Whole transcriptome profiling of 63 breast cancer tumours
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Illumina HiSeq 2000
ORGANISM(S): Homo sapiens
SUBMITTER: James Bradford
PROVIDER: E-MTAB-4993 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Whole transcriptome profiling of 63 breast cancer tumours
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Project description:Detection of breast cancer (BC) in young women is challenging because mammography, the most common tool for detecting BC, is not effective on the dense breast tissue characteristic of young women. In addition to the limited means for detecting their BC, young women face a transient increased risk of pregnancy-associated BC. As a consequence, reproductively active women could benefit significantly from a tool that provides them with accurate risk assessment and early detection of BC. One potential method for detection of BC is biochemical monitoring of proteins and other molecules in bodily fluids such as serum, nipple aspirate, ductal lavage, tear, urine, saliva and breast milk. Of all these fluids, only breast milk provides access to a large volume of breast tissue, in the form of exfoliated epithelial cells, and to the local breast environment, in the form of molecules in the milk. Thus, analysis of breast milk is a non-invasive method with significant potential for assessing BC risk. Here we analyzed human breast milk by mass spectrometry (MS)-based proteomics to build a biomarker signature for early detection of BC. Ten milk samples from 8 women provided 5 paired-groups (cancer versus control) for analysis of differentially expressed proteins: 2 within woman comparisons (milk from a diseased breast versus a healthy breast of the same woman) and 3 across women comparisons (milk from a woman with cancer versus a woman without cancer). Despite a wide range in the time between milk donation and cancer diagnosis (cancer diagnosis occurred from 1 month before to 24 months after milk donation), the levels of some proteins differed significantly between cancer and control in several of the 5 comparison groups. These pilot data are supportive of the idea that molecular analysis of breast milk will identify proteins informative for early detection and accurate assessment of BC risk, and warrant further research.
2017-12-18 | PXD007066 | Pride
Project description:We obtained peripheral blood samples for women from Utah (USA) and Ontario (Canada) who had a family history of breast cancer (or did not), who carried a BRCA1/2 mutation (or did not), and who had developed breast cancer (or had not). We classified the women into two groups: [1] those who had a family history of breast cancer (irrespective of BRCA1/2 mutation status) and had developed an early-onset breast tumor and [2] those who had a family history of breast cancer but had not developed a breast tumor or who did not have a family history of breast cancer (some of whom had developed sporadic breast cancer and and others who had not). We then used machine-learning methods to assess how well we could classify these women into either group. The Utah samples served as a training set, and the Ontario samples served as an independent validation set from a geographically distinct population. For the Utah cohort, there are 124 samples total: 16 who had a family history of breast cancer and carried a BRCA mutation and had developed breast cancer, 23 with a family history of breast cancer but did not carry a BRCA1/2 mutation and had developed breast cancer, 22 with a family history of breast cancer and carried a BRCA1/2 mutation but had not developed breast cancer, 22 with a family history of breast cancer but did not carry a BRCA1/2 mutation and had not developed breast cancer, 22 with no family history of breast cancer and had developed breast cancer, and 19 with no family history of breast cancer and had not developed breast cancer. The Ontario cohort included 73 samples: 11 who had a family history of breast cancer and carried a BRCA mutation and had developed breast cancer, 17 with a family history of breast cancer but did not carry a BRCA1/2 mutation and had developed breast cancer, 14 with a family history of breast cancer and carried a BRCA1/2 mutation but had not developed breast cancer, 18 with a family history of breast cancer but did not carry a BRCA1/2 mutation and had not developed breast cancer, 8 with no family history of breast cancer and had developed breast cancer, and 5 with no family history of breast cancer and had not developed breast cancer. 36 of the Ontario samples were scanned and processed at Duke University; the remaining 37 samples were handled at Boston University. The batch-adjustment process was repeated twice independently: [1] all 124 Utah samples were adjusted jointly with the 36 Ontario samples that had been processed at Duke University (set 1) and [2] all 124 Utah samples were adjusted jointly with the 37 Ontario samples that had been processed at Boston University (set 2). This dataset represents set 1.
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2007-03-31 | GSE7127 | GEO
Project description:We obtained peripheral blood samples for women from Utah (USA) and Ontario (Canada) who had a family history of breast cancer (or did not), who carried a BRCA1/2 mutation (or did not), and who had developed breast cancer (or had not). We classified the women into two groups: [1] those who had a family history of breast cancer (irrespective of BRCA1/2 mutation status) and had developed an early-onset breast tumor and [2] those who had a family history of breast cancer but had not developed a breast tumor or who did not have a family history of breast cancer (some of whom had developed sporadic breast cancer and and others who had not). We then used machine-learning methods to assess how well we could classify these women into either group. The Utah samples served as a training set, and the Ontario samples served as an independent validation set from a geographically distinct population.
2015-10-21 | GSE47861 | GEO
Project description:We obtained peripheral blood samples for women from Utah (USA) and Ontario (Canada) who had a family history of breast cancer (or did not), who carried a BRCA1/2 mutation (or did not), and who had developed breast cancer (or had not). We classified the women into two groups: [1] those who had a family history of breast cancer (irrespective of BRCA1/2 mutation status) and had developed an early-onset breast tumor and [2] those who had a family history of breast cancer but had not developed a breast tumor or who did not have a family history of breast cancer (some of whom had developed sporadic breast cancer and and others who had not). We then used machine-learning methods to assess how well we could classify these women into either group. The Utah samples served as a training set, and the Ontario samples served as an independent validation set from a geographically distinct population.
2015-10-21 | GSE47860 | GEO
Project description:Estrogen Receptor alpha (ERa) is the main driver of luminal breast cancer development and progression, and represents the main drug target in patient care. ERa chromatin binding has been extensively studied in breast cancer cell lines and a number of human tumors, often focused on differential binding patterns between groups or conditions. However, little is known about the inter-tumor heterogeneity of ERa chromatin action. Here, we use a large set of ERa ChIP-seq data from 70 ERa+ breast cancers (40 women & 30 men) to explore general inter-patient heterogeneity in ERa DNA binding in breast cancers. We found a total universe of 84,565 and 101,653 ERa sites in females and males respectively, with merely 1.2% and 5% of sites shared in at least half of the tumors analyzed, reflecting a high level of inter-patient heterogeneity. This heterogeneity was found to be most variable at putative enhancers as opposed to promoter regions, potentially reflecting a level of functional redundancy in enhancer action. Interestingly, commonly shared ERa sites showed the highest estrogen-driven enhancer activity, as determined using a massive parallel reporter assay, and were most-engaged in long-range chromatin interactions. In addition, the most-commonly shared ERa-occupied enhancers were found enriched for breast cancer risk SNP loci. We experimentally illustrate such SNVs can impact chromatin binding potential for ERa and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we could confirm these variations to associate with differences in expression for the target gene. Cumulatively, our data reveal a natural hierarchy of ERa-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ERa landscape, with the most-common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.
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