{"database":"biostudies-arrayexpress","file_versions":[],"scores":null,"additional":{"submitter":["Muyang Lin"],"organism":["Mus musculus"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15841"],"description":["Colorectal cancers are complex ecosystems, with interactions between the cancer epithelium and the tumor microenvironment (TME) shaping disease progression. Cancer-associated fibroblasts are key TME components, influencing epithelial plasticity and immune cell infiltration. In this study, we collected autochthonous tumours from KP (villinCreER KrasG12D/+ Trp53fl/fl) and KPN (villinCreER KrasG12D/+ Trp53fl/fl Rosa26N1icd/+) mice, colorectal cancer models that develop invasive tumours and metastasise to the liver with high penetrance and short latency. We aimed to characterise the cellular composition of these tumours, focusing on shifts in different cell compartments, particularly fibroblast phenotypes.  Dissociated single cells were enriched for fibroblasts by fluorescence-activated cell sorting based on negative expression of Epcam and Cd45 (Double negative, DN). Single-cell RNA sequencing and CITE-seq were performed. CITE-seq staining used the TotalSeq™-C Mouse Universal Cocktail V1.0 (BioLegend), and cell hashing was performed using TotalSeq™-C0308 anti-mouse Hashtag 8 (Barcode: TATAGAACGCCAGGC) and TotalSeq™-C0314 anti-mouse Hashtag 14 (Barcode: CTTTCGCCAACTCTG)."],"repository":["biostudies-arrayexpress"],"sample_protocol":["Nucleic Acid Extraction - NA","Sequencing - Libraries were sequenced on the Illumina NovaSeq X Series platform using paired-end sequencing with the 5' PE v3 configuration. The sequencing centre that generated the sequencing files is Novogene.","Sample Collection - Two autochthonous mouse tumours with different genotypic mutations (KP: KrasG12D/+, Trp53fl/fl; KPN: KrasG12D/+, Trp53fl/fl, Rosa26N1icd/+) were harvested and stored in the cryopreserved material (CryoStore10, STEMCELL Technologies) before use. Tissue samples were enzymatically dissociated using a digestion mix prepared fresh by combining Collagenase D (250 µg/mL, Sigma-Aldrich Cat. 11088866001), Dispase II (800 µg/mL, Thermo Scientific Cat. 17105041), and DNase I (100 µg/mL, Roche Cat. 10104159001) in RPMI medium. Frozen tumor tissues were thawed at room temperature and washed with RPMI to remove cryoprotectant. Following media removal, 4 mL of digestion mix was added per sample. Samples were incubated at 37°C in a benchtop Thermomixer C (Eppendorf) with shaking at 500-600 RPM for 20 minutes. After incubation, tissues were mechanically disrupted by pipetting with widened-bore tips, and the supernatant containing dissociated cells was collected and incubated on ice. Fresh digestion mix was added to remaining tissue and incubated for additional 10-minute intervals with intermittent mechanical disruption, repeating until complete digestion. Digestion supernatants from the same sample were pooled, filtered through a 70 µm strainer, and centrifuged at 400g for 10 minutes at 4°C. Cell suspensions from two tumor samples were individually labeled with TotalSeq™-C0308 anti-mouse Hashtag 8 antibody and TotalSeq™-C0314 anti-mouse Hashtag 14 antibody (both from BioLegend) and combined for staining with TotalSeq™-C Mouse Universal Cocktail, V1.0 (BioLegend). To enrich stromal cell populations and enable compartment-specific analysis, dissociated single cells were FACS-sorted into epithelial (Epcam⁺Cd45⁻), immune (CD45⁺EpCAM⁻), and stromal (EpCAM⁻CD45⁻) populations for subsequent downstream analysis (Flow antibodies: BD Biosciences, Cat. 740281; BioLegend, Cat. 147707).","Sample Treatment - Mouse tumours were induced at the age of 6-8 weeks old with intraperitoneal injection of tamoxifen at 80mg/kg.","Library Construction - Single-cell RNA sequencing (scRNA-seq) libraries were prepared using the Chromium Single Cell 5’ v3 Reagent Kits (10x Genomics) according to the manufacturer's protocol."],"figure_sub":["Organization","MINSEQE Score","Assays and Data","MAGE-TAB Files"],"omics_type":["Metabolomics","Unknown","Transcriptomics","Genomics","Proteomics"],"instrument_platform":["Illumina NovaSeq X"],"study_type":["RNA-seq of coding RNA from single cells"],"species":["Mus musculus"],"pubmed_title":["Therapeutic manipulation and spatial quantification of the tumour microenvironment in colorectal cancer"],"pubmed_authors":["Muyang Lin","Mulholland-Illingworth EJ*, Moore JW*, Lin M, Amirkhah R, Grzesiak L, Ligeza A, Bull JA, Boen TJ, Valbuena GN, Gillespie M, Corry SM, Ridgway R, Belnoue-Davis HL, Dunne PD, Sansom OJ, Byrne HM, Leedham SJ"],"additional_accession":[]},"is_claimable":false,"name":"Single-cell RNA-seq and CITE-seq of autochthonous KP and KPN mouse tumors","description":"Colorectal cancers are complex ecosystems, with interactions between the cancer epithelium and the tumor microenvironment (TME) shaping disease progression. Cancer-associated fibroblasts are key TME components, influencing epithelial plasticity and immune cell infiltration. In this study, we collected autochthonous tumours from KP (villinCreER KrasG12D/+ Trp53fl/fl) and KPN (villinCreER KrasG12D/+ Trp53fl/fl Rosa26N1icd/+) mice, colorectal cancer models that develop invasive tumours and metastasise to the liver with high penetrance and short latency. We aimed to characterise the cellular composition of these tumours, focusing on shifts in different cell compartments, particularly fibroblast phenotypes.  Dissociated single cells were enriched for fibroblasts by fluorescence-activated cell sorting based on negative expression of Epcam and Cd45 (Double negative, DN). Single-cell RNA sequencing and CITE-seq were performed. CITE-seq staining used the TotalSeq™-C Mouse Universal Cocktail V1.0 (BioLegend), and cell hashing was performed using TotalSeq™-C0308 anti-mouse Hashtag 8 (Barcode: TATAGAACGCCAGGC) and TotalSeq™-C0314 anti-mouse Hashtag 14 (Barcode: CTTTCGCCAACTCTG).","dates":{"release":"2026-02-23T00:00:00Z","modification":"2026-02-23T09:36:22.848Z","creation":"2025-10-28T17:07:54.824Z"},"accession":"E-MTAB-15841","cross_references":{"ENA":["ERP183228"],"EFO":["EFO_0002944","EFO_0004170","EFO_0005684","EFO_0005518","EFO_0004184","EFO_0003969"]}}