Project description:microRNA expression signatures can differentiate normal and breast cancer tissues and can define specific clinico-pathological phenotypes in breast tumors. In order to further evaluate the microRNA expression profile in breast cancer, we analyzed the expression of 667 microRNAs in 29 tumors and 21 adjacent normal tissues using TaqMan Low-density arrays. 130 miRNAs showed significant differential expression (adjusted P value=0.05, Fold Change=2) in breast tumors compared to the normal adjacent tissue. Importantly, the role of 43 of these microRNAs has not been previously reported in breast cancer, including several evolutionary conserved microRNA*, showing similar expression rates to that of their corresponding leading strand.
Project description:Breast Cancer is the cancer with most incidence and mortality in women. microRNAs are emerging as novel prognosis/diagnostic tools. Our aim was to identify a serum microRNA signature useful to predict cancer development. We focused on studying the expression levels of 30 microRNAs in the serum of 96 breast cancer patients versus 92 control individuals. Bioinformatic studies provide a microRNA signature, designated as a predictor, based upon the expression levels of 5 microRNAs. Then, we tested the predictor in a group of 60 randomly chosen women. Lastly, a proteomic study unveiled the over-expression and down-regulation of proteins differently expressed in the serum of breast cancer patients versus that of control individuals. Twenty-six microRNAs differentiate cancer tissue from healthy tissue and 16 microRNAs differentiate the serum of cancer patients from that of the control group. The tissue expression of miR-99a-5p, mir-497-5p, miR-362, and miR-1274, and the serum levels of miR-141 correlated with patient survival. Moreover, the predictor consisting of mir-125b-5p, miR-29c-3p, mir-16-5p, miR-1260, and miR-451a was able to differentiate breast cancer patients from controls. The predictor was validated in 20 new cases of breast cancer patients and tested in 60 volunteer women, assigning 11 out of 60 women to the cancer group. An association of low levels of mir-16-5p with a high content of CD44 protein in serum was found. Circulating microRNAs in serum can represent biomarkers for cancer prediction. Their clinical relevance and use of the predictor here described might be of potential importance for breast cancer prediction.
Project description:The purpose of this study was to understand the genomic and metabolomic changes in the breast tissue microenvironment at various stages of cancer development and progression (i.e. normal breast, DCIS, benign disease and invasive cancer). To understand the way in which metabolic microenvironments evolve with breast cancer, this study analyzed normal breast tissue adjacent to benign and malignant lesions at various stages of cancer development and studied samples adjacent to invasive cancers of distinct breast cancer subtypes.
Project description:microRNA expression signatures can differentiate normal and breast cancer tissues and can define specific clinico-pathological phenotypes in breast tumors. In order to further evaluate the microRNA expression profile in breast cancer, we analyzed the expression of 667 microRNAs in 29 tumors and 21 adjacent normal tissues using TaqMan Low-density arrays. 130 miRNAs showed significant differential expression (adjusted P value=0.05, Fold Change=2) in breast tumors compared to the normal adjacent tissue. Importantly, the role of 43 of these microRNAs has not been previously reported in breast cancer, including several evolutionary conserved microRNA*, showing similar expression rates to that of their corresponding leading strand. The procedure begins with the retro-transcription of 70ng of total RNA with stem-loop primers to obtain a cDNA template. A pre-amplification step was included in order to increase the concentration of the original material and to detect microRNAs that are expressed at low levels. The pre-amplified product was loaded into the TaqManM-BM-. Low Density Arrays and amplification signal detection was carried out using the 7900 FAST real time thermal cycler (ABI). A total of 29 tumor and 21 normal samples (two pools: one containing five samples, other containing 12 samples, plus 4 independent normal samples) were analyzed. 23 tumors and the two normal pools were processed by triplicate, representing 82% of the total samples.
Project description:Proteomics analysis of matched tumor and normal adjacent tumor regions of 40 patients with multiparametric magnetic resonance imaging (mpMRI) visible or invisible tumors. All patients have clinically significant intermediate-risk (pathological ISUP Grade Group 2), localized prostate cancer.
Project description:The aim of our study was to identify a microRNA signature for metastatic CRC that could predict and differentiate metastatic target organ localization. Normal and cancer tissues of three different groups of CRC patients were analyzed. RNA microarray and TaqMan Array analysis were performed on 66 italian patients with or without lymph nodes and/or liver recurrences. Data obtained with the two assays, were analyzed separately and then intersected to identify a primary CRC metastatic signature. Five differentially expressed microRNAs (hsa-miR-21, -103, -93, -31 and -566) were validated by qRT-PCR on a second group of 16 american metastatic patients. In situ hybridization was performed on the 16 american patients as well as on three distinct commercial tissues microarray (TMA), containing normal adjacent colon, the primary adenocarcinoma, normal and metastatic lymph nodes and liver. Hsa-microRNA-31,-21,-93, and-103 upregulation together with hsa-miR-566 downregulation defined the CRC metastatic signature, while in situ hybridization data identified a lymphonodal invasion profile.