Prognostic factors in prostate cancer deep sequencing pilot project TAPG
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ABSTRACT:
PROVIDER: EGAS00001000879 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:This is a pilot project to determine whether the TAPG FFPE DNA's are suitable for deep sequencing. If successful an investigation of SNP distribution in a larger cohort will follow.
| EGAD00001001237 | EGA
Project description:Objectives: Despite recent advancements in diagnostic tools, the genomic landscape of hereditary hearing loss remains largely uncharacterized. One strategy to understand genome-wide aberrations includes the analysis of copy number variation that can be mapped using SNP-microarray technology. A growing collection of literature has begun to uncover the importance of copy number variation in hereditary hearing loss. This pilot study underpins a larger effort that involves the stage-wise analysis of hearing loss patients, many of whom have advanced to high-throughput sequencing analysis. Data description: Our data originate from Infinium HumanOmni1-Quad v1.0 SNP-microarrays (Illumina) that provide useful markers for genome-wide association studies and copy number variation analysis. This dataset comprises a cohort of 108 individuals (99 with hearing loss, 9 normal hearing family members) for the purpose of understanding the genetic contribution of copy number variations to hereditary hearing loss.
2018-03-06 | GSE111131 | GEO
Project description:Mycobacterium tuberculosis pilot
| PRJEB2221 | ENA
Project description:Introduction: The aim of this pilot study is to establish a radiogenomic characterisation of a clear-cell renal cell carcinoma (ccRCC) subpopulation, focusing on the transcriptomic underpinnings of radiomic features. Materials & Methods: To establish the viability of conducting a combined analysis of both radiomic and genomic data, a pilot cohort of 6 patients with <5cm G2 unilateral non-metastatic T1a-b ccRCC, who underwent surgery, was evaluated. Transcriptomic analysis was conducted through RNA-seq on tumor samples, while radiomic data was extracted from pre-operative 4 phase contrast-enhanced multidetector CT scans. Genomic heterogeneity was assessed with principal component analysis run on unrestricted data, on a clear-cell renal cell carcinoma associated gene list with zero-centered Reads Per Kilobase of transcript, per million mapped reads values. The underlying pathways and gene ontologies were established with enrichment analysis. In addition, Pearson’s correlation between radiomic data and the transcription of significant genes was fitted, and dendrogram and heatmap plots were drawn. Results: Even in a clinically homogeneous population, the employed analyses have demonstrated that RCC should be regarded as an intrinsically heterogeneous disease. The analysis of the radiomic features and gene expression correlation using heatmap and dendrogram showed four distinct radiogenomic correlation patterns: with one including 5 radiomic features, and the other three including 2 features each. Conclusion: The current pilot study is the first investigation demonstrating an innovative radiogenomic characterisation of clear-cell RCC. Based on such observations, further investigation into the radiomic and genomic approaches for the enhanced diagnosis of RCC is warranted.
2019-06-28 | GSE133460 | GEO
Project description:We performed a pilot proteogenomic study to compare lung adenocarcinoma to lung squamous cell carcinoma using quantitative proteomics (6-plex TMT) combined with a customized Affymetrix GeneChip. Using MaxQuant software, we identified 51,001 unique peptides that mapped to 7,241 unique proteins and from these identified 6,373 genes with matching protein expression for further analysis. We found a minor correlation between gene expression and protein expression; both datasets were able to independently recapitulate known differences between the adenocarcinoma and squamous cell carcinoma subtypes. We found 565 proteins and 629 genes to be differentially expressed between adenocarcinoma and squamous cell carcinoma, with 113 of these consistently differentially expressed at both the gene and protein levels. We then compared our results to published adenocarcinoma versus squamous cell carcinoma proteomic data that we also processed with MaxQuant. We selected two proteins consistently overexpressed in squamous cell carcinoma in all studies, MCT1 (SLC16A1) and GLUT1 (SLC2A1), for further investigation. We found differential expression of these same proteins at the gene level in our study as well as in other public gene expression datasets. These findings combined with survival analysis of public datasets suggest that MCT1 and GLUT1 may be potential prognostic markers in adenocarcinoma and druggable targets in squamous cell carcinoma.
2015-11-06 | PXD002622 | Pride
Project description:Pilot RNA-seq dataset created by the Geuvadis consortium (www.geuvadis.org)
2010-04-14 | E-GEUV-4 | biostudies-arrayexpress