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Series GSE161657 Query DataSets for GSE161657
Status Public on Nov 08, 2021
Title Identifying non-genetic determinants of malignant clonal fitness at single cell resolution (primary leukaemia barcode-seq)
Organisms Mus musculus; synthetic construct
Experiment type Other
Summary All cancers emerge following a period of clonal selection and subsequent clonal expansion. Whilst the evolutionary principles imparted by genetic intra-tumour heterogeneity (ITH) are becoming increasingly clear, little is known about the non-genetic mechanisms that contribute to ITH and malignant clonal fitness. Using SPLINTR, a synthetic expressed barcoding strategy, in three clinically relevant mouse models of acute myeloid leukaemia (AML) we find that malignant clonal dominance is a stable and heritable property that is facilitated by the repression of antigen presentation and the increased expression of Slpi, a leukocyte protease inhibitor that has not previously been characterised in AML. Increased transcriptional heterogeneity is a consistent feature enabling clonal fitness in diverse tissue / immune microenvironments and in the context of clonal competition between genetically distinct clones within a uniform microenvironment. Compared to extramedullary sites, leukaemia initiating capacity is most enriched in malignant cells resident within the bone marrow microenvironment and leukaemia stem cells (LSC), like normal haematopoietic stem cells, display heritable clone-intrinsic properties of high, and low clonal output that contribute to the overall tumour mass. Finally, we demonstrate that clonal output does not dictate sensitivity to chemotherapy and both high and low output LSC clones retain marked cellular plasticity enabling them to survive potent therapeutic challenge and persist as minimal residual disease. Together these data provide fundamental insights into the non-genetic transcriptional processes that underpin malignant clonal fitness which may inform future therapeutic strategies.
 
Overall design DNA barcode-seq of MLL-AF9 leukaemia cells
 
Contributor(s) Dawson MA, Fennell K, Vassiliadis D
Citation(s) 34880496
Submission date Nov 17, 2020
Last update date Jan 17, 2022
Contact name Mark Dawson
E-mail(s) mark.dawson@petermac.org
Organization name Peter MacCallum Cancer Centre
Street address 305 Grattan Street
City Melbourne
State/province VIC
ZIP/Postal code 3000
Country Australia
 
Platforms (2)
GPL19057 Illumina NextSeq 500 (Mus musculus)
GPL19424 Illumina NextSeq 500 (synthetic construct)
Samples (14)
GSM4912381 GFP barcode reference ibrary
GSM4912382 BFP barcode reference ibrary
GSM4912383 mCHERRY barcode reference ibrary
This SubSeries is part of SuperSeries:
GSE161676 Identifying non-genetic determinants of malignant clonal fitness at single cell resolution
Relations
BioProject PRJNA679042
SRA SRP292946

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE161657_BFP_barcode_reference_library.fasta.gz 8.0 Mb (ftp)(http) FASTA
GSE161657_GFP_barcode_reference_library.fasta.gz 3.1 Mb (ftp)(http) FASTA
GSE161657_KF05_KRAS_filtered_collapsed_CPM.txt.gz 58.2 Kb (ftp)(http) TXT
GSE161657_mCHERRY-barcode-library_filtered_starcode_over1_truebc.fasta.gz 1.8 Mb (ftp)(http) FASTA
SRA Run SelectorHelp
Raw data are available in SRA
Processed data are available on Series record

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