ArticleGenome medicine2022
Transcriptional signatures of the BCL2 family for individualized acute myeloid leukaemia treatment.
Article in Genome medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- Article
- Review
- Apoptosis-targeting BH3 mimetics: transforming treatment for patients with acute myeloid leukaemia.Nature reviews. Clinical oncology · 2025Review
- Targeting mitochondrial RNAs enhances the efficacy of the DNA-demethylating agents.Scientific reports · 2024Article
- Application of omics in the diagnosis, prognosis, and treatment of acute myeloid leukemia.Biomarker research · 2024Review
- Predicting the risk of primary Sjögren's syndrome with key N7-methylguanosine-related genes: A novel XGBoost model.Heliyon · 2024Article
- Single-cell transcriptomics dissects the transcriptome alterations of hematopoietic stem cells in myelodysplastic neoplasms.Journal of translational medicine · 2024Article
- Comprehensive analysis of clinical prognostic features and tumor microenvironment landscape of CD11bCellular oncology (Dordrecht, Netherlands) · 2023Article
- Proteomic analysis identifies HMGA2 as a novel biomarker of overall survival in papillary renal cell carcinoma.Cancer medicine · 2023Article
- Identification of disulfidptosis-related genes and immune infiltration in lower-grade glioma.Open medicine (Warsaw, Poland) · 2023Article
- Transcriptional signatures of the BCL2 family for individualized acute myeloid leukaemia treatment.Genome medicine · 2022Article
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Authors and funding
9 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlthough anti-apoptotic proteins of the B-cell lymphoma-2 (BCL2) family have been utilized as therapeutic targets in acute myeloid leukaemia (AML), their complicated regulatory networks make individualized therapy difficult. This study aimed to discover the transcriptional signatures of BCL2 family genes that reflect regulatory dynamics, which can guide individualized therapeutic strategies.
methodsFrom three AML RNA-seq cohorts (BeatAML, LeuceGene, and TCGA; n = 451, 437, and 179, respectively), we constructed the BCL2 family signatures (BFSigs) by applying an innovative gene-set selection method reflecting biological knowledge followed by non-negative matrix factorization (NMF). To demonstrate the significance of the BFSigs, we conducted modelling to predict response to BCL2 family inhibitors, clustering, and functional enrichment analysis. Cross-platform validity of BFSigs was also confirmed using NanoString technology in a separate cohort of 47 patients.
resultsWe established BFSigs labeled as the BCL2, MCL1/BCL2, and BFL1/MCL1 signatures that identify key anti-apoptotic proteins. Unsupervised clustering based on BFSig information consistently classified AML patients into three robust subtypes across different AML cohorts, implying the existence of biological entities revealed by the BFSig approach. Interestingly, each subtype has distinct enrichment patterns of major cancer pathways, including MAPK and mTORC1, which propose subtype-specific combination treatment with apoptosis modulating drugs. The BFSig-based classifier also predicted response to venetoclax with remarkable performance (area under the ROC curve, AUROC = 0.874), which was well-validated in an independent cohort (AUROC = 0.950). Lastly, we successfully confirmed the validity of BFSigs using NanoString technology.
conclusionsThis study proposes BFSigs as a biomarker for the effective selection of apoptosis targeting treatments and cancer pathways to co-target in AML.
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