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15,247 results for “Breast Cancer”
FTIR Breast Cancer
<p>Two breast cancer subtypes FTIR spectroscopy imaging</p> <p>A = LA breast cancer</p> <p>B = HER2 breast cancer</p>
TCGA Breast Cancer 450K Methylation Data
<p>The archived folder holds level 1 450K DNA methylation IDAT files for the TCGA Breast Cancer dataset. The data is used in the analysis pipeline associated with the GitHub repository: https://github.com/gwaygenomics/brca_lowstage_DMGRs</p>
Raw BRCA1/2 variants in breast cancer patients and healthy relatives produced with GATK.
<p>Aligned sequencing data is available in the NCBI Sequence Read Archive (SRA, https://www.ncbi.nlm.nih.gov/sra/) under accession SRP095082. Variants were called using GATK HaplotypeCaller (version 3.6). After joint performing joint genotyping multi-sample vcf file was generated. Next, SNPs and indels were extracted into two different vcf files and specific set of filters were applied for each case.</p> <p> </p> <p><strong>File descriptions</strong></p> <p><strong><em>Datasets</em></strong></p> <p><strong>BRCA_SNVs.vcf</strong> - this file contains SNPs called with GATK and hard filters applied. Following filtering options were applied: "QD < 2.0", "FS > 60.0", "MQ < 40.0", "MQRankSum < -12.5", "ReadPosRankSum < -8.0", "SB < -0.10" , "DP < 10" , "GQ < 30" , and "SOR > 3.0"</p> <p><strong>BRCA_indels.vcf</strong> - This file contains indels called with GATK and hard filters applied. Following filtering options were applied: "QD < 2.0", "FS > 200.0", "ReadPosRankSum < -20.0", "InbreedingCoeff < -0.8", "SOR > 10.0".</p> <p> </p> <p><strong><em>Scripts package (scritps.zip)</em></strong></p> <p>Scripts.zip file contains scripts and supporting files for genotype calling and filtering. </p> <p><strong>raw.variant.caling.sh </strong>– bam files preprocessing, alignment refining and raw genotype calling with HaplotypeCaller.</p> <p><strong>genotyping_and_filtering.sh </strong>– joint genotyping, variant hard filtering and callset refinement.</p> <p><strong>LIST.txt</strong> – supporting file that contains bam filenames containing aligned reads.</p> <p><strong>sample_order.txt</strong> – supporting file for sample renaming.</p> <p> </p> <p><strong><em>Reference files (hg19) used in variant calling scripts</em></strong></p> <p>Reference files can be downloaded from GATK bundle web-site at https://software.broadinstitute.org/gatk/download/bundle. </p> <p><strong>ucsc.hg19.fasta</strong> - human genome assembly;</p> <p><strong>Mills_and_1000G_gold_standard.indels.hg19.sites.vcf.gz</strong> – set of known indels to be used for local realignment;</p> <p><strong>1000G_phase1.indels.hg19.sites.vcf.gz</strong> – set of known indels to be used for local realignment;</p> <p><strong>dbsnp_138.hg19.vcf.gz</strong> – a recent dbSNP release (build 138); </p> <p><strong>1000G_phase3_v4_20130502.hg19.lifted.sites.vcf</strong> – the latest set from 1000G phase 3 (v4) for genotype refinement.</p> <p> </p>
Quantum Cascade Laser Spectral Histopathology: Breast Cancer Diagnostics Using High Throughput Chemical Imaging
<p>Fourier transform infrared (FT-IR) microscopy, coupled with machine learning approaches, has been demonstrated to be a powerful technique for identifying abnormalities in human tissue. The ability to objectively identify the prediseased state, and diagnose cancer with high levels of accuracy, has the potential to revolutionise current histopathological practice. Despite recent technological advances in FT-IR microscopy, sample throughput and speed of acquisition are key barriers to clinical translation. Wide-field quantum cascade laser (QCL) infrared imaging systems with large focal plane array detectors utilising discrete frequency imaging, have demonstrated that large tissue microarrays (TMA) can be imaged in a matter of minutes. However this ground breaking technology is still in its infancy and its applicability for routine disease diagnosis is, as yet, unproven. In light of this we report on a large study utilising a breast cancer TMA comprised of 207 different patients. We show that by using QCL imaging with continuous spectra acquired between 912 and 1800 cm<sup>-1</sup>, we can accurately differentiate between 4 different histological classes. We demonstrate that we can discriminate between malignant and non-malignant stroma spectra with high sensitivity (93.56%) and specificity (85.64%) for an independent test set. Finally, we classify each core in the TMA and achieve high diagnostic accuracy on a patient basis with 100% sensitivity and 86.67% specificity. The absence of false negatives reported here opens up the possibility of utilising high throughput chemical imaging for cancer screening, thereby reducing pathologist workload and improving patient care.</p>
Supplementary File 7 from: Rapier-Sharman N et. al., Secondary Transcriptomic Analysis of Triple-Negative Breast Cancer Reveals Reliable Universal and Subtype-Specific Mechanistic Markers, 2024
<p>Supplementary Materials File 7. Please note that though the order of the supplementary materials has changed since initial upload (File S7 was previously File S9 or S10), the contents of this zipped folder remain the same.</p>
Molecular features of luminal breast cancer defined through spatial and single-cell transcriptomics (codes and data files)
<p>This dataset includes all the relevant codes and data files associated with the paper ("Molecular features of luminal breast cancer defined through spatial and single-cell transcriptomics") in Clinical and Translational Medicine journal.</p>
Imaging Mass Cytometry Dataset of exhausted and non-exhausted breast cancer microenvironments
<p>A cohort of human breast tumor samples were annotated as having an "exhausted" or "non-exhausted" immune environment based on CyTOF characterization of T cell phenotypes (see Wagner et al. 2019). 12 samples (6 exhausted, 6 non-exhausted) were then selected for further analysis by Imaging Mass Cytometry (IMC) with the goal to compare the two immune environment types and to comprehensively characterize exhaustion-associated spatial features of the tumor microenvironment. For IMC, two consecutive FFPE sections of each sample were stained with two different antibody panels (Protein Panel and RNAscope Panel), and 4-10 regions of interest (ROIs, 1mm x 1mm) were measured on each section. ROIs on consecutive sections were registered manually to be as spatially close as possible.</p>
Dataset of the study "Thirty seconds sit-to-stand test as an alternative for estimating peak oxygen uptake and six-minutes walking distance in women with breast cancer: a cross-sectional study"
<p>Data was collected to study the usefulness of the thirty seconds sit-to-stand test as an alternative for estimating peak oxygen uptake and six-minutes walking distance in women with breast cancer, which is a cross-sectional study derived from the ONCORE project (Randomized controlled trial on comprehensive exercise-based cardiac rehabilitation program for the prevention of anthracyclines and/or anti-HER2 antibodies-induced cardiotoxicity in breast cancer), ClinicalTrials.gov Identifier: NCT03964142</p> <p> </p> <p>DATASET FILE (xlsx) includes 4 sheets:<br> - Dataset_variables: all variables collected pre-post intervention<br> - Descriptive data (baseline): variables used for the descriptive analysis before the intervention (baseline)<br> - Data_CPET-30STS(pre-post): pooled data from CPET-30STS pre-post intervention<br> - Data_6MWD-30STS(pre-post): pooled data from 6MWD-30STS pre-post intervention</p>
ATOPE+Breast, Continuous Monitoring of Training Load in Patients with Breast Cancer during Therapeutic Exercise Intervention
<p>The ATOPE+Breast dataset (ATOPE+ for patients with breast cancer) describes the daily status of 23 patients with breast cancer during therapeutic exercise intervention with daily measures of HRV, self-reported wellness, physical activity, and sleep. Besides, the ATOPE+Breast dataset contains information about training sessions, such as intensity recorded, demographic data, treatment details, initial evaluations of quality of life, physical activity levels, previous medical conditions, and risk factors. ATOPE+Breast was recorded using the ATOPE+ mHealth system, whose usability [1] and reliability [2] were successfully validated.</p> <p>References</p> <ul> <li>[1] S. Moreno-Gutierrez et al., “ATOPE+: An mHealth System to Support Personalized Therapeutic Exercise Interventions in Patients With Cancer,” IEEE Access, vol. 9, pp. 16878–16898, 2021, doi: 10.1109/ACCESS.2021.3049398.</li> <li>[2] P. Postigo-Martin et al., “mHealth system (ATOPE+) to support exercise prescription in breast cancer survivors: A validity and reliability, cross-sectional observational study (ATOPE study) (Preprint),” JMIR mHealth and uHealth, Preprint, Jan. 2022. doi: 10.2196/preprints.36733.</li> </ul>
Supplementary Figures, Files and Datasets: Reduction of Metastasis via Epigenetic Modulation in a Murine Model of Metastatic Triple Negative Breast Cancer (TNBC)
<p>*denotes authors contributed equally to this work</p> <p>FileS1_Figures_Proofread.pdf: (Updated) Supplementary Figures (Figure S1: RNA-sequencing experimental design; Figure S2: Experiments measuring proliferation between drug-treated and control conditions indicate no significant difference 6 hrs. after scratch; Figure S3: Effect of 4SC-202 treatment on 4T1 tumor volume in mice; Figure S4: Differential expression between 4SC-202- and Vorinostat-treated 4T1 tumors; Figure S5: Top underexpressed differentially expressed genes 4SC-202 vs Control; Figure S6: HDACi target genes are not differentially expressed in RNA-sequencing data from 4SC-202-treated mice relative to control mice; Figure S7: Differential expression and expression of genes implicated gene ontology biological processes of interest; Figure S8: IPA visualization of the Regulation of Epithelial Mesenchymal Transition By Growth Factors Pathway emphasizing influence of 4SC-202-induced consensus DEGs; Figure S9: 4SC-202 modulates gene networks related to Cancer, Endocrine System Disorders, and Organismal Injury and Abnormalities; Figure S10: 4SC-202 modulates gene networks related to Cancer, Cellular Movement, and Organismal Injury and Abnormalities; Figure S11: 4SC-202 modulates gene networks related to Cell-mediated Immune Response, Cellular Movement, and Hematological System Development and Function; Figure S12: 4SC-202 differentially modulates gene networks related to Cellular Movement, Hematological System Development and Function, and Immune Cell Trafficking relative to Vorinostat); File S2: DAVID 4SC vs. Control 70DEG results: DAVID Annotation 4SC-202 vs Control 70 DEGs: Full functional annotation clustering results from DAVID Bioinformatics Resource for the 4SC-202-induced, consensus differentially expressed genes.; File S3: DAVID 4SC vs. Vori 33 DEGs results: DAVID Annotation 4SC-202 vs Control 33 DEGs: Full functional annotation clustering results from DAVID Bioinformatics Resource for the 4SC-202 versus Vorinostat consensus differentially expressed genes.; File S4: IPA 70 All Results: IPA Canonical Pathways Enrichment 70 DEGs: Full Ingenuity Pathway Analysis (IPA) canonical pathways enrichment results for the 4SC-202-induced, consensus differentially expressed genes.; File S5: IPA 33 Summary: Ingenuity Pathway Analysis (IPA) summary of the enrichment results for the 4SC-202-induced, consensus differentially expressed genes against Vorinostat.; File S6: Experiment RIN Numbers: RNA extraction quality control step, one of the various steps of quality control within the RNA-sequencing workflow. These RNA Integrity numbers are from the Agilent 2100 Bioanalyzer that looks for RNA contamination and degradation.; File S7: 4SC vs. Control all DEGs: Workflow results including all DEGs for 4SC-202 vs Control: Full excel file that contains all of the DEGs from the results of all workflows for 4SC-202.</p>
The spindle assembly checkpoint is a therapeutic vulnerability of CDK4/6 inhibitor-resistant ER+ breast cancer with mitotic aberrations
<p>This study aims to investigate the accumulation of genomic instability and chromosome segregation errors after the acquisition of resistance to CDK4/6i in ER+ breast cancer and to test the efficacy of mitotic kinase inhibitors as a potential treatment for CDK4/6i-resistant breast cancer patients.</p> <p><strong>This repository contains whole-exome and shallow whole-genome sequencing from luminal breast cancer cell lines (T47D, LY2, MDA-MB-361, CAMA1, MCF7, KPL1, ZR751, HCC1428) both at the untreated or Parental state and post resistance to Palbociclib.</strong></p> <p>Palbociclib resistance was developed by continuous dose-escalation of palbociclib up to 0.5-1 μM until cell growth was observed in the presence of the drug (6-8 months for cell lines). During this time, parental cell lines and organoids were cultured in regular media to match the time spent in culture. Once resistance was established, Palbo-R cell lines were cultured in a regular growth medium without palbociclib. Cells were cultured without palbociclib for at least two weeks before evaluating resistance.</p>
A Large-scale Synthetic Pathological Dataset for Deep Learning-enabled Segmentation of Breast Cancer
<p>Dataset access for the paper: A Large-scale Synthetic Pathological Dataset for Deep Learning-enabled Segmentation of Breast Cancer</p>
Feasibility and acceptability of personalized breast cancer screening (DECIDO Study): A single-arm proof-of-concept trial
<p>The aim of this study was to assess the acceptability and feasibility of offering risk-based breast cancer screening and its integration into regular clinical practice. A single-arm proof-of-concept trial was conducted with a sample of 387 women aged 40–50 years residing in the city of Lleida (Spain). The study intervention consisted of breast cancer risk estimation, risk communication and screening recommendations, and a follow-up. A polygenic risk score with 83 single nucleotide polymorphisms was used to update the Breast Cancer Surveillance Consortium risk model and estimate the 5-year absolute risk of breast cancer. The women expressed a positive attitude towards varying the frequency of breast screening according to individual risk and, especially, more frequently inviting women at higher-than-average risk. A lower intensity screening for women at lower risk was not as welcome, although half of the participants would accept it. Knowledge of the benefits and harms of breast screening was low, especially with regard to false positives and overdiagnosis. The women expressed a high understanding of individual risk and screening recommendations. The participants' intention to participate in risk-based screening and satisfaction at 1-year were very high.</p>
Data from: Identification of a minority population of LMO2+ breast cancer cells that integrate into the vasculature and initiate metastasis.
<p>Metastasis is responsible for the majority of breast cancer-related deaths, however, identifying the cellular determinants of metastasis has remained challenging. Here, we identified a minority population of immature THY1+/VEGFA+ tumor epithelial cells in human breast tumor biopsies that display angiogenic features and are marked by the expression of the oncogene, LMO2. Higher abundance of LMO2+ basal cells correlated with tumor endothelial content and predicted poor distant recurrence-free survival in patients. Using MMTV-PyMT/Lmo2CreERT2 mice, we demonstrated that Lmo2 lineage-traced cells integrate into the vasculature and have a higher propensity to metastasize. LMO2 knockdown in human breast tumors reduced lung metastasis by impairing intravasation, leading to a reduced frequency of circulating tumor cells. Mechanistically, we find that LMO2 binds to STAT3 and is required for STAT3 activation by TNFα and IL6. Collectively, our study identifies a population of metastasis-initiating cells with angiogenic features and establishes the LMO2-STAT3 signaling axis as a therapeutic target in breast cancer metastasis.</p>
Association between Dysregulated Expression of Ca2+ and ROS-Related Gene Pairs and Breast Cancer Patient Survival
<p>This file is composed of two documents:</p> <ul> <li>Supplementary File 1 containing three Excel files with cumulative proportion survival from redox-related genes, calcium-related genes, and redox and calcium-related genes.</li> <li>Supplementary Table 3 including an Excel file with a functional enrichment analysis using redox and calcium correlated genes. Cell cycle regulation (sheet 1) and Cell adhesion and projection (sheet 2) were the biological processes more enriched.</li> </ul> <p>Both supplementary tables belongs to the study <strong>Association between Dysregulated Expression of Ca2+ and ROS-Related Gene Pairs and Breast Cancer Patient Survival</strong>, published in <strong>Molecular Diagnosis and therapy</strong></p>
Supplementary dataset for 'A randomised phase III trial of carboplatin compared with docetaxel in BRCA1/2 mutated and pre-specified triple negative breast cancer "BRCAness" subgroups: the TNT Trial'
<p>This dataset corresponds to the PAM50 gene expression profiling of primary tumour samples that were collected as part of the TNT clinical trial (ISRCTN97330959, NCT00532727, CRUK/07/012). NanoString® platform nCounter analysis was performed on the RNA extracts at the Institute of Cancer Research and Royal Marsden Hospital. The manuscript describing the trial outcome is currently under review in Nature Medicine.</p>
Data File for Manuscript "Comprehensive Molecular Simulation on Triple Negative Breast Cancer Transcriptomics Features of mir-145 and 3' UTR of ARF6 mRNA"
<p>This is a data file for the manuscript "Comprehensive Molecular Simulation on Triple Negative Breast Cancer Transcriptomics Features of mir-145 and 3’ UTR of ARF6 mRNA". It comprises of molecular docking (AUTODOCK VINA 4) and dynamics data (NAMD and VMD).</p>
Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation
<p>This dataset contains supplemental tables and tracks for the study entitled: "Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation".</p> <ul> <li>Files <ul> <li>PMDs_CGIs.zip <ul> <li>The included files contain</li> <li>Genome positions of detected PMDs with their mean methylation (weighted mean, see Methods)</li> <li>Genome positions of CpG islands with their mean methylation (weighted mean)</li> <li>The "Brinkman" directory contains files from breast cancer data produced in this study</li> <li>The "normals" directory contains files from normal tissues (external data) analyzed in this study</li> <li>The "tumors" directory contains files from tumors (external data) analyzed in this study</li> <li>All genome positions are based on GRCh37/hg19 </li> <li>All files are TAB-delimited text files (.tsv)</li> </ul> </li> <li>DNAme_bigwigs.zip <ul> <li>The included files are BIGWIG files (http://genome.ucsc.edu/goldenPath/help/bigWig.html) for viewing the DNA methylation profiles in a genome browser such as UCSC (http://genome.ucsc.edu). Each file represents a whole-Genome Bisulfite Sequencing (WGBS) DNA methylation profile from one tumor used in this study. The used genome build was GRCh37/hg19. For every CpG with a coverage of at least 4 reads, the DNA methylation value (range: 0-1) is included.</li> </ul> </li> </ul> </li> <li>Methods <ul> <li>Detection of partially methylated domains (PMDs) in all whole-genome bisulfite sequencing (WGBS) methylation profiles throughout this study was done using the MethylSeekR package for R (1). Before PMD calling, CpGs overlapping common SNPs (dbSNP build 137) were removed. The alpha distribution (1) was used to determine whether PMDs were present at all, along with visual inspection of WGBS profiles. After PMD calling, the resulting PMDs were further filtered by removing regions overlapping with centromers (undetermined sequence content).</li> <li>Mean methylation values from WGBS inside CGIs were calculated using the ‘weighted methylation level’ (2).</li> <li>Mean methylation values from WGBS inside PMDs were calculated using the ‘weighted methylation level’ (2). Calculation of mean methylation within PMDs involved removing all CpGs overlapping with CpG island(-shores) and promoters, as the high CpG densities within these elements yield unbalanced mean methylation values, not representative of PMD methylation. </li> </ul> </li> <li>References <ul> <li>(1) Burger, L., Gaidatzis, D., Schübeler, D. & Stadler, M. B. Identification of active regulatory regions from DNA methylation data. Nucleic Acids Research 41, (2013).</li> <li>(2) Schultz, M. D., Schmitz, R. J. & Ecker, J. R. ’Leveling’ the playing field for analyses of single-base resolution DNA methylomes. Trends in Genetics 28, 583–585 (2012).</li> </ul> </li> </ul>
Figure 1 in Strategies for false positive reduction and multimodal lesion characterization in computer-aided diagnosis of breast cancer
Figure 1. - Representative ultrasound images at four-month post copulation (8 Sep. 2010) before resorption, five-month post copulation (20 Oct. 2010) during resorption, and six-month post copulation (3 Nov. 2010) after resorption. A: Uterine horn; B: Fetus; C: Ovary; D: Follicle.
Loss of multi-level 3D genome organization during breast cancer progression - Processed LAD files
<p>This entry contains the processed LAD files produced as part of the following study:<br><strong>Loss of multi-level 3D genome organization during breast cancer progression</strong></p>
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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.