DOI: 10.6084/m9.figshare.12793700.v1
title: Data and metadata supporting the published article: Upregulation of lipid metabolism genes in the breast prior to cancer diagnosis

description: In this study, the authors employed laser microdissection and whole transcriptome profiling of the breast epithelium prior to and post tumor diagnosis, to identify the earliest alterations in breast carcinogenesis. Furthermore, a comprehensive analysis of the three tissue compartments (microdissected epithelium, stroma and adipose tissue) was performed on the breast donated by either healthy subjects or women prior to the clinical manifestation of cancer (labeled “susceptible normal tissue”).<br><b>Data access</b>: The processed RNA sequencing data generated during this study are publicly available in Gene Expression Omnibus under the accession <b>https://identifiers.org/geo:GSE141828</b>. The raw fastq files are publicly available in Sequence Read Archive under the accession <b>https://identifiers.org/ncbi/insdc.sra:SRP236605</b>. Immunohistochemical quantification staining data and supplementary tables 1-14, are publicly available in the figshare repository as part of this data record: <b>https://doi.org/10.6084/m9.figshare.12793700</b>. Data supporting table 1, and supplementary tables 7-12, will be made available on reasonable request from the corresponding author, Dr. Natascia Marino, Department of Medicine, Hematology/Oncology Division, Indiana University School of Medicine, email address: <b>marinon@iu.edu</b>. Ingenuity Pathways Analysis (IPA) datasets, supporting supplementary tables 7-12 are only available on the PI’s personal account on IPA. UALCAN and cBioPortal data analysed during the study are publicly available on CBioPortal (<b>https://www.cbioportal.org/results/oncoprint?cancer_study_list=acbc_mskcc_2015,breast_alpelisib_2020,brca_metabric,breast_msk_2018,brca_mskcc_2019,brca_smc_2018,brca_bccrc_xenograft_2014,bfn_duke_nus_2015,brca_bccrc,brca_broad,brca_sanger,brca_tcga_pub2015,brca_tcga,brca_tcga_pub,brca_tcga_pan_can_atlas_2018,brca_igr_2015,brca_mbcproject_wagle_2017&Z_SCORE_THRESHOLD=2.0&RPPA_SCORE_THRESHOLD=2.0&data_priority=0&profileFilter=0&case_set_id=all&gene_list=AKR1C1
CD36
LIPE
AQP7&geneset_list= &tab_index=tab_visualize&Action=Submit</b>) and UALCAN (<b>http://ualcan.path.uab.edu/cgi-bin/ualcan-res.pl</b>), respectively. The Gene ontology and pathway analysis: PANTHER GO (<b>http://www.pantherdb.org/geneListAnalysis.do</b>) tool was used to perform gene ontology enrichment analysis, and the resulting data support supplementary figure 3.<br><b>Study approval and patient consent</b>: Specimens used in the study, were obtained from the Susan G. Komen Tissue Bank at the IU Simon Cancer Center (KTB) and included an informed consent from the donors. All the samples were collected from consented donors recruited by the KTB. Subjects were recruited under a protocol approved by the Indiana University Institutional Review Board (IRB protocol number 1011003097 and 1607623663) and according to The Code of Ethics of the World Medical Association (Declaration of Helsinki).<br><b>Study aims and methodology</b>: To acquire new insights into the breast cancer initiation process, the authors examined how cancer-prone breast tissue differs from the contralateral breast and, especially, from matched healthy breast tissue. In this study, the authors investigated the transcriptomic profile of the breast epithelium prior to and post tumor diagnosis, and the differences between susceptible normal and matched healthy breast tissues. In the latter, for a comprehensive analysis, microdissection of the three tissue compartments (epithelium, stroma and adipose tissue) was performed.This was a case-controlled study of a total of 87 women. The transcriptome profiling was performed on breast tissue cores from 25 premenopausal (mean age 45 years) KTB donors including 2 women who donated breast tissue biopsies prior to and post diagnosis, 7 susceptible and 16 matched healthy women.The following techniques are described in more detail in the published article: breast tissue microdissection and RNA extraction, whole transcriptome sequencing, data analysis, quantitative real time polymerase chain reaction (qPCR), immunohistochemistry, primary breast epithelial cells: cultures and immunofluorescence, and statistical analysis.<br><b>Dataset description: </b><b>IHC quantification.xlsx</b>: Immunohistochemical staining was performed using antibodies specific for AKR1C1, HSL, CD36, AQP7, CD45, CD68, ki67, CD4, CD8, CD20, LC3B, TOMM20. Whole slide digital imaging was performed using the Aperio ScanScope CS system (Aperio, Vista, CA). Aperio Image Scope v12.3.2 software was used to quantify the signal of the epithelial staining using positive pixel count algorithm, while QuPath v0.2.0 software was used to obtain an automatic count of the cells positive to CD45, CD68, CD8, CD4 and CD20. Statistical analysis: matched susceptible and healthy samples were compared using the paired Wilcoxon signed-rank test. The excel file includes one spreadsheet for each staining quantification and one spreadsheet with the statistical analysis of the data.<br><b>Supplementary Tables_.xlsx</b>: The file includes the Supplementary Tables 1-14 in excel format. Descriptions of the contents of each table are included in the individual spreadsheets. <br>Please see <b>Marino, N. et al.xlsx</b> for a complete list of the datasets generated during the current study. <br>