This DAC controls 240 datasets:

Dataset Accessionsort descending Technology Samples Description
EGAD00001000145 Illumina HiSeq 2000, Illumina HiSeq 2000; 58 Matched Pair Cancer Cell line Whole Genomes
EGAD00001000149 Illumina HiSeq 2000 2 A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome
EGAD00001000154 Illumina HiSeq 2000, Illumina Genome Analyzer II 12 Single-cell genome sequencing reveals DNA-mutation per cell cycle
EGAD00001000175 Illumina Genome Analyzer II; 48 Identification of SPEN as a novel cancer gene and FGFR2 as a potential therapeutic target in adenoid cystic carcinoma
EGAD00001000205 Illumina HiSeq 2000; 3 BRAF and MEK resistant cell line clones
EGAD00001000226 Illumina Genome Analyzer II;, Illumina HiSeq 2000; 18 Chordoma is a rare malignant bone tumor that expresses the transcription factor T. We conducted an association study of 40 patients with chordoma and 358 ancestry-matched, unaffected individuals with replication in an independent cohort. Whole-exome and Sanger sequencing of T exons reveals a strong risk association ( allelic odds ratio (OR) = 4.9, P = 3.3x10-11, CI= 2.9-8.1) with the common (minor allelic frequency >5%) non-synonymous SNP rs2305089 in chordoma, which is exceptional in cancer genetics.
EGAD00001000243 Illumina HiSeq 2000; 43 Melanoma-TIL Study Exomes
EGAD00001000245 Illumina HiSeq 2000; 20 Pulldown cytosine deaminases
EGAD00001000246 Illumina HiSeq 2000; 106 Integrative Oncogenomics of multiple myeloma
EGAD00001000247 Illumina HiSeq 2000; 51 Integrative Oncogenomics of multiple myeloma
EGAD00001000248 Illumina HiSeq 2000; 6 RNAseq Pulldown
EGAD00001000252 Illumina HiSeq 2000; 12 Evaluation of PCR library method on whole genome samples
EGAD00001000253 Illumina HiSeq 2000; 1972 AML targeted resequencing study
EGAD00001000255 Illumina HiSeq 2000; 32 Testing the feasibility of genome scale sequencing in routinely collected FFPE cancer specimens versus matched fresh frozen samples
EGAD00001000264 Illumina HiSeq 2000; 29 Resistance towards chemotherapy is one of the main causes of treatment failure and death among breast cancer patients.The main objective of this project is to identify genetic mechanisms causing some breast cancer patients not to respond to a particluar type of chemotherapy (epirubicin) while other patients respond very well to the same treatment. In the project we will perform genome / exome sequencing of a selection of breast cancer patients (n=30). These patients are drawn from a cohort where all patients have recieved treatment with epirubicin monotherapy before surgical removal of a locally advanced breast tumour, and where all patients have been subjected to objective evaluation of the response to the therapy. Subsequent to sequencing, we will analyse the data and compare with the clinical data for each patient (object response to therapy). The main aim being to identify mutations that are associated with resistance to epirubicin. Identification of mutations with strong predictive value, may have a direct impact on cancer treatment since it opens the possibility for genetic testing of a tumour, and desicion on which drug is likely to work best, prior to treatment start.