Computational protocol: Reduced BRCA1 transcript levels in freshly isolated blood leukocytes from BRCA1 mutation carriers is mutation specific

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Protocol publication

[…] The nCounter Analysis System (NanoString Technologies) was used to measure mRNA gene expression (expressed as counts) at the University Health Network (Toronto, Canada) [] using the Human Cancer Reference Kit consisting of 236 cancer-related genes. Briefly, the nCounter Analysis System probe library contains two sequence-specific probes, the capture probe and the reporter probe, for each gene of interest. Probe pairs are mixed with total RNA in one hybridization reaction, and then the structures are imaged with the use of fluorescent microscopy. Expression is measured by counting the number of unique color tags within the gene-probe tripartite structures and is reported as counts, a direct measure of the number of RNA transcripts of each gene of interest.Data acquisition and normalization was carried out using the nSolver Analysis software version 2.0 (NanoString Technologies). Positive and negative controls were used to check for background expression. Reference housekeeping gene normalization was then performed to adjust counts relative to probes that are not expected to vary between samples or replicates, allowing meaningful comparisons between samples. We chose the set of housekeeping genes recommended by Nanostring, which comprised the following genes: CLTC (clathrin, heavy chain), GAPDH (glyceraldehyde-3-phosphate dehydrogenase), GUSB (glucuronidase, beta), HPRT1 (hypoxanthine phosphoribosyltransferase 1), TUBB (tubulin, beta class 1), and PGK1 (phosphoglycerate kinase 1). [...] Student’s t test was used to compare continuous variables in mutation carriers and non-carriers and the chi-square test was used to test for differences in categorical variables. The Shapiro-Wilk test was used to verify the normality of BRCA1 mRNA expression. As expression of BRCA1 was normally distributed (P = 0.26), the Pearson correlation coefficient (ρ) was used to evaluate the correlation between BRCA1 mRNA expression, BRCA1 mutation status and various reproductive and lifestyle factors. Linear regression was used to evaluate the relationship between BRCA1 mutation status and mRNA expression, adjusting for significant predictors of BRCA1 mRNA levels including parity (parous/nulliparous), breastfeeding (ever/never), and menopausal status (premenopausal/postmenopausal). A significance level of P <0.05 was used as the criterion for including variables in the multivariate model.We assigned the BRCA1 mutations into one of three mutation clusters reported to be differentially associated with the risk of breast vs. ovarian cancer: group 1 contained mutations in exons 1–10; group 2 contained mutations in exon 11; and group 3 contained mutations in exons 12–22 []. One-way analysis of variance (ANOVA) was used to compare mean BRCA1 expression levels between the three mutation clusters.Unsupervised hierarchical clustering was performed using Pearson-centered correlation metric with centroid linkage to categorize samples into homogenous groups based on similar levels of gene expression. Heat maps were generated using Java Treeview []. Student’s t test was used to identify genes expressed differentially between BRCA1 mutation carriers and non-carriers by testing for differences in mean gene expression levels with a Benjamini-Hochberg false discovery rate of P < 0.05. The PathDIP database ( was used to identify over-represented signaling pathways using data from significantly upregulated and downregulated genes through functional enrichment analysis. Statistical significance was defined at the level of P < 0.05 and all analyses were carried out using SPSS, IBM® SPSS® Statistics, version 23, 2015. […]

Pipeline specifications

Software tools nSolver Analysis Software, TreeView, SPSS
Databases pathDIP
Applications nCounter System, Miscellaneous
Organisms Homo sapiens
Diseases Neoplasms, Hereditary Breast and Ovarian Cancer Syndrome