ArticleBlood advances2023
A comprehensive landscape of transcription profiles and data resources for human leukemia.
Article in Blood advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Epigenetics and In Silico Transcriptome Analysis of Pediatric Acute Myeloid Leukemia.European journal of haematology · 2026Review
- Biological Data Resources and Machine Learning Frameworks for Hematology Research.Genomics, proteomics & bioinformatics · 2025Review
- Patterns and variations of copy number alterations in acute myeloid leukemia: insights from the LeukAtlas database.Leukemia · 2025Article
- Bridging the Gap in Cancer Research: Sulfur Metabolism of Leukemic Cells with a Focus on L-Cysteine Metabolism and Hydrogen Sulfide-Producing Enzymes.Biomolecules · 2024Review
- Mitochondrial abnormalities as a target of intervention in acute myeloid leukemia.Frontiers in oncology · 2024Review
- Novel circular RNAs of the apoptosis-related BAX and BCL2L12 genes identified in a chronic lymphocytic leukemia cell line using nanopore sequencing.FEBS open bio · 2023Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As a heterogeneous group of hematologic malignancies, leukemia has been widely studied at the transcriptome level. However, a comprehensive transcriptomic landscape and resources for different leukemia subtypes are lacking. Thus, in this study, we integrated the RNA sequencing data sets of >3000 samples from 14 leukemia subtypes and 53 related cell lines via a unified analysis pipeline. We depicted the corresponding transcriptomic landscape and developed a user-friendly data portal LeukemiaDB. LeukemiaDB was designed with 5 main modules: protein-coding gene, long noncoding RNA (lncRNA), circular RNA, alternative splicing, and fusion gene modules. In LeukemiaDB, users can search and browse the expression level, regulatory modules, and molecular information across leukemia subtypes or cell lines. In addition, a comprehensive analysis of data in LeukemiaDB demonstrates that (1) different leukemia subtypes or cell lines have similar expression distribution of the protein-coding gene and lncRNA; (2) some alternative splicing events are shared among nearly all leukemia subtypes, for example, MYL6 in A3SS, MYB in A5SS, HMBS in retained intron, GTPBP10 in mutually exclusive exons, and POLL in skipped exon; (3) some leukemia-specific protein-coding genes, for example, ABCA6, ARHGAP44, WNT3, and BLACE, and fusion genes, for example, BCR-ABL1 and KMT2A-AFF1 are involved in leukemogenesis; (4) some highly correlated regulatory modules were also identified in different leukemia subtypes, for example, the HOXA9 module in acute myeloid leukemia and the NOTCH1 module in T-cell acute lymphoblastic leukemia. In summary, the developed LeukemiaDB provides valuable insights into oncogenesis and progression of leukemia and, to the best of our knowledge, is the most comprehensive transcriptome resource of human leukemia available to the research community.
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Registered trials
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