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ShareScore release 0.9.0
Dataset results
22 results for “intra-tumor heterogeneity”
Proteomic characterization of intra-tumor heterogeneity in human endometrial cancer.
<p>Endometrial cancer (EC) is one of the most frequently diagnosed gynecological cancers worldwide, and its prevalence has increased by more than 50% over the last two decades. Despite the understanding of the major signaling pathways driving the growth and metastasis of EC cells, clinical trials targeting these signaling pathways in human patients have reported poor outcomes. Heterogeneous nature of EC is suspected to be one of the key reasons for the failure of targeted therapies. However, no study so far has explored EC heterogeneity within the same patient at the proteomic level. In this study, we isolated proteins from tumor tissue samples obtained from different sites of EC from individual patients (~2-4 samples/patient). We then performed a SWATH-based comparative proteomic analysis, using liquid chromatography-tandem mass spectrometry (LC-MS/MS), to profile the protein content of different areas within EC tissue. Our results highlighted an average of 1424 unique proteins in 20 patient-derived EC tissues with a confidence corresponding to a false discovery rate below 1%. We have identified protein biomarkers that differentiate between premenopausal vs postmenopausal cancer, macroscopic vs microscopic tumor, more vs less invasive cancer, and DNA mismatch repair defective vs intact tumor. Furthermore, the data revealed a list of unique proteins that, for the same patient, exist only in a single EC location but are not present in other locations within the same tumor. Overall, our proteomic analysis highlighted that tumor tissue samples collected from different sites of EC within the same patient can harbor diverse protein profiles. Importantly, this study sets the foundation for further investigations into the mechanisms of endometrial heterogeneity and some of the proteins identified here may represent potential novel EC drug targets.</p>
Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability
<p>"Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability", F. Raynaud, M. Mina, D. Tavernari and G. Ciriello</p> <p>These files are necessary to generate the supplementary table containing:</p> <p>#Sample_name #Cancer_type #Cancer_subtype #Mean_reads_per_mutations #Number_of_mutations #Number_of_altered_segments #Number_of_clones #TreeScore #Number_of_mutations_first_clone #Number_of_mutations_other_clones</p> <p>REQUIREMENTS</p> <p>Phylogenies generated by PhyloWGS (PhyloWGS: Reconstructing subclonal composition and evolution from whole-genome sequencing of tumors](<a href="http://genomebiology.com/2015/16/1/35">http://genomebiology.com/2015/16/1/35</a>), Deshwar et al.)</p> <p>Output files from PhyloWGS for each sample:</p> <ul> <li> <p>top_k_trees which contains the best phylogenies (50 by default) with the label of each clone, the population frequency of each clone, the number of children of each clone, number of mutations in the clone, the labels of the mutations</p> </li> <li> <p>top_k_trees1, top_k_trees2, ... , top_k_treesN output file for the best k trees (50 by default)</p> </li> </ul> <p>FILES</p> <p>*Molecular data for the tumor types: CESC, UCEC, UVM, THCA, KICH, BRCA, SKCM, ACC, CRC, STAD, BLCA, LUAD, KIRP, PRAD, LIHC; has been collected in July 2015 *Molecular data for the tumor types: SARC, PAAD, MESO, LGG, GBM, DLBC, UCS, THYM, TGCT, PCPG, OV, LUSC, LAML, KIRC, HNSC, ESCA, CHOL; has been collected in 2018</p> <p>from the FireHose (<a href="https://gdac.broadinstitute.org/">https://gdac.broadinstitute.org/</a>) and cBioPortal (Cerami et al., 2012) (<a href="http://www.cbioportal.org/">http://www.cbioportal.org/</a>) data repositories for The Cancer Genome Atlas (TCGA). Only TCGA datasets publicly available at that time were used in our study.</p> <p>-Mutation files (MAF format): combined_2015_2018_MAF.maf.bz2</p> <p>-Copy number segmentation files: combined_seg_2015_2018.seg.bz2</p> <p>-analyze_public.py: Python file to generate the Supplementary Table run: python2.7 analyze_public.py</p> <p>- All input data and results from PhyloWGS: PhyloWGS_input_output.tar.bz2 </p>
Single-cell landscapes of primary glioblastomas and matched organoids and cell lines reveal variable retention of inter- and intra-tumor heterogeneity [scWGS]
GEO Series GSE173279. Homo sapiens. 16 samples. Type: Other.
Overcoming intra-tumoral heterogeneity for biomarker discovery in the High-Grade Serous Ovarian Cancer proteome
GEO Series GSE277107. Homo sapiens. 22 samples. Type: Expression profiling by high throughput sequencing.
ZEB2 drives intra-tumor heterogeneity and skin squamous cell carcinoma formation with distinct EMP transition states.
GEO Series GSE265908. Mus musculus. 3 samples. Type: Expression profiling by high throughput sequencing.
Single-cell landscapes of primary glioblastomas and matched organoids and cell lines reveal variable retention of inter- and intra-tumor heterogeneity [scRNA-seq]
GEO Series GSE173278. Homo sapiens. 99 samples. Type: Expression profiling by high throughput sequencing.
Integrated Methylation and Spatial Transcriptomic Profiling of Metaplastic Breast Cancer to Investigate Intra-tumoral Heterogeneity.
GEO Series GSE283412. Homo sapiens. 8 samples. Type: Other.
Single-Nuclei Multiome (ATAC + Gene Expression) Sequencing of a Primary Canine Osteosarcoma Elucidates Intra-Tumoral Heterogeneity and Characterizes the Tumor Microenvironment
GEO Series GSE244116. Canis lupus familiaris. 2 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Single-cell analysis reveals inter- and intra-tumor heterogeneity in metastatic breast cancer
GEO Series GSE202695. Homo sapiens. 2982 samples. Type: Expression profiling by high throughput sequencing.
Benchmarking Intra-tumor Heterogeneity In Ovarian Cancer: Linking In-vivo Imaging Phenotypes With Histology And Genomics
ClinicalTrials.gov study NCT02144311. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Explore Intra-tumor Heterogeneity and Prognostic Value of Postoperative Blood ctDNA of ⅡA - ⅢA Stage Non-squamous NSCLC Based on the Capture-based Sequencing and UMI Technology of Burning Rock
ClinicalTrials.gov study NCT03337711. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Single-cell landscapes of primary glioblastomas and matched organoids and cell lines reveal variable retention of inter- and intra-tumor heterogeneity [multi-generation scRNA-seq]
GEO Series GSE193884. Homo sapiens. 11 samples. Type: Expression profiling by high throughput sequencing.
Single cell analysis reveals intra-tumor heterogeneity and microenvironment for clear cell renal cell carcinoma
GEO Series GSE156632. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
A live single-cell state reporter assay links intra-tumor heterogeneity to metastatic proclivity in Ewing sarcoma
GEO Series GSE163699. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing.
Deciphering functional intra-tumoral heterogeneity in BRAFV600E-driven mouse thyroid cancer reveals EMT trajectory and metabolic remodeling
GEO Series GSE311419. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Intra-Tumor DNA Methylation Heterogeneity in Glioblastoma; Implications for DNA Methylation-based Classification
GEO Series GSE116298. Homo sapiens. 47 samples. Type: Methylation profiling by array.
Intra-tumor genetic heterogeneity in breast cancers with heterogeneous HER2 gene amplification
GEO Series GSE67908. Homo sapiens. 25 samples. Type: Genome variation profiling by array.
Gene expression-based dissection of inter-histotype, in-tra-histotype and intra-tumor heterogeneity in pediatric tumors
GEO Series GSE197147. Homo sapiens. 79 samples. Type: Expression profiling by array.
Intra-tumor Genetic Heterogeneity in Rectal Canger
GEO Series GSE73365. Homo sapiens. 15 samples. Type: Genome variation profiling by SNP array.
Single-cell landscapes of primary glioblastomas and matched organoids and cell lines reveal variable retention of inter- and intra-tumor heterogeneity.
GEO Series GSE173280. Homo sapiens. 126 samples. Type: Expression profiling by high throughput sequencing; Other.
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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.