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15,247 results for “Breast cancer”
Supplementary data for "Profiling the peripheral immune landscape of metastatic HER2+ breast cancer"
<p>Supplementary data (Supplementary Table III.1) and high-resolution versions of figures III.3 - III.9 for Chapter III of the PhD thesis "The effect of dual HER2 blockade on anti-tumor immune cells" (ITQB-NOVA, Oeiras, Portugal).</p>
Targeted therapy of BRCA2 hypermethylation of breast cancer tumorigenesis in carrier females: A Review
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Review of Breast Cancer Prognosis MicroRNAslncRNAs, Obesity, The LPR6 Biomarker, and Night Fasting
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Dataset for the manuscript: Serum HER2 as potential prognostic biomarker in primary breast cancer patients
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HCC38 and MDA-MB-231 Triple-Negative Breast Cancer time lapses at different densities
<p>Supporting data set for Burger et al. Density-dependent migration characteristics of cancer cells driven by pseudopod coordination. In preparation.</p>
A low glycemic index Mediterranean diet reduced the Dietary Inflammatory Index scores in patients with breast cancer
<p><strong>ABSTRACT (word count 263)</strong></p> <p><strong>Background:</strong> Inflammation is directly associated with breast cancer (BC) incidence and mortality, dietary inflammatory index (DII®) and dietary glycemic index (GI) scores, and inversely associated with Mediterranean diet (MD). We therefore investigated the DII in women diagnosed with BC, randomized in a trial to follow either a MD diet or MD with low-GI (MDLGI) carbohydrates.</p> <p><strong>Methods:</strong> Data were derived from 223 women living in Italy, mean age of 59±9.3 years, within 12 months of BC surgery (stages I-III). Dietary data from 7-day food records, the Mediterranean Dietary Assessment Screener (MEDAS) and serum high sensitivity C-reactive protein (hsCRP) levels were collected at baseline and after 12 months of treatment. Student’s t-test, two-way ANOVA, Spearman correlations, Pearson correlation and regression analyses were conducted.</p> <p><strong>Results: </strong>Adherence to the Mediterranean diet increased after 12-months of treatment in both MD and MDLGI groups, MEDAS from 8.1 to 9.1 and from 8.3 to 9.9, respectively (p<0.001); dietary GI decreased from 55.5 to 52.4 and from 55.1 to 47.6, respectively (p<0.001); and DII decreased from 2.08 to 1.49 and from 1.60 to 0.81, respectively (p<0.001). No treatment difference in hsCRP levels and no significant correlation between CRP levels and DII scores were found. The analysis of variance suggested that low GI may independently contribute to lowering the DII (beta-coefficient 0.08, p<0.001).</p> <p><strong>Conclusions: </strong>The DII decreased after 12 months (4 sessions) of dietary counseling on a traditional MD. This effect was particularly stronger when carbohydrates were of low GI. These results are relevant given that lowering the inflammatory potential of the diet may have implications in cancer prognosis and overall survival.</p>
Data associated with "Survival outcomes are associated with genomic instability in luminal breast cancers".
<p>Data utilised in <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0245042">Survival outcomes are associated with genomic instability in luminal breast cancers</a>.</p>
Elevated expression of TUBA1C in breast cancer predicts poor prognosis
<p>α1C-tubulin (<em><span>TUBA1C</span></em>) is a member of the α-tubulin family and has served as a potential biomarker in a variety of cancers in many studies. In this study, the gene expression profile of <em><span>TUBA1C </span></em>in The Cancer Genome Atlas (TCGA) was extracted for analysis, and the prognostic value of <em><span>TUBA1C</span></em> in breast cancer was comprehensively evaluated. The Wilcoxon signed-rank test, Kruskal-Wallis test, and logistic regression analysis were performed to confirm the correlations between <em><span>TUBA1C</span></em> expression and the clinical characteristics of breast cancer patients. The effect of <em><span>TUBA1C</span></em> expression on the survival of breast cancer patients was assessed by Kaplan-Meier curve, Cox regression analysis, and the Kaplan-Meier plotter (an online database). The TCGA data set was used for the Gene Set Enrichment Analysis (GSEA). The results confirmed that high <em><span>TUBA1C</span></em> expression in breast cancer was closely correlated with survival time, survival status, and tumor size. In addition, elevated <em><span>TUBA1C</span></em> expression can predict poor overall survival (OS), recurrence-free survival (RFS), and distant metastasis-free survival (DMFS). Univariate and multivariate analyses (Cox regression analyses) confirmed that <em><span>TUBA1C</span></em> was an independent prognostic factor for the OS of breast cancer patients. The GSEA identified that the high <em><span>TUBA1C</span></em> expression phenotype was differentially enriched in cell cycle, basal transcription factor, P53 signaling pathway, pathways in cancer, TOLL-like receptor signaling pathway, and NOD-like receptor signaling pathway. In summary, high messenger RNA (mRNA) expression of <em><span>TUBA1C</span></em> is an independent risk factor for poor prognosis of breast cancer.</p>
Analysis of Circulating Biomarkers for Minimally Invasive Early Detection of Breast Cancer
<p>A nested case–control study was conducted on plasma samples of 65 cases and 66 controls (discovery set) and 32 cases and 127 controls (validation set). 10 circulating microRNAs have been analyzed by RT-qPCR and 7 microRNA ratios (as the difference between their threshold cycles) have been included in a model to predict the presence of breast cancer. Together with the women identifier (andromeda_id) and the seven microRNA ratios, menopause staus (menopause), body mass index (bmi_di), the interaction term between menopause and BMI (bmi_men), the life-style score according to the World Cancer Research Fund (score_wcrf), the breast density classification (tabar), the cancer diagnosis (status) and the type of control (class2 - only for the validation cohort where there were two types of controls: mammography negatives (N) and mammography false-positives(N2)) are reported in the first sheet (validation set) and in the third sheet (discovery set). The second sheet contains the time intervals between enrollment with blood sampling and breast cancer diagnosis. This information was used only for the validation set, where these intervals were much higher than in the discovery set.</p> <p>Raw threshold cycles (Ct) are available upon request.</p>
Triple-negative breast cancer and Natural killer cells
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Triple-negative breast cancer and Natural killer cells
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Association between Dysregulated Expression of Ca2+ and ROS-Related Gene Pairs and Breast Cancer Patient Survival
<p>This file is composed by two documents:</p> <ul> <li>Supplementary Table 1 containing an Excel file with data on gene expression, differential gene expression (tumoral versus normal), and survival outcomes related to redox (sheet 1) and calcium-related (sheet 2) genes.</li> <li>Suplementary Table 2 including a table summarizing the primary functions of selected redox- and calcium-related genes and various studies reporting their impact on breast cancer</li> </ul> <p>Both supplementary tables belongs to the study <strong><strong>Association between Dysregulated Expression of Ca2+ and ROS-Related Gene Pairs and Breast Cancer Patient Survival</strong></strong>, published in <strong>Molecular Diagnosis and therapy </strong></p>
NF-kB suppresses the breast cancer cell's growth via the p38 MAPK inhibitor
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TCGA Breast cancer selection dataset
<p>MS and TCGA Breast cancer selection dataset</p>
Supplementary Tables for the manuscript be Kuligina et al. "Germline variants in the immune response-related genes: possible modifying effect on age-dependent BRCA1 penetrance in breast cancer patients"
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Dataset associated with publication of Budzyń et al. "The significance of monocyte CCR2_CCL2 axis in triple negative breast cancer"
<p>Row data</p>
Data from: Fusion transcript discovery in formalin-fixed paraffin-embedded human breast cancer tissues reveals a link to tumor progression
The identification of gene fusions promises to play an important role in personalized cancer treatment decisions. Many rare gene fusion events have been identified in fresh frozen solid tumors from common cancers employing next-generation sequencing technology. However the ability to detect transcripts from gene fusions in RNA isolated from formalin-fixed paraffin-embedded (FFPE) tumor tissues, which exist in very large sample repositories for which disease outcome is known, is still limited due to the low complexity of FFPE libraries and the lack of appropriate bioinformatics methods. We sought to develop a bioinformatics method, named gFuse, to detect fusion transcripts in FFPE tumor tissues. An integrated, cohort based strategy has been used in gFuse to examine single-end 50 base pair (bp) reads generated from FFPE RNA-Sequencing (RNA-Seq) datasets employing two breast cancer cohorts of 136 and 76 patients. In total, 118 fusion events were detected transcriptome-wide at base-pair resolution across the 212 samples. We selected 77 candidate fusions based on their biological relevance to cancer and supported 61% of these using TaqMan assays. Direct sequencing of 19 of the fusion sequences identified by TaqMan confirmed them. Three unique fused gene pairs were recurrent across the 212 patients with 6, 3, 2 individuals harboring these fusions respectively. We show here that a high frequency of fusion transcripts detected at the whole transcriptome level correlates with poor outcome (P<0.0005) in human breast cancer patients. This study demonstrates the ability to detect fusion transcripts as biomarkers from archival FFPE tissues, and the potential prognostic value of the fusion transcripts detected.
Data from: Quantification of sensitivity and resistance of breast cancer cell lines to anti-cancer drugs using GR metrics
Traditional means for scoring the effects of anti-cancer drugs on the growth and survival of cell lines is based on relative cell number in drug-treated and control samples and is seriously confounded by unequal division rates arising from natural biological variation and differences in culture conditions. This problem can be overcome by computing drug sensitivity on a per-division basis. The normalized growth rate inhibition (GR) approach yields per-division metrics for drug potency (GR50) and efficacy (GRmax) that are analogous to the more familiar IC50 and Emax values. In this work, we report GR-based, proliferation-corrected, drug sensitivity metrics for ~4,700 pairs of breast cancer cell lines and perturbagens. Such data are broadly useful in understanding the molecular basis of therapeutic response and resistance. Here, we use them to investigate the relationship between different measures of drug sensitivity and conclude that drug potency and efficacy exhibit high variation that is only weakly correlated. To facilitate further use of these data, computed GR curves and metrics can be browsed interactively at http://www.GRbrowser.org/.
Supplementary material 1 from: Yusuf H, Kamarlis RK, Yusni Y, Fahriani M (2021) The anticancer activity of ethanol extract of Chromolaena odorata leaves in 7,12-Dimethylbenz[a]anthracene in (DMBA) induced breast cancer Wistar rats (Rattus novergicus). Pharmacia 68(2): 493-499. https://doi.org/10.3897/pharmacia.68.e63956
Table S1
Data from: Mutation screening of 1,237 cancer genes across six model cell lines of basal-like breast cancer
Basal-like breast cancer is an aggressive subtype generally characterized as poor prognosis and lacking the expression of the three most important clinical biomarkers, estrogen receptor, progesterone receptor, and HER2. Cell lines serve as useful model systems to study cancer biology in vitro and in vivo. We performed mutational profiling of six basal-like breast cancer cell lines (HCC38, HCC1143, HCC1187, HCC1395, HCC1954, and HCC1937) and their matched normal lymphocyte DNA using targeted capture and next-generation sequencing of 1,237 cancer-associated genes, including all exons, UTRs and upstream flanking regions. In total, 658 somatic variants were identified, of which 378 were non-silent (average 63 per cell line, range 37–146) and 315 were novel (not present in the Catalogue of Somatic Mutations in Cancer database; COSMIC). 125 novel mutations were confirmed by Sanger sequencing (59 exonic, 48 3'UTR and 10 5'UTR, 1 splicing), with a validation rate of 94% of high confidence variants. Of 36 mutations previously reported for these cell lines but not detected in our exome data, 36% could not be detected by Sanger sequencing. The base replacements C/G>A/T, C/G>G/C, C/G>T/A and A/T>G/C were significantly more frequent in the coding regions compared to the non-coding regions (OR 3.2, 95% CI 2.0–5.3, P<0.0001; OR 4.3, 95% CI 2.9–6.6, P<0.0001; OR 2.4, 95% CI 1.8–3.1, P<0.0001; OR 1.8, 95% CI 1.2–2.7, P = 0.024, respectively). The single nucleotide variants within the context of T[C]T/A[G]A and T[C]A/T[G]A were more frequent in the coding than in the non-coding regions (OR 3.7, 95% CI 2.2–6.1, P<0.0001; OR 3.8, 95% CI 2.0–7.2, P = 0.001, respectively). Copy number estimations were derived from the targeted regions and correlated well to Affymetrix SNP array copy number data (Pearson correlation 0.82 to 0.96 for all compared cell lines; P<0.0001). These mutation calls across 1,237 cancer-associated genes and identification of novel variants will aid in the design and interpretation of biological experiments using these six basal-like breast cancer cell lines.
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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.