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      <r:Content xml:lang="sv">Inom stroman av duktalt adenokarcinom hos pankreas (PDAC) differentierar mesenkymala celler till cancerassocierade fibroblastsubtyper (CAF) som successivt medierar sjukdomsprogression. Att definiera den reglerande mekanismen och mångfalden av CAF-subtyper kan identifiera potentiella terapeutiska strategier för att utnyttja CAFs tumörhejdande aktiviteter. För att undersöka detta använde vi RNA-sekvensering hos enskilda celler för att karakterisera mesenkymala celler hos human PDAC som utrycker fibroblastaktiveringsprotein-alfa (FAP). De mesenkymala subpopulationerna i PDAC reflekterade mesenkymal cellheterogenitet som finns i normalt utvecklande pankreas. Förutom en detaljerad karakterisering av subpopulationer av inflammatorisk CAF (iCAF) och myofibroblastisk CAF (myCAF), avslöjade analysen en tidigare okänd subtyp av en interferon-respons CAF (ifCAF). Signaler från tumören inducerade specifika CAF-subtyper från pankreatiska stellatceller (PSCs) i en organoidbaserad samodlingsmodell, och tidsförloppsexperiment avslöjade regulatoriska mekanismer som styr subtypbildning. STING-agonister främjade en ifCAF-fenotyp in vivo och in vitro. Viktigt är att induktion av en ifCAF-fenotyp hejdade tumörcellinvasivitet och inducerade en antitumörfenotyp i tumörassocierade neutrofiler. Sammanfattningsvis ger denna studie detaljerad insyn i FAP+ stromacellsheterogenitet i PDAC och identifierar en ifCAF-subtyp som kan induceras för att bromsa tumörfrämjande egenskaper hos PDAC (Cumming m. fl. 2025).

Detta dataset innehåller följande data- och metadatafiler:

1. Sex par fastq-filer som innehåller den faktiska sekvenseringsdatan. Den totala storleken är 230 Gb. Varje fastq par representerar singel-cell RNA-sekvensering från ett separat patientprov. Fastq-filer är textfiler med genomsekvens och sekvenskvalitetsmått. De är lagrade som komprimerade gzip-filer.
2. En metadatafil med provinformation. De inkluderade variablerna är: Provnamn, sekvenseringsbiblioteks-ID, sekvenseringsdjup, sekvenseringsindex, antal celler, barcode set, patientens pseudo-ID (P1-P5), patologisk diagnos, kön, ålder, kirurgiskt ingrepp, patologisk klassificering, tumörens läge, histologisk status (desmoplasi). Detta är en Excelfil (xlsx).
3. En metadatafil med provinformation enligt Federated European Genome-Phenome Archive Sweden (FEGA-Sweden) mallformat. Detta är en Excelfil (xlsx).
4. Tolv bearbetade datatabeller med råa sekvens-reads (UMI) count; Sex filer med kvalitetsfiltrerade celler, och sex filer med alla celler. Detta motsvarar genuttrycksnivåer efter mappning till referensgenomet. Datan är lagrad i MEX-format, dvs tre tabbavgränsade textfiler i gles matrisformat. Filerna är komprimerade med gzip.
5. Två cellannoteringstabeller för singel-cell datan. Tabellerna beskriver read count, genantal, klusternummer och celltypannotering för 30786/26733 celler från de 6 proverna som beskrivs i metadatafilen med provinformation. Tabellerna är i tabbavgränsade textfiler.
6. Två binära filer skrivna i R-programmeringsspråket som innehåller ett objekt läsbart av Seurat-paketet. Filerna innehåller processad data i form av read-count (dvs genuttrycksnivåer) samt transformerad (normaliserad och skalad) data och analysresultat. Filerna är i RDS-format och kan laddas in i R.

För mer information om datafilerna, vänligen läs dokumentationsfilerna som medföljer denna databeskrivning. Om du vill skicka in en begäran om åtkomst till data i denna datauppsättning, vänligen läs dokumentet Readme_before_submission_of_an_access_request.</r:Content>
      <r:Content xml:lang="en">Within the stroma of pancreatic ductal adenocarcinoma (PDAC), mesenchymal cells differentiate into cancer-associated fibroblast (CAF) subtypes that differentially mediate disease progression. Defining the regulatory mechanism and diversity of CAF subtypes could identify potential therapeutic strategies to harness the tumor suppressive activities of CAFs. To address this, we utilized single-cell RNA sequencing to profile fibroblast activation protein-alpha (FAP) expressing mesenchymal cells in human PDAC. The mesenchymal subpopulations in PDAC reflected mesenchymal cell heterogeneity found in the normal developing pancreas. In addition to characterizing inflammatory CAF (iCAF) and myofibroblastic CAF (myCAF) subpopulations in detail, the analysis uncovered a previously undescribed interferon-response CAF (ifCAF) subtype. Tumor-derived signals induced specific CAF subtypes from pancreatic stellate cells (PSCs) in an organoid-based co-culture model, and time-course experiments revealed regulatory mechanisms that govern subtype formation. STING agonists promoted an ifCAF phenotype in vivo and in vitro. Importantly, induction of an ifCAF phenotype suppressed tumor cell invasiveness and induced an anti-tumor phenotype in tumor-associated neutrophils. Together, this study resolves FAP+ stromal cell heterogeneity in PDAC and identifies an ifCAF subtype that can be induced to suppress pro-tumorigenic features of PDAC (Cumming et al., 2025).

This dataset contains the following data and metadata files:

1.  Six pairs of fastq files that contain the actual sequencing data. The total size is 230 GB.  Each pair represents a paired-end single-cell RNA sequencing from an individual patient sample.  The fastq files are text files with genomic sequence and sequence quality metrics. They are stored as compressed gzip-ed files.
2. A metadata file with sample information. The variables included are:  Sample name, sequencing library ID, sequencing depth, sequencing index, number of cells, barcode set, patient pseudo ID (P1-P5), pathologic diagnosis, gender, age, surgical procedure, pathological classification, tumour location, histological status (desmoplasia).  This is an Excel file (xlsx).
3. A metadata file with sample information according to the Federated European Genome-Phenome Archive Sweden (FEGA-sweden) template format. This is an Excel file (xlsx).
4. Twelve processed data tables with raw read (UMI) count; Six files for quality filtered cells, and six files with all cells. Each table corresponds to a separate sample. This corresponds to gene expression levels after mapping to the reference genome. The data is stored in MEX format, i.e. three tab-delimited text files in sparse matrix format. The files are compressed with gzip. 
5. Two cell annotation tables for the single-cell data. The tables describe read count, gene count, cluster number, and cell type annotation for 30786/26733 single cells from the 6 samples described in the sample information metadata file. The tables are submitted as tab-delimited text files.
6. Two binary files written in R programming language containing an object readable by the Seurat package. The files contain processed data in the form of read count (i.e. gene expression levels) and also as transformed (normalized and scaled) data and analysis results. The files are in RDS format and can be loaded in R.

For more information about the data files, please read the documentation files that accompany this data description. If you would like to submit a request to access data of this dataset, please read the document Readme_before_submission_of_an_access_request.</r:Content>
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        <r:Keyword xml:lang="en" controlledVocabularyID="D010190" controlledVocabularyName="MeSH">Pancreatic Neoplasms</r:Keyword>
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