Capturing tumour heterogeneity in pre- and post-chemotherapy colorectal cancer ascites-derived cells using single-cell RNA-sequencing

Author:

Poonpanichakul Tiraput123ORCID,Shiao Meng-Shin4ORCID,Jiravejchakul Natnicha2,Matangkasombut Ponpan23ORCID,Sirachainan Ekaphop56,Charoensawan Varodom378ORCID,Jinawath Natini689ORCID

Affiliation:

1. Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Samut Prakan, Thailand

2. Department of Microbiology, Faculty of Science, Mahidol University, Bangkok, Thailand

3. Systems Biology of Diseases Research Unit (SyBiD), Faculty of Science, Mahidol University, Bangkok, Thailand

4. Research Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand

5. Division of Medical Oncology, Department of Internal Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand

6. Ramathibodi Comprehensive Cancer Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand

7. Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand

8. Integrative Computational BioScience (ICBS) Center, Mahidol University, Nakhon Pathom, Thailand

9. Program in Translational Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand

Abstract

Abstract Malignant ascites is an abnormal accumulation of fluid within the peritoneal cavity, caused by metastasis of several types of cancers, including colorectal cancer (CRC). 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 the present study, we have employed single-cell RNA-sequencing (scRNA-seq) to explore and characterise ascites-derived cells from a CRC 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 subclusters 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 contraction after the treatment, suggesting that the majority 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.

Publisher

Portland Press Ltd.

Subject

Cell Biology,Molecular Biology,Biochemistry,Biophysics

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