Learning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysis
Abstract Acute myeloid leukemia (AML) is caused by proliferation of mutated myeloid progenitor cells. The standard chemotherapy regimen does not efficiently cause remission as there is a high relapse rate. Resistance acquired by leukemic stem cells is suggested to be one of the root causes of relaps...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-05-01
|
| Series: | BioData Mining |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13040-025-00444-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850270869777022976 |
|---|---|
| author | Suruthy Sivanathan Ting Hu |
| author_facet | Suruthy Sivanathan Ting Hu |
| author_sort | Suruthy Sivanathan |
| collection | DOAJ |
| description | Abstract Acute myeloid leukemia (AML) is caused by proliferation of mutated myeloid progenitor cells. The standard chemotherapy regimen does not efficiently cause remission as there is a high relapse rate. Resistance acquired by leukemic stem cells is suggested to be one of the root causes of relapse. Therefore, there is an urgency to develop new drugs for therapy. Repurposing approved drugs for AML can provide a cost-friendly, time-efficient, and affordable alternative. The multiscale interactome network is a computational tool that can identify potential therapeutic candidates by comparing mechanisms of the drug and disease. Communities that could be potentially experimentally validated are detected in the multiscale interactome network using the algorithm CRank. The results are evaluated through literature search and Gene Ontology (GO) enrichment analysis. In this research, we identify therapeutic candidates for AML and their mechanisms from the interactome, and isolate prioritized communities that are dominant in the therapeutic mechanism that could potentially be used as a prompt for pre-clinical/translational research (e.g. bioinformatics, laboratory research) to focus on biological functions and mechanisms that are associated with the disease and drug. This method may allow for an efficient and accelerated discovery of potential candidates for AML, a rapidly progressing disease. |
| format | Article |
| id | doaj-art-290970ca41ef489f9d3de1573dcc80fb |
| institution | OA Journals |
| issn | 1756-0381 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BioData Mining |
| spelling | doaj-art-290970ca41ef489f9d3de1573dcc80fb2025-08-20T01:52:25ZengBMCBioData Mining1756-03812025-05-0118112710.1186/s13040-025-00444-xLearning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysisSuruthy Sivanathan0Ting Hu1School of Computing and the Department of Biomedical and Molecular Sciences, Queen’s UniversitySchool of Computing, Queen’s UniversityAbstract Acute myeloid leukemia (AML) is caused by proliferation of mutated myeloid progenitor cells. The standard chemotherapy regimen does not efficiently cause remission as there is a high relapse rate. Resistance acquired by leukemic stem cells is suggested to be one of the root causes of relapse. Therefore, there is an urgency to develop new drugs for therapy. Repurposing approved drugs for AML can provide a cost-friendly, time-efficient, and affordable alternative. The multiscale interactome network is a computational tool that can identify potential therapeutic candidates by comparing mechanisms of the drug and disease. Communities that could be potentially experimentally validated are detected in the multiscale interactome network using the algorithm CRank. The results are evaluated through literature search and Gene Ontology (GO) enrichment analysis. In this research, we identify therapeutic candidates for AML and their mechanisms from the interactome, and isolate prioritized communities that are dominant in the therapeutic mechanism that could potentially be used as a prompt for pre-clinical/translational research (e.g. bioinformatics, laboratory research) to focus on biological functions and mechanisms that are associated with the disease and drug. This method may allow for an efficient and accelerated discovery of potential candidates for AML, a rapidly progressing disease.https://doi.org/10.1186/s13040-025-00444-xAcute myeloid leukemia (AML)DrugsTherapeutic targetsHuman interactomeNetworksCommunity detection |
| spellingShingle | Suruthy Sivanathan Ting Hu Learning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysis BioData Mining Acute myeloid leukemia (AML) Drugs Therapeutic targets Human interactome Networks Community detection |
| title | Learning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysis |
| title_full | Learning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysis |
| title_fullStr | Learning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysis |
| title_full_unstemmed | Learning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysis |
| title_short | Learning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysis |
| title_sort | learning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysis |
| topic | Acute myeloid leukemia (AML) Drugs Therapeutic targets Human interactome Networks Community detection |
| url | https://doi.org/10.1186/s13040-025-00444-x |
| work_keys_str_mv | AT suruthysivanathan learningthetherapeutictargetsofacutemyeloidleukemiathroughmultiscalehumaninteractomenetworkandcommunityanalysis AT tinghu learningthetherapeutictargetsofacutemyeloidleukemiathroughmultiscalehumaninteractomenetworkandcommunityanalysis |