Unravelling cancer stem cell heterogeneity in myeloproliferative neoplasms Professor Adam Mead (Biomedical science seminar series)
Event details
Intratumoural heterogeneity (ITH) underlies many of the challenges we face in cancer medicine, including therapy-resistance, disease progression/evolution and relapse after seemingly effective therapy. While many of the scientific questions relating to ITH have remained the same over many decades, our ability to address these questions has advanced dramatically not least because of advances in technology.
ITH in cancer occurs at many levels, not restricted to genetics (mutations) but also other factors, such as cell cycle and presence of cancer stem cells (CSCs). As it is only CSCs that propagate tumours, it is ultimately CSCs that are the unit of evolution and selection by therapy, and techniques to resolve this heterogeneity at the single-cell level are ideally placed to provide entirely new insights into cancer biology.
Arguably, the best characterised CSC-propagated malignancies are chronic myeloid neoplasms, including myeloproliferative neoplasms (MPN) and chronic myeloid leukaemia (CML). We recently applied single-cell RNA-sequencing (scRNA-seq) to reveal that despite sharing phenotypic features, CML-CSCs are molecularly highly-distinct from normal HSCs.
Furthermore, despite CML-CSCs sharing an identical genomic lesion (BCR-ABL), we showed that they are markedly heterogeneous; unravelling this heterogeneity identified CML-CSC subpopulations which evade therapy, establishing the importance of additional components of ITH, revealed through single-cell transcriptomics, to characterise cellular and molecular mechanisms of therapy-resistance.
More recently, we have applied similar approaches to analyse heterogeneity of myelofibrosis-CSCs using a novel technique which allows us to link transcriptomic and genetic data at the single cell level. We are now using this approach to study stem cells from MPN patients undergoing progression to acute leukaemia and these unpublished data will be presented.