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Decoding leukemia at the single-cell level: clonal architecture, classification, microenvironment, and drug resistance.

ABSTRACT: Leukemias are refractory hematological malignancies, characterized by marked intrinsic heterogeneity which poses significant obstacles to effective treatment. However, traditional bulk sequencing techniques have not been able to effectively unravel the heterogeneity among individual tumor cells. With the emergence of single-cell sequencing technology, it has bestowed upon us an unprecedented resolution to comprehend the mechanisms underlying leukemogenesis and drug resistance across various levels, including the genome, epigenome, transcriptome and proteome. Here, we provide an overview of the currently prevalent single-cell sequencing technologies and a detailed summary of single-cell studies conducted on leukemia, with a specific focus on four key aspects: (1) leukemia's clonal architecture, (2) frameworks to determine leukemia subtypes, (3) tumor microenvironment (TME) and (4) the drug-resistant mechanisms of leukemia. This review provides a comprehensive summary of current single-cell studies on leukemia and highlights the markers and mechanisms that show promising clinical implications for the diagnosis and treatment of leukemia.

SUBMITTER: Liu J

PROVIDER: S-EPMC10826069 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Decoding leukemia at the single-cell level: clonal architecture, classification, microenvironment, and drug resistance.

Liu Jianche J Jiang Penglei P Lu Zezhen Z Yu Zebin Z Qian Pengxu P

Experimental hematology & oncology 20240130 1

Leukemias are refractory hematological malignancies, characterized by marked intrinsic heterogeneity which poses significant obstacles to effective treatment. However, traditional bulk sequencing techniques have not been able to effectively unravel the heterogeneity among individual tumor cells. With the emergence of single-cell sequencing technology, it has bestowed upon us an unprecedented resolution to comprehend the mechanisms underlying leukemogenesis and drug resistance across various leve ...[more]

PMID: 38291542

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Project description:We used all five current human African trypanosomiasis drugs for genome-scale RNA interference (RNAi) target sequencing (RIT-seq) screens in Trypanosoma brucei, revealing the transporters, organelles, enzymes and metabolic pathways that function to facilitate anti-trypanosomal drug action. RIT-seq profiling links more than fifty additional genes to drug action. This data has been described in the following article [doi:10.1038/nature10771] and its further analysis can be freely submitted for publication. For information on the proper use of data shared by the Wellcome Trust Sanger Institute (including information on acknowledgement), please see http://www.sanger.ac.uk/datasharing/. Protocol - Assembly of the bloodstream-form T. brucei RNAi library and the RNAi target sequencing (RIT-seq) approach were reported previously (Alsford, S. et al. High-throughput phenotyping using parallel sequencing of RNA interference targets in the African trypanosome. Genome Res 21, 915-924, 264 doi:gr.115089.110 [pii] 265 10.1101/gr.115089.110 (2011). Briefly, a tetracycline-inducible RNAi plasmid library, containing randomly sheared genomic fragments (mean ~600 bp) under the control of head-to-head T7 promoters, was targeted to a single genomic locus that had been validated for robust expression. For this study, the library was grown under inducing conditions with drug selection and genomic DNA was isolated from surviving populations. For chemical RIT-seq profiling, adapter-ligated sequencing libraries were prepared from each genomic DNA sample and used to amplify DNA fragments containing RNAi cassette-insert junctions in semi-specific PCR reactions; one primer was specific for the RNAi vector and the other for the Illumina adapter. Size-selected DNA was sequenced with 76 cycle paired-end runs on an Illumina GAII. Illumina sequencing reads containing a nine-base RNAi vector junction sequence were then mapped to the T. brucei reference genome. Where loss of function increases drug tolerance, RNAi-target sequence representation is increased relative to the otherwise susceptible population, revealing hot spots.

Dataset Information

Decoding leukemia at the single-cell level: clonal architecture, classification, microenvironment, and drug resistance.

Publications

Decoding leukemia at the single-cell level: clonal architecture, classification, microenvironment, and drug resistance.

Similar Datasets

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