Hereditary BrEAst Case CONtrol study
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001005043 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:The BEACCON study aimed to address the lack of power of previous studies to identify novel BC predisposition genes by performing extensive sequencing in 12,000 women (11,511 analysed following exclusions) and further enhancing power by using an ‘extreme phenotype’ design with enrichment of familial non-BRCA1 and BRCA2 cases, compared with a control population of older women with ongoing confirmation of cancer-free status at June 2019. Three-quarters of the 1303 candidate genes screened were selected based on empiric evidence from local (69 multi-case BC families) or international whole exome sequencing studies, and the remainder were included to provide detailed coverage of functional pathways with established associations with BC.
| EGAD00001007025 | EGA
Project description:Breast carcinoma (BC) is the leading cause of death in women worldwide, making up 23% of all cancers in women, with 1.38 million new cases worldwide annually and responsible for 460,000 deaths. Despite the significant advances in the identification of molecular markers and different modalities of treatment in primary BC, the ability to predict the metastatic behavior in breast cancer is still limited. The purpose of this study was to help identify novel molecular markers associated with clinical outcome in a cohort of Brazilian BC patients. We generated global gene expression profiles from 24 patients with invasive ductal BC followed for ⥠5-years, including 15 samples from patients classified as presenting good prognosis based on traditional markers and clinical criteria and 9 patients that developed metastasis. We identified a set of 58 differentially expressed genes (p â¤0.01) between groups of patients with good and poor prognosis. Up-regulation of B3GNT7, PPM1D, TNKS2, PHB and GTSE1 in patients with poor prognosis was confirmed by quantitative RT-PCR in an independent sample set from patients with BC (47 with good prognosis and 8 that presented metastasis). Expression of BAD protein was investigated by immunohistochemistry in 1276 BC samples and confirmed the reduced expression levels in metastatic cases observed in the oligoarray data. These findings point to novel prognostic markers that can distinguish breast carcinoma samples according to clinical course and progression of the disease. Global expression profiles from 38 ductal breast tumor patient samples were used to search for molecular signatures correlated with current prognostic markers. A subset of 24 cases comprising 15 patients that remained free of disease after surgery and 9 patients that developed metastasis was used to identify candidate biomarkers associated with metastatic progression. Candidates were subsequently validated in additional independent samples by RT-qPCR or immunohistochemistry.
2016-06-30 | E-GEOD-73383 | biostudies-arrayexpress
Project description:Breast Cancer (BC) remains a major cause of mortality, and early detection is considered important for reducing BC-associated deaths. Early detection of BC is challenging in young women, due to the limitations of mammography on the dense breast tissue of young women. We recently reported results of a pilot study, using one-dimensional polyacrylamide gel electrophoresis (1D-PAGE)-based mass spectrometry (MS) to investigate differences in milk proteins from women with and without BC. Here, we applied two-dimensional polyacrylamide gel electrophoresis (2D-PAGE)-based MS to compare the protein pattern in milk from the breasts of a single woman who was diagnosed with BC in one breast 24 months after donating her mil. Statistically different gel spots were picked for protein digestion followed by nanoLC-MS/MS analysis. The upregulated proteins in BC versus control are alpha-amylase, gelsolin isoform a precursor, alpha-2-glycoprotein 1 zinc isoform CRA_b partial, apoptosis-inducing factor 2 and vitronectin. Several proteins were downregulated in the milk of the breast later diagnosed with cancer as compared to the milk from the healthy breast, including different isoforms of albumin, cholesterol esterase, different isoforms of lactoferrin, different proteins from the casein family and different isoforms of lysozyme. Results warrant further studies to determine the usefulness of these milk proteins for assessing risk and detecting occult disease.
2018-06-25 | PXD009860 | Pride
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 collected queens and their eggs from 3 beekeepers in British Columbia and Alberta. Samples were collected in both mid-May and mid-June from the 2 BC beekeepers, and late June for the AB beekeeper.
2024-08-16 | MSV000095627 | MassIVE
Project description:Bladder cancer (BC) is the most common malignant tumor of the urinary tract, ranking 4th among men and 18th among women, and it is mainly divided into non-muscle invasive and muscle-invasive. Recent studies showed that changes in the transcriptome activity may contribute to carcinogenesis. Thus, the study of the transcriptome may allow the identification of additional differentially expressed cancer-related candidate genes and, consequently, a better understanding of the molecular basis of gene regulation in BC. This case-control study consists of a mRNA analysis performed by RNA-seq in 11 BC patients (11 males; mean age 63.00±9.88 years) and 19 age- and sex-matched healthy controls (19 males ; mean age 58.81±23.41 years) from publish dataset.
2023-06-30 | E-MTAB-12828 | biostudies-arrayexpress
Project description:miRNA expression from breast tumor tissue obtained from two groups of breast cancer (BC) patients: one group formed by women younger than 36 years and the other group by women older than 65 years.
2014-09-12 | GSE48088 | GEO
Project description:Breast Cancer (BC) is one of the most common cancers and one of the most common causes for cancer- related mortality. Discovery of protein biomarkers associated with cancer, is considered as important for early diagnosis and prediction of the cancer risk. Protein biomarkers could be investigated by large-scale protein investigation or proteomics, using mass spectrometry (MS)- based techniques. Our group applies MS-based proteomics to study the protein pattern in human breast milk from women with BC and controls and investigates the alterations and dysregula-tions of breast milk proteins in comparison pairs of BC versus control. These dysregulated pro-teins might be considered as potential future biomarkers of BC. Identification of potential bi-omarkers in breast milk may benefit young women without BC, but who could collect the milk for future assessment of BC risk. Previously we identified several dysregulated proteins in dif-ferent sets of human breast milk samples from BC patients and controls using gel-based protein separation coupled with MS. Here, we performed two-dimensional polyacrylamide gel electro-phoresis (2D-PAGE) coupled with nano-liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) in a small-scale study on a set of 6 human breast milk samples (3 BC samples vs. 3 controls) and we identified several dysregulated proteins which have potential roles in cancer progression and might be considered as potential BC biomarkers in the future.
2023-10-20 | PXD040188 | Pride
Project description:Breast cancer (BC) is an important disease with high incidence as well as mortality among women, and critical socio-economic impacts. In the past 50 years, it has become a major health problem for women worldwide with over 2 million new cases diagnosed in 2018. This represents about 12% of all new cancer cases, 25% of all cancers in women and more than 600.000 cases of deaths worldwide in 2018 (Bray et al, 2018). If the cancer is located only in the breast, the 5-year relative survival rate of people with BC is 99% but this rate decreases if it is spread to lymph nodes (85%) and more dramatically if diagnosed with distant metastasis (26%) (Howlader et al, 2019; Siegel et al, 2017). Metastatic process, or the spread of tumor cells throughout the body, is responsible for about 90% of cancer patient deaths (Chaffer et al, 2011) and represents the central clinical challenge of solid tumor oncology. The development and progression of BC are complex processes that involve hormonal factors as well as numerous genetic and epigenetic alterations. During the past 10 years, many studies have focused on the role of the tumor microenvironment and the peritumoral stromal fraction, composed of adipose tissue, cancer-associated fibroblasts, endothelial cells and immune cells as macrophages and leukocytes. During tumor progression, cancer cells will deeply modify their microenvironment which in return will promote the growth and dissemination of the tumor (Allen et al, 2011; Polanska et al, 2013). Adipose tissue, consisting of mainly mature adipocytes and progenitors (preadipocytes and adipose-derived stem cells (ADSCs), is the most abundant component surrounding BC cells. Adipose tissue exerts a major endocrine and secretory role, and represents then an essential actor in the inflammatory, angiogenic or remodeling responses of the extracellular matrix, which influences tumor behavior.
2021-02-09 | PXD014328 | Pride
Project description:Mammographic breast cancer screening is effective in reducing breast cancer mortality. Nevertheless, several limitations are known. The objective of this study was to identify circulating microRNAs (miRs) ratios associated with BC in women attending mammography screening. A nested case-control study was conducted within the ANDROMEDA cohort (women of age 46-67 attending BC screening in northern Italy), where pre-diagnostic plasma samples, information on life-styles and common BC risk factors were collected. Small RNA sequencing was carried out on plasma samples from 65 cases and 66 controls. miR-ratios associated with BC were selected by two-sample Wilcoxon test and lasso logistic regression. Subsequent assessment by RT-qPCR of the miRs contained in the selected miR-ratios was carried out as a platform validation. Penalized logistic regression was further applied to candidate miR-ratios alone, or in combination with non-molecular factors, to build a diagnostic model.
2023-07-26 | GSE210329 | GEO