Transcriptomics

Dataset Information

0

Identifying non-genetic determinants of malignant clonal fitness at single cell resolution (NSG vs. BL6 scRNAseq)


ABSTRACT: 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.

ORGANISM(S): Mus musculus

PROVIDER: GSE161666 | GEO | 2021/11/08

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2021-11-08 | GSE161673 | GEO
2021-11-08 | GSE161672 | GEO
2021-11-08 | GSE161662 | GEO
2021-11-08 | GSE161661 | GEO
2021-11-08 | GSE161658 | GEO
2021-11-08 | GSE161657 | GEO
2021-11-08 | GSE161669 | GEO
2021-11-08 | GSE186303 | GEO
2021-11-08 | GSE186307 | GEO
2021-11-08 | GSE186306 | GEO