 script, 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

Other data links

Data availability statement

The datasets presented in this study can be found in GitHub (https://github.com/HuasongYu/MachineLearn).

Reproduced under the paper's license (CC BY), 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 2, 28 September 2026

  • Funding: added National Natural Science Foundation of China: 82370120; Tianjin Science and Technology Committee

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 15 authors, 5 keywords, 46 references.

Cite

This paper

Zhang, Y., Yu, H., Jiao, Z., Yang, M., Zhang, W., Wang, C., Zhang, H., Wang, W., Zhang, M., Li, X., Song, L., Jiang, B., Qi, J., Li, Y., & Gao, Y. (2026). LTF promotes central nervous system leukemia progression via neutrophil serine proteases. Frontiers in pharmacology, 17, 1813396. https://doi.org/10.3389/fphar.2026.1813396

BibTeX

@article{zhang2026ltf,
author = {Zhang, Yiran and Yu, Huasong and Jiao, Zhongxiang and Yang, Ming and Zhang, Wenshan and Wang, Chaoqun and Zhang, Hexiao and Wang, Wei and Zhang, Minghe and Li, Xiaoyue and Song, Lin and Jiang, Bo and Qi, Junyuan and Li, Yinghui and Gao, Yingdai},
title = {{LTF promotes central nervous system leukemia progression via neutrophil serine proteases}},
journal = {Frontiers in pharmacology},
year = {2026},
month = jul,
volume = {17},
pages = {1813396},
publisher = {Frontiers Media SA},
issn = {1663-9812},
doi = {10.3389/fphar.2026.1813396},
url = {https://doi.org/10.3389/fphar.2026.1813396},
pmid = {42460014},
pmcid = {PMC13368923}
}

RIS

TY - JOUR
AU - Zhang, Yiran
AU - Yu, Huasong
AU - Jiao, Zhongxiang
AU - Yang, Ming
AU - Zhang, Wenshan
AU - Wang, Chaoqun
AU - Zhang, Hexiao
AU - Wang, Wei
AU - Zhang, Minghe
AU - Li, Xiaoyue
AU - Song, Lin
AU - Jiang, Bo
AU - Qi, Junyuan
AU - Li, Yinghui
AU - Gao, Yingdai
TI - LTF promotes central nervous system leukemia progression via neutrophil serine proteases
T2 - Frontiers in pharmacology
J2 - Front Pharmacol
PY - 2026
DA - 2026/07/01
VL - 17
SP - 1813396
SN - 1663-9812
PB - Frontiers Media SA
DO - 10.3389/fphar.2026.1813396
UR - https://doi.org/10.3389/fphar.2026.1813396
LA - en
ER -

CSL-JSON

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