Metadata record for the article: A subset of lung cancer cases shows robust signs of homologous recombination deficiency associated genomic mutational signatures

<b>Summary</b><br> This metadata record provides details of the data supporting the claims of the related article: “A subset of lung cancer cases shows robust signs of homologous recombination deficiency associated genomic mutational signatures”. The related study analysed all available whole genome sequencing data from the TCGA lung adenocarcinoma (LUAD) and squamous lung cancer (LUSC) cohorts and determined which of a list of mutational signatures were present in these cases, analysing whole genome and whole exome data to estimate the frequency of potentially homologous recombination (HR) deficient lung cancer cases. Type of data: single nucleotide variation; binary alignment maps Subject of data: Eukaryotic cell lines; <i>Homo sapiens</i> Population characteristics: lung cancer cases Recruitment: Cancer cell lines were sourced from Cancer Cell Line Encyclopedia, Genomics of Drug Sensitivity in Cancer data portal. The exceptional responder was identified as part of a larger ongoing study to understand the determinants of treatment response to platinum based therapy. <b>Data access</b> The results shown here are in part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga, and the LUAD and LUSC data are available at ICGC (https://dcc.icgc.org/) and GDC (https://portal.gdc.cancer.gov/) data portals. A comprehensive list of the file names underlying the figures and supplementary materials of the related article, along with direct links to the data in the above sources, is provided in the file ‘Diossy_et_al_2021_underlying_data_list.xlsx’, which is included with this data record. Sample single nucleotide variation analysis of a stage IVA lung squamous carcinoma case with a durable (&gt; 20 months), symptom-free survival in response to platinum-based treatment (H75T) has been deposited in the <i>European Variation Archive</i> under accession https://identifiers.org/ebi/bioproject:PRJEB45238. <b>Corresponding author(s) for this study</b> Zoltan Szallasi, Computational Health Informatics Program (CHIP) Boston Children’s Hospital, Harvard Medical School, 300 Longwood Ave., Boston Massachusetts, USA, 02215, e-mail: [e-mail], [phone]. <br> <b>Study approval </b> The Hungarian Scientific and Research Ethics Committee of the Medical Research Council, No 2285-1/2019/EUIG és 2307-3/2020/EUIG has approved the study.