Project description:Brain metastasis is a major distant metastasis occurring in patients with advanced breast cancer, and is associated with poor prognosis. MicroRNAs (miRNAs) have a strong influence on various oncological functions and have been reported as potential biomarkers for detecting distant metastasis. Specific biomarkers and unique miRNAs for brain metastasis have yet to be reported. The aim of this study was to identify novel miRNAs in serum, to assist in the diagnosis of brain metastasis in patients with advanced breast cancer. We retrospectively analyzed the medical records of patients with breast cancer and collected clinical data. In addition, we evaluated serum miRNA profiles in patients with breast cancer, with and without brain metastasis, using high-sensitivity microarrays. All patients underwent computed tomography or magnetic resonance imaging brain imaging tests. A total of 51 serum samples from patients with breast cancer and brain metastasis, stored in the National Cancer Center Biobank, were used, and 28 serum samples were obtained from controls without brain metastasis. Two miRNAs, miR-4428 and miR-4480, could significantly distinguish patients with brain metastasis, with area under the receiver operating characteristic curve (AUC) values of 0.779 and 0.781, respectively, while a combination of miR-4428 and progesterone receptor had an AUC value of 0.884. No significant correlations were identified between the expression levels of these two miRNAs in serum and clinical data. We conclude that serum miR-4428 and miR-4480 may be useful as biomarkers for predicting brain metastasis in patients with breast cancer.
Project description:MicroRNAs play a crucial role in tumorigenesis. However, the value of microRNAs in the diagnosis and treatment of tongue squamous cell carcinoma (TSCC) still await investigations. To identify the microRNAs associated with the metastasis of TSCC, we analyzed the transcriptomic difference between metastatic and the non-metastatic TSCC tissue. We identified a set of metastasis-related microRNAs with potential prognostic value.
Project description:Understanding the molecular mechanisms and gene expression in laryngeal squamous cell carcinoma (LSCC) may explain its aggressive biological behavior and regional metastasis pathways. Better understanding of the molecular mechanisms underlying LSCC metastasis and the search for possible molecular targets seems promising. Interpreting the links between the differentially expressed genes in advanced stages can lead to a search for predictive markers that can also help determine the possible treatment routes. We designed this study to detect possible genetic alterations in a homogeneous group of patients with locoregionally advanced laryngeal cancer who underwent total laryngectomy and neck dissection. Patients with and without lymph node metastasis were selected to examine the differential gene expression in the normal mucosa, tumor, and lymph node tissues of each patient. Our main purpose was to identify the possible commonly expressed genes in this homogenous group of Turkish patients with locoregionally advanced laryngeal cancer. Second, we aimed to determine the predictive role of these genes in lymph node metastasis and overall prognosis.
Project description:MicroRNAs (miRNAs) have been recently detected in the circulation of cancer patients, where they are associated with clinical parameters. Discovery profiling of circulating small RNAs has not been previously reported in breast cancer (BC), and was carried out in this study to identify blood-based small RNA markers of BC clinical outcome. The pre-treatment sera of 42 stage II–III locally advanced and inflammatory BC patients who received neoadjuvant chemotherapy (NCT) followed by surgical tumor resection were analyzed for marker identification by deep sequencing all circulating small RNAs.
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:To identify lung metastasis associated microRNAs in triple negative breast cancer (TNBC), we have employed the commercially available Agilent Human miRNA V19.0 Microarray (Platform GPL19730) as a discovery platform. In comparison with LM-Normal, 11 microRNAs significantly altered in both LM-Met and LM-Tumor, and then three of them (hsa-miR-21-3p, hsa-miR-21-5p and hsa-miR-211-3p) were excluded, which were also up-regulated in RF-Tumor. Consequently, eight deregulated microRNAs were identified to be putatively involved in process of lung metastasis, especially miR-629-3p, which was most up-regulated in both LM-Met and LM-Tumor. To validate the microarray data, we utilized qRT-PCR to assess expression levels of the eight miRNAs in the same samples.
Project description:Microarray analysis of 28 brain metastasis samples from lung adenocarcinoma patients. 28 brain metastasis samples: 19 from Marc Ladanyi 9 from William L. Gerald
Project description:The central nervous system (CNS) is a common site of metastatic disease in patients with breast cancer and has few therapeutic options with dismal outcomes. The purpose of our study was to identify common and rare events that underlie breast cancer CNS metastasis. We performed deep genomic profiling, which integrated gene copy number, gene expression and DNA methylation datasets on a collection of breast brain metastases. We identified frequent large chromosomal gains in 1q, 5p, 8q, 11q, and 20q and frequent broad level deletions involving 8p, 17p, 21p and Xq. Frequently amplified and overexpressed genes included ATAD2, BRAF, DERL1, DNMTRB and NEK2A. The ATM, CRYAB and HSPB2 genes were commonly deleted and underexpressed. Knowledge mining revealed enrichment in cell cycle and G2/M transition pathways, which contained AURKA, AURKB and FOXM1. Using the PAM50 breast cancer intrinsic classifier, Luminal B, Her2+/ER negative, and basal-like tumors were identified as the most commonly represented breast cancer subtypes in our CNS metastasis cohort. While overall methylation levels were increased in breast cancer CNS metastasis, basal-like CNS metastases were associated with significantly lower levels of methylation. Integrating DNA methylation data with gene expression revealed defects in cell migration and adhesion due to hypermethylation and downregulation of PENK, EDN3, and ITGAM. Hypomethylation and upregulation of KRT8 likely affects adhesion and permeability. Genomic and epigenomic profiling of breast CNS metastasis has provided insight into the somatic events underlying this disease, which have potential in forming the basis of future therapeutic strategies. Three sample-types: 35 Breast Brain Metastasis samples, 10 Non-Neoplastic Brain samples, and 10 Non-Neoplastic Breast samples.