Understanding the effect of chemotherapy on tumour heterogeneity and metastatic ability in colorectal cancer

"Chemotherapy remains the mainstay treatment for metastatic colorectal cancer (CRC), which can prolong overall survival to more than two years. However, over half of patients may be unresponsive to standard chemotherapy regimes and immunotherapies show limited efficacy for most patients. Consequently, a more detailed understanding of how chemotherapy remodels CRC metastases is required for improving therapeutic options.
Tumour heterogeneity and plasticity contribute to therapy evasion. We aim to better understand how chemotherapy alters both malignant cells and the tumour microenvironment (TME) at the single-cell level, by investigating the impact of chemotherapy-induced transcriptional heterogeneity and plasticity on CRC metastasis.
Using single-nucleus multiome data, we have identified malignant cell states common to both chemotherapy-treated and therapy-naïve CRC liver metastases. These subpopulations, including cancer-specific states and cell hierarchies reminiscent of the normal colon, show similar abundance between treated and therapy-naïve tumours, with a shift away from stem-like cells following treatment. Differential expression and pathway analyses suggest transcriptional similarity between treated and untreated tumours, with some enrichment of interferon response signalling in therapy-naïve tumours. This may indicate that the plasticity of malignant cells enables their reversion to a pre-treatment state.
In the TME, we detect significant differences in levels of myeloid and T cell subsets following chemotherapy treatment. To investigate the relationship between the therapy-remodelled microenvironment and malignant cells, we have performed spatial transcriptomics analysis of patient metastasis samples. We will determine whether chemotherapy alters the co-localisation of cancer cell states with specific TME populations, which will inform cell-cell communication analyses. This will help us identify candidate signalling factors driving distinct malignant states.
To model the effect of chemotherapy on cell state transitions, we will treat patent-derived organoids with chemotherapy and generate single-cell time series data. This will elucidate regulatory and/or signalling factors that can be targeted to restrict transitions into resistant cell states."