Project description:In order to develop novel biomarkers in breast cancer, we applied a competing endogenous RNA (ceRNA) microarray to identify differentially expressed lncRNAs in BC tissue.
Project description:To screen promising serum-based lncRNA biomarkers for different molecular subtype of breast cancer,we uesed a genome-wide lncRNA microarray to identify differentially expressed lncRNAs from serum samples of patients with four different molecular subtype of BC and healthy controls.
Project description:To identify biologically and clinically novel lncRNAs potentially involved in the progression of breast cancer, we profiled the expression of lncRNAs in two stage III triple-negativebreast cancer tissues and their paired adjacent noncancerous tissues by LncRNA Array 3.0 (ArrayStar). Expression of the mostly upregulated lncRNA (BCAR4) from this signature was quantified in the breast caner tissue microarray by RNA In situ Hybridization and bioinformatic analysis of Oncomine database, confirming its correlation with breast cancer metastasis.
Project description:Breast cancer (BC) recovery has considerably increased thanks to the advances achieved from research in this field. However, despite the important results obtained, BC remains a complex multifactorial disease with distinct subtypes associated with different outcomes.So, many efforts from radiobiological research are needed to help clinicians in understanding molecular features of a specific tumor subtype, in order to better define the most successful treatment plan, including the choice of the best Radiation Teraphy (RT) modality and schedule in clinical practice. The aim of the present study was to analyze the GEPs in primary breast cancer cells following irradiation with doses of 9 Gy and 23 Gy electron beam delivered by IOERT treatment, in order to define gene signatures of response to high doses of IR.
Project description:To identify lncRNAs dysregulated in BC, we assessed the lncRNA expression profile in pooled urine samples of 10 BC patients and 10 controls by microarray. A total of 3093 lncRNAs determined differential expression (fold change>=2.0) between BC patients and controls. Among them, 1680 lncRNAs were up-regulated and 1413 lncRNAs were down-regulated in BC. Of all the differentially expressed lncRNAs indicated by lncRNA expression profiling, 26 lncRNAs (fold change>25) were firstly selected for further evaluation, in which 16 lncRNAs were up-regulated and 10 lncRNAs were down-regulated in BC.
Project description:Breast carcinoma (BC) is the leading cause of death in women worldwide, making up 23% of all cancers in women, with 1.38 million new cases worldwide annually and responsible for 460,000 deaths. Despite the significant advances in the identification of molecular markers and different modalities of treatment in primary BC, the ability to predict the metastatic behavior in breast cancer is still limited. The purpose of this study was to help identify novel molecular markers associated with clinical outcome in a cohort of Brazilian BC patients. We generated global gene expression profiles from 24 patients with invasive ductal BC followed for ⥠5-years, including 15 samples from patients classified as presenting good prognosis based on traditional markers and clinical criteria and 9 patients that developed metastasis. We identified a set of 58 differentially expressed genes (p â¤0.01) between groups of patients with good and poor prognosis. Up-regulation of B3GNT7, PPM1D, TNKS2, PHB and GTSE1 in patients with poor prognosis was confirmed by quantitative RT-PCR in an independent sample set from patients with BC (47 with good prognosis and 8 that presented metastasis). Expression of BAD protein was investigated by immunohistochemistry in 1276 BC samples and confirmed the reduced expression levels in metastatic cases observed in the oligoarray data. These findings point to novel prognostic markers that can distinguish breast carcinoma samples according to clinical course and progression of the disease. Global expression profiles from 38 ductal breast tumor patient samples were used to search for molecular signatures correlated with current prognostic markers. A subset of 24 cases comprising 15 patients that remained free of disease after surgery and 9 patients that developed metastasis was used to identify candidate biomarkers associated with metastatic progression. Candidates were subsequently validated in additional independent samples by RT-qPCR or immunohistochemistry.