Alternative splicing: the pledge, the turn, and the prestige : The key role of alternative splicing in human biological systems.

Alternative pre-mRNA splicing is a tightly controlled process conducted by the spliceosome, with the assistance of several regulators, resulting in the expression of different transcript isoforms from the same gene and increasing both transcriptome and proteome complexity. The differences between alternative isoforms may be subtle but enough to change the function or localization of the translated proteins. A fine control of the isoform balance is, therefore, needed throughout developmental stages and adult tissues or physiological conditions and it does not come as a surprise that several diseases are caused by its deregulation. In this review, we aim to bring the splicing machinery on stage and raise the curtain on its mechanisms and regulation throughout several systems and tissues of the human body, from neurodevelopment to the interactions with the human microbiome. We discuss, on one hand, the essential role of alternative splicing in assuring tissue function, diversity, and swiftness of response in these systems or tissues, and on the other hand, what goes wrong when its regulatory mechanisms fail. We also focus on the possibilities that splicing modulation therapies open for the future of personalized medicine, along with the leading techniques in this field. The final act of the spliceosome, however, is yet to be fully revealed, as more knowledge is needed regarding the complex regulatory network that coordinates alternative splicing and how its dysfunction leads to disease.

Considerations for the processing and analysis of GoldenGate-based two-colour Illumina platforms.

Illumina's GoldenGate technology is a two-channel microarray platform that allows for the simultaneous interrogation of about 1,500 locations in the genome. GoldenGate has proved a flexible platform not only in the choice of those 1,500 locations, but also in the choice of the property being measured at them. It retains the desirable properties of Illumina's BeadArrays in that the probes (in this case 'beads') are randomly arranged across the microarray, there are multiple instances of each probe and many samples can be processed simultaneously. As for other Illumina technologies, however, these properties are not exploited as they might be. Here we review the various common adaptations of the GoldenGate platform, review the analysis methods that are associated with each adaptation and then, with the aid of a number of example data sets we illustrate some of the improvements that can be made over the default analysis.

Global microRNA profiles in cervical squamous cell carcinoma depend on Drosha expression levels.

Gain of chromosome 5p is seen in over 50% of advanced cervical squamous cell carcinomas (SCCs), although the genes responsible for the selective advantage provided by this abnormality are poorly understood. In the W12 cervical carcinogenesis model, we observed that 5p gain was rapidly selected over approximately 15 population doublings and was associated with the acquisition of a growth advantage and invasiveness. The most significantly upregulated transcript following 5p gain was the microRNA (miRNA) processor Drosha. In clinically progressed cervical SCC, Drosha copy-number gain was seen in 21/36 clinical samples and 8/10 cell lines and there was a significant association between Drosha transcript levels and copy-number gain. Other genes in the miRNA processing pathway, DGCR8, XPO5 and Dicer, showed infrequent copy-number gain and over-expression. Drosha copy-number and expression were not elevated in pre-malignant cervical squamous intraepithelial lesions. Importantly, global miRNA profiling showed that Drosha over-expression in cervical SCC appears to be of functional significance. Unsupervised principal component analysis of a mixed panel of cervical SCC cell lines and clinical specimens showed clear separation according to Drosha over-expression. miRNAs most significantly associated with Drosha over-expression are implicated in carcinogenesis in other tissues, suggesting that they regulate fundamental processes in neoplastic progression. Our evidence suggests that copy-number driven over-expression of Drosha and consequent changes in miRNAs are likely to be important contributors to the selective advantage provided by 5p gain in cervical neoplastic progression.

Using array-comparative genomic hybridization to define molecular portraits of primary breast cancers.

We analysed 148 primary breast cancers using BAC-arrays containing 287 clones representing cancer-related gene/loci to obtain genomic molecular portraits. Gains were detected in 136 tumors (91.9%) and losses in 123 tumors (83.1%). Eight tumors (5.4%) did not have any genomic aberrations in the 281 clones analysed. Common (more than 15% of the samples) gains were observed at 8q11-qtel, 1q21-qtel, 17q11-q12 and 11q13, whereas common losses were observed at 16q12-qtel, 11ptel-p15.5, 1p36-ptel, 17p11.2-p12 and 8ptel-p22. Patients with tumors registering either less than 5% (median value) or less than 11% (third quartile) total copy number changes had a better overall survival (log-rank test: P=0.0417 and P=0.0375, respectively). Unsupervised hierarchical clustering based on copy number changes identified four clusters. Women with tumors from the cluster with amplification of three regions containing known breast oncogenes (11q13, 17q12 and 20q13) had a worse prognosis. The good prognosis group (Nottingham Prognostic Index (NPI)

A gene-expression signature to predict survival in breast cancer across independent data sets.

Prognostic signatures in breast cancer derived from microarray expression profiling have been reported by two independent groups. These signatures, however, have not been validated in external studies, making clinical application problematic. We performed microarray expression profiling of 135 early-stage tumors, from a cohort representative of the demographics of breast cancer. Using a recently proposed semisupervised method, we identified a prognostic signature of 70 genes that significantly correlated with survival (hazard ratio (HR): 5.97, 95% confidence interval: 3.0-11.9, P = 2.7e-07). In multivariate analysis, the signature performed independently of other standard prognostic classifiers such as the Nottingham Prognostic Index and the 'Adjuvant!' software. Using two different prognostic classification schemes and measures, nearest centroid (HR) and risk ordering (D-index), the 70-gene classifier was also found to be prognostic in two independent external data sets. Overall, the 70-gene set was prognostic in our study and the two external studies which collectively include 715 patients. In contrast, we found that the two previously described prognostic gene sets performed less optimally in external validation. Finally, a common prognostic module of 29 genes that associated with survival in both our cohort and the two external data sets was identified. In spite of these results, further studies that profile larger cohorts using a single microarray platform, will be needed before prospective clinical use of molecular classifiers can be contemplated.