Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA189289 | ENA |
REPOSITORIES: ENA
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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: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:DNA methylation alterations have similar patterns in normal aging tissue and in cancer. In this study, we investigated breast tissue-specific age-related DNA methylation alterations and used those methylation sites to identify individuals with outlier phenotypes. Outlier phenotype is identified by unsupervised anomaly detection algorithms and is defined by individuals who have normal tissue age-dependent DNA methylation levels that vary dramatically from the population mean. To identify age-dependent DNA methylation sites, we generated DNA methylation sequencing data for 29 purified normal adjacent human breast epithelia (age range 33-82 years old) using Digital Restriction Enzyme Analysis of Methylation (DREAM). Next, we validated the age-related sites in publicly available DNA methylation (450K array) of 97 normal adjacent TCGA samples. We found that hypermethylation in normal breast tissue is the best predictor of hypermethylation in cancer. Using unsupervised anomaly detection approaches, we found that about 10% of the individuals (39 /427) were outliers for DNA methylation from 6 publicly available DNA methylation datasets (GSE88883, GSE74214, GSE101961, GSE69914(normal), GSE69914(normal-adjacent), TCGA (Firehose Legacy)). We also found that there were significantly more outlier samples in normal-adjacent to cancer (24/139, 17.3%) then in normal samples (15/228, 5.2%). Additionally, we found significant differences between predicted ages based on DNA methylation and the chronological ages among outliers and not-outliers. Additionally, we found that accelerated outliers (older predicted age) were more frequent in normal-adjacent to cancer (14/17, 82%) compared to normal samples from individuals without cancer (3/17, 18%). Furthermore, in matched samples, the epigenome of the outliers in the pre-malignant tissue was as severely altered as in cancer.
2021-05-26 | GSE160233 | GEO
Project description:Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. The relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors, is complex. Low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, but very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. The molecular impact of these factors on tumor initiation and growth is not well-understood. We modeled the difference in gene expression between 195 breast adenocarcinomas and 195 matched adjacent normal breast tissue samples, using age, body mass index (BMI), and tumor subtype as covariates. Age and BMI were independently associated with inflammation in normal tissue but not tumors. Older patients with ER-positive disease had tumors with higher levels of Estrogen Receptor (ER) signaling compared to adjacent normal tissue and had lower relative levels of tumor macrophage expression. We developed a novel statistic to quantify the rewiring of gene co-expression networks and demonstrate that in ER-positive tumors basal gene networks are rewired even though their expression levels of these genes are not significantly different from those in adjacent normal tissue. Patient age influences the molecular profile of ER-positive breast tumors. Our data support an immunosuppressive effect of estrogen signaling in the breast tumor microenvironment, suggesting this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors. 137 total samples: 43 mammaplastic reduction, 47 breast adenocarcinoma, 47 paired adjacent normal breast tissue
2016-07-01 | E-GEOD-70905 | biostudies-arrayexpress
Project description:Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. The relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors, is complex. Low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, but very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. The molecular impact of these factors on tumor initiation and growth is not well-understood. We modeled the difference in gene expression between 195 breast adenocarcinomas and 195 matched adjacent normal breast tissue samples, using age, body mass index (BMI), and tumor subtype as covariates. Age and BMI were independently associated with inflammation in normal tissue but not tumors. Older patients with ER-positive disease had tumors with higher levels of Estrogen Receptor (ER) signaling compared to adjacent normal tissue and had lower relative levels of tumor macrophage expression. We developed a novel statistic to quantify the rewiring of gene co-expression networks and demonstrate that in ER-positive tumors basal gene networks are rewired even though their expression levels of these genes are not significantly different from those in adjacent normal tissue. Patient age influences the molecular profile of ER-positive breast tumors. Our data support an immunosuppressive effect of estrogen signaling in the breast tumor microenvironment, suggesting this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors. 296 total samples: 148 breast adenocarcinoma, 148 paired adjacent normal breast tissue
2016-07-01 | E-GEOD-70947 | biostudies-arrayexpress
Project description:Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. The relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors, is complex. Low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, but very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. The molecular impact of these factors on tumor initiation and growth is not well-understood. We modeled the difference in gene expression between 195 breast adenocarcinomas and 195 matched adjacent normal breast tissue samples, using age, body mass index (BMI), and tumor subtype as covariates. Age and BMI were independently associated with inflammation in normal tissue but not tumors. Older patients with ER-positive disease had tumors with higher levels of Estrogen Receptor (ER) signaling compared to adjacent normal tissue and had lower relative levels of tumor macrophage expression. We developed a novel statistic to quantify the rewiring of gene co-expression networks and demonstrate that in ER-positive tumors basal gene networks are rewired even though their expression levels of these genes are not significantly different from those in adjacent normal tissue. Patient age influences the molecular profile of ER-positive breast tumors. Our data support an immunosuppressive effect of estrogen signaling in the breast tumor microenvironment, suggesting this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors.
2016-07-01 | GSE70905 | GEO
Project description:Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. The relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors, is complex. Low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, but very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. The molecular impact of these factors on tumor initiation and growth is not well-understood. We modeled the difference in gene expression between 195 breast adenocarcinomas and 195 matched adjacent normal breast tissue samples, using age, body mass index (BMI), and tumor subtype as covariates. Age and BMI were independently associated with inflammation in normal tissue but not tumors. Older patients with ER-positive disease had tumors with higher levels of Estrogen Receptor (ER) signaling compared to adjacent normal tissue and had lower relative levels of tumor macrophage expression. We developed a novel statistic to quantify the rewiring of gene co-expression networks and demonstrate that in ER-positive tumors basal gene networks are rewired even though their expression levels of these genes are not significantly different from those in adjacent normal tissue. Patient age influences the molecular profile of ER-positive breast tumors. Our data support an immunosuppressive effect of estrogen signaling in the breast tumor microenvironment, suggesting this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors.
2016-07-01 | GSE70947 | GEO
Project description:Younger age and obesity increase the incidence and rates of metastasis of triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer. The tissue microenvironment, specifically the extracellular matrix (ECM), is known to promote tumor invasion and metastasis. We sought to characterize the effect of both age and obesity on the ECM of liver tissue. We used a diet-induced obesity (DIO) model where 10-week-old female mice were fed a high-fat diet (HFD) for 12 weeks or a control chow diet (CD) where time points were every 4 weeks to monitor age and obesity. We isolated liver tissue to characterize the ECM at each time point. Utilizing proteomics, we found that the early stages of obesity were sufficient to induce distinct differences in the ECM composition of the livers. ECM proteins previously implicated in TNBC invasion, Collagen V and Collagen IV, were enriched with weight gain. Together these data implicate ECM changes in the primary tumor microenvironment as mechanisms by which age and obesity contribute to breast cancer progression.
2024-06-06 | PXD051409 | Pride
Project description:The underlying biology through which established breast cancer risk factors contribute to disease risk is not well characterized. One key risk factor for breast cancer is age, and age-related DNA methylation alterations may contribute to increased risk of disease. Here we assessed normal breast tissues and tested the relation of DNA methylation with known breast cancer risk factors. Cancer-free women donated breast tissue biopsy specimens through the Susan G. Komen Foundation and provided detailed risk factor data (n=100). Bisulfite modified DNA was profiled for DNA methylation genome-wide using the Infinium 450K DNA methylation array. We tested the relation of known breast cancer risk factors such as age, BMI, parity, and family history of disease with DNA methylation adjusted for variation in cell type proportions using a novel cellular mixture deconvolution algorithm. We identified 787 CpGs that exhibited significant (FDR adjusted, q-value < 0.01) differential DNA methylation associated with subject age, but not with other breast cancer risk factors. We observed an enrichment among the risk factor-related CpGs for Polycomb group target genes (Fisher’s Exact test, P = 1.74E-06), and breast myoepithelial cell enhancer regions (H3K4me1; Fisher’s Exact test, P = 7.1E-20). We validated our risk factor-related findings in two independent populations of normal breast tissue (n=18 and n=97). In addition, age-related CpGs were further deregulated in both pre-invasive (DCIS, n=40) and invasive breast cancers (TCGA, n=731). Overall, our results suggest that the breast cancer risk factor age contributes to epigenetic dysregulation in normal breast tissue that exhibit progressive changes in cancer.
2017-06-20 | GSE88883 | GEO
Project description:There is a lack of systematic investigations of large-scale transcriptome patterns associated with normal breast development. Herein, we profiled whole-transcriptome (by microarrays) of normal mammary glands in female Sprague-Dawley rats, an animal model widely used in breast cancer research, across six distinctive developmental stages – pre-pubertal, peri-pubertal, pubertal, lactation, and adult parous and age-matched nulliparous.
2018-07-04 | GSE87613 | GEO