Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of normal breast epithelium of breast cancer patients reveals gene expression abnormalities

ABSTRACT: Normal-appearing epithelium of cancer patients can harbor occult genetic abnormalities. Data comprehensively comparing gene expression between histologically normal breast epithelium of breast cancer patients and cancer-free controls are limited. The present study compares global gene expression between these groups. We performed microarrays using RNA from microdissected histologically normal terminal ductal-lobular units (TDLU) from 2 groups: (i) cancer normal (CN) (TDLUs adjacent to untreated ER1 breast cancers (n = 14)) and (ii) reduction mammoplasty (RM) (TDLUs of age-matched women without breast disease (n = 15)). Cyber-T identi?ed differentially expressed genes. Quantitative RT-PCR (qRT-PCR), immunohistochemistry (IHC), and comparison to independent microarray data including 6 carcinomas in situ (CIS), validated the results. Gene ontology (GO), UniProt and published literature evaluated gene function. About 127 probesets, corresponding to 105 genes, were differentially expressed between CN and RM (p < 0.0009, corresponding to FDR <0.10). 104/127 (82%) probesets were also differentially expressed between CIS and RM, nearly always (102/104 (98%)) in the same direction as in CN vs. RM. Two-thirds of the 105 genes were implicated previously in carcinogenesis. Overrepresented functional groups included transcription, G-protein coupled and chemokine receptor activity, the MAPK cascade and immediate early genes. Most genes in these categories were under-expressed in CN vs. RM. We conclude that global gene expression abnormalities exist in normal epithelium of breast cancer patients and are also present in early cancers. Thus, cancer-related pathways may be perturbed in normal epithelium. These abnormalities could be markers of disease risk, occult disease, or the tissueâs response to an existing tumor. Experiment Overall Design: 29 samples from histologically normal microdissected breast epithelium are included in this series. 14 samples are from epithelium adjacent to a breast tumor, 15 samples were obtained from patients undergoing reduction mammoplasty without apparent breast cancer

ORGANISM(S): Homo sapiens

SUBMITTER: Marc Lenburg

PROVIDER: E-GEOD-9574 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Gene expression abnormalities in histologically normal breast epithelium of breast cancer patients.

Tripathi Anusri A King Chialin C de la Morenas Antonio A Perry Victoria Kristina VK Burke Bohdana B Antoine Gregory A GA Hirsch Erwin F EF Kavanah Maureen M Mendez Jane J Stone Michael M Gerry Norman P NP Lenburg Marc E ME Rosenberg Carol L CL

International journal of cancer 20080401 7

Normal-appearing epithelium of cancer patients can harbor occult genetic abnormalities. Data comprehensively comparing gene expression between histologically normal breast epithelium of breast cancer patients and cancer-free controls are limited. The present study compares global gene expression between these groups. We performed microarrays using RNA from microdissected histologically normal terminal ductal-lobular units (TDLU) from 2 groups: (i) cancer normal (CN) (TDLUs adjacent to untreated ...[more]

PMID: 18058819

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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: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 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.

Project description:Introduction: microRNAs (miRNAs) are short non-coding RNAs that negatively regulate gene expression and may play a causal role in invasive breast cancer. Since many genetic aberrations of invasive disease are detectable in earlier stages, we hypothesized that miRNA expression dysregulation and the predicted changes in gene expression would also be found in early breast neoplasias. Methods: Expression profiling of 365 miRNAs by RT-qPCR was combined with laser-capture microdissection to obtain an epithelial specific miRNA expression signature of normal breast epithelium (n=9) and of paired samples of histologically normal epithelium (HN) and ductal carcinoma in situ (DCIS) (n=16). To determine how miRNAs may control the expression of co-dysregulated mRNAs we also performed gene expression microarray analysis in the same paired HN and DCIS samples and integrated this with miRNA-target prediction. We further validated several target pairs by modulating the expression levels of miRNAs in MCF7 cells and measured the expression of target mRNAs and proteins. Results: Thirty-five miRNAs were aberrantly expressed between RM, HN and DCIS. Twenty-nine miRNAs and 420 mRNAs were aberrantly expressed between HN and DCIS. Combining these two datasets with miRNA-target prediction we identified two established target pairs (miR-195:CCND1 and miR-21:NFIB) and tested several novel miRNA:mRNA target pairs. Over-expression of the putative tumor-suppressor miR-125b, under-expressed in DCIS, repressed the expression of MEMO1, which is required for ErbB2-driven cell motility (also a target of miR-125b); and NRIP1/RIP140, which modulates the transcriptional activity of the estrogen receptor. Knockdown of the putative oncogenic miRNAs miR-182 and miR-183, both highly over-expressed in DCIS, increased the expression of CBX7 (which regulates E-cadherin expression), DOK4, NMT2, and EGR1. Augmentation of CBX7 by knockdown of miR-182 expression, in turn, positively regulated the expression of E-cadherin, a key protein involved in maintaining normal epithelial cell morphology which is commonly lost during neoplastic progression. Conclusions: These data provide the first miRNA expression profile of normal breast epithelium and of pre-invasive breast carcinoma. Further, we demonstrate that altered miRNA expression can modulate gene expression changes that characterize these early cancers. We conclude that miRNA dysregulation likely plays a substantial role in early breast cancer development. The expression of 365 microRNAs were measured in 19 total samples via multiplex reverse transcription PCR using the TaqMan Human MicroRNA Low Density Array. Patients age ranged from 42-75. Equal amounts of total RNA from 9 reduction mammoplasty samples (age range 42-75) were combined into a pooled RM control (PRM), this sample was run in triplicate. Remaining 16 samples consist of matched samples of ductal carcinoma in situ and adjacent histologically normal breast epithelium, these are identified by case number and histologic lesion.

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.

Dataset Information

Transcription profiling of normal breast epithelium of breast cancer patients reveals gene expression abnormalities

Publications

Gene expression abnormalities in histologically normal breast epithelium of breast cancer patients.

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