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McLaren, A.

Publications and source records attributed to McLaren, A..

2 recordsLinked to original sources

Characterising neutrophil subtypes in cancer using human and murine single-cell RNA sequencing datasets

Neutrophils are a highly heterogenous cellular population. However, a thorough examination of the different transcriptional neutrophil states, between health and malignancy, has not been performed. We utilised single-cell RNA-sequencing of human and murine datasets, both publicly available and independently generated, to identify neutrophil transcriptomic subtypes and their developmental lineages in health and malignancy. Datasets of lung, breast and colorectal cancer (CRC) were integrated to establish and validate the reproducibility of neutrophil gene-signatures. Pseudo-time analysis was used to identify genes driving neutrophil development from health to cancer. Finally, ligand-receptor interactions and signalling pathways between neutrophils and other immune cell populations in primary CRC and metastatic CRC were investigated. We define two main neutrophil subtypes in primary tumours: an activated subtype sharing the transcriptomic signatures of healthy neutrophils; and a tumour-specific subtype. This signature is conserved in murine and human cancer, across different tumour types. In CRC metastases, neutrophils are more heterogenous, exhibiting additional transcriptomic subtypes. Pseudo-time analysis implicates an IL1B/CXCL8/CXCR2 axis in the progression of neutrophils from health to cancer and metastasis, with effects on T-cell effector function. Assessment of global communication signalling identified CD4+ T-cells and macrophages as dominant regulators of the immunosuppressive, metastatic niche, whereas CD8+ T-cells are receivers of signals from other immune cells. We propose that the emergence of metastatic-specific neutrophil subtypes is driven by an IL1/CXCL8/CXCR2 axis, with the evolution of different transcriptomic signals that impair T-cell function at the metastatic site. Thus, a better understanding of the neutrophil transcriptomic programming could optimise immunotherapeutic interventions into early and late interventions, targeting different neutrophil subtypes.

bioinformatics↗

Mathematical modeling quantifies ERK-activity in response to inhibition of the BRAFV600E-MEK-ERK cascade.

BackgroundSimultaneous inhibition of multiple components of the BRAF-MEK-ERK cascade (vertical inhibition) has become a standard of care for treating BRAF-mutant melanoma. However, the molecular mechanism of how vertical inhibition synergistically suppresses intracellular ERK-activity, and consequently cell proliferation, are yet to be fully elucidated. MethodsWe develop a mechanistic mathematical model that describes how the mutant BRAF-inhibitor, dabrafenib, and the MEK-inhibitor, trametinib, affect BRAFV600E-MEK-ERK signalling. The model is based upon a system of chemical reactions that describes cascade signalling dynamics. Using mass action kinetics, the chemical reactions are re-expressed as ordinary differential equations which are parameterised by in vitro data and solved numerically to obtain the temporal evolution of cascade component concentrations. ResultsThe model provides a quantitative method to compute how dabrafenib and trametinib can be used in combination to synergistically inhibit ERK-activity in BRAFV600E-mutant melanoma cells. The model elucidates molecular mechanisms of vertical inhibition of the BRAFV600E-MEK-ERK cascade and delineates how elevated BRAF concentrations generate drug resistance to dabrafenib and trametinib. The computational simulations further suggest that elevated ATP levels could be a factor in drug resistance to dabrafenib. ConclusionsThe model can be used to systematically motivate which dabrafenib-trametinib dose-combinations, for treating BRAFV600E-mutated melanoma, warrant experimental investigation.

cancer biology↗