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15,247 results for “Breast Cancer”
Loss of multi-level 3D genome organization during breast cancer progression - Third-party datasets
<p>This entry contains the following datasets:</p> <p>Datasets used by <a href="https://github.com/dixonlab/hic_breakfinder" target="_blank" rel="noopener">hic_breakfinder</a>:</p> <ul> <li>inter_expect_1Mb.hg38.txt</li> <li>intra_expect_100kb.hg38.txt</li> </ul> <p>FIles were originally downloaded from <a href="https://salkinstitute.box.com/s/m8oyv2ypf8o3kcdsybzcmrpg032xnrgx" target="_blank" rel="noopener">this</a> URL.</p> <p>Datasets used by <a href="https://github.com/parklab/HiNT" target="_blank" rel="noopener">HiNT</a>:</p> <ul> <li>backgroundMatrices_hg38.zip</li> <li>refData_hg38.zip</li> </ul> <p>Files were originally downloaded from the following URLs: <a href="http://compbio.med.harvard.edu/hint/refData/" target="_blank" rel="noopener">link1</a>, <a href="http://compbio.med.harvard.edu/hint/backgroundMatrices/" target="_blank" rel="noopener">link2</a>.</p> <p>The above datasets are used by the data analysis workflows hosted at <a href="https://github.com/paulsengroup/2022-mcf10a-cancer-progression" target="_blank" rel="noopener">paulsengroup/2022-mcf10a-cancer-progression.</a><br>The results produced by running the workflows from the above repository were used as part of the following study:<br><strong>Loss of multi-level 3D genome organization during breast cancer progression</strong></p>
Spatial Tumor-Immune Analysis: Insights from Pathology Slides and Breast Cancer Survival
<p>Cancer is the second leading cause of death in the US. Among the various forms of cancer, breast cancer and lung cancer are particularly significant due to their prevalence and impact. Breast cancer in particular contributing to around 30\% of all new female cases each year, while also having some of the highest mortality rates. Scientists and doctors rely on pathology slides to aid in the discovery of a cure, diagnose patients, and provide treatment. These slides play a crucial role in examining samples and identifying any abnormalities. The primary goal of this project was to analyze pathology slides from 873 cancer patients in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA). We developed STAIN (Spatial Tumor and Immune Analysis for Novel insights) with the hypothesize that quantitative analysis of cell type specific clusters in the spatial context can lead to novel insights on patient survival. First, we identified tumor and immune cells using a HD-Yolo algorithm. Then we identify tumor clusters and immune cell clusters. Next, descriptive statistics such as Jaccard distance, Hausdorff distance, Wasserstein distance, tumor density, and immune cell density were derived and correlated with the patients survival while adjusting for clinical attributes such as patient age and tumor stage using Cox proportional Hazard models. The results discover spatial attributes and known clinical risk features associated with survival. </p>
EV based miR-6772-5p secreted by breast cancer cells in response to radiation exposure is involved in development of radioresistance
<p>This dataset serves as a supplementary material for the research article <em>EV-based miR-6772-5p secreted by breast cancer cells in response to radiation exposure is involved in development of radioresistance</em> by Tynjälä <em>et al</em>. For further details, please refer to our publication for a detailed description of the methods used to generate this dataset.</p> <p>In summary, we isolated and sequenced miRNAs from extracellular vesicles (EVs) isolated from irradiated and non-irradiated MCF7 cells. Sequencing libraries were prepared with QIAseq miRNA Library Kit (Qiagen, Germany) and sequenced with Illumina NextSeq 500 platform (Illumina). In-house bioinformatics workflow was used to process the sequencing data. Unique molecular identifier (UMI) sequences were first extracted and added to FASTQ header with UMI-tools while discarding the 3’ adapter and primer sequences. Reads shorter than 16 bp were discarded with cutadapt. Provided sequencing data is in FASTQ format and trimmed from adapter and UMI sequences. We have also provided miRNA counts and results of following differential gene expression analysis in tab-delimited format.</p> <p> </p> <p> </p>
Seer Breast Cancer Data
<p><strong>Abstract</strong>:</p> <p>This dataset of breast cancer patients was obtained from the 2017 November update of the SEER Program of the NCI, which provides information on population-based cancer statistics. The dataset involved female patients with infiltrating duct and lobular carcinoma breast cancer (SEER primary cites recode NOS histology codes 8522/3) diagnosed in 2006-2010. Patients with unknown tumor size, examined regional LNs, regional positive LNs, and patients whose survival months were less than 1 month were excluded; thus, 4024 patients were ultimately included.</p> <p> </p> <p><strong>Inspiration:</strong></p> <p>This dataset uploaded to U-BRITE for "AI against CANCER DATA SCIENCE HACKATHON"</p> <p>https://cancer.ubrite.org/hackathon-2021/</p> <p><strong>Acknowledgements</strong></p> <p>JING TENG, January 18, 2019, "SEER Breast Cancer Data", IEEE Dataport, doi: https://dx.doi.org/10.21227/a9qy-ph35.</p> <p>https://ieee-dataport.org/open-access/seer-breast-cancer-data</p> <p><strong>U-BRITE last update date:</strong> 07/21/2021</p>
Automated Nuclear Pleomorphism Scoring in Breast Cancer: Slide-Study test set
<p>This dataset contains data from the Slide-Study data set used in the paper:</p> <p>[1]<em> C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polonia, H. M. Horlings, W. Weichert, J. M. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J.-M Bokhorst, J. van der Laak, F. Ciompi, Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer. NPJ Breast Cancer, 2022.</em></p> <p>The dataset consists of n=118 digital pathology whole-slide images (WSI) of breast cancer surgical resections, stained with hematoxylin and eosin (H&E) at Radboud University Medical Centers, Nijmegen (The Netherlands).</p> <p>The WSIs were scanned with a 3DHistech P1000 scanners at 0.25 um/px spacing, originally stored in MRXS file format. However, the WSIs made available here have been converted to TIFF format with a maximum spacing of 0.5 um/px. This was done to make slides broadly accessible (since MRXS files are sometimes not compatible with some digital pathology viewers or APIs), and with the same spacing used in the prediction of the pleomorphism score in the NPJ breast cancer paper.</p> <p>Note that we are solely releasing the Slide-Study test set used in [1]. Together with the data, we have released a web-based evaluation platform via the <a href="https://grand-challenge.org/">grand-challenge.org</a> platform, which can be found at this link: <a href="https://breastpleomorphism.grand-challenge.org/">https://breastpleomorphism.grand-challenge.org/</a>. In this way, researchers can download the WSI from Zenodo, process them with their algorithm to predict a single pleomorphism score for each slide, compile the predictions as indicated on the grand-challenge.org page, and submit them, to compare the results with the ones presented in the paper and with the opinion of a panel of four pathologists involved in the study.</p> <p>The data is released under CC BY-NC 4.0 license.</p>
Fast-food consumption by adolescent girls may sow the seeds of breast cancer decades later
<p>An hypothesis of breast cancer development:</p> <p>•Breast development occurs largely during the years of puberty in adolescent girls</p> <p>•Environmental assaults during that vulnerable time window can seed changes that take decades to complete</p> <p>•Advanced glycation end-products (AGE) are found in high concentrations in processed foods, especially fast-food</p> <p>•In mice, AGE produce pubertal breast changes in both epithelium and stroma, including atypical hyperplasia</p> <p>•The stromal changes in humans may be manifest as increased breast density as measured by mammography</p> <p>•These data provide a link between processed, fast-food, high breast density, and future breast cancer</p> <p>•Breast cancer prevention may include the avoidance of fast-food, especially in adolescent girls undergoing pubertal breast development</p>
Trastuzumab Deruxtecan (DS-8201a) Versus Investigator's Choice for HER2-low Breast Cancer That Has Spread or Cannot be Surgically Removed [DESTINY-Breast04]
ClinicalTrials.gov study NCT03734029. IPD Sharing: YES. Countries: 20. Publications: 8.
Phase 1 Study to Evaluate the Effect of DS-8201a on the QT/QTc Interval and Pharmacokinetics in HER2-Expressing Breast Cancer
ClinicalTrials.gov study NCT03366428. IPD Sharing: YES. Countries: 1. Publications: 1.
ErbB2 Over-expressing Metastatic Breast Cancer Study Using Paclitaxel, Trastuzumab, and Lapatinib
ClinicalTrials.gov study NCT00272987. IPD Sharing: YES. Countries: 2. Publications: 1.
Study In Women And Men With Metastatic Breast Cancer That Have Overexpression Of ErbB2
ClinicalTrials.gov study NCT00281658. IPD Sharing: YES. Countries: 8. Publications: 2.
A Study to Compare the Safety and Efficacy of an Aromatase Inhibitor in Combination With Lapatinib, Trastuzumab or Both for the Treatment of Hormone Receptor Positive, HER2+ Metastatic Breast Cancer
ClinicalTrials.gov study NCT01160211. IPD Sharing: YES. Countries: 29. Publications: 2.
A Study of Neratinib Plus Capecitabine Versus Lapatinib Plus Capecitabine in Patients With HER2+ Metastatic Breast Cancer Who Have Received Two or More Prior HER2 Directed Regimens in the Metastatic S
ClinicalTrials.gov study NCT01808573. IPD Sharing: YES. Countries: 28. Publications: 2.
Phase 2 Window Study of SAR439859 (Amcenestrant) Versus Letrozole in Post-menopausal Patients With ER+, HER2- Pre-operative Post-menopausal Primary Breast Cancer
ClinicalTrials.gov study NCT04191382. IPD Sharing: YES. Countries: 9. Publications: 1.
Study Evaluating The Effects Of Neratinib After Adjuvant Trastuzumab In Women With Early Stage Breast Cancer
ClinicalTrials.gov study NCT00878709. IPD Sharing: YES. Countries: 40. Publications: 7.
DS-8201a Versus T-DM1 for Human Epidermal Growth Factor Receptor 2 (HER2)-Positive, Unresectable and/or Metastatic Breast Cancer Previously Treated With Trastuzumab and Taxane [DESTINY-Breast03]
ClinicalTrials.gov study NCT03529110. IPD Sharing: YES. Countries: 15. Publications: 9.
Amcenestrant (SAR439859) Plus Palbociclib as First Line Therapy for Patients With ER (+) HER2(-) Advanced Breast Cancer
ClinicalTrials.gov study NCT04478266. IPD Sharing: YES. Countries: 30. Publications: 2.
Individualizing Surveillance Mammography for Older Breast Cancer Survivors
ClinicalTrials.gov study NCT03865654. IPD Sharing: YES. Countries: 1. Publications: 1.
Small-group, Virtual Program for Improving Symptoms and Distress Related to Hormonal Therapy for Breast Cancer Survivors
ClinicalTrials.gov study NCT03837496. IPD Sharing: YES. Countries: 1. Publications: 3.
A Phase II Study of Everolimus in Combination With Exemestane Versus Everolimus Alone Versus Capecitabine in Advance Breast Cancer.
ClinicalTrials.gov study NCT01783444. IPD Sharing: YES. Countries: 18. Publications: 1.
Open-label, Phase II, Study of Everolimus Plus Letrozole in Postmenopausal Women With ER+, HER2- Metastatic or Locally Advanced Breast Cancer
ClinicalTrials.gov study NCT01698918. IPD Sharing: YES. Countries: 13. Publications: 1.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.