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565
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ShareScore release 0.9.0
Dataset results
565 results for “cancer type”
A Phase II Study to Evaluate the Efficacy of TKI258 for the Treatment of Patients With FGFR2 Mutated or Wild-type Advanced and/or Metastatic Endometrial Cancer
ClinicalTrials.gov study NCT01379534. IPD Sharing: Not stated. Countries: 7. Publications: 1.
PEAK: Panitumumab Plus mFOLFOX6 vs. Bevacizumab Plus mFOLFOX6 for First Line Treatment of Metastatic Colorectal Cancer (mCRC) Patients With Wild-Type Kirsten Rat Sarcoma-2 Virus (KRAS) Tumors
ClinicalTrials.gov study NCT00819780. IPD Sharing: Not stated. Countries: 6. Publications: 12.
A Study to Test Different Doses of BI 891065 Alone and in Combination With BI 754091 in Asian Patients With Different Types of Advanced Cancer (Solid Tumours)
ClinicalTrials.gov study NCT04138823. IPD Sharing: NO. Countries: 1. Publications: 1.
Panitumumab in Cetuximab Refractory KRAS Wild-Type Colorectal Cancer
ClinicalTrials.gov study NCT00842257. IPD Sharing: NO. Countries: 1. Publications: 1.
A Study Called EPI VITRAKVI to Compare Treatment Results in Patients With Infantile Fibrosarcoma (IFS), a Type of Connective Soft Tissue Cancer, Who Received a Treatment Called Larotrectinib From a St
ClinicalTrials.gov study NCT05236257. IPD Sharing: NO. Countries: 1. Publications: 1.
A Study to Find the Best Dose of BI 836880 Alone and in Combination With BI 754091 in Japanese Patients With Different Types of Advanced Cancer
ClinicalTrials.gov study NCT03972150. IPD Sharing: NO. Countries: 1. Publications: 1.
A Multi-omics-based Metabolic Typing Study of Gastric Cancer
ClinicalTrials.gov study NCT06134011. IPD Sharing: NO. Countries: 1. Publications: 3.
EMD 525797 in Combination With Cetuximab and Irinotecan in K-ras Wild Type Metastatic Colorectal Cancer
ClinicalTrials.gov study NCT01008475. IPD Sharing: Not stated. Countries: 12. Publications: 1.
Cost-effectiveness analysis of cetuximab combined with chemotherapy as a first-line treatment for RAS wild-type metastatic colorectal cancer patients based on the TAILOR trial
<p><b>Objectives</b> Cetuximab plus leucovorin, fluorouracil, and oxaliplatin (FOLFOX-4) is superior to FOLFOX-4 alone as a first-line treatment for patients with RAS wild-type metastatic colorectal cancer (wt mCRC), with significantly improved survival benefit by TAILOR, an open-label, randomized, multicentre, phase III trial. Nevertheless, the cost-effectiveness of these two regimens remains uncertain. The following study aims to determine whether cetuximab combined with FOLFOX-4 is a cost-effective strategy for specific RAS wt mCRC patients in China.</p> <p><b>Design</b> A combined decision tree and Markov model with three health states (stable, progressive and dead) was constructed to simulate a hypothetical cohort of patients with RAS wt mCRC. The health outcomes and utility scores were derived from the TAILOR trial and previously published sources, respectively. Costs were calculated with reference to the Chinese societal perspective. A lifetime horizon was used. Univariate and probabilistic sensitivity analyses were carried out to test the robustness of the model results.</p> <p><b>Participants</b> The included patients were newly diagnosed Chinese patients with fully RAS wt mCRC. <b>Interventions</b> Either cetuximab plus FOLFOX-4 or FOLFOX-4 alone as a first-line treatment.</p> <p><b>Main outcome measures</b> The primary outcomes are costs, quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs).</p> <p><b>Results</b> Baseline analysis showed that the addition of cetuximab increased the QALYs by 0.383, while an increase of $62,947 was observed in relation to FOLFOX-4 chemotherapy. This led to an incremental cost-effectiveness ratio (ICER) of $164,044/QALY. Sensitivity analysis showed that across the wide variation in parameters, the ICER exceeded the willingness-to-pay threshold of $28,106/QALY, which was three times the per capita GDP in China.</p> <p><b>Conclusions</b> Despite the survival benefit, cetuximab combined with FOLFOX-4 is not a cost-effective treatment for the first line treatment of patients with RAS wt mCRC in China.</p>
A Lung Nodule Dataset with Histopathology-based Cancer Type Annotation (DICOM VERSION)
<p>We constructed a groundbreaking lung CT dataset, which includes 330 annotated nodules from 95 patients. It is worth noting that we have integrated the results of patient clinical diagnosis, frozen diagnosis, and pathological diagnosis, supplementing this with labeled lung cancer types on 308 samples containing nodules.</p>
Allele-specific chromatin accessibility for 23 cancer types and weight files for Regulome Wide Association-Studies (RWAS)
<p><strong>stratAS_results.tar.gz</strong></p> <p>This folder contains the results of analyses of allele-specific chromatin accessibility for 23 cancer types + pan-cancer using the stratAS software. The analyses identified allelically imbalanced genomic regions from 406 cancer ATAC-Seq samples. The files are named after each cancer type (or “pancancer” for the pan-cancer analysis) and contain the following columns:</p> <p>CHR - Chromosome<br> POS - Position of test<br> SNP RSID - ID of test SNP<br> P0 - Start of gene/peak<br> P1 - End of gene/peak<br> NAME - Name of gene/peak<br> CENTER - Center position of peak (or TSS for gene)<br> N.HET - Number of heterozygous individuals tested N.READS - Number of reads tested in total<br> ALL.AF - Allelic fraction estimate from beta binomial test across both conditions<br> ALL.BBINOM.P - Beta-binomial test for imbalance across both conditions<br> C0.AF - Allelic fraction estimate from condition 0<br> C0.BBINOM.P - Beta-binomial test for imbalance in condition 0<br> C1.AF - Allelic fraction estimate from condition 1<br> C1.BBINOM.P - Beta-binomial test for imbalance in condition 1<br> DIFF.BBINOM.P - Beta-binomial test for difference between conditions<br> IND.C0 - Number of each condition 0 individual included in this test (comma separated)<br> IND.C0.COUNT.REF - condition 0 REF allele counts of each individual included in this test (comma separated)<br> IND.C0.COUNT.ALT - condition 0 ALT allele counts of each individual included in this test (comma separated)<br> IND.C1 - Number of each condition 1 individual included in this test (comma separated)<br> IND.C1.COUNT.REF - condition 1 REF allele counts of each individual included in this test (comma separated)<br> IND.C1.COUNT.ALT - condition 1 ALT allele counts of each individual included in this test (comma separated)</p> <p>In our analysis, samples that belong to a cancer type that is analyzed for allelic imbalance are assigned to Condition 1 (C1) while samples belonging to the remaining 22 cancer types are assigned to Condition 0 (C0). For the pan-cancer analysis, samples from all 23 cancer types are assigned to C1. P-values denoting the significance of allelic imbalance in a given cancer type (or pan-cancer analysis) are listed in the column C1.BBINOM.P. P-values denoting the significance of differential allelic imbalance between a given cancer type and the remaining 22 cancer types are listed in column DIFF.BBINOM.P (set to NA for pan-cancer analysis since all samples are assigned to C1).</p> <p>More information about stratAS and its output format can be found at https://github.com/gusevlab/stratAS.</p> <p>The conducted analyses are described in detail in the methods section of Grishin D. and Gusev A. Allelic imbalance of chromatin accessibility in cancer identifies candidate causal risk variants and their mechanisms (2022).</p> <p><strong>RWAS_weights.tar.gz</strong></p> <p>This folder contains weight files that can be used together with GWAS summary statistics to conduct Regulome Wide Association-Studies (RWAS) using the FUSION software package.</p> <p>Each weight file corresponds to a single accessible element in the FUSION format. Instructions on how to use FUSION for RWAS can be found at http://gusevlab.org/projects/fusion/. RWAS is conducted in the same manner as TWAS using these RWAS weights.</p> <p>The weight files were generated using a pan-cancer peak set. A BED file containing pan-cancer peaks can be found in the peaks_hg19 folder along with other BED files containing cancer-type specific peaks. Cancer-type specific peak files can be used to restrict the RWAS analysis to regulatory elements active in specific cancer types.</p> <p>The conducted analyses are described in detail in the methods section of Grishin D. and Gusev A. Allelic imbalance of chromatin accessibility in cancer identifies candidate causal risk variants and their mechanisms (2022).</p>
Integration of single-cell RNA-sequencing data across tissues and cancer types towards immune cell characterization
<p>To better understand dendritic cell states and subtypes, we collected individual single-cell RNAseq datasets from various studies and further integrated, batch corrected, and reprocessed the data using Besca (https://github.com/bedapub/besca).</p> <p>The following files are included:<br> 1) study_table_integrated_DCs.xlsx - contains a list of studies from where the datasets were gathered.<br> 2) int_dcs.raw.h5ad - An anndata object file containing the combined raw single-cell counts for DCs from individual studies. The datasets were joined based on the union of variables.<br> 3) intersection_genes_integrated_dcs.tsv - List of genes if the datasets were joined based on the intersection of variables. These variables were used in the subsequent analyses.</p> <p>4) int_dcs.annotated.h5ad - An anndata object file containing single-cell logarithmized counts for DCs data that have been integrated and reprocessed. The rows of the file contain cells, and the columns contain highly variable genes. A sparse matrix containing the logarithmized counts from all the genes (from the intersection genes integrated dcs.tsv file) can also be found (adata.raw.X) in the object. In the observations, cell-type annotation is available at three different hierarchal levels.<br> <br> This data was further used to produce results for the publication (https://jitc.bmj.com/content/10/6/e004268) on the effects of Toll-like receptor 8 agonists on conventional DCs.</p>
Genomic Alterations of the Metabolic Pathways Across 32 Cancer Types and Their Clinical Significance
<p>Supplementary Information for the thesis chapter: Genomic Alterations of the Metabolic Pathways Across 32 Cancer Types and Their Clinical Significance </p>
The STRIVE Study: Development of a Blood Test for Early Detection of Multiple Cancer Types
ClinicalTrials.gov study NCT03085888. IPD Sharing: NO. Countries: 1. Publications: 1.
Benefit of Chemotherapy Over Best Supportive Care in Metastatic and Squamous Cell-type Esophageal Cancer.
ClinicalTrials.gov study NCT01248299. IPD Sharing: NO. Countries: 1. Publications: 1.
Lymph Node Staging System With a Novel Concept for Gastric Cancer: a Hybrid Type of Topographic and Numeric Ones
ClinicalTrials.gov study NCT01961791. IPD Sharing: Not stated. Countries: 1. Publications: 5.
P13Kinase Inhibitor BKM120 in Combination With Panitumumab in Metastatic/Advanced RAS-Wild Type Colorectal Cancer.
ClinicalTrials.gov study NCT01591421. IPD Sharing: NO. Countries: 1. Publications: 1.
IMRT Combined With Erlotinib for EGFR Wild Type Non-small Cell Lung Cancer With 4-10 Brain Metastases
ClinicalTrials.gov study NCT02556593. IPD Sharing: Not stated. Countries: 1. Publications: 34.
A Study Comparing Two Types of Supportive Interventions for Caregivers of Patients With Cancer
ClinicalTrials.gov study NCT04802720. IPD Sharing: YES. Countries: 1. Publications: 0.
Anlotinib Plus Docetaxel for the Treatment of EGFR Wild-type Advanced Non-small-cell Lung Cancer
ClinicalTrials.gov study NCT03624309. 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.