Project description:Studies of fusion genes have mainly focused on the formation of fusions that result in the production of hybrid proteins or, alternatively, on promoter-switching events that put a gene under the control of aberrant signals. However, gene fusions may also disrupt the transcriptional control of genes that are encoded in introns downstream of the breakpoint. By ignoring structural constraints of the transcribed fusions, we highlight the importance of a largely unexplored function of fusion genes. Using breast cancer as an example, we show that miRNA host genes are specifically enriched in fusion genes and that many different, low-frequency, 5' partners may deregulate the same miRNA irrespective of the coding potential of the fusion transcript. These results indicate that the concept of recurrence, defined by the rate of functionally important aberrations, needs to be revised to encompass convergent fusions that affect a miRNA independently of transcript structure and protein-coding potential.
Project description:SnowShoes-FTD, a fusion transcript discovery tool, was used to identify fusions in breast cancer cell lines using the RNA-Seq data Total RNA extracted from cell lines. The total RNA was used for construction of RNA-Seq library for RNA-Sequencing.
Project description:To identify novel gene amplification events that may contribute to breast cancer progression, we examined copy number variation in 161 primary breast cancer samples using the Affymetrix 250K_Nsp and 250K_Sty microarrays or the Affymetrix SNP5.0 microarray.
Project description:This study was conducted by using Flag tag to IP proteins expressed with fusion small peptides encoding LncRNA MAGI2-AS3 and identified by high resolution mass spectrometry.
Project description:To identify novel gene amplification events that may contribute to breast cancer progression, we examined copy number variation in 161 primary breast cancer samples using the Affymetrix 250K_Nsp and 250K_Sty microarrays or the Affymetrix SNP5.0 microarray. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from primary breast cancer samples. Copy number variations were determined from probeset signal intensities.
Project description:We characterized the DNA sequences spanning telomere fusion junctions focusing on XpYp:17p inter-chromosomal events in HCT116 LIG3-/-:mL3, HCT116 LIG4-/-, WT HCT116 and MRC5HPVE6E7 cells.
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:MicroRNAs (miRNAs), which are stably present in serum, have been reported to be potentially useful for detecting cancer. In the present study, we examined the expression profiles of serum miRNAs in large cohorts to identify the miRNAs that can be used to detect breast cancer in the early stage. We comprehensively evaluated serum miRNA expression profiles using highly sensitive microarray analysis. A total of 1,280 serum samples of breast cancer patients stored in the National Cancer Center Biobank were used. Additionally, 2,836 serum samples were obtained from non-cancer controls and 514 from patients with other types of cancers or benign diseases. The samples were divided to a training cohort including non-cancer controls, other cancers and breast cancer and a test cohort including non-cancer controls and breast cancer. The training cohort was used to identify a combination of miRNAs that detect breast cancer, and the test cohort was used to validate that combination. miRNA expression was compared between breast cancer and non-breast cancer serum , and a combination of five miRNAs (miR-1246, miR-1307-3p, miR-4634, miR-6861-5p, and miR-6875-5p) was found to detect breast cancer. This combination had a sensitivity of 97.3%, specificity of 82.9%, and accuracy of 89.7% for breast cancer in the test cohort Additionally, the combination could detect breast cancer in the early stage (sensitivity of 98.0% for T0).