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Gene Expression Profiles of Estrogen Receptor–Positive and Estrogen Receptor–Negative Breast Cancers Are Detectable in Histologically Normal Breast Epithelium

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Gene Expression Profiles of Estrogen Receptor–Positive and Estrogen Receptor–Negative Breast Cancers Are Detectable in Histologically Normal Breast Epithelium Published OnlineFirst November 8, 2010; DOI: 10.1158/1078-0432.CCR-10-1369 Clinical Cancer Human Cancer Biology Research Gene Expression Profiles of Estrogen Receptor–Positive and Estrogen Receptor–Negative Breast Cancers Are Detectable in Histologically Normal Breast Epithelium Kelly Graham1, Xijin Ge4, Antonio de las Morenas2, Anusri Tripathi3, and Carol L. Rosenberg1,2,3 Abstract Purpose: Previously, we found that gene expression in histologically normal breast epithelium (NlEpi) from women at high breast cancer risk can resemble gene expression in NlEpi from cancer-containing breasts. Therefore, we hypothesized that gene expression characteristic of a cancer subtype might be seen in NlEpi of breasts containing that subtype. Experimental Design: We examined gene expression in 46 cases of microdissected NlEpi from untreated women undergoing breast cancer surgery. From 30 age-matched cases [15 estrogen receptor (ER)þ,15ERÀ] we used Affymetryix U133A arrays. From 16 independent cases (9 ERþ,7ERÀ), we validated selected genes using quantitative real-time PCR (qPCR). We then compared gene expression between NlEpi and invasive breast cancer using four publicly available data sets. Results: We identified 198 genes that are differentially expressed between NlEpi from breasts with ERþ (NlEpiERþ) compared with ERÀ cancers (NlEpiERÀ). These include genes characteristic of ERþ and ERÀ cancers (e.g., ESR1, GATA3, and CX3CL1, FABP7). qPCR validated the microarray results in both the 30 original cases and the 16 independent cases. Gene expression in NlEpiERþ and NlEpiERÀ resembled gene expression in ERþ and ERÀ cancers, respectively: 25% to 53% of the genes or probes examined in four external data sets overlapped between NlEpi and the corresponding cancer subtype. Conclusions: Gene expression differs in NlEpi of breasts containing ERþ compared with ERÀ breast cancers. These differences echo differences in ERþ and ERÀ invasive cancers. NlEpi gene expression may help elucidate subtype-specific risk signatures, identify early genomic events in cancer development, and locate targets for prevention and therapy. Clin Cancer Res; 17(2); 236–46. Ó2010 AACR. Introduction tions are important to breast cancer initiation or early progression. Unexpectedly, alterations—genetic, epige- Breast cancer is a heterogeneous disease. One well-docu- netic, gene expression, and protein-–have been found in mented and clinically important dichotomizing character- histologically normal breast tissue, but their biological istic of breast cancers is expression (or not) of estrogen significance and clinical utility are poorly understood (refs. receptor–a (ER). ER expression is of major importance in 6–16; for review see ref. 17). They may mark increased risk, breast cancer prevention, treatment, and outcome (1–3), or be evidence of a field effect (e.g., due to an exposure or to and may even help define a cancer’s cell of origin (4). an occult dysregulation of a gene or pathway). They could Many of the genomic aberrations present in each subtype reveal breast cancer’s earliest genomic changes, they could of invasive breast cancers can also be detected in earlier be random effects, or they could be a response to a tumor lesions, such as carcinoma in situ and even hyperplastic existing in the breast. Although challenging to address, a lesions (for review see ref. 5), suggesting that these aberra- better understanding of the changes in histologically nor- mal tissue should provide insight into breast cancer risk, initiation, and early progression. Authors' Affiliation: 1Genetics and Genomics Program and Departments 2 3 Recently, we found that gene expression in histologi- of Pathology and Medicine, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts; and 4Department of cally normal breast epithelium (NlEpi) in women with Mathematics and Statistics, South Dakota State University, Brookings, breast cancers could be distinguished from NlEpi gene South Dakota expression in women without breast cancer who were Note: Supplementary data for this article are available at Clinical Cancer undergoing reduction mammoplasty (11, 18), and that Research Online (http://clincancerres.aacrjournals.org/). Current address for K. Graham: Roswell Park Cancer Institute, Buffalo, NY. NlEpi gene expression in women at high risk of breast Corresponding Author: Carol L. Rosenberg, Boston University Medical cancer undergoing prophylactic mastectomy resembles Center, 650 Albany Street, Boston, MA. Phone: 617-638-7523; Fax: 617- NlEpigeneexpressioninwomenwithbreastcancer 414-1831; Email: [email protected] (18). This suggests that aberrant NlEpi gene expression doi: 10.1158/1078-0432.CCR-10-1369 may indicate increased breast cancer risk by showing either Ó2010 American Association for Cancer Research. the cancer’s earliest genomic changes, or the influence of www.aacrjournals.org OF1 Downloaded from clincancerres.aacrjournals.org on October 2, 2021. © 2010 American Association for Cancer Research. Published OnlineFirst November 8, 2010; DOI: 10.1158/1078-0432.CCR-10-1369 Graham et al. Translational Relevance to ask whether these gene expression profiles mirrored the gene expression profiles in ERþ and ERÀ breast cancers We find that gene expression differs in histologically from independent cases. If this were true, then NlEpi normal epithelium of breasts containing ERþ compared expression could help define a risk signature for specific with ERÀ breast cancers. These differences reflect the cancer subtypes, identify genomic features distinguishing gene expression differences in ERþ compared with ERÀ the subtypes early in cancer development, and suggest new invasive cancers. Explanations of these findings include targets for subtype-specific prevention and therapy, which À an effect of the extracellular environment, a field effect, is of particular importance for ER cancers. predisposition to particular tumor subtypes due to inherited susceptibility genes, or detection of breast Materials and Methods cancer subtype-specific genomic changes prior to his- tologic abnormality. Regardless of which explanation is Case selection correct, normal epithelium gene expression profiles All cases were obtained using an IRB-approved protocol could help define a breast cancer subtype-specific risk for collection of de-identified breast tissue not required signature, identify the initial genomic differences for diagnosis. For microarray analysis, cases were ran- þ À between subtypes, and suggest new targets for preven- domly selected from women with ER or ER tumors tion and therapy, which is especially important for ERÀ undergoing cancer surgery. No patient had undergone cancers. chemotherapy or radiation treatment prior to tissue acquisition. Each ERþ case was age matched (within 2years)toanERÀ case, to account for effects of age the microenvironment on the epithelium. These findings on gene expression (refs. 19–21; Table 1). Seventeen of 30 led us to hypothesize that specific gene expression profiles cases had been used in other studies (11, 18). For quan- might characterize NlEpi associated with particular sub- titative real-time PCR (qPCR) validation of the array data, types. To test this hypothesis, the goals of this study were, an independent set of 16 cases (9 ERþ and 7 ERÀ)was first, to compare gene expression in NlEpi in breasts selected using the same criteria as described earlier in the containing 2 cancer subtypes, ERþ and ERÀ,and,second, text (Supplementary Table S1). Table 1. Clinical pathologic characteristics of 30 breast cancer patients whose histologically normal breast epithelium (NlEpi) was analyzed by microarray Patients with Patients with ERþ tumors (n ¼ 15) ERÀ tumors (n ¼ 15) Sample Age NlEpi distance ER/PR/ Staged Sample Age NlEpi distance ER/PR/ Staged (y) from tumor (cm) HER2c (y) from tumor (cm) HER2c 351Ha 35 <2 þ/þ/À IIA 319Hb 34 <2 À/À/À IIIA 297BHa 46 <2 þ/þ/À IIIC 364Hb 47 >2 À/À/þ IIIA 359Ha 48 <2 þ/þ/NA I 289Hb 47 <2 À/À/À IIA 304BHa,b 49 <2 þ/þ/þ I 342Hb 48 <2 À/À/À IIA 248Ha 49 >2 þ/þ/À I 273Hb 49 <2 À/À/þ III 345H 58 >2 þ/þ/À IIB 272Hb 58 >2 À/À/þ IIIC 388AHb 58 <2 þ/À/À I 322Hb 58 <2 À/À/À I 232Hb 59 >2 þ/þ/NA 0 226Ha,b 61 <2 À/À/þ IIIA 258Ha 65 <2 þ/þ/À IIA 452H 63 <2 À/À/À I 405H 67 >2 þ/þ/À III 298H 67 <2 À/À/À IIB 311H 69 >2 þ/þ/À IIA 429H 69 <2 À/À/À IIA 453H 76 >2 þ/À/À II 333Hb 76 >2 À/À/þ IIB 394H 81 >2 þ/þ/À IIA 413H 79 <2 À/À/À I 275H 85 <2 þ/þ/À IIIA 296H 82 <2 À/À/À I 228H 92 <2 þ/À/À IIB 401H 94 <2 À/À/À IIIA aUsed in Tripathi et al. (11). bUsed in Graham et al. (18). cEstrogen receptor, progesterone receptor, HER2 status of coincident tumor. dStage using AJCC stage criteria (61). Abbreviation: NA, not available. OF2 Clin Cancer Res; 17(2) January 15, 2011 Clinical Cancer Research Downloaded from clincancerres.aacrjournals.org on October 2, 2021. © 2010 American Association for Cancer Research. Published OnlineFirst November 8, 2010; DOI: 10.1158/1078-0432.CCR-10-1369 Normal Epi Gene Expression Reflects Cancer Gene Expression RNA extraction and microarray hybridization with differential expression with a false discovery rate Tissue preparation, microdissection, RNA extraction, (FDR) less than 5%, chosen to trade off sensitivity and amplification, hybridization, and normalization were specificity. Probes selected 80% or more of the time were completed as described previously (11, 18). Briefly, tissues included in the final list of differentially expressed genes were snap frozen, embedded in optimal cutting tempera- and the final probability scores and fold changes are ture embedding medium, sectioned at 10 mm, stained with based on all samples (Table 2). Heatmaps were generated hematoxylin and eosin (50% diluted with H20) and then using the package HeatPlus from Bioconductor and sim- histologically normal epithelium—both terminal ductal- ple hierarchical clustering was used to cluster samples lobular units (TDLU) and ducts—were identified and based on their expression profiles.
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