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:Molecular subtyping plays a vital role in the treatment of breast cancer, however, current clinical outcomes remain unsatisfactory despite having multiple molecular subtypes available, particularly for triple-negative breast cancers. Henceforth, our research primarily focuses on traditional molecular subtyping by utilizing transcriptome sequencing and ATAC-seq sequencing techniques to classify both tumor tissues and adjacent tissues from patients with breasts cancers into distinct groups. Through this process, we aim to identify key gene expressions involved in the development of breasts cancers as well as epigenetic characteristics influenced by alterations in chromatin accessibility patterns. Subsequently, employing conventional methods used for classifying breasts cancers into different molecular types enables us to further investigate significant variations observed specifically within triple-negative breasts cancers regarding their gene expression profiles and chromatin accessibility patterns. Lastly, utilizing data from TCGA database pertaining exclusively to cases involving triple-negative breasts cancers allows us to conduct regression analyses concerning our aforementioned findings while simultaneously selecting relevant molecular models closely associated with this particular subtype of breasts malignancy. Additionally evaluating how these differentially expressed genes influence prognosis through prognostic modeling analysis tailored towards predicting outcomes solely within cases involving individuals diagnosed with triple negative-breast malignancies will enable us ultimately construct an innovative model incorporating both gene expressions along with chromatin accessibility patterns as distinguishing features providing more substantial guidance towards improving clinical treatments targeting individuals afflicted by such conditions.
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: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.
