ArticleNature communications2022
Integrative multi-omics and drug response profiling of childhood acute lymphoblastic leukemia cell lines.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed, 52 citations in OpenAlex.
- Differential protein expression analysis of quantitative mass spectrometry data using DEqMS.Nature protocols · 2026Review
- Proteomic Profiling of Bone Marrow Aspirates from Patients with Methotrexate- and Vincristine-Resistant B-Cell Acute Lymphoblastic Leukemia: A Retrospective Analysis.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Article
- An integrative molecular map of pediatric B-cell precursor acute lymphoblastic leukemia.Communications medicine · 2026Article
- The clinical characteristics and prognosis analysis of acute B-cell lymphoblastic leukemia with MEF2D fusions.Annals of hematology · 2026Article
- Integrative Multiomics and Drug Sensitivity Profiling Reveal Potential Biomarkers and Therapeutic Strategies in Pediatric Solid Tumors.Cancer research · 2026Article
- Article
- SIMD: Synergistic integration mutualistic platform based on single-cell and proteotranscriptomics for drug repositioning.NPJ breast cancer · 2025Article
- G2PDeep-v2: A Web-Based Deep-Learning Framework for Phenotype Prediction and Biomarker Discovery for All Organisms Using Multi-Omics Data.Biomolecules · 2025Article
- Novel molecular mechanisms of FLT3 deregulation: from the acute myeloid leukemia experience to therapeutic insights in acute lymphoblastic leukemia.Molecular cancer · 2025Review
- A Decade of Transformation in the Management of Childhood Acute Lymphoblastic Leukemia: From Conventional Chemotherapy to Precision Medicine.Pediatric reports · 2025Review
- Transcriptional regulation of Ligase IV by an intronic regulatory element directs thymocyte development.Genes and immunity · 2025Article
- Identification of Cancer-Associated Proteins in Colorectal Cancer Using Mass Spectrometry.Proteomes · 2025Article
- Molecular mechanisms of unique therapeutic potential of CUDC-907 for MEF2D fusion-driven BCP-ALL.Signal transduction and targeted therapy · 2025Article
- Ex vivo drug responses and molecular profiles of 597 pediatric acute lymphoblastic leukemia patients.HemaSphere · 2025Article
- Deep transfer learning approach for automated cell death classification reveals novel ferroptosis-inducing agents in subsets of B-ALL.Cell death & disease · 2025Article
- KMT2A degradation is observed in decitabine-responsive acute lymphoblastic leukemia cells.Molecular oncology · 2025Article
- Algorithms and tools for data-driven omics integration to achieve multilayer biological insights: a narrative review.Journal of translational medicine · 2025Review
- H1-0 is a specific mediator of the repressive ETV6::RUNX1 transcriptional landscape in preleukemia and B cell acute lymphoblastic leukemia.HemaSphere · 2025Article
- A multiomic characterization of the leukemia cell line REH using short- and long-read sequencing.Life science alliance · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Although standard-of-care chemotherapeutics are sufficient for most ALL cases, there are subsets of patients with poor response who relapse in disease. The biology underlying differences between subtypes and their response to therapy has only partially been explained by genetic and transcriptomic profiling. Here, we perform comprehensive multi-omic analyses of 49 readily available childhood ALL cell lines, using proteomics, transcriptomics, and pharmacoproteomic characterization. We connect the molecular phenotypes with drug responses to 528 oncology drugs, identifying drug correlations as well as lineage-dependent correlations. We also identify the diacylglycerol-analog bryostatin-1 as a therapeutic candidate in the MEF2D-HNRNPUL1 fusion high-risk subtype, for which this drug activates pro-apoptotic ERK signaling associated with molecular mediators of pre-B cell negative selection. Our data is the foundation for the interactive online Functional Omics Resource of ALL (FORALL) with navigable proteomics, transcriptomics, and drug sensitivity profiles at https://proteomics.se/forall .
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.