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10,694 results for “carcinoma,”
STRA6 promotes thyroid carcinoma progression via activation of the ILK/AKT/mTOR axis in cells and female nude mice
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Nectin-4 PET for predicting enfortumab vedotin dose-response in urothelial carcinoma
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Data from: Defining metabolic flexibility in hair follicle stem cell induced squamous cell carcinoma
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Response to primary chemoradiotherapy of locally advanced oropharyngeal carcinoma is determined by the degree of cytotoxic T cell infiltration within tumor cell aggregates
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Presence of tertiary lymphoid structures and exhausted tissue-resident T cells determines clinical response to PD-1 blockade in renal cell carcinoma
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Data for: Preliminary study based on methylation and transcriptome gene sequencing of lncRNAs and immune infiltration in hypopharyngeal carcinoma
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Hormone receptors AR, ER, PR and growth factor receptor Her-2 expression in oral squamous cell carcinoma: Correlation with overall survival, disease-free survival and 10-year survival in a high-risk population
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Leptomeningeal metastasis from Adrenocortical carcinoma: a case report
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Opportunities for targeted therapies: trametinib as a therapeutic approach to canine oral squamous cell carcinomas
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Tumor growth kinetics of subcutaneously implanted Lewis Lung carcinoma cells
<p><strong>Please cite</strong><br> Benzekry, S., Lamont, C., Beheshti, A., Tracz, A., Ebos, J. M. L., Hlatky, L., & Hahnfeldt, P. (2014). Classical mathematical models for description and prediction of experimental tumor growth. <em>PLoS Computational Biology</em>, <em>10</em>(8), e1003800. http://doi.org/10.1371/journal.pcbi.1003800</p> <p><strong>Cell culture</strong><br> Murine Lewis lung carcinoma (LLC) cells, originally derived from a spontaneous tumor in a C57BL/6 mouse [1], were obtained from American Type Culture Collection (Manassas, VA). </p> <p><strong>Tumor injections</strong><br> For the subcutaneous mouse syngeneic lung tumor model, C57BL/6 male mice with an average lifespan of 878 days were used [2]. At time of injection mice were 6 to 8 weeks old (Jackson Laboratory, Bar Harbor, Maine). Subcutaneous injections of 10<sup>6</sup> LLC cells in 0.2 ml phosphate-buffered saline (PBS) were performed on the caudal half of the back in anesthetized mice.</p> <p><strong>Tumor measurements</strong><br> Tumor size was measured regularly with calipers to a maximum of 1.5 cm<sup>3</sup> for the lung data set. Largest (L) and smallest (w) diameters were measured subcutaneously using calipers and the formula V = <span class="math-tex">\(\frac{\pi}{6}w^2 L\)</span> was then used to compute the volume (ellipsoid). Volumes ranged 14–1492 mm<sup>3</sup> over time spans from 4 to 22 days for the lung tumor model (two experiments of 10 animals each).</p> <p>[1] Bertram JS, Janik P (1980) Establishment of a cloned line of Lewis Lung Carcinoma cells adapted to cell culture. Cancer Lett 11: 63–73. Available: http://www.ncbi.nlm.nih.gov/pubmed/7226139. Accessed 9 July 2013.</p> <p>[2] Kunstyr I, Leuenberger HG (1975) Gerontological data of C57BL/6J mice. I. Sex differences in survival curves. J Gerontol 30: 157–162. Available: http:// www.ncbi.nlm.nih.gov/pubmed/1123533. Accessed 9 July 2013.</p>
DATA for manuscript entitled "Integrating Transcriptomes and Somatic Mutations to Identify RNA Methylation Regulators as a Prognostic Marker in Hepatocellular Carcinomas"
<p><strong>Raw data of TCGA dataset and 7-meta data.</strong></p>
The supplemental files of 'DNA Methylation Data-based prognosis-subtype distinctions in Patients with Esophageal carcinoma'
<p>Our upload is the suplemental files which have been cited in the manuscript 'DNA Methylation Data-based prognosis-subtype distinctions in Patients with Esophageal carcinoma'</p>
Protein expression of hepatocellular carcinoma in a fibrotic liver in mice
<p>Hepatocellular carcinoma (HCC) is a liver tumor that arises in patients with cirrhosis. One of the key players in the progression of cirrhosis to HCC is the hepatic stellate cell, which is activated during liver damage. Activated stellate cells play an essential role in the pathogenesis of HCC by creating a fibrotic micro-environment that sustains tumor growth and by producing growth factors and cytokines that enhance tumor cell proliferation and migration. We assessed the role of endoplasmic reticulum (ER) stress in the cross-talk between hepatic stellate cells and HCC-cells. Mice with a fibrotic HCC were treated with the IRE1A-inhibitor 4mu8C. The oncogenic protein expression was assessed using a multiplex proximity extension assay for ninety-two biomarkers in the murine exploratory panel (Olink Bioscience, Uppsala, Sweden) in liver samples from healthy mice, mice with HCC and mice with HCC treated with the IRE1A-inhibitor 4mu8C.</p>
Data from: Identification of biomarkers for Barcelona Clinic Liver Cancer staging and overall survival of patients with hepatocellular carcinoma
The aim of the current study was to identify biomarkers that correlate with the Barcelona Clinic Liver Cancer (BCLC) staging system and prognosis of patients with hepatocellular carcinoma (HCC). We downloaded 4 gene expression datasets from the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo), and screened for genes that were differentially expressed between HCC and normal liver tissues, using significance analysis of the microarray algorithm. We used a weighted gene co-expression network analysis (WGCNA) to identify hub genes that correlate with BCLC staging, functional enrichment analysis to associate hub genes with their functions, protein-protein interaction network analysis to identify interactions among hub genes, UALCAN analysis to assess gene expression levels based on tumour stage, and survival analyses to clarify the effects of hub genes on patients' overall survival (OS). We identified 50 relevant hub genes using WGCNA; among them, 13 genes (including TIGD5, C8ORF33, NUDCD1, INSB8, and STIP1) correlated with OS and BCLC staging. Significantly enriched gene ontology biological process terms included RNA processing, non-coding RNA processing and phosphodiester bond hydrolysis, and 6 genes were found to interact with 10 or more hub genes. We identified several candidate biomarkers that correlate with BCLC staging and OS of HCC. These genes might be used for prognostic assessment and selection of HCC patients for surgery, especially those with intermediate or advanced disease.
Data from: Neoadjuvant and concurrent chemotherapy have varied impacts on the prognosis of patients with the ascending and descending types of nasopharyngeal carcinoma treated with intensity-modulated radiotherapy
Purpose: To compare the outcomes of patients with ascending type (T4&N0-1) and descending type (T1-2&N3) of nasopharyngeal carcinoma (NPC) treated with concurrent chemoradiotherapy (CCRT), neoadjuvant chemotherapy (NACT) + intensity-modulated radiotherapy (RT) or NACT + CCRT. Methods: Retrospective analysis of 839 patients with ascending or descending types of NPC treated at a single institution between October 2009 to February 2012. CCRT was delivered to 236 patients, NACT + RT to 302 patients, and NACT + CCRT to 301 patients. Results: The 4-year overall survival rate, distant metastasis-free survival rate, local relapse-free survival rate, nodal relapse-free survival rate, loco-regional relapse-free survival rate, and progression free survival rate were 75.2% and 73.4% (P = 0.114), 85.7% and 74.1% (P = 0.008), 88.8% and 97.1% (P = 0.013), 96.9% and 94.1% (P = 0.122), 86.9% and 91.2% (P = 0.384), 73.7% and 66.2% (P = 0.063) in ascending type and descending type. Subgroup analyses indicated that NACT + RT significantly improved distant metastasis-free survival rate and progression-free survival rate when compared with CCRT in the ascending type, and there were no significant differences between the survival curves of NACT +RT and NACT + CCRT. For descending type, there were no significant differences among the survival curves of NACT +RT, CCRT, and NACT + CCRT groups, and the survival benefit mainly came from CCRT. Conclusions: Compared with NACT + CCRT or CCRT, NACT + RT may be a reasonable approach for ascending type; Although concurrent chemotherapy was effective in descending type, NACT + CCRT may be a more appropriate strategy for descending type.
Data from: CXCL17 expression predicts poor prognosis and correlates with adverse immune infiltration in hepatocellular carcinoma
CXC ligand 17 (CXCL17) is a novel CXC chemokine whose clinical significance remains largely unknown. In the present study, we characterized the prognostic value of CXCL17 in patients with hepatocellular carcinoma (HCC) and evaluated the association of CXCL17 with immune infiltration. We examined CXCL17 expression in 227 HCC tissue specimens by immunohistochemical staining, and correlated CXCL17 expression patterns with clinicopathological features, prognosis, and immune infiltrate density (CD4 T cells, CD8 T cells, B cells, natural killer cells, neutrophils, macrophages). Kaplan-Meier survival analysis showed that both increased intratumoral CXCL17 (P = 0.015 for overall survival [OS], P = 0.003 for recurrence-free survival [RFS]) and peritumoral CXCL17 (P = 0.002 for OS, P<0.001 for RFS) were associated with shorter OS and RFS. Patients in the CXCL17low group had significantly lower 5-year recurrence rate compared with patients in the CXCL17high group (peritumoral: 53.1% vs. 77.7%, P<0.001, intratumoral: 58.6% vs. 73.0%, P = 0.001, respectively). Multivariate Cox proportional hazards analysis identified peritumoral CXCL17 as an independent prognostic factor for both OS (hazard ratio [HR] = 2.066, 95% confidence interval [CI] = 1.296–3.292, P = 0.002) and RFS (HR = 1.844, 95% CI = 1.218–2.793, P = 0.004). Moreover, CXCL17 expression was associated with more CD68 and less CD4 cell infiltration (both P<0.05). The combination of CXCL17 density and immune infiltration could be used to further classify patients into subsets with different prognosis for RFS. Our results provide the first evidence that tumor-infiltrating CXCL17+ cell density is an independent prognostic factor that predicts both OS and RFS in HCC. CXCL17 production correlated with adverse immune infiltration and might be an important target for anti-HCC therapies.
Dataset related to the paper "Role of enhancement modifications in evaluating tumor response to immunotherapy in metastatic renal cell carcinoma"
<p>Dataset related to the paper "Role of enhancement modifications in evaluating tumor response to immunotherapy in metastatic renal cell carcinoma"</p>
Senegenin Modulates O-GlcNAc Glycosylation to Thwart Hepatocellular Carcinoma Progression
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CXCL3 and TGFβ-Mediated Crosstalk Between CAFs and Tumor Cells Augments Renal Cell Carcinoma Progression and Sunitinib Resistance Yunxia Wang et al
<p>The two tables are the results of proteomics sequencing, the volcano map is drawn based on _all proteins, and the cluster analysis map is drawn based on _differential proteins. When drawing a cluster analysis diagram, if the p-value in the table is 0, we consider the p-value to be 0.0001, otherwise the log value is meaningless.</p>
Single Cell CPTAC Renal Cell Carcinoma
<p>These data include a subset of single-cell samples from the CPTAC Renal Cell Carcinoma data processed using the following steps:<br><br></p> <ol> <li><em>Loom</em> files were read into R and converted into <em>SingleCellExperiment</em> objects.</li> <li>Ensembl gene ID's were matched to HGNC symbols, chromosome name, starting position, and ending position via Biomart using the <em>scater</em> R package.</li> <li>Size factors were computed using the <em>scran</em> R package.</li> <li>UMAP dimensions were computed using the <em>scater</em> R package.</li> <li>Probes without matching HGNC symbols were removed.</li> <li>Where duplicate HGNC symbols were present, the gene with the maximum normalized range was retained.</li> <li>Cell types were inferred using the <em>scMRMA</em> R package.</li> <li>Cells with less than or equal to 1,000 features were removed.</li> <li>Cells with mitochondrial reads greater than or equal to 50% were removed.</li> <li>Expression data for podocytes and macrophages were saved separately for each sample.</li> <li>For podocytes and macrophages for each sample, expression data were projected onto the first 100 principal components using the <em>irlba</em> R package. The results are available from <strong>CPTAC_RCC_PCA.zip.</strong></li> <li>For macrophages for each sample, a differentiation trajectory was estimated using the <em>monocle3</em> R package, and plots were colored by combined expression of the M0 markers CSF1R, CD14, CD68, and CD11B, the M1 markers CD86, MARC0, CXCL9, CXCL10, CXCL11, NOS2, SOCS1, and CD64, and the M2 markers TGM2, CD23, ARG1, CCL22, CD163, and CD206 (from PMC8268869). Pseudotime starting points were annotated in <em>monocle3</em> using visual inspection of plots. Only samples in which a visible trajectory from M0 -> M1 -> M2 was evident using these markers were retained.</li> <li>For podocytes for each sample, a differentiation trajectory was estimated using the <em>monocle3</em> R package, and plots were colored by combined expression of the dedifferentiation markers DACH1 (from PMC5908116) and PTPRO (from PMID9639039. Pseudotime starting points were annotated in <em>monocle3</em> using visual inspection of plots. Only samples in which a visible trajectory of dedifferentiation was evident using these markers were retained. These pseudotime assignments and the macrophage assignments are available from <strong>CPTAC_RCC_pseudotime_all_cells.zip.</strong></li> <li>For podocytes and macrophages for each sample, 10-fold cross-validation matrices for expression, PCA, and pseudotime were generated across 5 random splits, for a total of 50 files per cell type, per sample. These files are available from <strong>CPTAC_RCC_expression_all_cells.zip.</strong></li> <li>Expression data were subset to include 63 randomly-selected podocytes and 63 randomly-selected macrophages to ensure balanced data. These expression data are available from <strong>CPTAC_RCC_expression.zip</strong>. Pseudotimes were also subset and are available in <strong>CPTAC_RCC_pseudotime.zip</strong>.</li> <li>Expression data were projected onto the first 100 principal components. These data are available from <strong>CPTAC_RCC_expression_dimReduced.zip</strong>.</li> </ol>
ScienceDex guides
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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.