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

Summary

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; Homo sapiens

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.

Data
access

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 (> 20 months), symptom-free survival in response to platinum-based
treatment (H75T) has been deposited in the
European Variation Archive under accession https://identifiers.org/ebi/bioproject:PRJEB45238.

Corresponding author(s) for this study

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].

Study approval

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.