Project description:In this study, we aimed to identify CRC treatment resistance mechanisms by focusing on POU5F1-positive cells. Despite the small number of POU5F1-positive cells, single POU5F1-expressing cells produced heterogeneous cell populations in vitro and in vivo colorectal cancer organod. This study unveils a mechanism of CRC treatment resistance and highlights the potential of POU5F1-expressing cells as CTCs.
Project description:1,591 single cells from 11 colorectal cancer patients were profiled using Fluidigm based single cell RNA-seq protocol to characterized cellular heterogeneity of colorectal cancer. 630 single cells from 7 cell lines were profiled similarly to benchmark de novo cell type identification algorithms.
Project description:About 50% of colorectal cancer patients develop liver metastases. Patients with metastatic colorectal cancer have 5-year survival rates below 20% despite new therapeutic regimens. Tumor heterogeneity has been linked with poor clinical outcome, but was so far mainly studied via bulk genomic analyses. In this study we performed spatial proteomics via MALDI mass spectrometry imaging on six patient matched CRC primary tumor and liver metastases to characterize interpatient, intertumor and intratumor hetereogeneity. We found several peptide features that were enriched in vital tumor areas of primary tumors and liver metastasis and tentatively derived from tumor cell specific proteins such as annexin A4 and prelamin A/C. Liver metastases of colorectal cancer showed higher heterogeneity between patients than primary tumors while within patients both entities show similar intratumor heterogeneity sometimes organized in zonal pattern. Together our findings give new insights into the spatial proteomic heterogeneity of primary CRC and patient matched liver metastases.
Project description:Intratumoralmheterogeneity is a major obstacle to cancer treatment and a significant confounding factor in bulk-tumor profiling. We performed an unbiased analysis of transcriptional heterogeneity in colorectal tumors and their microenvironments using single-cell RNA–seq from 11 primary colorectal tumors and matched normal mucosa. To robustly cluster single-cell transcriptomes, we developed reference component analysis (RCA), an algorithm that substantially improves clustering accuracy. Using RCA, we identified two distinct subtypes of cancer-associated fibroblasts (CAFs). Additionally, epithelial–mesenchymal transition (EMT)-related genes were found to be upregulated only in the CAF subpopulation of tumor samples. Notably, colorectal tumors previously assigned to a single subtype on the basis of bulk transcriptomics could be divided into subgroups with divergent survival probability by using single-cell signatures, thus underscoring the prognostic value of our approach. Overall, our results demonstrate that unbiased single-cell RNA–seq profiling of tumor and matched normal samples provides a unique opportunity to characterize aberrant cell states within a tumor.
Project description:Our objective is to clarify the function of EWS-POU5F1 chimera. Specifially, GBS6 cells were established from an undifferentiated bone sarcoma carrying translocation t(6;22)(p21;q12). The translocation resulted in a gene fusion between EWS and POU5F1. Gene expression analysis of t(6;22) undifferentiated sarcoma cell line GBS6 transfected with POU5F1 specific siRNA to investigate the function of EWS-POU5F1.