Comment[ArrayExpressAccession] E-GEOD-43467 MAGE-TAB Version 1.1 Public Release Date 2013-07-12 Investigation Title Role of HGF in epithelial-stromal cell interactions during progression from benign breast disease to ductal carcinoma in situ Comment[Submitted Name] Role of HGF in epithelial-stromal cell interactions during progression from benign breast disease to ductal carcinoma in situ Experiment Description ABSTRACT: Introduction: Basal-like and luminal breast cancers have distinct stromal-epithelial interactions, which likely play a role in progression to invasive cancer. However, little is known about how stromal-epithelial interactions evolve in benign and pre-invasive lesions.Methods: To study epithelial-stroma interactions in basal-like breast cancer progression, we cocultured reduction mammoplasty fibroblasts with the isogenic MCF10 series of cell lines (representing benign/normal, atypical hyperplasia, and ductal carcinoma in situ). We used gene expression microarrays to identify pathways induced by coculture in premalignant cells (MCF10DCIS) compared to normal and benign (MCF10A and MCF10AT1). Relevant pathways were then (1) targeted in vitro and effects on morphogenesis were evaluated and (2) evaluated in vivo for associations with basal-like subtype. Results: Our results show that premalignant MCF10DCIS cells express characteristic gene expression patterns of invasive basal-like microenvironments. Furthermore, while HGF secretion is upregulated (relative to normal, MCF10A levels) when fibroblasts are cocultured with either atypical (MCF10AT cells) or premalignant (MCF10DCIS) cells, only MCF10DCIS cells upregulate the HGF receptor, MET. In 3-dimensional cultures, upregulation of HGF/MET in MCF10DCIS cells induced morphological changes suggestive of invasive potential, and these changes were reversed by antibody-based blocking of HGF signaling. These results are relevant to in vivo progression because high expression of a novel MCF10DCIS-derived HGF signature was correlated with basal-like subtype among invasive cancers, with approximately 86% of basal-like cancers highly expressing the HGF signature. Conclusions: In this study we document coordinated and complementary changes in HGF secretion and MET expression in epithelium and stroma in pre-invasive lesions. These results suggest that targeting stroma-derived HGF signaling in early carcinogenesis may block progression of basal-like precursor lesions.Introduction: In breast cancers, the basal-like subtype has high levels of genomic instability relative to other breast cancer subtypes with many basal-like-specific regions of aberration. There is evidence that this genomic instability extends to smaller scale genomic aberrations as well, as shown by a previously described micro-event in the PTEN gene in the Basal-like SUM149 breast cancer cell line. Methods: We sought to identify if small regions of genomic change exist by using a high density, gene centric Comparative Genomic Hybridizations (CGH) array on both cell lines and primary tumors. A custom Agilent tiling array for CGH (244,000 probes, 200bp tiling resolution) was created to identify small regions of genomic change and was focused on previously identified basal-like-specific, and general cancer genes. Tumor genomic DNA from 94 patients and 2 breast cancer cell lines was labeled and hybridized to these arrays. Aberrations were called using SWITCHdna and the smallest 25% of SWITCHdna-defined genomic segments being called micro-aberrations (<64 contiguous probes, ~ <15kb). Results: Our data showed that primary tumor breast cancer genomes frequently contained areas of small-scale copy number gains and losses, termed micro-aberrations, which are undetectable using lower-density genome-wide platforms. The basal-like subtype exhibited the highest incidence of these events. These micro-aberrations sometimes altered expression of the involved gene as suggested by data from microarray and mRNA-seq studies. We confirmed the presence of the PTEN micro-amplification in SUM149 and by mRNA-seq showed that this resulted in loss of expression of all exons downstream of this event. Micro-aberrations disproportionately affected the 5’ regions of the affected genes, including the promoter region, and a high frequency of micro-aberrations was associated with poor survival outcomes. Conclusion: Using a high probe density, gene-centric aCGH microarray, we present evidence of small-scale genomic aberrations that contribute to gene inactivation, and thus, genomic instability and tumor formation through a mechanism not detected using conventional copy number analyses. reference x sample Term Source Name ArrayExpress EFO Term Source File http://www.ebi.ac.uk/arrayexpress/ http://www.ebi.ac.uk/efo/efo.owl Person Last Name Troester Casbas-Hernandez Troester Person First Name Melissa Patricia Melissa Person Mid Initials A Person Email troester@unc.edu Person Affiliation University of North Carolina at Chapel Hill Person Address Epidemiology, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC, USA Person Roles submitter Protocol Name P-GSE43467-1 P-GSE43467-6 P-GSE43467-3 P-GSE43467-7 P-GSE43467-11 P-GSE43467-4 P-GSE43467-9 P-GSE43467-2 P-GSE43467-5 P-GSE43467-10 P-GSE43467-8 Protocol Description Data for both channels were Lowess-normalized and then log(2) ratio was taken ID_REF = Spot Reference ID VALUE = log2_ratio of CH2DL_MEAN over CH1DL_MEAN (LOG_RAT2L_MEAN) SPOT = spot number on array CH1_MEAN = CH1_SD = standard deviation of channel 1 intensity CH1_BKD_MEDIAN = channel 1 background median intensity CH1_BKD_SD = standard deviation of channel 1 background median intensity CH2_MEAN = channel 2 mean intensity CH2_SD = standard deviation of channel 2 intensity CH2_BKD_MEDIAN = channel 2 background median intensity CH2_BKD_SD = standard deviation of channel 2 background median intensity TOT_BPIX = number of background pixels TOT_SPIX = number of spot pixels CH2BN_MEDIAN = channel 2 normalized background median intensity CH2IN_MEAN = channel 2 normalized mean intensity CH1DL_MEAN = channel 1 Lowess_normalized mean intensity CH2DL_MEAN = channel 2 Lowess_normalized mean intensity LOG_RAT2N_MEAN = log2_ratio of channel 2 normalized over channel 1 (global normalization) CORR = correlation coefficient among pixels FLAG = Spot flag. 0:not flagged; negative:flagged as bad spots; positive:flagged as good spots Described in Hu et al. 2005, BioTechniques, 38:121-124 (PMID 15679094). Agilent protocol Agilent protocol plus anti-HGF treatment every two hours after 36 in coculutre with fibroblasts coculture with reduction mammary fibroblasts plus rHGF treatment every 2 hours for 6 hours Qiagen Rneasy Mini growth in DMEM:F12 complete media with supplements growth in DMEM:F12 serum free Fluorescent array images were collected for both Cy3 and Cy5 with an Agilent scanner and image intensity data were analyzed with Agilent software. Protocol Type normalization data transformation protocol labelling protocol labelling protocol hybridization protocol sample treatment protocol sample treatment protocol sample treatment protocol nucleic acid extraction protocol growth protocol growth protocol array scanning protocol Experimental Factor Name SAMPLE TYPE CELL LINE TREATMENT Experimental Factor Type sample type cell line treatment Comment[SecondaryAccession] GSE43467 Comment[GEOReleaseDate] 2013-07-12 Comment[ArrayExpressSubmissionDate] 2013-01-11 Comment[GEOLastUpdateDate] 2013-07-17 Comment[AEExperimentType] transcription profiling by array SDRF File E-GEOD-43467.sdrf.txt