Genomic data on breast cancer transcript profile modulation by 17beta-hydroxysteroid dehydrogenase type 1 and 17-beta-estradiol

The data presented here are related to the research article entitled “Estradiol-independent modulation of breast cancer transcript profile by 17beta-hydroxysteroid dehydrogenase type 1” (J.A. Aka, E.L. Calvo, S.X. Lin, 2016) [1]. We evaluated the effect of the steroidal enzyme 17β-HSD1 and its product, the estrogenic hormone 17-beta-estradiol (E2), on gene transcription profile of breast cancer cells. RNA interference technique was used to knock down the 17β-HSD1 gene (HSD17B1) in the hormone-dependent breast cancer cell line T47D in steroid-deprived medium. Transfected cells were subsequently treated with E2, and microarray analyses (with three contrasts) were used to investigate (i) the effect of 17β-HSD1 expression on breast cancer cell transcript profile in steroid-deprived condition, (ii) the effect of E2 on breast cancer gene expression and (iii) if E2 affects gene regulation by 17β-HSD1. Functional enrichments of the differentially expressed genes were assessed using Ingenuity Pathway Analysis (IPA). Here, we showed data on 140 genes that are induced or repressed 1.5 time or higher (p < 0.05) in the HSD17B1-silenced and E2-treated T47D cells revealed by microarray analysis, and presented the 14 functional terms found in the cancer and in the cell death and survival categories revealed by the IPA biological function analysis. Data on IPA Canonical Pathway and network analyses is also presented. Further discussion on gene regulation by 17β-HSD1 and E2 is provided in the accompanying publication [1].

categories revealed by the IPA biological function analysis. Data on IPA Canonical Pathway and network analyses is also presented. Further discussion on gene regulation by 17β-HSD1 and E2 is provided in the accompanying publication [1].
& T47D cells were transfected with 17β-HSD1 siRNAs followed by estradiol treatment two days later for an additional two days, and total RNA was extracted for analysis. Experimental features 3 Â 10 5 T47D cells were transfected in 6-well plates in charcoal-treated medium with 200 nM mixed 17β-HSD1 specific siRNAs or with negative control siRNA. Two days later, transfected cells were treated with 1 nM estradiol or ethanol as a vehicle control in fresh charcoal-treated medium and cells were incubated for two additional days before RNA extraction and analysis. Data source location N/A Data accessibility Data is available within this article and available at the NCBI database via Gene Expression Omnibus (GEO accession number GSE77345).

Value of the data
Provide information on genes regulated by 17β-HSD1 and its product estradiol, useful for further studies on breast cancer cell mechanisms.
Can contribute to elucidate hormone-independent cell growth pathways in hormone-dependent breast cancer cells.
May stimulate further research on understanding 17β-HSD1 roles in breast cancer development. Table 1 showed data on gene expression profile in T47D cells (genes regulated 1.5 time or higher) transfected with 17β-HSD1 siRNAs (si17B1) or negative control siRNA (NC), and treated with 1 nM Table 1 List of the 140 genes induced or repressed 1.5 time or higher (po 0.05) in T47D cells after transfection with 17β-HSD1 siRNAs (si17B1) or negative control siRNA (NC) for two days and cell treatment with 1 nM estradiol (E2). Data was obtained from microarray analysis using contrast NCþ E2 vs. si17B1þ E2 (see Table 5).

Experimental design, materials and methods
2.1. Cell culture, siRNA transfections, steroid treatment and RNA preparation T47D cells were obtained from the American Type Culture Collection (ATCC) and were cultured as described in ref [1]. The detailed procedure of siRNA transfections, steroid treatment and RNA preparation have been described in ref [1]. Briefly, two days before transfection, T47D cells were cultured in dextran-coated charcoal-treated medium; on the transfection day, 3 Â 10 5 cells were reversetransfected in 6-well plates with 200 nM mixed 17β-HSD1 specific siRNAs [2,3] (si17B1) or with Scramble siRNA used as negative control siRNA (NC) using Lipofectamine siRNAMax (Invitrogen), and cells were incubated in steroid deprived medium. Two days after transfection, cell culture media were replaced by fresh charcoal-treated medium containing either the steroid estradiol (1 nM) or ethanol as a vehicle control (see Table 5), and cells were incubated for two more days before RNA extraction using Trizol Reagent (Invitogen). The RNA samples included two independent biological replicates, coming from two independent cell culture experiments, for a total of eight RNA samples.

Microarray processing
RNA samples were processed according to the manufacturer's recommended procedures on GeneChip Whole Transcript (WT) Sense Target Labeling Assay from Affymetrix (http://www.affyme trix.com/support/downloads/manuals/wt_sensetarget_label_manual.pdf). The assay was started with 0.2 mg of each T47D cells RNA samples and the protocol is based on the principle of performing one cycle of cDNA synthesis and in vitro transcription (IVT) for target amplification to generate cRNA following by reverse transcription reactions to synthesis the WT cDNA. About 2.7 mg sample of Table 3 The 14 functional terms found in the cell death and survival category of the IPA Biological function analysis of 208 genes regulated by 17β-HSD1 and/or estradiol in T47D cells.

Number
Functional term 1 Apoptosis 2 Apoptosis of breast cancer cell lines 3 Apoptosis of breast cell lines 4 Apoptosis of mammary epithelial cells 5 Apoptosis of mammary tumor cells 6 Apoptosis of tumor cell lines 7 Cell death 8 Cell death of tumor cell lines 9 Cell survival 10 Cell viability 11 Cytotoxicity of cells 12 Cytotoxicity of cytotoxic T cells 13 Cytotoxicity of T lymphocytes 14 Necrosis Table 4 IPA network analysis of 208 genes regulated by 17β-HSD1 and/or estradiol in T47D cells from the three contrasts listed in Table 5. Molecules in Network: All of the molecules that compose each network are listed. Score: The score is based on a p-value calculation, which calculates the likelihood that the Network Eligible Molecules that are part of a network are found therein by random chance alone. Mathematically, the score is simply the negative exponent of the right-tailed Fisher's exact test result. For example, if the score is 3, then the there is a 1 in 1000 chance that the Network Eligible Molecules found in that network appeared there just by chance. In other words, the score is simply a measure of the number of Network Eligible Molecules in a network, and the greater the number of Network Eligible Molecules in a network, the higher the score (lower the p-value) will be.   Tap   28  17  Endocrine system disorders, gastrointestinal  disease, immunological disease  7   AHNAK2, ANKRD27, ARL8B, BRCA2, BTN3A3, CA8, CBX8, CEP170,  CKAP2L, CPAMD8, CTSL1, DDX6L, DLG5, DNPEP, ESCO2, EXOC1,  FAM72A, GOLGA4, HCST, HIC1, KIF18A, KIF20A, KIF4A, LIPH, LPXN,  MICB, PSMD14, RAB6A, RAB6B, SNX24, TAZ, TUBGCP2,  fragmented cDNAs was used to hybridize human oligonucleotide array Gene 1.0 ST (Genechip; Affymetrix). The array comprised more than 750,000 unique 25-mer oligonucleotides constituting over 28,000 gene-level probe sets of the human genome. The cDNA probe corresponding to each biological repetition for each condition was hybridized on separate arrays. After hybridization, chips were processed using the Affymetrix GeneChip Fluidic Station 450 (protocol F450_0007). Chips were scanned with a GeneChip scanner 3000 7G (Affymetrix) and images were extracted with the Table 5 Summary of the cell experiments and microarray analyses. GeneChip operating software (Affymetrix GCOS v1.4). The microarray processing was performed at the DNA Biochip Platform service at CHU de Québec -CHUL Research Centre (Québec, Canada).

Microarray analysis
The microarray analysis has been described in the accompanying paper [1]. Quantified Affymetrix image files (".CEL" files) for each of the treatment conditions (including two independent replicates per treatment condition) were used to perform the microarray analyses using the Bioconductor package OneChannelGUI [4,5] in the statistical software environment R. Three contrasts (see Table 5) were using the RMA method [6]. Data filtering was performed at signal feature level by interquantile range (IQR) then by intensity. To identify differentially expressed genes, gene expression intensity was compared using a moderated t-test and a Bayes smoothing approach developed for a low number of replicates [7], and the false discovery rate was estimated from P-values derived from the moderated t-test statistics for correction for the effect of multiple testing [8]. Genes were considered to be significantly differentially expressed if p-values were o0.05. The log 2 transformed signal intensities were averaged, and the mean value was used to compute the fold changes. Genes that were differentially expressed 1.5-fold or higher were considered for subsequent analyses. Our microarray data is available in the Gene Expression Omnibus (GEO) repository, accession number GSE77345.

Functional enrichment analysis
Ingenuity pathway analysis (IPA s , QIAGEN Redwood City, www.qiagen.com/ingenuity) was used to assess the functional enrichment of the 208 modulated genes revealed by the three-contrast microarray analysis (genes which fold change equal or higher than 1.5 in at least one contrast). Three analyses made by IPA were presented here: identification of biological functions, gene networks and canonical pathways (see ref for additional information). Criteria used for the IPA analyses have been described in the accompanying research article [1].