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262
datasets available to search
ShareScore release 0.9.0
Dataset results
262 results for “tumor heterogeneity”
Vaccine-primed CAR T-cells reject antigen-heterogenous tumors via host immunity
GEO Series GSE212453. Mus musculus. 27 samples. Type: Expression profiling by high throughput sequencing; Other.
PRC2 Heterogeneity Drives Tumor Growth in Medulloblastoma
GEO Series GSE206009. Homo sapiens; Mus musculus. 10 samples. Type: Expression profiling by high throughput sequencing.
Integrated multiomic analysis reveals comprehensive tumor heterogeneity in primary and recurrent hepatocellular carcinomas
GEO Series GSE164359. Homo sapiens. 47 samples. Type: Expression profiling by high throughput sequencing.
Starfysh reveals heterogeneous spatial dynamics in the breast tumor microenvironment
GEO Series GSE218951. Homo sapiens. 9 samples. Type: Expression profiling by high throughput sequencing; Other.
Expression of deregulated MYC with activated NeuNT in mammary gland developed mammary tumors with molecular heterogeneity
GEO Series GSE132528. Mus musculus. 21 samples. Type: Expression profiling by high throughput sequencing.
3D Intercellular Assembly of Decellularized Matrix Recapitulates In Vivo Tumor Heterogeneity
GEO Series GSE267071. Homo sapiens; Mus musculus. 34 samples. Type: Expression profiling by high throughput sequencing.
Unraveling Heterogeneity in Tumor Evolution Induced by Diverse Radiation Modes: Insights from Systems Biology
GEO Series GSE273937. Homo sapiens. 7 samples. Type: Expression profiling by high throughput sequencing.
Recapitulating Patient-to-Patient Colorectal Cancer Tumor Heterogeneity Using Patient-Derived Xenograft Cells in an Engineered Tissue Model
GEO Series GSE311262. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
Targeting heterogeneous tumor microenvironments in pancreatic cancer mouse models of metastasis by TGFB depletion
GEO Series GSE275596. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Immunocompetent murine models recapitulate the heterogeneous tumor immune microenvironment of human liposarcoma
GEO Series GSE300537. Mus musculus. 17 samples. Type: Expression profiling by high throughput sequencing.
PRC2 Heterogeneity Drives Tumor Growth in Medulloblastoma [mouse]
GEO Series GSE206003. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
PRC2 Heterogeneity Drives Tumor Growth in Medulloblastoma [Human]
GEO Series GSE206000. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Intra-tumoral heterogeneity in metastatic potential and survival signaling between iso-clonal HCT116 and HCT116b human colon carcinoma cell lines
GEO Series GSE44381. Homo sapiens. 2 samples. Type: Expression profiling by array.
Targeting PyMT oncogene to diverse mammary cell populations enhances tumor heterogeneity and generates rare breast cancer subtypes
GEO Series GSE40001. Mus musculus. 43 samples. Type: Expression profiling by array.
Profiling the transcriptional heterogeneity of diverse pediatric solid tumors - Neuroblastoma
For more information, including a more complete description, data generator contact information, and reference, please see: https://scpca.alexslemonade.org/projects/SCPCP000004.
Profiling the transcriptional heterogeneity of diverse pediatric solid tumors - Rhabdomyosarcoma
For more information, including a more complete description, data generator contact information, and reference, please see: https://scpca.alexslemonade.org/projects/SCPCP000005.
Profiling the transcriptional heterogeneity of diverse pediatric solid tumors - Retinoblastoma
For more information, including a more complete description, data generator contact information, and reference, please see: https://scpca.alexslemonade.org/projects/SCPCP000011.
Structurally Complex Osteosarcoma Genomes Exhibit Limited Heterogeneity within Individual Tumors and across Evolutionary Time
A key characteristic of osteosarcoma is extensive and complex genomic rearrangements. However, published models explaining how these genomic rearrangements occur disagree about if these rearrangements occur early in tumor progression and then are stable afterwards, or if there is ongoing genomic instability. Previous studies have employed bulk sequencing technologies to characterize genomic alterations. A limitation of this approach is that it averages all changes within the bulk sample, essentially masking intra-sample heterogeneity and making evaluation of ongoing genomic instability difficult. To overcome this limitation and compliment previous work, we utilized single-cell whole genome sequencing to quantify somatic copy number alterations (SCNA). By interrogating individual cells within a sample, we were able to examine intra-sample heterogeneity. We found that the SCNA patterns between cells within a single sample were remarkably consistent, which supports the concept that the genomes of osteosarcoma tumors are relatively stable after early genome fragmentation events.
Dataset related to article "Targeted Mutational Analysis of Circulating Tumor DNA to Decipher Temporal Heterogeneity of High-Grade Serous Ovarian Cancer"
<p>This record contains raw data related to article<strong> "</strong>Targeted Mutational Analysis of Circulating Tumor DNA to Decipher Temporal Heterogeneity of High-Grade Serous Ovarian Cancer<strong>".</strong></p> <p>We have previously demonstrated that longitudinal untargeted analysis of plasma samples withdrawn from patients with high-grade serous ovarian cancer (HGS-EOC) can intercept the presence of molecular recurrence (TRm) earlier than the diagnosis of clinical recurrence (TRc). This finding opens a clinical important temporal window to acquire through plasma sample analysis a real-time picture of those emerging molecular lesions that will drive and sustain the growth of relapsed disease and ultimately will confer resistance. In this proof of principle study, the same genomic libraries obtained at the diagnosis (T0), TRm and TRc were further analyzed by targeted resequencing approach to sequence the coding region of a panel of 65 genes to provide longitudinal analysis of clonal evolution as a novel strategy to support clinical decisions for the second-line treatment. Experiments were performed on plasma and tumor tissues withdrawn on a selection of previously analyzed cohorts of cases (i.e., 33 matched primary and synchronous lesions and 43 plasma samples from 18 patients). At T0, the median concordance of mutations shared by each tumor tissue biopsy and its matched plasma sample was 2.27%. This finding confirms the limit of a single tumor biopsy to be representative of the entire disease, while plasma analysis can recapitulate most of the main molecular lesions of the disease. A comparable scenario was observed during longitudinal analysis, where, with the exception of the <em>TP53</em> gene and germline mutations in <em>BRCA1/2</em> genes, no other gene shared the same locus specific gene mutation across T0, TRm and TRc time points. This high level of temporal heterogeneity has important implications for planning second-line treatment. For example, in three out of 13 cases, plasma ctDNA analysis at TRm or TRc reported acquired novel variants in the <em>TP53BP1</em> gene not present at T0. In particular, patient 21564, potentially eligible for PARP-inhibitor (PARPi) treatment at the time of diagnosis (<em>BRCA1</em> c.5182delA mutation), would unlikely respond to these drugs in second-line therapy due to the presence of eight distinct <em>TP53BP1</em> variants in plasma samples collected TRc. This study demonstrates that liquid biopsy provides a real-time molecular picture to intercept those actionable genetic vulnerabilities or drug resistance mechanisms that could be used to plan a more rational second-line treatment.</p>
Single-cell spatial profiling of small cell lung cancer suggests clinical outcome related tumor heterogeneity and immune colony niche
<p>High-dimension processed tif images of the publication "<strong>Spatial evolution and colony landscape of small cell lung cancer</strong>". The code used to produce the results of this study is available at <a href="https://github.com/ wangjun-hub/CODEX_SCLC">https://github.com/ wangjun-hub/CODEX_SCLC</a>.</p>
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.