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1,195 results for “Cancer Genomics”
Genomic Sequencing of Pediatric Rhabdoid Cancers
In this study, we sequenced the exomes of 35 rhabdoid tumors, highly aggressive cancers of early childhood. This study is part of a larger effort to characterize pediatric cancers as part of the Slim Initiative for Genomic Medicine (SIGMA) project.
The Institute for Genomic Medicine at Nationwide Children's Hospital Pediatric Cancer and Blood Disorder Project
The aim of this study is to enable the unification of the clinical and research arms of comprehensive genomic profiling in the setting of cancer and hematologic disease. Increasingly, studies of the genomic etiology of cancer and hematologic diseases are being utilized for patient management, including prognostication, informing diagnosis, and evaluating eligibility for targeted therapeutics and clinical trials. Clinically available testing can be limited in scope and follow-up, and thus assessment of the impact on patient outcomes is difficult to ascertain. N-of-1 studies have the ability to more broadly impact our understanding of the mechanisms of cancer and hematologic disease, and can have benefit for the individual as well as the larger population of patients with these diseases. Thus, we seek to study and characterize the genomic underpinnings of cancer and hematologic disease through genomic profiling studies bridging both clinical and research components. We will rigorously perform and vet research sequencing and genomic studies protocols for the purpose of transitioning these assays to clinically valid testing for use in clinical patient care.
Feasibility and Clinical Utility of Whole Genome Profiling in Pediatric and Young Adult Cancers
Open the record for dataset details and reuse information.
Distinct genomic and immunologic tumor evolution in germline TP53-driven breast cancers
GEO Series GSE306117. Homo sapiens. 74 samples. Type: Expression profiling by high throughput sequencing.
Dataset related to article "Copy number alterations in stage I epithelial ovarian cancer highlight three genomic patterns associated to prognosis"
<p>This record contains data related to article "Copy number alterations in stage I epithelial ovarian cancer highlight three genomic patterns associated to prognosis"</p> <p><strong>Background: </strong>Stage I epithelial ovarian cancer (EOC) encompasses five histologically different subtypes of tumors confined to the ovaries with a generally favorable prognosis. Despite the intrinsic heterogeneity, all stage I EOCs are treated with complete resection and adjuvant therapy in most of the cases. Owing to the lack of robust prognostic markers, this often leads to overtreatment. Therefore, a better molecular characterization of stage I EOCs could improve the assessment of the risk of relapse and the refinement of optimal treatment options.</p> <p><strong>Materials and methods: </strong>205 stage I EOCs tumor biopsies with a median follow-up of eight years were gathered from two independent Italian tumor tissue collections, and the genome distribution of somatic copy number alterations (SCNAs) was investigated by shallow whole genome sequencing (sWGS) approach.</p> <p><strong>Results: </strong>Despite the variability in SCNAs distribution both across and within the histotypes, we were able to define three common genomic instability patterns, namely stable, unstable, and highly unstable. These patterns were based on the percentage of the genome affected by SCNAs and on their length. The genomic instability pattern was strongly predictive of patients' prognosis also with multivariate models including currently used clinico-pathological variables.</p> <p><strong>Conclusions: </strong>The results obtained in this study support the idea that novel molecular markers, in this case genomic instability patterns, can anticipate the behavior of stage I EOC regardless of tumor subtype and provide valuable prognostic information. Thus, it might be propitious to extend the study of these genomic instability patterns to improve rational management of this disease.</p>
Dataset related to article "Genomic instability analysis in DNA from Papanicolaou test provides proof-of-principle early diagnosis of high-grade serous ovarian cancer"
<p>This record contains data related to the article "Genomic instability analysis in DNA from Papanicolaou test provides proof of principle early diagnosis of high-grade serous ovarian cancer".</p><p>Abstract</p><p>Late diagnosis and the lack of screening methods for early detection define high-grade serous ovarian cancer (HGSOC) as the gynecological malignancy with the highest mortality rate. In the work presented here, we investigated a retrospective and multicentric cohort of 250 archival Papanicolaou (Pap) test smears collected during routine gynecological screening. Samples were taken at different time points (from 1 month to 13.5 years before diagnosis) from 113 presymptomatic women who were subsequently diagnosed with HGSOC (pre-HGSOC) and from 77 healthy women. Genome instability was detected through low-pass whole-genome sequencing of DNA derived from Pap test samples in terms of copy number profile abnormality (CPA). CPA values of DNA extracted from Pap test samples from pre-HGSOC women were substantially higher than those in samples from healthy women. Consistently with the longitudinal analysis of clonal pathogenic <i>TP53</i> mutations, this assay could detect HGSOC presence up to 9 years before diagnosis. This finding confirms the continual shedding of tumor cells from fimbriae toward the endocervical canal, suggesting a new path for the early diagnosis of HGSOC. We integrated the CPA score into the EVA (early ovarian cancer) test, the sensitivity of which was 75% (95% CI, 64.97 to 85.79), the specificity 96% (95% CI, 88.35 to 100.00), and the accuracy 81%. This proof-of-principle study indicates that the early diagnosis of HGSOC is feasible through the analysis of genomic alterations in DNA from endocervical smears.</p>
Genome-wide analysis of matched microRNA-mRNA time-course data after androgen injection to prostate cancer LNCaP cell line
GEO Series GSE21245. Homo sapiens. 20 samples. Type: Expression profiling by array; Non-coding RNA profiling by array.
Drug screening and genomic analyses of HER2 positive breast cancer cell lines reveal predictors for treatment response [CGH]
GEO Series GSE58886. Homo sapiens. 4 samples. Type: Genome variation profiling by genome tiling array.
Integrative genome-wide analysis in non-small cell lung cancer cells
GEO Series GSE63356. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Genome-wide analysis of gene expression by LSD1 overexpression or inhibiting by ORY1001 with or without irradiation in MDA-MB-231 breast cancer cells
GEO Series GSE120193. Homo sapiens. 6 samples. Type: Expression profiling by array.
Genome-wide synthetic lethal Crispr screen identifies SRM as a target that enhances erdafitinib efficacy in FGFR-mutant bladder cancer
GEO Series GSE276411. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Genome-wide analysis of fatty acid synthase (FASN) gene silenced retinoblastoma cancer cells (WERI RB1) using cDNA microarray analysis
GEO Series GSE63746. Homo sapiens. 8 samples. Type: Expression profiling by array.
Integrated analysis of genome-wide DNA methylation and gene expression profiles identifies potential novel biomarkers of rectal cancer [expression]
GEO Series GSE75548. Homo sapiens. 12 samples. Type: Expression profiling by array.
Genome-wide Scan for Methylation Profiles in head and Neck Cancer
GEO Series GSE67114. Homo sapiens. 8 samples. Type: Methylation profiling by genome tiling array.
Genomic and transcriptomic profiling expands precision cancer medicine: the WINTHER trial (Lung patients)
GEO Series GSE171702. Homo sapiens. 32 samples. Type: Expression profiling by array.
Epigenetic and 3D Genome Changes Drive Primary Trastuzumab Resistance in HER2+ Breast Cancer
GEO Series GSE297774. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.
Genome wide gene expression profiling of pre and post treatment breast cancer biopsy
GEO Series GSE179674. Homo sapiens. 46 samples. Type: Expression profiling by array.
Subtype-associated epigenomic landscape and 3D genome structure in bladder cancer
GEO Series GSE148079. Homo sapiens. 51 samples. Type: Expression profiling by high throughput sequencing; Other; Genome binding/occupancy profiling by high throughput sequencing.
Genome-wide analysis of YAP and TFCP2 occupancy and regulated expression in liver cancer cells
GEO Series GSE99315. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Nucleolar Expansion Drives 3D Genome Reorganization and Transcriptional Repression in Cancer
GEO Series GSE315576. Homo sapiens. 34 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.