Cell lines and culture conditions
MCF-10A ER-Src and MCF-10A pBABE cells were grown in DMEM/F12 medium supplemented as described in (Debnath et al., 2003
) with the addition of puromycin. The Src oncogene was induced by the addition of 1 uM Tamoxifen (Sigma) to confluent cell cultures for times indicated in the text. For testing the effect of drugs on transformation, each drug was titrated for optimum inhibition with minimal effects on non-transformed cells. All BJ fibroblast cell lines, described previously (Hahn et al., 1999
), were cultured on KO-DMEM media, 10% FBS, Medium 199 glutamine and Pen/strep. Each drug used in the drug screen was titrated for optimum inhibition with minimal effects on non transformed cells. The following drugs were used in the following concentrations: metformin (0.1 mM), cerulenin (1 µg/ml), tocilizumab (2 µg/ml), Aspirin (0.1 mM), exendin4 (15 µm), sulindac (100 mM), Simvastatin (10 µM), meloxicam (30 µM), Indomethacin (30 µg/ml), celecoxib (10 µM), piroxicam (100 µM), Nimesulide (50 µM), Sulindac (100 µM), mevastatin (1 µM).
RNA was extracted from all cell lines by Trizol method followed by RNeasy columns purification. These samples were hybridized on an Affymetrix U133 2.0A array at the Dana Farber Array Facility.
Gene expression analyses
All gene expression data was normalized and summarized with RMA algorithm (Irizarry et al., 2003
) with an updated Entrez gene probeset definition (Dai et al., 2005
). ComBat (Johnson et al., 2007
) was used to remove non-biological experimental variation or batch effects between batches of microarray experiments. In order to detect differentially expressed genes, Significance Analysis of Microarrays (SAM) algorithm (Tusher et al., 2001
) was used to calculate the q-values (False Discovery Rate) for genes in each time point. For ER-Src expression arrays, 7 samples were used as controls, including: Er-src_12EtOH (D1, D2, D3), Er-src_24EtOH (D1, D3), Er-src_0hr_TAM (D2, D3). A gene will be regarded as differentially expressed gene, only if 1) it was ‘present’, in terms Affymetrix MAS5 present/absent calls, in at least one time points and 2) q-value < 1 (either up-regulated or down-regulated) in at least one time points.
Disease gene sets
Gene sets were collected directly from previously published papers. These include the 1406 gene set for metabolic disorders (Chen et al., 2008
), the 494 gene set for atherosclerosis (Sluimer et al., 2007
), the 60 gene set for inflammatory breast cancer (Lerebours et al., 2008
), the 28 gene set for inflammatory gastric cancer (Ellmark et al., 2006
), the 687 gene set for thyroid cancer (Delys et al., 2007
), and the 80 gene set for pancreatic cancer (Logsdon et al., 2003
Lever algorithm analysis
The Lever algorithm was described previously (Warner et al., 2008
). We incorporated the phylogenetic information from 12 mammals: mouse, rat, human, rabbit, chimp, macaque, cow, dog, armadillo, tenrec, opossum and elephant and used the MultiZ 17-way alignment as described in Supplementary Methods
. The PBM data used in the study was for 104 TFs (transcription factors) from 22 structural classes (Badis et al., 2009
) and for 178 TFs from the Homeodomain class (Berger et al., 2008
). We used “Seed-and-Wobble” algorithm that has been described previously (Berger et al., 2006
) in order to represent these data as position weight matrices (PWMs) for each TF. We used these PWMs in the Lever analysis.
Ingenuity pathway analysis
Ingenuity Pathways Analysis, (Ingenuity Systems, Mountain View, CA) is a robust and expertly curated database containing up-to-date information on over 20,000 mammalian genes and proteins, 1.4 million biological interactions, and one hundred canonical pathways incorporating over 6,000 discreet gene concepts. This information is integrated with other relevant databases such as EntrezGene and Gene Ontology. The experimental datasets were used to query the IPA and to compose a set of interactive networks taking into consideration canonical pathways, the relevant biological interactions, and the cellular and disease processes.
The overlap count was computed by counting the number of genes in the intersection between two different gene sets. P values were calculated by Fisher Exact Test and Hypergeometric Probability Distribution Analysis in order to estimate the statistical significance of overlap between two gene sets.
Small interference RNA transfection experiments
MCF10A ER-Src cells were seeded in 6-well plates and were transfected with 100 nM siRNAs from Ambion Inc. against OLR1 (s9842 and s9843), GLRX (s5841 and s229668), PLAU (s10610 and s10612), GRN (s6149 and s6151), PGS1 (s18191 and s18192), SCD1 (s12505), FGD6 (s31504), MRPL9 (s35151), MOCOS (s230170), MYC (s1930), AKT (s659), SOCS3 (s17190), STAT3 (s744), HIF1A (s6539), NF-κB (s11914), IL6 (s7313), RAS (s806), VEGF (s460) using siPORT NeoFX transfection agent. SiPORT NeoFX is a lipid transfection agent consisting of a mixture of lipids that spontaneously complex small interference RNA and facilitates its transfer to the cells. Transfection with 100 nM siRNA (s4390846) was used as a control. No cell toxicity was detected due to the transfection agent.
Soft agar colony assay
Triplicate samples were mixed 4:1 (v/v) with 2.0% agarose in cell growth medium for a final concentration of 0.4% agarose. The cell mixture was plated on top of a solidified layer of 0.5% agarose in growth medium. Cells were fed every 6 to 7 days with growth medium containing 0.4% agarose. The number of colonies was counted after 15 days. The experiment was repeated thrice and the statistical significance was calculated using Student’s t test.
Cell migration, invasion, and wound healing assays
For the migration assay, 105
trypinized cells were added to the top chambers of the transwell (8 µm pore size; BD Bioscience, Bedford, MA), and assay medium was added to the bottom chambers. After overnight incubation, the migratory cells were fixed and stained with 0.1% crystal violet solution. The experiment was repeated thrice and the statistical significance was calculated using Student’s t test. Invasion of matrigel has conducted by using standardized conditions with BDBioCoat growth factor reduced MATRIGEL invasion chambers (PharMingen). Assays were conducted according to manufacturer’s protocol, by using 5% horse serum (GIBCO) and 20 ng/ml EGF as chemoattractants. Wound healing assays have been described previously (Hirsch et al., 2009
Equal amounts of purified RNA samples from untreated and TAM-induced (1, 2, 4, 8, 12, 16, 24, 36h) MCF10A ER-Src cells or from other cancer cell lines were reverse-transcribed to form cDNA, which was subjected to SYBR Green based real-time PCR analysis. To analyze patient samples, RNAs from 48 mammary adenocarcinoma tissues and 3 normal mammary tissues; 44 prostate adenocarcinoma and 3 normal tissues were purchased from Origene (Rockville, MD). The experiments have been performed in triplicate and data are presented as mean ± SD.
The NF-kB/p65 ActivELISA Kit measured nuclear p65 levels in MCF10 ER-Src untreated or TAM-treated for 36h. The anti-p65 antibody coated plate captures free p65 and the amount of bound p65 is detected by adding a second anti-p65 antibody followed by alkaline phosphatase (AKP) -conjugated secondary antibody using colorimetric detection in an ELISA plate reader at absorbance 405nm. To detect IκBα phosphorylation status (serine 32), we used a solid phase sandwich enzyme-linked immunosorbent assay (cat no 7276, Cell Signaling) according to the manufacturer’s instructions. The magnitude of the absorbance (450 nm) is proportional to the quantity of bound target protein. To detect TNFα production, we used a TNF-alpha Quantikine ELISA Kit (cat no. DTA00C, R&D Systems) according to manufacturer’s instructions. For all ELIZA assays, each sample was loaded in triplicate and data are presented as mean ± SD.
Tumor growth in xenografts
To assess the role of OLR1, 5×106 transformed MCF10A ER-Src cells were injected into the right flank of 15 female nu/nu mice (Charles River Laboratories), all of which developed tumors in 15 days with size ~125mm3. The mice were randomly distributed into 3 groups that were untreated, or treated by intraperitoneal injections every 5 days (4 cycles) with 100 nM siRNA against OLR1 or a control siRNA. To assess the effects of metformin (20 mg/kg), cerulenin (40 mg/kb), simvastatin (20 mg/kg) and sulindac (15 mg/kg), the same procedure was followed except that drug treatment started 10 days of tumor formation (size ~60mm3). Tumor volume was measured at various times after the initial injection. All mouse experiments were approved by the Tufts University Institutional Animal Care and Use Committee.
Microarray data has been deposited at GEO, with an accession number of GSE17941.
Although there are epidemiological and clinical connections between cancer and other diseases, the molecular bases of these connections are not well understood. mRNA expression profiling in two isogenic models of cellular transformation identifies a transcriptional signature and underlying gene regulatory networks that underlie diverse human diseases. In addition, it reveals the heretofore unappreciated importance of lipid metabolism to cellular transformation as well as the connection of cancer to atherosclerosis. These observations lead to the view that a variety of phenotypically diverse disease states are nevertheless linked through a common transcriptional program involving inflammatory and metabolic pathways.