<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Maria Puschhof</submitter><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-16433</full_dataset_link><description>Patient-derived colorectal cancer organoids were injected into mice to grow into subcutaneous tumors. Starting at 100 mm3, tumors were treated with Trodelvy (Sacituzumab Govitecan (SG)) or vehicle twice per week for 28 days before samples were harvested and subjected to single-cell RNA-sequencing of the tumor cells.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Nucleic Acid Extraction - Hashtag oligo-labelled samples were pooled (12,000 cells each) and processed for single-cell RNA-sequencing using the 10X Chromium Next GEM Single Cell Reagent Kit 3.1 according to the manufacturer’s instructions (Dual Index protocol). First, cells are resuspended in a master mix and loaded onto a chip. After encapsulation, cells were lysed inside their GEMs.</sample_protocol><sample_protocol>Sequencing - Next generation sequencing was performed at the German Cancer Research Center using an Illumina NovaSeq 6000 SP instrument (paired-end, two lanes per library).</sample_protocol><sample_protocol>Sample Treatment - Treatment was started at a tumor size of 100 mm3. Mice were treated with 25 mg/kg Sacituzumab Govitecan (SG, Trodelvy) in 100 µl  0.9% NaCl or vehicle (100 µl  0.9% NaCl) for 4 weeks through intraperitoneal injections twice per week. When two injections were needed, they were separated by one hour.</sample_protocol><sample_protocol>Sample Collection - Tumors were enzymatically dissociated with a tumor dissociation kit (Miltenyi) following the manufacturer’s instructions. In short, tumor fragments were incubated together with an enzyme cocktail in a gentleMACS Octo Dissociator with heaters (Miltenyi) using the default programs 37C_h_TDK_1 (for human tissue). Afterwards, the sample was strained to obtain single cells (100µM strainer) and processed directly for single-cell sequencing. For sample multiplexing, single cells were incubated with hashing antibodies (Total-Seq-B, BioLegend, 1 µg antibody) and additional cell sorting antibodies (anti-human EpCAM, Miltenyi; anti-mouse CD45, BioLegend) according to the manufacturer’s protocol. In short, single cells were thawed and washed in FACS buffer. About 2 million cells were resuspended in 50-100 µl with Fc Blocking Reagent Mouse (Miltenyi) in FACS buffer (ratio 1:50) and incubated with the antibody cocktail at 4°C for 30 min in the dark. Then, samples were washed three times in FACS buffer before resuspending in 600 µl FACS buffer with ZombieNIR (BioLegend) for live tumor cell isolation (EpCAM-positive, CD45-negative).</sample_protocol><sample_protocol>Library Construction - After cell lysis inside of GEMs, mRNA is reverse transcribed to cDNA with droplet-specific barcodes. After GEM breakdown, the library is being prepared according to the protocol including cDNA amplification by PCR in 11 cycles.</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Sequence Alignment - Reads were mapped to the human reference genome assembly refdata-gex-GRCh38-2020-A and demultiplexed into their original samples using the cellranger multi pipeline with default settings of the 10X Genomics Cell Ranger (v7.1.0).</data_protocol><data_protocol>Data Transformation - Quality control and filtering was performed at sample level. First, the fraction of mitochondrial reads (scanpy.pp.calculate_qc_metrics) and the doublet probability per cell barcode (scanpy.external.pp.scrublet) was computed. Cells were filtered for having at least 200 genes, while genes were filtered for being expressed in at least 3 cells. Finally, cells with a gene count exceeding the 95 % quantile or with a mitochondrial fraction larger than 20 % or with a doublet score larger than 0.2 were excluded. Count matrices of high quality cells were concatenated (across samples), normalized and log1p transformed for downstream analysis.</data_protocol><omics_type>Metabolomics</omics_type><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Illumina NovaSeq 6000</instrument_platform><study_type>RNA-seq of coding RNA from single cells</study_type><species>Homo sapiens</species><pubmed_title>TROP2 targeting reveals therapy-driven cell state dynamics and vulnerabilities in colorectal cancer</pubmed_title><pubmed_authors>Nuria Vaquero-Siguero, Nikolaos Georgakopoulos, Maria C Puschhof, Ioannis Chiotakakos, Jasmin Meier, Sigrid K Fey, Gabriele Diamante, Manuel Mastel, Aitana Guiseris Martinez, Guillaume Belthier, Nikolai Schleußner, Julia Volk, Carolin Artmann, Bryce Lim, Ronald Koschny, Cyrill Wehling, Kyanna S Ouyang, Michael Günther, Solveig Kuss, Paula Hoffmeister, Moritz Mall, Jens Neumann, Steffen Ormanns, Martin Schneider, Thomas Schmidt, Jens Puschhof, Andreas Trumpp, Jacco van Rheenen, Julio Saez-Rodriguez, Bruno C Köhler, Rene Jackstadt</pubmed_authors><pubmed_authors>Maria Puschhof</pubmed_authors></additional><is_claimable>false</is_claimable><name>Single-cell RNA-sequencing of colorectal cancer PDOX tumors treated with vehicle or the TROP2-targeting antibody-drug conjugate Sacituzumab Govitecan</name><description>Patient-derived colorectal cancer organoids were injected into mice to grow into subcutaneous tumors. Starting at 100 mm3, tumors were treated with Trodelvy (Sacituzumab Govitecan (SG)) or vehicle twice per week for 28 days before samples were harvested and subjected to single-cell RNA-sequencing of the tumor cells.</description><dates><release>2026-04-29T00:00:00Z</release><modification>2026-04-29T16:08:55.015Z</modification><creation>2025-12-19T13:40:50.739Z</creation></dates><accession>E-MTAB-16433</accession><cross_references><pubmed>publ-0-mfkv-removable</pubmed><ENA>ERP186838</ENA><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005684</EFO><EFO>EFO_0004917</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0004184</EFO><EFO>EFO_0003969</EFO></cross_references></HashMap>