4.6 Article

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

期刊

BIOSCIENCE REPORTS
卷 41, 期 12, 页码 -

出版社

PORTLAND PRESS LTD
DOI: 10.1042/BSR20212093

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资金

  1. Newton Advanced Fellowship through the Thailand Science Research and Innovation (TSRI) [DBG60800003]
  2. Royal Society [NA160153]
  3. Mid-Career Researcher Grant from National Research Council of Thailand (NRCT)
  4. Mahidol University [NRCT5-RSA63015-24]
  5. Program Management Unit for National Competitiveness Enhancement (PMU-C) [C10F640057]
  6. Thailand Grand Challenge Program for Research University Network (RUN) under the Precision Medicine for Cancer Project by the National Research Council of Thailand (NRCT)
  7. Government Research Grant by the Health Systems Research Institute (HSRI) [HSRI 63-140]
  8. Office of National Higher Education Science Research and Innovation Policy Council (NXPO) through the Integrative Computational BioScience (ICBS) Center, Mahidol University [B05F630055]

向作者/读者索取更多资源

This study employed single-cell RNA-sequencing to explore ascites-derived cells from a colorectal cancer patient, revealing highly heterogeneous cancer subpopulations that respond differently to treatment, with the majority of ascites-derived cells showing resistance to therapy.
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 charac-terise ascites-derived cells from a CRC patient. The samples were prepared using mechan-ical 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 af-ter 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 appropri-ate treatments and real-time monitoring of therapeutic response in cancer patients through routinely discarded ascites samples.

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