Project description:We select 3 pairs of tissue samples, including 3 breast tissues and 3 adjacent tissues, and then perform miRNA chip detection to find differential miRNAs. We used microarrays to identify differential expressed miRNAs in breast cancer and paired normal breast tissue
Project description:Circulating transcriptional landscapes between breast cancer tissues and adjacent normal tissues were compared using the Affymetrix Human OE LncRNA Microarray with probes for profiling of 63542 human lncRNAs. Goal was to investigate potential lncRNAs involved in breast cancer progression.
Project description:To discriminate miRNA expression differences between adjacent normal and tumor tissues of breast cancer. 101 breast tumor + 15 adjacent breast normal tissue samples.
Project description:To identify aberrantly expressed long intergenic noncoding RNAs (lincRNAs) in muscle-invasive bladder cancer tissues compared with normal adjacent tissues, we have employed microarray expression profiling as a discovery platform to identify lincRNAs that may play important roles in bladder cancer progression. Samples of fresh frozen cancer tissues, together with normal adjacent tissues (3 cm away from the tumor), were obtained during surgical resection, and total RNA was extracted for microarray analysis.
Project description:To identify aberrantly expressed long intergenic noncoding RNAs (lincRNAs) in bladder cancer tissues compared with normal adjacent tissues, we have employed microarray expression profiling as a discovery platform to identify lincRNAs that may play important roles in bladder cancer origin and progression. Samples of fresh frozen cancer tissues, together with normal adjacent tissues (3 cm away from the tumor), were obtained during surgical resection, and total RNA was extracted for microarray analysis.
Project description:Penile cancer is a rare disease that has high morbidity and mortality rates. While a few biomarkers related to prognosis have been previously described to date, none of them was adopted in clinical practice. We used microarrays to identify miRNA-based molecular signatures to identify penile carcinoma regions from paired normal-adjacent tissues. We also used microarray information to distinguish patients with a high risk of metastatic penile carcinoma.