Dataset Information

EGAD00000000048

ABSTRACT: Sequencing data from oestrogen-receptor-alpha-positive metastatic lobular breast cancer sample

PROVIDER: EGAD00000000048 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Publications

Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution.

Shah Sohrab P SP Morin Ryan D RD Khattra Jaswinder J Prentice Leah L Pugh Trevor T Burleigh Angela A Delaney Allen A Gelmon Karen K Guliany Ryan R Senz Janine J Steidl Christian C Holt Robert A RA Jones Steven S Sun Mark M Leung Gillian G Moore Richard R Severson Tesa T Taylor Greg A GA Teschendorff Andrew E AE Tse Kane K Turashvili Gulisa G Varhol Richard R Warren René L RL Watson Peter P Zhao Yongjun Y Caldas Carlos C Huntsman David D Hirst Martin M Marra Marco A MA Aparicio Samuel S

Nature 20091001 7265

Recent advances in next generation sequencing have made it possible to precisely characterize all somatic coding mutations that occur during the development and progression of individual cancers. Here we used these approaches to sequence the genomes (>43-fold coverage) and transcriptomes of an oestrogen-receptor-alpha-positive metastatic lobular breast cancer at depth. We found 32 somatic non-synonymous coding mutations present in the metastasis, and measured the frequency of these somatic mutat ...[more]

PMID: 19812674

Publication: 1/2

Similar Datasets

Project description:About one-third of oestrogen receptor alpha- positive breast cancer patients treated with tamoxifen relapse. Here we identify the nuclear receptor retinoic acid receptor alpha as a marker of tamoxifen resistance. Using quantitative mass spectrometry-based proteomics, we show that retinoic acid receptor alpha protein networks and levels differ in a tamoxifen-sensitive (MCF7) and a tamoxifen-resistant (LCC2) cell line. High intratumoural retinoic acid receptor alpha protein levels also correlate with reduced relapse-free survival in oestrogen receptor alpha-positive breast cancer patients treated with adjuvant tamoxifen solely. A similar retinoic acid receptor alpha expression pattern is seen in a comparable independent patient cohort. An oestrogen receptor alpha and retinoic acid receptor alpha ligand screening reveals that tamoxifen-resistant LCC2 cells have increased sensitivity to retinoic acid receptor alpha ligands and are less sensitive to oestrogen receptor alpha ligands compared with MCF7 cells. Our data indicate that retinoic acid receptor alpha may be a novel therapeutic target and a predictive factor for oestrogen receptor alpha-positive breast cancer patients treated with adjuvant tamoxifen. Peptide and protein identification data set 1: Peptide identification from the MALDI-TOF/TOF data was carried out using the Paragon algorithm in the ProteinPilot 2.0 software package (Applied Biosystems) 46. Default settings for a 4800 instrument were used (i.e., no manual settings for mass tolerance was given). The following parameters were selected in the analysis method: iTRAQ 4plex peptide labelled as sample type, MMTS as alkylating agent of cysteine, trypsin as digesting enzyme, 4800 as instrument, gel based ID and Urea denaturation as special factors, biological modifications as ID focus, and thorough ID as search effort. Peptide identification from the Q-TOF data was carried out using the Spectrum Mill Protein Identification software (Agilent). Data was extracted between MH+ 600 and 4000 Da (Agilent's definition). Scans with the same precursor m/z 90 sec, 0.05 m/z matching with a minimum of 20 peaks in MS2 were merged. Peptide and protein identification data set 2: Proteome discoverer 1.3 with sequest-percolator was used for protein identification. Precursor mass tolerance was set to 10 ppm and for fragments 0.8 Da and 0.02 Da were used for detection in the linear iontrap and the orbitrap, respectively. Oxidized methionine and phosphorylation on S,T and Y was set as dynamic modifications, and carbamidomethylation, N-terminal 8plex iTRAQ, and lysyl 8plex iTRAQ as fixed modifications. Spectra were matched to ensembl 68 limited to human protein sequences, and results were filtered to 1% FDR.

Dataset Information

EGAD00000000048

Publications

Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure