Age-associated gene expression in normal breast tissue mirrors qualitative age-at-incidence patterns for breast cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Troester Melissa
PROVIDER: S-ECPF-GEOD-43973 | biostudies-other |
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Background: Age is the strongest breast cancer risk factor, with overall breast cancer risk increasing steadily beginning at approximately 30 years of age. However, while breast cancer risk is lower among younger women, young women’s breast cancer may be more aggressive. Though several genomic and epidemiologic studies have shown higher prevalence of aggressive, estrogen-receptor negative breast cancer in younger women, the age-related gene expression that predisposes to these tumors is poorly understood. Characterizing age-related patterns of gene expression in normal breast tissues may provide insights on etiology of distinct breast cancer subtypes that arise from these tissues. Methods: To identify age-related changes in normal breast tissue, 96 tissue specimens from reduction mammoplasty patients aged 14 to 70 were assayed by gene expression microarray. Results: Significant associations between gene expression levels and age were identified for 802 probes (481 increased, 321 decreased with increasing age). Enriched functions included ‘aging of cells’, ‘shape change’, and ‘chemotaxis’, and enriched pathways included Wnt/beta-catenin signaling, Ephrin Receptor Signaling, and JAK/Stat Signaling. Applying the age-associated genes to publicly available tumor datasets, the age-associated pathways defined two groups of tumors with distinct survival. Conclusion: The hazard rates of young-like tumors mirrored that of high grade tumors in the Surveillance, Epidemiology and End Results Program, providing a biological link between normal aging and age-related tumor aggressiveness. Impact: These data show that studies of normal tissue gene expression can yield important insights about the pathways and biological pressures that are relevant during tumor etiology and progression. reference x sample
2013-08-31 | E-GEOD-43973 | biostudies-arrayexpress
Project description:Age is the strongest breast cancer risk factor, with overall breast cancer risk increasing steadily beginning at approximately 30 years of age. However, while breast cancer risk is lower among younger women, young women's breast cancer may be more aggressive. Although, several genomic and epidemiologic studies have shown higher prevalence of aggressive, estrogen-receptor negative breast cancer in younger women, the age-related gene expression that predisposes to these tumors is poorly understood. Characterizing age-related patterns of gene expression in normal breast tissues may provide insights on etiology of distinct breast cancer subtypes that arise from these tissues.To identify age-related changes in normal breast tissue, 96 tissue specimens from patients with reduction mammoplasty, ages 14 to 70 years, were assayed by gene expression microarray.Significant associations between gene expression levels and age were identified for 802 probes (481 increased, 321 decreased with increasing age). Enriched functions included "aging of cells," "shape change," and "chemotaxis," and enriched pathways included Wnt/beta-catenin signaling, Ephrin receptor signaling, and JAK/Stat signaling. Applying the age-associated genes to publicly available tumor datasets, the age-associated pathways defined two groups of tumors with distinct survival.The hazard rates of young-like tumors mirrored that of high-grade tumors in the Surveillance, Epidemiology, and End Results Program, providing a biologic link between normal aging and age-related tumor aggressiveness.These data show that studies of normal tissue gene expression can yield important insights about the pathways and biologic pressures that are relevant during tumor etiology and progression.
| S-EPMC3684707 | biostudies-literature
Project description:Background: Age is the strongest breast cancer risk factor, with overall breast cancer risk increasing steadily beginning at approximately 30 years of age. However, while breast cancer risk is lower among younger women, young women’s breast cancer may be more aggressive. Though several genomic and epidemiologic studies have shown higher prevalence of aggressive, estrogen-receptor negative breast cancer in younger women, the age-related gene expression that predisposes to these tumors is poorly understood. Characterizing age-related patterns of gene expression in normal breast tissues may provide insights on etiology of distinct breast cancer subtypes that arise from these tissues. Methods: To identify age-related changes in normal breast tissue, 96 tissue specimens from reduction mammoplasty patients aged 14 to 70 were assayed by gene expression microarray. Results: Significant associations between gene expression levels and age were identified for 802 probes (481 increased, 321 decreased with increasing age). Enriched functions included ‘aging of cells’, ‘shape change’, and ‘chemotaxis’, and enriched pathways included Wnt/beta-catenin signaling, Ephrin Receptor Signaling, and JAK/Stat Signaling. Applying the age-associated genes to publicly available tumor datasets, the age-associated pathways defined two groups of tumors with distinct survival. Conclusion: The hazard rates of young-like tumors mirrored that of high grade tumors in the Surveillance, Epidemiology and End Results Program, providing a biological link between normal aging and age-related tumor aggressiveness. Impact: These data show that studies of normal tissue gene expression can yield important insights about the pathways and biological pressures that are relevant during tumor etiology and progression.
2013-08-31 | GSE43973 | GEO
Project description:High serum levels of estradiol are associated with increased risk of postmenopausal breast cancer. Little is known about the gene expression in normal breast tissue in relation to levels of circulating serum estradiol.We compared whole genome expression data of breast tissue samples with serum hormone levels using data from 79 healthy women and 64 breast cancer patients. Significance analysis of microarrays (SAM) was used to identify differentially expressed genes and multivariate linear regression was used to identify independent associations.Six genes (SCGB3A1, RSPO1, TLN2, SLITRK4, DCLK1, PTGS1) were found differentially expressed according to serum estradiol levels (FDR = 0). Three of these independently predicted estradiol levels in a multivariate model, as SCGB3A1 (HIN1) and TLN2 were up-regulated and PTGS1 (COX1) was down-regulated in breast samples from women with high serum estradiol. Serum estradiol, but none of the differentially expressed genes were significantly associated with mammographic density, another strong breast cancer risk factor. In breast carcinomas, expression of GREB1 and AREG was associated with serum estradiol in all cancers and in the subgroup of estrogen receptor positive cases.We have identified genes associated with serum estradiol levels in normal breast tissue and in breast carcinomas. SCGB3A1 is a suggested tumor suppressor gene that inhibits cell growth and invasion and is methylated and down-regulated in many epithelial cancers. Our findings indicate this gene as an important inhibitor of breast cell proliferation in healthy women with high estradiol levels. In the breast, this gene is expressed in luminal cells only and is methylated in non-BRCA-related breast cancers. The possibility of a carcinogenic contribution of silencing of this gene for luminal, but not basal-like cancers should be further explored. PTGS1 induces prostaglandin E2 (PGE2) production which in turn stimulates aromatase expression and hence increases the local production of estradiol. This is the first report studying such associations in normal breast tissue in humans.
| S-EPMC3163631 | biostudies-literature
Project description:BackgroundBreast density and exposure to sex steroids are major risk factors for breast cancer. The local microenvironment plays an essential role in progression of breast cancer. Metabolic adaption is a major hallmark of cancer. Whether proteins from the extracellular space regulating metabolism are affected in breast cancer, dense breasts or by estrogen exposure are not yet fully elucidated.MethodsWomen with breast cancer, postmenopausal women with normal breast tissue with varying breast density or premenopausal women with breasts exposed to high levels of estradiol were included in the study. Microdialysis was used to collect proteins from the extracellular space in vivo in 73 women; 12 with breast cancer, 42 healthy postmenopausal women with different breast densities, and 19 healthy premenopausal women. Breast density was determined as lean tissue fraction (LTF) using magnetic resonance imaging. Data were evaluated in a murine breast cancer model. We quantified a panel of 92 key proteins regulating metabolism using proximity extension assay.ResultsWe report that 29 proteins were upregulated in human breast cancer. In dense breasts 37 proteins were upregulated and 17 of these were similarly regulated as in breast cancer. 32 proteins correlated with LTF. In premenopausal breasts 19 proteins were up-regulated and 9 down-regulated. Of these, 27 correlated to estradiol, a result that was confirmed for most proteins in experimental breast cancer. Only two proteins, pro-cathepsin H and galanin peptide, were similarly regulated in breast cancer, dense- and estrogen exposed breasts.ConclusionsMetabolic proteins may be targetable for breast cancer prevention. Depending on risk factor, this may, however, require different approaches as breast density and estradiol induce distinct different expression patterns in the breast. Additionally, metabolic proteins from the extracellular space may indeed be further explored as therapeutic targets for breast cancer treatment.
| S-EPMC10090464 | biostudies-literature
Project description:BackgroundAge is one of the most important risk factors for developing breast cancer. However, age-related changes in normal breast tissue that potentially lead to breast cancer are incompletely understood. Quantifying tissue-level DNA methylation can contribute to understanding these processes. We hypothesized that occurrence of breast cancer should be associated with an acceleration of epigenetic aging in normal breast tissue.ResultsNinety-six normal breast tissue samples were obtained from 88 subjects (breast cancer?=?35 subjects/40 samples, unaffected?=?53 subjects/53 samples). Normal tissue samples from breast cancer patients were obtained from distant non-tumor sites of primary mastectomy specimens, while samples from unaffected women were obtained from the Komen Tissue Bank (n?=?25) and from non-cancer-related breast surgery specimens (n?=?28). Patients were further stratified into four cohorts: age <?50 years with and without breast cancer and age ??50 with and without breast cancer. The Illumina HumanMethylation450k BeadChip microarray was used to generate methylation profiles from extracted DNA samples. Data was analyzed using the "Epigenetic Clock," a published biomarker of aging based on a defined set of 353 CpGs in the human genome. The resulting age estimate, DNA methylation age, was related to chronological age and to breast cancer status. The DNAmAge of normal breast tissue was strongly correlated with chronological age (r?=?0.712, p?<?0.001). Compared to unaffected peers, breast cancer patients exhibited significant age acceleration in their normal breast tissue (p?=?0.002). Multivariate analysis revealed that epigenetic age acceleration in the normal breast tissue of subjects with cancer remained significant after adjusting for clinical and demographic variables. Additionally, smoking was found to be positively correlated with epigenetic aging in normal breast tissue (p?=?0.012).ConclusionsWomen with luminal breast cancer exhibit significant epigenetic age acceleration in normal adjacent breast tissue, which is consistent with an analogous finding in malignant breast tissue. Smoking is also associated with epigenetic age acceleration in normal breast tissue. Further studies are needed to determine whether epigenetic age acceleration in normal breast tissue is predictive of incident breast cancer and whether this mediates the risk of chronological age on breast cancer risk.
| S-EPMC6114717 | biostudies-literature
Project description:miRNA deregulation has been found to promote carcinogenesis. Little is known about miRNA deregulation in hereditary breast tumors as no miRNA expression profiling studies have been performed in normal breast tissue of BRCA1 and BRCA2 mutation carriers. miRNA profiles of 17 BRCA1- and 9 BRCA2-associated breast carcinomas were analyzed using microarrays. Normal breast tissues from BRCA1 and BRCA2 mutation carriers (both n = 5) and non-mutation carriers (n = 10) were also included. Candidate miRNAs were validated by qRT-PCR. Breast carcinomas showed extensive miRNA alteration compared to normal breast tissues in BRCA1 and BRCA2 mutation carriers. Moreover, normal breast tissue from BRCA1 mutation carriers already showed miRNA alterations compared to non-mutation carriers. Chromosomal distribution analysis showed several hotspots containing down- or up-regulated miRNAs. Pathway analysis yielded many similarities between the BRCA1 and BRCA2 axes with miRNAs involved in cell cycle regulation, proliferation and apoptosis. Lesser known pathways were also affected, including cellular movement and protein trafficking. This study provides a comprehensive insight into the potential role of miRNA deregulation in BRCA1/2-associated breast carcinogenesis. The observed extensive miRNA deregulation is likely the result of genome-wide effects of chromosomal instability caused by impaired BRCA1 or BRCA2 function. This study's results also suggest the existence of common pathways driving breast carcinogenesis in both BRCA1 and BRCA2 germ-line mutation carriers.
| S-EPMC4741663 | biostudies-literature
Project description:Parallels between phylogeny and ontogeny have been discussed since almost two centuries and a number of theories have been proposed to explain such patterns. Especially elusive is the so-called phylotypic stage, a phase during development where species within a phylum are particularly similar to each other. While this has formerly been interpreted as a recapitulation of phylogeny, it is nowadays thought to reflect an ontogenetic progression phase, where strong constraints on developmental regulation and gene interactions exist. Several studies have shown that genes expressed during this stage evolve slower, but it has so far not been possible to derive an unequivocal molecular signature associated with this stage. We use here a combination of phylostratigraphy and stage specific gene expression data to generate a cumulative index that reflects the evolutionary age of the transcriptome at given ontogenetic stages. Using zebrafish ontogeny and adult development as a model, we find that the phylotypic stage does indeed express the oldest transcriptome set and that younger sets are expressed during early and late development, thus faithfully mirroring the hourglass model of morphological divergence. Reproductively active animals show the youngest transcriptome, with major differences between males and females. Intriguingly, aging animals express also increasingly older genes. Comparisons with similar datasets from flies and nematodes show that this pattern occurs across phyla. Our results suggest that an old transcriptome marks the phylotypic phase and that phylogenetic differences at other ontogenetic stages correlate with the expression of newly evolved genes. Zebrafish (Danio rerio) were kept in 12L flow-through tanks at 26.5 °C (around 60 animals per tank). For accurate staging, fertilized eggs were collected within 15 min intervalls and incubated in Petri dishes at 28.5°C with water changes every 2-6 hours. After hatching, larvae were transferred to 1 liter tanks and kept at 28.5 °C. We took 72 samples in at least two biological replicates (147 experiments in total) that correspond to 61 stages across zebrafish ontogeny (50 stages before the sex could be clearly recognized plus 11 adult stages of males and females each). Staging was done according to post-fertilization time. Embryos were additionally staged under the dissecting microscope to check for the consistency of post-fertilization timing and morphological development at standard temperature (28.5 °C). Only healthy animals that showed the expected morphological features for a given post-fertilization time were sampled. Each sample contained around 50 individuals until the 1 day and 3 hour embryo stage, 15 individuals until the 10 day larval stage, 10 individuals until the 18 day larval stage, 5 individuals until the 45 days juvenile stage, while in later juvenile and adult stages we sampled males and females separately and each sample contained 2 individuals. All samples were snap frozen in liquid nitrogen and stored at -80 °C until RNA extraction. To avoid severe biases due to the excess of unfertilized eggs we squeezed eggs from adult females before freezing them in liquid nitrogen.
2010-12-14 | E-GEOD-24616 | biostudies-arrayexpress
Project description:The underlying biological mechanisms through which epidemiologically defined breast cancer risk factors contribute to disease risk remain poorly understood. Identification of the molecular changes associated with cancer risk factors in normal tissues may aid in determining the earliest events of carcinogenesis and informing cancer prevention strategies.Here we investigated the impact cancer risk factors have on the normal breast epigenome by analyzing DNA methylation genome-wide (Infinium 450 K array) in cancer-free women from the Susan G. Komen Tissue Bank (n?=?100). We tested the relation of established breast cancer risk factors, age, body mass index, parity, and family history of disease, with DNA methylation adjusting for potential variation in cell-type proportions.We identified 787 cytosine-guanine dinucleotide (CpG) sites that demonstrated significant associations (Q value <0.01) with subject age. Notably, DNA methylation was not strongly associated with the other evaluated breast cancer risk factors. Age-related DNA methylation changes are primarily increases in methylation enriched at breast epithelial cell enhancer regions (P?=?7.1E-20), and binding sites of chromatin remodelers (MYC and CTCF). We validated the age-related associations in two independent populations, using normal breast tissue samples (n?=?18) and samples of normal tissue adjacent to tumor tissue (n?=?97). The genomic regions classified as age-related were more likely to be regions altered in both pre-invasive (n?=?40, P?=?3.0E-03) and invasive breast tumors (n?=?731, P?=?1.1E-13).DNA methylation changes with age occur at regulatory regions, and are further exacerbated in cancer, suggesting that age influences breast cancer risk in part through its contribution to epigenetic dysregulation in normal breast tissue.
| S-EPMC5504720 | biostudies-literature
Project description:Parallels between phylogeny and ontogeny have been discussed since almost two centuries and a number of theories have been proposed to explain such patterns. Especially elusive is the so-called phylotypic stage, a phase during development where species within a phylum are particularly similar to each other. While this has formerly been interpreted as a recapitulation of phylogeny, it is nowadays thought to reflect an ontogenetic progression phase, where strong constraints on developmental regulation and gene interactions exist. Several studies have shown that genes expressed during this stage evolve slower, but it has so far not been possible to derive an unequivocal molecular signature associated with this stage. We use here a combination of phylostratigraphy and stage specific gene expression data to generate a cumulative index that reflects the evolutionary age of the transcriptome at given ontogenetic stages. Using zebrafish ontogeny and adult development as a model, we find that the phylotypic stage does indeed express the oldest transcriptome set and that younger sets are expressed during early and late development, thus faithfully mirroring the hourglass model of morphological divergence. Reproductively active animals show the youngest transcriptome, with major differences between males and females. Intriguingly, aging animals express also increasingly older genes. Comparisons with similar datasets from flies and nematodes show that this pattern occurs across phyla. Our results suggest that an old transcriptome marks the phylotypic phase and that phylogenetic differences at other ontogenetic stages correlate with the expression of newly evolved genes.
2010-12-14 | GSE24616 | GEO