Capturing tumor heterogeneity in pre- and post-chemotherapy colorectal cancer ascites-derived cells using single-cell RNA-sequencing
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ABSTRACT:
PROVIDER: PRJNA656202 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12418421_1.fastq.gz | Fastqsanger.gz | |||
| SRR12418421_2.fastq.gz | Fastqsanger.gz | |||
| SRR12418422_1.fastq.gz | Fastqsanger.gz | |||
| SRR12418422_2.fastq.gz | Fastqsanger.gz | |||
| SRR12418423_1.fastq.gz | Fastqsanger.gz |
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Project description:Purpose: Malignant ascites is an abnormal accumulation of fluid within the peritoneal cavity, caused by metastasis of several cancer types including colorectal cancer. Cancer cells in ascites reflect poor prognosis and can be a source of recurrence. They also represent a good source of specimens for the study of tumor heterogeneity. Single-cell RNA-sequencing (scRNA-seq) has recently emerged as a powerful tool for exploring and characterizing cellular heterogeneity in both normal tissues and cancers. However, molecular profiles of malignant ascites cells in response to treatment are still poorly understood. Materials and Methods: We have performed scRNA-seq of ascites-derived cells from a colorectal cancer patient to profile and characterize the cellular heterogeneity and different expression hallmarks within the cell populations before and after a chemotherapy treatment. The effect of different single cell preparation protocols, namely, manual and enzymatic methods, on cell viability and gene expression were also assessed. Results: Unbiased clustering of 19,653 cells in total reveals 12 sub-clusters with unique transcriptomic patterns from four major cell types: epithelial cells, myeloid cells, fibroblast, and lymphocytes. Interestingly, the percentages of cells recovered from different cell types appeared to be influenced by the preparation protocols; enzymatic and mechanical separations, with more than 90% reduction in myeloid cell number when enzymatic method was used. Subcluster analysis of epithelial cell populations before and after chemotherapy treatment identified distinct cell clusters with unique transcriptomic profiles. Moreover, there were only three out of 11 epithelial subclones with more than 50% reduction in tumor cell number after treatment. This finding indicated that most clones were resistant to the treatment, which reflected the poor treatment outcome observed in our patient. Conclusions: Overall, our study underscores cellular heterogeneity within malignant ascites and uncovers the gene expression profile of colorectal cancer ascites-derived cells in single-cell resolution. Our findings emphasize the potential benefit of using scRNA-Seq to monitor real-time treatment response in cancer patients.
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Project description: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.
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Project description:Peritoneal carcinomatosis with malignant ascites is associated with dismal prognosis in gastric cancer. Malignant ascites is the most relevant body fluid in which to seek diagnostic biomarkers for peritoneal carcinomatosis. We aimed to identify and validate ascites-derived circulating microRNAs (miRNAs) that are differentially expressed between liver cirrhosis-associated benign ascites (LC-ascites) and gastric cancer-associated malignant ascites (GC-ascites). MiRNA expression levels were investigated in three independent cohorts. Overall, 165 ascites samples (73 LC-ascites and 92 GC-ascites) were obtained from the National Biobank of Korea. Initially, microarrays were used to screen the expression levels of 2,006 miRNAs in the discovery cohort (n = 22). Subsequently, quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analyses were used to validate the expression levels of selected miRNAs in the training (n = 70) and validation (n= 73) cohorts. In addition, the levels of carcinoembryonic antigen (CEA), a commonly used tumor marker, were determined in the ascites samples. Expression levels of miR-574-3p, miR-181b-5p, miR-4481, and miR-181d were significantly lower in the GC-ascites samples than in the LC-ascites samples, and miR-181b-5p showed the best diagnostic performance for GC-ascites (area under the curve [AUC] = 0.798 and 0.846 for the training and validation cohorts, respectively). The diagnostic performance of CEA for GC-ascites was improved if CEA and miR-181b-5p were analyzed together (AUC = 0.981 and 0.946 for the training and validation cohorts, respectively). Overall, we identified ascites-derived circulating miRNAs capable of differentiating non-malignant ascites and GC-ascites, and demonstrated that the combined use of miR-181b-5p and CEA produces the optimal diagnostic yield.
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