Malignant ascites is an abnormal accumulation of fluid within the peritoneal cavity, caused by metastasis of several types of cancers, including colorectal cancer. Cancer cells in ascites reflect poor prognosis and serve as a good specimen to study tumour heterogeneity, as they represent a collection of multiple metastatic sites in the peritoneum. In this study, we have employed single-cell RNA-sequencing (scRNA-seq) to explore and characterise ascites-derived cells from a colorectal cancer patient. The samples were prepared using mechanical and enzymatic dissociations, and obtained before and after a chemotherapy treatment. Unbiased clustering of 19,653 cells from four samples reveals 14 sub-clusters with unique transcriptomic patterns in four major cell types: epithelial cells, myeloid cells, fibroblasts, and lymphocytes. Interestingly, the percentages of cells recovered from different cell types appeared to be influenced by the preparation protocols, with more than 90% reduction in the number of myeloid cells recovered by enzymatic preparation. Analysis of epithelial cell subpopulations unveiled only three out of eleven subpopulations with clear expansion or contraction after the treatment, suggesting that only parts of the heterogeneous ascites-derived cells were resistant to the treatment, potentially reflecting the poor treatment outcome observed in the patient. Overall, our study showcases highly heterogeneous cancer subpopulations at single-cell resolution, which respond differently to a particular chemotherapy treatment. All in all, this work highlights the potential benefit of single-cell analyses in planning appropriate treatments and real-time monitoring of therapeutic response in cancer patients through routinely discarded ascites samples.

This content is only available as a PDF.
This is an Accepted Manuscript; not the final Version of Record. You are encouraged to use the final Version of Record that, when published, will replace this manuscript and be freely available under a Creative Commons licence.