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565 results for “cancer type”
BeBOD estimates of incidence, prevalence, and years lived with disability for 57 cancer types, 2004-2021
<p><strong>Belgian National Burden of Disease Study</strong></p><p><strong>Estimates of the morbidity burden of disease for 57 cancer sites</strong></p><p><i>Incidence</i></p><p>Data on new cancer cases in Belgium are collected by the <a href="https://kankerregister.org/Annual%20Tables">Belgian Cancer Registry</a> (BCR). For the current study, we selected 80 ICD-10 (C00.0-96.9 and chronic myeloid neoplasms) codes resulting in 57 cancer sites. Data were extracted by year (from 2004 to 2021), age group (5-years), sex and region (N=3). We excluded "Respiratory system and intrathoracic organs, NOS (not otherwise specified)" from further analyses because of too few cases.</p><p><i>Prevalence</i></p><p>Prevalence estimates were estimated using the above-described incidence estimates and the survival estimates also provided by BCR, derived from linkage with the Belgian Crossroads Bank for Social Security. We used a 10-year prevalence perspective meaning that from the year 2013 onwards, we were able to define the prevalence in a given year as the sum of person-months spent in the different health states. Specifically, we used a microsimulation approach to simulate future health states for each year-, age-, sex-, region- and cancer-specific cohort of incident cases.</p><p>See for more details: <a href="https://doi.org/10.1186/s12885-021-09109-4">https://doi.org/10.1186/s12885-021-09109-4</a></p><p><i>Years Lived with Disability</i></p><p>Years Lived with Disability (YLDs) were calculated using both an incidence and prevalence perspective as a measure of morbidity. YLDs are calculated as the product of the number of prevalent cases with the disability weight (DW), averaged over the different health states of the disease. The DWs reflect the relative reduction in quality of life, on a scale from 0 (perfect health) to 1 (death). We calculate YLDs using the Global Burden of Disease DWs.</p>
Catalog of stool metagenome-assembled genomes from patients with different cancer types
<p><strong>A non-redundant catalog of 3,816 genomes with at least 75% completeness and no more than 15% contamination assembled from metagenomes. Samples of 976 metagenomes were obtained from patients receiving immunotherapy for the treatment of different types of cancers.</strong></p>
GERONTE H2020 project - GERDAT006 - Dataset of symptoms and proms for specific cancer types and gender
<p>This dataset describes a series of symptoms, potentially indicative of treatment-related complications, destabilised comorbidity or functional decline, to be used in the Geronte project for symptoms monitoring in older patients with multimorbidity during and after their cancer treatment</p>
Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data.
<p>Bulk ATAC-seq data of tumour samples result in an averaged signal across different cell-types (cancer, stromal, vascular and immune cells). We propose a deconvolution framework called EPIC-ATAC (<a href="https://doi.org/10.7554/eLife.94833.1">https://doi.org/10.7554/eLife.94833.1</a>), which relies on newly identified cell-type specific ATAC-Seq marker peaks and reference profiles for all major cancer-relevant cell-types to predict the proportions of each cell-type.</p> <p>To evaluate EPIC-ATAC, we generated a bulk ATAC-Seq dataset from peripheral blood mononuclear cells (PBMCs) samples, from which the number of cells in each cell-type has been estimated using flow cytometry, as ground truth for cell proportions. The data provided in this Zenodo deposit correspond to:</p> <p>- The raw counts matrix for each peak called in this ATAC-Seq dataset: PBMC_counts.txt</p> <p>- The normalized (TPM-like) counts matrix for each peak called in this ATAC-Seq dataset: PBMC_counts_norm.txt</p> <p>- The cell fractions of each cell type in each sample: PBMC_cell_fractions.txt</p> <p>- The peaks called in each sample using MACS2 (*narrow.peaks): *_normalized.narrowPeak</p> <p>- Bed files listing ATAC-Seq fragments for each sample: *.bed</p> <p>We also evaluated EPIC-ATAC on multiple pseudobulks generated from single-cell ATAC-Seq data. We provide rds files containing the pseudobulks data used in our work for the evaluation of EPIC-ATAC. The rds files are located in the zip file "pseudobulks.zip".</p> <p>The file "additional_data.zip" contains additional files used to generate the reference profiles in EPIC-ATAC and to reproduce the main analyses performed in the manuscript: <a href="https://doi.org/10.7554/eLife.94833.1">https://doi.org/10.7554/eLife.94833.1</a>. These files are required to run the code available on the following GitHub repository: GfellerLab/EPIC-ATAC_manuscript. </p>
Classification of Gene Mutations and Cancer-Types with BioBombe Compressed Gene Expression Features
<p>BioBombe analysis applied to gene expression data from The Cancer Genome Atlas (TCGA) PanCanAtlas.</p> <p>Then, the compressed features learned through the serial compression are fed into several machine learning algorithms.</p> <p>The algorithms are used to predict mutation status (for the top 50 most mutated genes in TCGA) and cancer-type using the compressed gene expression features.</p> <p>Method and results described in https://github.com/greenelab/BioBombe. We use the classification approach outlined in https://github.com/greenelab/pancancer</p>
Modulation of the tumour promoting functions of cancer associated fibroblasts by phosphodiesterase type 5 inhibition increases the efficacy of chemotherapy in human preclinical models of esophageal adenocarcinoma
<p>These are whole-slide digital pathology images of esophageal adenocarcinoma (EAC) patient-derived xenograft models. EAC biopsy specimens were cultured <em>in vitro</em> before implanting into immuno-deficient mice. Mice were then divided into the following treatment groups and treated with combinations of chemotherapy and PDE5 inhibitors as follows:</p> <ol> <li>Untreated</li> <li>Epirubicin + Cisplatin + Capecitabine (ECX)</li> <li>ECX + Vardenafil</li> <li>ECX + Tadalafil</li> </ol> <p>All whole slide images are in Olympus .vsi format and can be opened using the BioFormats library in QuPath. We have also included classifiers and scripts for performing the digital pathology analysis in QuPath, and information to link each mouse with treatment groups and corresponding whole slide images.</p> <p>File metadata:</p> <p>classifiers.zip - Folder containing pixel classifiers used for segmentation of IHC stains. These classifiers are to be important into QuPath for the respective analysis of Periostin (POSTN) and alpha Smooth Muscle Actin (SMA) staining using the included Groovy scripts in the scripts folder.</p> <p>SMA.zip - Folder containing whole slide images of mouse patient-derived xenograft tumours in .vsi format (Olympus VS110). Immunohistochemistry with anti-alpha Smooth Muscle Actin antibody.<br> POSTN.zip - Folder containing whole slide images of mouse patient-derived xenograft tumours in .vsi format (Olympus VS110). Immunohistochemistry with anti-Periostin antibody.</p> <p>scripts.zip - Folder containing all groovy scripts used in QuPath for tissue detection (Whole Section Tissue Detection.groovy), and segmentation of POSTN (POSTN Quantification Mice.groovy) and SMA staining tissue areas (SMA Quantification Mice.groovy).</p> <p>POSTN.xlsx - Data on the mice for which anti-POSTN IHC is available. Column names as follows:<br> Image: file name (corresponding to .vsi file).<br> Mouse_ID: Mouse identifier.<br> Treatment: Treatment administered. ECX - Epirubicin, Cisplatin and Capecitabine.<br> POSTN_Area: Total measured area of POSTN+ tissue in the tissue section (in um^2).<br> Total_Area: Total area of the tissue section (in um^2).<br> percentage_POSTN: Percentage of total tissue area that is stained with POSTN (%).</p> <p>SMA.xlsx - Data on the mice for which anti-SMA IHC is available. Column names as follows:<br> Image: file name (corresponding to .vsi file).<br> Mouse_ID: Mouse identifier.<br> Treatment: Treatment administered. ECX - Epirubicin, Cisplatin and Capecitabine.<br> SMA_Area: Total measured area of SMA+ tissue in the tissue section (in um^2).<br> Total_Area: Total area of the tissue section (in um^2).<br> percentage_SMA: Percentage of total tissue area that is stained with SMA (%).</p>
Study of Cemiplimab in Patients With Type of Skin Cancer Stage II to IV Cutaneous Squamous Cell Carcinoma
ClinicalTrials.gov study NCT04154943. IPD Sharing: YES. Countries: 3. Publications: 2.
Study of Oral cMET Inhibitor INC280 in Patients With EGFR Wild-type (wt), Advanced Non-small Cell Lung Cancer (NSCLC) (Geometry Mono-1)
ClinicalTrials.gov study NCT02414139. IPD Sharing: YES. Countries: 20. Publications: 3.
Supplementary Material v1: Multivariate entropy characterizes the gene expression and protein -protein networks in four types of cancer
<p>Supplementary Material PDF</p> <p>Multivariate entropy characterizes the gene expression and protein -protein networks in four types of cancer</p>
cProt: Types of Cancer in Human
<p>cProt: Types of Cancer in Human</p>
QL1706 Plus Neoadjuvant Chemotherapy Followed by Type I Hysterectomy for Locally Advanced Cervical Cancer
ClinicalTrials.gov study NCT07205497. IPD Sharing: YES. Countries: 1. Publications: 8.
SBRT, Chemotherapy, and AK112 Neoadjuvant Therapy for Luminal-type Breast Cancer
ClinicalTrials.gov study NCT06402435. IPD Sharing: YES. Countries: 1. Publications: 1.
FOLFOXIRI Plus Panitumumab Patients With Metastatic KRAS Wild-Type Colorectal Cancer With Liver Metastases Only
ClinicalTrials.gov study NCT01226719. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Study of Nimotuzumab Combinated With Gemcitabine in K-RAS Wild-type Locally Advanced and Metastatic Pancreatic Cancer
ClinicalTrials.gov study NCT02395016. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Phase II Trial of Talazoparib in BRCA1/2 Wild-type HER2-negative Breast Cancer and Other Solid Tumors
ClinicalTrials.gov study NCT02401347. IPD Sharing: NO. Countries: 1. Publications: 1.
Brightline-1: A Study to Compare Brigimadlin (BI 907828) With Doxorubicin in People With a Type of Cancer Called Dedifferentiated Liposarcoma
ClinicalTrials.gov study NCT05218499. IPD Sharing: YES. Countries: 22. Publications: 1.
ASPECCT: A Study of Panitumumab Efficacy and Safety Compared to Cetuximab in Patients With KRAS Wild-Type Metastatic Colorectal Cancer
ClinicalTrials.gov study NCT01001377. IPD Sharing: Not stated. Countries: 29. Publications: 7.
Randomized Phase II Study of AZD6244 (Mitogen-activated Protein Kinase Inhibitor) MEK-Inhibitor With Erlotinib in KRAS Wild Type Advanced Non-Small Cell Lung Cancer (NSCLC) and a Randomized Phase II S
ClinicalTrials.gov study NCT01229150. IPD Sharing: NO. Countries: 1. Publications: 4.
Perflutren Protein-Type A Microspheres and Contrast-Enhanced Ultrasound in Improving Response to Radioembolization Therapy in Patients With Liver Cancer
ClinicalTrials.gov study NCT03199274. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Irinotecan and Cetuximab With or Without Bevacizumab in Treating Patients With RAS Wild-Type Locally Advanced or Metastatic Colorectal Cancer That Cannot Be Removed by Surgery
ClinicalTrials.gov study NCT02292758. IPD Sharing: Not stated. Countries: 1. 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.