Homo sapiens
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PROVIDER: PRJNA208904 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:A nested case-control study to investigate drivers for metastatic disease in breast cancer (QC substudy)
| PRJNA323489 | ENA
Project description:The purpose of this study was to improve prediction of patients at high-risk for metastatic disease utilizing a nested case-control design that uniquely enables enrichment for relevant phenotypes. We identified all women diagnosed with primary breast cancer from January 1, 1997, to December 31, 2005, in the Stockholm health care region. Patients developing distant metastatic disease (cases) were selected and controls (free from distant disease) were randomly matched by adjuvant therapy, age and calendar period at diagnosis. The nested case-control study included 768 study subjects with clinical information and gene expression arrays (Human Cancer G110). Study subjects were randomly and equally divided into training set (discovery) or testing (validation) set. Metastatic onset prediction was then compared including either clinical variables only or combining clinical and genetic information. Differentially expressed genes and pathways between cases and controls included a wide-spectrum of well known as well as candidate regulators of the metastatic cascade. The nested case-control study included 768 study subjects corresponding to 623 primary tumor samples. Details concerning case-control status are given in the samples section. Each case and its' matching controls form risk sets, indicated by the setnr variable.
2014-11-03 | E-GEOD-48091 | biostudies-arrayexpress
Project description:The purpose of this study was to improve prediction of patients at high-risk for metastatic disease utilizing a nested case-control design that uniquely enables enrichment for relevant phenotypes. We identified all women diagnosed with primary breast cancer from January 1, 1997, to December 31, 2005, in the Stockholm health care region. Patients developing distant metastatic disease (cases) were selected and controls (free from distant disease) were randomly matched by adjuvant therapy, age and calendar period at diagnosis. The nested case-control study included 768 study subjects with clinical information and gene expression arrays (Human Cancer G110). Study subjects were randomly and equally divided into training set (discovery) or testing (validation) set. Metastatic onset prediction was then compared including either clinical variables only or combining clinical and genetic information. Differentially expressed genes and pathways between cases and controls included a wide-spectrum of well known as well as candidate regulators of the metastatic cascade.
2015-07-08 | GSE48091 | GEO
Project description:This is a quality control (QC) substudy of GSE48091. The QC substudy comprises gene-expression profiling of re-extracted tumor RNA for a subset of the tumours in the full study. As background, a population-based cohort study of metastatic breast cancer patients was first designed. Thereafter, a case-control study nested in the corresponding population-based cohort of primary breast cancer patients was designed by selecting distant metastasis-free controls to each case. Tumor RNA was extracted in the same order. All RNA was profiled on microarrays in randomized order. For quality control, RNA was also re-extracted (new tumor piece) in a randomized order for randomly selected cases-controls sets and profiled with the rest. Keywords: Expression profiling by array The nested case-control study included 768 study subjects corresponding to 623 primary tumor samples. This QC substudy comprises 97 of the study subjects (all different primary tumor samples). Details concerning case-control status are given in the samples section. This Series includes a re-analysis of 97 samples from GSE48091. The file "full_data_matrix.txt" includes the re-normalized values for the 97 samples from GSE48091 and the normalized values for the 97 new samples from the same patients that were analyzed together.
2016-05-28 | E-GEOD-81954 | biostudies-arrayexpress
Project description:This is a quality control (QC) substudy of GSE48091. The QC substudy comprises gene-expression profiling of re-extracted tumor RNA for a subset of the tumours in the full study. As background, a population-based cohort study of metastatic breast cancer patients was first designed. Thereafter, a case-control study nested in the corresponding population-based cohort of primary breast cancer patients was designed by selecting distant metastasis-free controls to each case. Tumor RNA was extracted in the same order. All RNA was profiled on microarrays in randomized order. For quality control, RNA was also re-extracted (new tumor piece) in a randomized order for randomly selected cases-controls sets and profiled with the rest. Keywords: Expression profiling by array
2016-05-28 | GSE81954 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE30758: Epigenome analysis of normal cells from the uterine cervix in a nested prospective case control study within the ARTISTIC trial GSE30759: Epigenome analysis of normal and cancer tissue from the uterine cervix Refer to individual Series
2012-02-20 | E-GEOD-30760 | biostudies-arrayexpress
Project description:Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer. Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer. Controls: 5 cases; ER +/HER2- breast cancer patients : 11 cases
2013-12-12 | E-GEOD-53179 | biostudies-arrayexpress
Project description:The association between vaginal microbiota composition and miscarriage: a nested case-control study
| PRJEB32479 | ENA
Project description:Metastasis of breast cancer to other distant organs is fatal to patients. However, few studies have revealed biomarkers associated with distant metastatic breast cancer. Furthermore, the inability of current biomarkers such as HER2, ER and PR, in accurately differentiating between distant metastatic breast cancers from non-distant metastatic ones necessitates the development of novel biomarkers. An integrated proteomics approach that combines filter-aided sample preparation, tandem mass tag labeling (TMT), high pH fractionation, and high resolution MS was applied to acquire in-depth proteome data of distant metastatic breast cancer FFPE tissue. Bioinformatics analyses for gene ontology and signaling pathways using differentially expressed proteins (DEPs) were performed to investigate molecular characteristics of distant metastatic breast cancer. In addition, real-time polymerase chain reaction (RT-PCR) and invasion/migration assays were performed to validate the differential regulation and functional capability of biomarker candidates. A total of 9,459 and 8,760 proteins were identified from the pooled sample set and the individual sample set, respectively. Through our stringent criteria, TUBB2A was selected as a novel biomarker. The metastatic functions of the candidate were subsequently validated. Bioinformatics analysis using DEPs were able to characterize the overall molecular features of distant metastasis as well as investigate the differences across breast cancer subtypes. Our study is the first to explore the distant metastatic breast cancer proteome using FFPE tissue. The depth of our dataset enabled the discovery of novel biomarker and the investigation of proteomic characteristics of distant metastatic breast cancer. The distinct molecular features of breast cancer subtypes were also observed. Our proteomic data has important utility as a valuable resource for the research on distant metastatic breast cancer.
2020-06-05 | PXD016061 | Pride
Project description:The project contains raw and result files from a proteomic profiling of a male breast cancer (MBC) case. Label-free quantification-mass spectrometry (LFQ-MS) and bioinformatics analysis were employed to investigate the differentially expressed proteins (DEPs) among distinct tissue samples: the primary breast tumor, axillary metastatic lymph nodes and the adjacent non-tumor breast tissue. An additional proteomic comparative analysis was performed with a primary breast tumor of a female patient. A number of Ingenuity® Pathway Analysis (IPA) (QIAGEN Inc.) and functional annotation tools were used to further analyze the DEPs. Altogether, our findings revealed deregulated proteins into signaling pathways involved in the cancer development and provided a landscape of proteomic data for the MBC research.
2021-09-08 | PXD012453 | Pride