Metadata supporting the published article: The TP53 mutation rate differs in breast cancers that arise in women with high or low mammographic density
Creators: name: Cheasley, Dane
name: Devereux, Lisa
name: Hughes, Siobhan
name: Nickson, Carolyn
name: Procopio, Pietro
name: Lee, Grant
name: Li, Na
name: Pridmore, Vicki
name: Elder, Kenneth
name: Mann, G Bruce
name: Kader, Tanjina
name: Rowley, Simone M
name: Fox, Stephen B
name: Byrne, David
name: Saunders, Hugo
name: Fujihara, Kenji M
name: Lim, Belle
name: Gorringe, Kylie L
name: Campbell, Ian G
Publisher: name: figshare
Year: 2020
Subjects: subject: Biological Sciences not elsewhere classified
subject: Biological Techniques
subject: Cancer
subject: Genomics
subject: Genetics
subject: FOS: Biological sciences
subject: Cancer Cell Biology
subject: Cancer Genetics
subject: Medical and Health Sciences not elsewhere classified

description: Mammographic density (MD) influences breast cancer risk but how this is mediated is unknown. Molecular differences between breast cancers arising in the context of the lowest and highest quintiles of mammographic density may identify the mechanism through which MD drives breast cancer development. In this study, the authors report the largest and most detailed somatic genetic analysis of breast cancers arising in women with breasts of high versus low MD, to gain insights into the mechanism of cancer predisposition associated with MD.<br><b>Data access</b>: The DNA sequencing data generated during the study are publicly available in the NCBI Sequence Read Archive (SRA): <b>https://identifiers.org/ncbi/insdc.sra:SRP269052</b>. All other datasets generated and analysed during the current study, will be made available on reasonable request, from the corresponding author Dr. Dane Cheasley, Cancer Genetics Laboratory, Research Division, Peter MacCallum Cancer Centre, 305 Grattan Street, Melbourne, Victoria,3000, Australia, e-mail: <b>dane.cheasley@petermac.org</b>.<b><br></b><b>Patient consent and study approval</b>: All participants in this study gave written informed consent and research was approved by the Peter MacCallum Cancer Centre Human Ethics Committee under protocol #0966.<br><b>Study aims and methodology</b>: The aim of this study was to determine the biological relationship of breast cancers arising in the lowest and highest quintiles of MD through somatic genomic analyses of a large cohort of well annotated breast cancers.Subjects were recruited from the Lifepool study (www.lifepool.org) which is a prospective cohort of women participating in population-based mammographic screening. The women were cancer-free at time of recruitment. Epidemiological and mammographic screening data were available for all study subjects.Breast density measurements were attained from digital mammograms using AutoDensity, which identifies the breast area in the digital mammogram (breast segmentation) and then classifies breast density by identifying distinctly white areas to be classified as ‘dense’ (breast density segmentation).The following techniques are described in more detail in the published article: DNA sequencing and mutation detection, genome-wide copy number analysis, homologous recombination deficiency and fraction of the genome altered scoring, p53 immunohistochemistry and scoring, tumor infiltrating lymphocyte evaluation, and statistical analysis.<br><b>Datasets supporting the figures, tables and supplementary tables in the published article</b>: The DNA sequencing data, in <b>FASTQ</b> file format, generated during the study are publicly available in Sequence Read Archive here: https://identifiers.org/insdc.sra:SRP269052.All other datasets generated and analysed during the study, will be made available on request as described in the Data access section above.The contents and file formats of all the datasets generated and analysed during the study, are described in the data file <b>Cheasley et al.xlsx</b>.<br>