Fresh vs. frozen cell preparations of colorectal cancer single-cell RNA sequencing
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PROVIDER: EGAS00001003769 | EGA |
REPOSITORIES: EGA
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Project description:To evaluate 3 different tissue dissociation protocols or fresh vs. frozen cell preparations, we performed single-cell RNA sequencing on cancer or distant normal tissue dissociates from 2 colorectal cancer patients. Total 18,409 cells from 10 sample preparations were analyzed (5 primary colorectal cancer and 5 matched normal mucosa). The results suggest highly consistent cellular proportions were recovered with different sample preparation methods.
2020-04-04 | GSE132257 | GEO
Project description:To evaluate 3 different tissue dissociation protocols or fresh vs. frozen cell preparations, we performed single-cell RNA sequencing on cancer or distant normal tissue dissociates from 2 colorectal cancer patients. Total 18,409 cells from 10 sample preparations were analyzed (5 primary colorectal cancer and 5 matched normal mucosa). The results suggest highly consistent cellular proportions were recovered with different sample preparation methods.
| EGAD00001005191 | EGA
Project description:Single cell RNA sequencing of colorectal cancer with diverse tissue dissociation protocols or fresh vs. frozen cell preparations.
| PRJNA546616 | ENA
Project description:Tissue dissociation, mechanical and/or enzymatic, is a method of disaggregating 3D connective tissue to release cells for downstream single cell analysis. Without proper controls for tissue dissociation experiments, potential artifacts can be mistaken for baseline tissue data. We hypothesized that enzymatic (collagenase/hyaluronidase) compared to mechanical dissociation leads to dissociated related artifacts not found in endogenous tumor tissue. To distinguish artifacts between enzymatic and mechanical dissociation, we compared separate enzymatic and mechanical dissociated samples with baseline samples from healthy and tumor patient whole blood, melanoma and head and neck squamous cell carcinoma (HNSCC) tumor tissues in flow cytometry, RNA sequencing and CODEX experiments. In bulk sorted tumor tissue, there is a significant difference between enzymatic and mechanical digested samples in cell stress, heat shock proteins and cell death related genes. These genes were also significantly upregulated in enzymatic over mechanical samples in the single cell RNA sequencing HNSCC tissue data. Fibroblasts and CD39+CD103+ CD8 T cells from tumor tissue, appear to require enzymatic digestion for efficient release from tissue compared to the mechanical digested samples. CD39+CD103+ CD8 tumor infiltrating lymphocytes (TILs) show different phenotypes depending on dissociation technique and tumor tissue. In tumor tissue, CD3+CD8+CD69+ T cells and gene expression were elevated in the enzymatic samples over the mechanical and baseline frozen tissue. Tissue dissociation techniques and tissue analysis from downstream applications have the potential for dissociation related artifacts that can mislead both protein and RNA sequencing data analysis in cancer research.
2023-09-19 | GSE243359 | GEO
Project description:Multiple samples of Patient Derived Xenografts (PDX) of a EGFR-resistant colorectal cancer are recovered at different times and profiled by scGET-seq.
2021-08-17 | E-MTAB-9659 | biostudies-arrayexpress
Project description:Tissue dissociation, mechanical and/or enzymatic, is a method of disaggregating 3D connective tissue to release cells for downstream single cell analysis. Without proper controls for tissue dissociation experiments, potential artifacts can be mistaken for baseline tissue data. We hypothesized that enzymatic (collagenase/hyaluronidase) compared to mechanical dissociation leads to dissociated related artifacts not found in endogenous tumor tissue. To distinguish artifacts between enzymatic and mechanical dissociation, we compared separate enzymatic and mechanical dissociated samples with baseline samples from healthy and tumor patient whole blood, melanoma and head and neck squamous cell carcinoma (HNSCC) tumor tissues in flow cytometry, RNA sequencing and CODEX experiments. In bulk sorted tumor tissue, there is a significant difference between enzymatic and mechanical digested samples in cell stress, heat shock proteins and cell death related genes. These genes were also significantly upregulated in enzymatic over mechanical samples in the single cell RNA sequencing HNSCC tissue data. Fibroblasts and CD39+CD103+ CD8 T cells from tumor tissue, appear to require enzymatic digestion for efficient release from tissue compared to the mechanical digested samples. CD39+CD103+ CD8 tumor infiltrating lymphocytes (TILs) show different phenotypes depending on dissociation technique and tumor tissue. In tumor tissue, CD3+CD8+CD69+ T cells and gene expression were elevated in the enzymatic samples over the mechanical and baseline frozen tissue. Tissue dissociation techniques and tissue analysis from downstream applications have the potential for dissociation related artifacts that can mislead both protein and RNA sequencing data analysis in cancer research.
2023-09-19 | GSE243360 | GEO
Project description:Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome (and transcriptome data) generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture in two commonly used deconvolution algorithms ESTIMATE and ConsensusTME (r ≥ 0.63). Here we have developed and optimized protein-based signatures to estimate cell admixture proportions and benchmarked these using bulk tumor proteomics data from over 150 HGSOC patients. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.
2024-01-12 | PXD044157 | Pride
Project description:Within just a few years single cell RNA sequencing has become a frequently used standard method in many research fWithin just a few years single cell RNA sequencing has become a frequently used standard method in many research facilities worldwide. Declining sequencing costs and further refinements of the available protocols will pave the way for previously unimaginable prospects, up to single cell transcriptomic maps of entire organisms. The sample collection process can constitute a severe bottleneck in scRNA-seq experiments especially for solid tissues. Lengthy dissociation protocols are not uncommon to obtain sufficient amounts of starting material and can lead to significant changes in the gene expression profiles of cells. Preservation of the transcriptome prior to single cell dissociation can overcome this setback. Here we present an extensive performance analysis of glyoxal as an alternative fixative for scRNA-seq application. High numbers of transcripts and genes were recovered from glyoxal-fixed cells subjected to Drop-seq methodology with the best performance in Drosophila cells. While glyoxal fixation in Drosophila Kc167 and human HEK 293T cells revealed transcriptome data similar to the unfixed condition, reduced library complexity was observed for the human sample. We found the integrity of Drosophila intestinal tissue maintained following glyoxal fixation, while dissociation of the fixed tissue allowed sufficient cell isolation. In conclusion, we present glyoxal as a well-suited fixative for Drosophila samples that allows high-quality single cell transcriptomic analysis and successful intestinal tissue disaggregationcilities worldwide. Declining sequencing costs and further refinements of the available protocols will pave the way for previously unimaginable prospects, up to single cell transcriptomic maps of entire organisms. The sample collection process can constitute a severe bottleneck in scRNA-seq experiments especially for solid tissues. Lengthy dissociation protocols are not uncommon to obtain sufficient amounts of starting material and can lead to significant changes in the gene expression profiles of cells. Preservation of the transcriptome prior to single cell dissociation can overcome this setback. Here we present an extensive performance analysis of glyoxal as an alternative fixative for scRNA-seq application. High numbers of transcripts and genes were recovered from glyoxal-fixed cells subjected to Drop-seq methodology with the best performance in Drosophila cells. While glyoxal fixation in Drosophila and human cells revealed transcriptome data similar to the unfixed condition, reduced library complexity was observed for the human sample and might require further protocol optimization. We found the integrity of Drosophila intestinal tissue maintained following glyoxal fixation, while dissociation of the fixed tissue allowed sufficient cell isolation. In conclusion, we present glyoxal as a well-suited fixative for Drosophila samples that allows high-quality single cell transcriptomic analysis and successful intestinal tissue disaggregation.
2021-06-22 | GSE163736 | GEO
Project description:Single cell genomics is essential to chart tumor ecosystems. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 212,498 cells and nuclei from 39 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate, and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.
2020-05-11 | GSE140819 | GEO
Project description:Investigation of whole genome gene expression level changes in a colorectal cancer cell line SW480 expressing FOXC2, compared to the pBabe control cells. Genes associated with metastasis regulated by FOXC2 in colorectal cancer were analysed. The role of FOXC2 in breast cancer metastasis are further described in Mani SA, Yang J et al. Mesenchyme Forkhead 1 (FOXC2) plays a key role in metastasis and is associated with aggressive basal-like breast cancers. PNAS 2007; 104: 10069-10074 . A six chip study using total RNA recovered from three separate cultures of SW480/pBabe and three separate cultures of SW480/FOXC2. Each chip measures the expression level of 45033 genes from SW480/pBabe or SW480/FOXC2.
2014-07-02 | E-GEOD-58980 | biostudies-arrayexpress