Project description:About 15-20% of all breast cancers are triple negative breast cancers, which are often highly aggressive. We performed global quantitative phosphotyrosine profiling of a large panel of triple negative breast cancer cell lines using high resolution Fourier transform mass spectrometry. Our study identified 1,903 tyrosine-phosphorylated peptides derived from 969 proteins. Heterogeneous activation of tyrosine kinases was observed in triple negative breast cancer derived cell lines.
Project description:We propose to definitively characterise the somatic genetics of triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.
Project description:Triple negative breast cancers (TNBC), defined by lacking the expression of oestrogen receptor-alpha (ERa), progesterone receptor, and HER2, is considered to be one of the most aggressive subtypes of all breast cancers. To elucidate the genomic and molecular aberrations in TNBC, we performed whole exon sequencing (WES) analysis on 36 TNBC, and identified 117 genes that significantly mutated (q < 0.05) in TNBC including MUC4, MUC6, TP53, and PIK3CA. Interestingly, genes associated with chromatin regulators including the subunits of SWI/SNF complex were frequently mutated in 44.7% of the cases. Furthermore, from the aspect of the possible association of epigenetic dysregulation and TNBC carcinogenesis, we focused on epigenome and genetic alterations of SALL3, an intrinsic inhibitor of DNMT3A, and identified the role of its dysfunction on cancer cell growth. Our study suggests that epigenetic aberrations caused by somatic alterations including DNA methylation might be a potential pathogenesis of TNBC in a certain number of cases.
Project description:This microarray dataset contains 51 triple-negative breast cancers with clinical and recurrence information for at least 3 years of follow-up and 106 luminal breast cancers (reanalyzed data from Series GSE24124, GSE9309, and GSE17040). A novel set of 45-gene signature that was statistically predictive of distant metastasis recurrence for triple-negative breast cancer was identified in this study.
Project description:Breast cancer is one of the most common cancers in women. Of the different subtypes of breast cancer, the triple negative breast cancer subtype of breast cancer is the most aggressive. A proteomic screen of nucleolar content across breast cancer subtypes found that triple negative breast cancer cell lines have a distinct nucleolar proteome signature in comparison to non-TNBC breast cancer cell lines.
Project description:This microarray dataset contains 51 triple-negative breast cancers, 25 normal breast tissues, and 106 luminal breast cancers (reanalyzed data from Series GSE24124, GSE9309, and GSE17040). Keywords: Expression profiling by array
Project description:Discrepancies in the prognosis of triple negative breast cancer exist between Caucasian and Asian populations. Yet, the gene signature of triple negative breast cancer specifically for Asians has not become available. Therefore, the purpose of this study is to construct a prediction model for recurrence of triple negative breast cancer in Taiwanese patients. Whole genome expression profiling of breast cancers from 185 patients in Taiwan from 1995 to 2008 was performed, and the results were compared to the previously published literature to detect differences between Asian and Western patients. Pathway analysis and Cox proportional hazard models were applied to construct a prediction model for the recurrence of triple negative breast cancer. Most expression data of samples (181/185) were reanalyzed from previous studies already uploaded to GEO (see "reanalysis of" links below). Four additional gene expression profiling data of triple negative breast cancer sample were added to this study.
Project description:Goal of this study was to investigate gene expression profiling across different molecular subtypes of breast cancers, such as Estrogen Receptor (ER) positive, HER2 amplified, Triple negative Basal A, Triple negative Basal B.
