biostudies-arrayexpressCatherine VOEGELEHomo sapiensSpaceRanger v1.3.0https://www.ebi.ac.uk/biostudies/studies/E-MTAB-17055This dataset contains spatial transcriptomics data of four lung neuroendocrine tumours (lung NETs), a rare and understudied type of lung cancer. The dataset consists of raw sequencing data, metadata, and gene expression matrices. It is part of the lungNENomics project. See https://doi.org/10.5281/zenodo.19366762 for processed data for the series, including downstream analyses data for the four samples in this dataset, such as inferred CNVs and aneuploidy status, and spatial domain and cell proportions for each spot. The lungNENomics project also generated other molecular data for a series of more than 200 samples. The raw sequencing data (fastq files for RNA-seq, cram files for WGS, and idat files for methylation arrays) is hosted on the European Genome-Phenome Archive website, study EGAS00001005979. Medical imaging data (Hematoxylin & Eosin stained whole-slide images) from the lungNENomics project is hosted in the EBI bioImage Archive (10.6019/S-BIAD3143).biostudies-arrayexpressNucleic Acid Extraction - Each sample was placed on a 10x Genomics Visium slide followed by deparaffinisation, H&E staining and decrosslinking steps, according to 10x Genomics guidelines.Library Construction - Human probes targeting approximately 18,000 genes were hybridised overnight on the slides and captured on each spot after ligation between the LHS and RHS probes. Libraries were produced for each sample following 10x Genomics protocols.Sample Collection - Formalin-fixed, paraffin-embedded (FFPE) tumour tissues were collected at diagnosis during surgical resection from contributing centres. Patients provided informed consent for tissue collection and its use in histopathological and molecular analyses (including somatic and germline whole-genome sequencing), as well as for the collection of de-identified clinical data. This study was approved by the International Agency for Research on Cancer Ethics Committee (project number 19-07).Sequencing - Libraries were prepared and sequenced on an Illumina NovaSeq 6000 machine with a target sequencing depth of 50,000 reads per spot.OrganizationMINSEQE ScoreAssays and DataProcessed DataMAGE-TAB FilesData Transformation - Data was processed using SpaceRanger (v1.3.0) to generate both raw and filtered matrices.MetabolomicsUnknownTranscriptomicsGenomicsProteomicsIllumina NovaSeq 6000spatial transcriptomics by high-throughput sequencingHomo sapiensA clinically relevant morpho-molecular classification of lung neuroendocrine tumoursCatherine VOEGELENicolas ALCALALynnette FERNANDEZ-CUESTAAlexandra Sexton-Oates, Émilie Mathian, Noah Candeli, Yuliya Lim, Catherine Voegele, Alex Di Genova, Laurane Mangé, Zhaozhi Li, Tijmen van Weert, Lisa M. Hillen, Ricardo Blázquez-Encinas, Abel Gonzalez-Perez, Maike L. Morrison, Eleonora Lauricella, Lise Mangiante, Lisa Bonheme, Laura Moonen, Gudrun Absenger, Janine Altmuller, Cyril Degletagne, Odd Terje Brustugun, Vincent Cahais, Giovanni Centonze, Amélie Chabrier, Cyrille Cuenin, Francesca Damiola, Vincent Thomas de Montpréville, Jean-François Deleuze, Anne-Marie C. Dingemans, Élie Fadel, Nicolas Gadot, Akram Ghantous, Paolo Graziano, Paul Hofman, Véronique Hofman, Alejandro Ibáñez-Costa, Stéphanie Lacomme, Nuria Lopez-Bigas, Marius Lund-Iversen, Massimo Milione, Lucia Anna Muscarella, Sergio Pedraza-Arevalo, Corinne Perrin, Gaetane Planchard, Helmut Popper, Luca Roz, Angelo Sparaneo, Wieneke Buikhuisen, José van den Berg, Margot Tesselaar, Jaehee Kim, Ernst Jan M Speel, Séverine Tabone-Eglinger, Thomas Walter, Gavin M. Wright, Justo P. Castaño, Lara Chalabreysse, Liming Chen, Christophe Caux, Marco Volante, Nicolas Girard, Jean-Michel Vignaud, Esther Conde, Audrey Mansuet-Lupo, Luka Brcic, Giuseppe Pelosi, Mauro Giulio Papotti, Sylvie Lantuejoul, Jules Derks, Talya Dayton, Nicolas Alcala, Matthieu Foll, Lynnette Fernandez-CuestaMatthieu FOLLfalseSpatial transcriptomics data from the lungNENomics cohort of lung neuroendocrine tumoursThis dataset contains spatial transcriptomics data of four lung neuroendocrine tumours (lung NETs), a rare and understudied type of lung cancer. The dataset consists of raw sequencing data, metadata, and gene expression matrices. It is part of the lungNENomics project. See https://doi.org/10.5281/zenodo.19366762 for processed data for the series, including downstream analyses data for the four samples in this dataset, such as inferred CNVs and aneuploidy status, and spatial domain and cell proportions for each spot. The lungNENomics project also generated other molecular data for a series of more than 200 samples. The raw sequencing data (fastq files for RNA-seq, cram files for WGS, and idat files for methylation arrays) is hosted on the European Genome-Phenome Archive website, study EGAS00001005979. Medical imaging data (Hematoxylin & Eosin stained whole-slide images) from the lungNENomics project is hosted in the EBI bioImage Archive (10.6019/S-BIAD3143).2026-05-22T00:00:00Z2026-05-22T01:02:24.429Z2026-05-18T14:54:04.275ZE-MTAB-17055ERP193570EFO_0002944EFO_0004170EFO_0030005EFO_0005518EFO_0003816EFO_000418410.1101/2025.07.18.25331556