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Gene expression profiles of breast cancer subtypes are detectable in histologically normal breast epithelium

ABSTRACT: Background: We hypothesize that important genomic differences between breast cancer subtypes occur early in carcinogenesis. Therefore, gene expression might distinguish histologically normal breast epithelium (NlEpi) from breasts containing estrogen receptor positive (ER+) compared with estrogen receptor negative (ER-) cancers. Methods: We examined gene expression in 46 cases of microdissected NlEpi from previously untreated women undergoing breast cancer surgery. From 30 age-matched cases (15 ER+, 15 ER-) we used Affymetryix U133A arrays. From 16 independent cases (9ER+, 7 ER-), we validated seven selected genes using qPCR. We then compared gene expression between NlEpi and invasive breast cancer using 4 publicly available datasets. Results: 216 probes (corresponding to 198 unique genes) distinguished the NlEpi from breasts with ER+ (NlEpiER+) compared to ER- cancers (NlEpiER-). These include genes characteristic of ER+ and ER- cancers themselves, (e.g., ESR1, GATA3, and CX3CL1, FABP7, respectively). QPCR validated the microarray results in both a sampling of the 30 original cases (84%) and all of the 16 independent cases (77%). Gene expression in NlEpiER+ and NlEPIERNlEpiER- resembled gene expression in ER+ and ER- cancers, respectively: 36%-53% of the genes or probes examined in each the 4 external datasets overlapped between NlEpi and the corresponding cancer subtype. Conclusions: Gene expression differs in NlEpi of breasts containing ER+ compared to ER- breast cancers. These differences echo differences in ER+ and ER- invasive cancers. Thus, breast cancer subtypes may be detectable before histologic abnormalities. NlEpi gene expression may help define subtype-specific risk signatures, identify initial subtype specific genomic differences, and suggest new targets for subtype-specific prevention and therapy. We determined that 216 probesets significantly differed between histologically normal epithelium from ER+ breast cancer patients and from ER- breast cancer patients, and that gene expression in each type of histologically normal epithelium resembles expression of the corresponding subtype of invasive breast cancer (i.e., ER+ or ER-). These findings suggest that characteristic features of breast cancer subtypes are detectable prior to any histologic abnormality. This suggestion has implications for understanding breast cancer biology and devising new tools for assessing breast cancer risk.

ORGANISM(S): Homo sapiens

PROVIDER: GSE21947 | GEO | 2010/12/07

SECONDARY ACCESSION(S): PRJNA127237

REPOSITORIES: GEO

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Project description:Background: We hypothesize that important genomic differences between breast cancer subtypes occur early in carcinogenesis. Therefore, gene expression might distinguish histologically normal breast epithelium (NlEpi) from breasts containing estrogen receptor positive (ER+) compared with estrogen receptor negative (ER-) cancers. Methods: We examined gene expression in 46 cases of microdissected NlEpi from previously untreated women undergoing breast cancer surgery. From 30 age-matched cases (15 ER+, 15 ER-) we used Affymetryix U133A arrays. From 16 independent cases (9ER+, 7 ER-), we validated seven selected genes using qPCR. We then compared gene expression between NlEpi and invasive breast cancer using 4 publicly available datasets. Results: 216 probes (corresponding to 198 unique genes) distinguished the NlEpi from breasts with ER+ (NlEpiER+) compared to ER- cancers (NlEpiER-). These include genes characteristic of ER+ and ER- cancers themselves, (e.g., ESR1, GATA3, and CX3CL1, FABP7, respectively). QPCR validated the microarray results in both a sampling of the 30 original cases (84%) and all of the 16 independent cases (77%). Gene expression in NlEpiER+ and NlEPIERNlEpiER- resembled gene expression in ER+ and ER- cancers, respectively: 36%-53% of the genes or probes examined in each the 4 external datasets overlapped between NlEpi and the corresponding cancer subtype. Conclusions: Gene expression differs in NlEpi of breasts containing ER+ compared to ER- breast cancers. These differences echo differences in ER+ and ER- invasive cancers. Thus, breast cancer subtypes may be detectable before histologic abnormalities. NlEpi gene expression may help define subtype-specific risk signatures, identify initial subtype specific genomic differences, and suggest new targets for subtype-specific prevention and therapy. We determined that 216 probesets significantly differed between histologically normal epithelium from ER+ breast cancer patients and from ER- breast cancer patients, and that gene expression in each type of histologically normal epithelium resembles expression of the corresponding subtype of invasive breast cancer (i.e., ER+ or ER-). These findings suggest that characteristic features of breast cancer subtypes are detectable prior to any histologic abnormality. This suggestion has implications for understanding breast cancer biology and devising new tools for assessing breast cancer risk. 30 total laser capture microdissected histologically normal breast tissue samples were analyzed with Affymetrix HU133A microarrays. All samples were age-matched between histologically normal epithelial samples from ER+ breast cancer patients (n=15) and histologically normal epithelial samples from ER- breast cancer patients (n=15). Sample numbers correspond to individual patient samples. Of the 4 publicly available datasets mentioned above, the only dataset with a GEO number was GSE3494, corresponding to the Miller dataset. The supplementary file below lists the 251 Samples used from the GSE3494 study. We did not reanalyze the data - there was no change made to the Miller dataset; we only used these data for confirmation of our own dataset.

Project description:To better understand the biology of hormone receptor-positive and negative breast cancer and to identify methylated gene markers of disease progression, we performed a genome-wide methylation array analysis on 103 primary invasive breast cancers and 21 normal breast samples using the Illumina Infinium HumanMethylation27 array that queried 27,578 CpG loci. Estrogen and/or progesterone receptor-positive tumors displayed more hypermethylated loci than ER-negative tumors. However, the hypermethylated loci in ER-negative tumors were clustered closer to the transcriptional start site compared to ER-positive tumors. An ER-classifier set of CpG loci was identified, which independently partitioned primary tumors into ER-subtypes. Forty (32 novel, 8 previously known) CpG loci showed differential methylation specific to either ER-positive or ER-negative tumors. Each of the 40 ER-subtype-specific loci was validated in silico using an independent, publicly available methylome dataset from The Cancer Genome Atlas (TCGA). In addition, we identified 100 methylated CpG loci that were significantly associated with disease progression; the majority of these loci were informative particularly in ER-negative breast cancer. Overall, the set was highly enriched in homeobox containing genes. This pilot study demonstrates the robustness of the breast cancer methylome and illustrates its potential to stratify and reveal biological differences between ER-subtypes of breast cancer. Further, it defines candidate ER-specific markers and identifies potential markers predictive of outcome within ER subgroups. Frozen breast cancer tissues that were excised from patients with Stage 1-3 disease prior to treatment (n=103) were retrieved from Surgical Pathology at Johns Hopkins Hospital (Baltimore, Maryland) and confirmed to contain > 50% epithelial cells. Normal breast organoids were prepared by enzymatic digestion of reduction mammoplasty specimens (n=15; median patient age = 52 years, range 47 to 71). Normal ducts from breast tissue > 2 cm away from the tumor (n=6) were isolated from cryosections using laser-capture micro-dissection (PALM MicroBeam, Carl Zeiss Microimaging, North America). To determine the differences in breast cancer biology/behavior between ER subtypes, we characterized methylation patterns at 8376 selected CpG loci according to ER status. These loci met two criteria: 1) showed the most variation across primary tumors (SD >0.100) and 2) had probe detection p-values <0.0001. To develop an epigenomic signature that predicts outcome in patients with breast cancer, we conducted differential methylation analysis on primary tumors from recurrent versus non-recurrent breast cancers. We used a subgroup of 82 well-annotated, invasive breast tumors derived from the discovery set of 103 tumors that included 44 ER-positive (7 recurrences) and 38 ER-negative (11 recurrences) breast cancers and independently queried the ER-positive and ER-negative tumor groups

Project description:Gene expression in histologically normal epithelium from breast cancer patients and cancer-free prophylactic mastectomy patients share a similar profile Introduction: We hypothesized that gene expression in histologically normal epithelium (NlEpi) would differ in breast cancer patients (HN) compared to usual-risk controls undergoing reduction mammoplasty (RM), and that gene expression in NlEpi from cancer-free prophylactic mastectomies from high-risk women (PM), would resemble HN gene expression. Methods: We analyzed gene expression in 73 NlEpi samples microdissected from frozen tissue. In 42 cases, we used Affymetrix HU133A microarrays to compare gene expression in 18 RM vs 18 age-matched HN (9 ER+, 9 ER-) and 6 PM. Data were validated with qPCR in 31 independent NlEpi samples (8 RM, 17 HN, 6 PM). Results: 98 probesets (86 genes) were differentially expressed between RM and HN samples. Perfoming supervised hierarchical analysis with these 98 probesets, PM and HN samples clustered together, away from RM samples. qPCR validation of independent samples was high (84%) and uniform in RM vs HN, and lower (58%), but more heterogeneous, in RM vs PM. The 86 genes were implicated in many processes including transcription and the MAPK pathway. Conclusion: Gene expression differs between NlEpi of cancer cases and controls. The cancer cases' profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes. We determined that 98 probesets significantly differed between reduction mammoplasty and histologically normal epithelium from breast cancer patients. We also found that the histologically normal epithelium from prophylactic mastectomy patients' gene expression was more similar to histologically normal epithelium from breast cancer patients' than to reduction mammoplasty patients' gene expression. These results demonstrate that gene expression differs between NlEpi of cancer cases and controls. The cancer casesâ?? profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes. 42 total laser capture microdissected histologically normal breast tissue samples were analyzed with Affymetrix HU133A microarrays. 36 samples were age-matched between reduction mammoplasty (n=18) and histologically normal epithelial samples from breast cancer patients (n=18; 9ER+, 9ER-). 6 histologically normal epithelial samples from prophylactic mastectomy patients were then compared to data generated from the original 36 sample comparison. Sample numbers correspond to individual patient samples.

Project description:Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer where cells restricted to the ducts exhibit an atypical phenotype. Some DCIS lesions are believed to rapidly transit to invasive ductal carcinomas (IDCs), while others remain unchanged. Existing classification systems for DCIS fail to identify those lesions that transit to IDC. We studied gene expression patterns of 31 pure DCIS, 36 pure invasive cancers and 42 cases of mixed diagnosis (invasive cancer with an in situ component) using Agilent Whole Human Genome Oligo Microarrays 44k. Six normal breast tissue samples were also included as controls. qRT-PCR was used for validation. All DCIS and invasive samples could be classified into the intrinsic molecular subtypes defined for invasive breast cancer. Hierarchical clustering establishes that samples group by intrinsic subtype, and not by diagnosis. We observed heterogeneity in the transcriptomes among DCIS of high histological grade and identified a distinct subgroup containing seven of the 31 DCIS samples with gene expression characteristics more similar to advanced tumours. A set of genes independent of grade, ER-status and HER2-status was identified by logistic regression that univariately classified a sample as belonging to this distinct DCIS subgroup. qRT-PCR of single markers clearly separated this DCIS subgroup from the other DCIS, and contains samples from several histopathological and intrinsic molecular subtypes. The genes that differentiate between these two types of DCIS suggest several processes related to the re-organisation of the microenvironment. This raises interesting possibilities for identification of DCIS lesions both with and without invasive characteristics, which potentially could be used in clinical assessment of a woman's risk of progression, and lead to improved management that would avoid the current over- and under-treatment of patients. Breast cancer samples, 31 pure DCIS patients, 36 IDC patients, 42 mixed and 6 normal.

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Gene expression profiles of breast cancer subtypes are detectable in histologically normal breast epithelium

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