5c3bae9e-5419-4598-869f-eed9a443bd1a - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001008437 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:NGS cancer gene panel seq profiled across 500 solid tumors screened for the Basket of Baskets study
| EGAS00001005893 | EGA
Project description:DNA was isolated from whole red blood cells from various lines and crosses of broiler chickens. DNA was genotyped using Axiom genome-wide chicken array and cel files were analyzed using Axiom Analysis Suite Software (version 3.0.1) with Gallus gallus 5.0 using the software's Best Practices for agricultural animals. The results were exported (Genotyping_Data-3-21-2018.vcf) for all genotype calls and text file of all SNPs with >= 97% call rate rate was also produced for filtering the VCF file (ALL_SNPSs_with_Call_Rate_97_Plus_3-21-2018).
2019-05-25 | GSE131764 | GEO
Project description:Germline variants calls were defined using the sequenced reads derived from 230 patients with hepatocellular carcinoma.
This dataset is comprised of one aggregated vcf file.
| EGAD00001009410 | EGA
Project description:Patient-derived lung cancer organoids cram files : targeted seq 13 samples, whole exome seq 12 samples
mutation profiles of PDO and matched tissue : aggregated vcf 1 file
details : https://www.nature.com/articles/s41467-019-11867-6
| EGAD00001005317 | EGA
Project description:TERT promoter variants are well known in solid tumors. However, less is known in hematological malignancies, thus we screened a large series of MDS and MDS/MPN.
2021-06-20 | GSE133150 | GEO
Project description:This experiment was conducted to generate targeted resequencing data covering a region associated with osteosarcoma in greyhounds. 8 greyhounds diagnosed with osteosarcoma and 7 greyhounds without tumors were sequenced. DNA from the 15 dogs was used to prepare libraries and hybrid capture performed to enrich the region of interest prior to paired-end sequencing using Illumina Genome Analyzer II. The reads were aligned to the dog-genome CanFam2.0 using bwa and pre-processed using Picard and GATK. Variant discovery was performed using GATK. The resulting list of variants were used in the study to finemap the associated region and look for causal variants. We submit the preprocessed BAM-files that still have all reads although some reads are flagged. We also submit the resulting vcf-file with called and filtered variants in all individuals.
2013-11-16 | E-MTAB-1984 | biostudies-arrayexpress
Project description:Gene expression profiles reflect unique aspects of individual biologic phenotypes and may characterize the heterogeneity of solid tumors. Using previously-described methodologies that employ DNA microarray data, a 50-gene expression profile (metagene) that predicts risk of recurrence in early stage colon carcinoma was identified. This analysis used an initial discovery cohort of 52 patients. The performance of the 50-gene predictor was evaluated in an independent validation cohort of 73 patients. Using a connectivity map analysis of the 50-gene model, we identified candidate agents and then tested the in vitro efficacy of these compounds in colon cancer cell lines. 73 samples that had patient recurrence data with stage information were used in the analysis. Keywords: Disease state analysis A total of 73 samples were spotted on microarray slides. No replicates are included in the study.
2010-05-15 | E-GEOD-10402 | biostudies-arrayexpress
Project description:Gene expression profiles reflect unique aspects of individual biologic phenotypes and may characterize the heterogeneity of solid tumors. Using previously-described methodologies that employ DNA microarray data, a 50-gene expression profile (metagene) that predicts risk of recurrence in early stage colon carcinoma was identified. This analysis used an initial discovery cohort of 52 patients. The performance of the 50-gene predictor was evaluated in an independent validation cohort of 73 patients. Using a connectivity map analysis of the 50-gene model, we identified candidate agents and then tested the in vitro efficacy of these compounds in colon cancer cell lines. 73 samples that had patient recurrence data with stage information were used in the analysis. Keywords: Disease state analysis
2008-12-03 | GSE10402 | GEO
Project description:Personalized treatment for patients with advanced solid tumors critically depends on the deep characterization of tumor cells from patient biopsies. Here, we comprehensively characterize a pan-cancer cohort of 150 malignant serous effusion (MSE) samples at the cellular, molecular, and functional level. We find that MSE-derived cancer cells retain the genomic and transcriptomic profiles of their corresponding primary tumors, validating their use as a patient-relevant model system for solid tumor biology. Integrative analyses reveal that baseline gene expression patterns relate to global ex vivo drug sensitivity, while high-throughput drug-induced transcriptional changes in MSE samples are indicative of drug mode of action and acquired treatment resistance. A case study exemplifies the added value of multi-modal MSE profiling for patients who lack genetically stratified treatment options. In summary, our study provides a functional multi-omics view on a pan-cancer solid tumor cohort and underlines the feasibility and utility of MSE-based precision oncology.
2024-10-04 | PXD052582 | Pride
Project description:Current prostate cancer prognostic models are based on pre-treatment prostate-specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict clinical disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models. We analyzed a Swedish Watchful Waiting cohort (1977â1999) with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer or developed metastases and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. We reasoned that tumor sampling might preclude the identification of the dominant metastatic nodule. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors. Thus the determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses preventing the development of molecular biomarkers for prostate cancer progression. 281 cases from the population-based Swedish-Watchful Waiting cohort. The cohort consists of men with localized prostate cancer (clinical stage T1-T2, Mx, N0); Training set: first 186 samples; Validation cohort: remaining 95 cases from the same population.
2010-05-07 | E-GEOD-16560 | biostudies-arrayexpress