Transcriptome sequencing and microarray development for the Manila clam, Ruditapes philippinarum: genomic tools for environmental monitoring

Abstract Background The Manila clam, Ruditapes philippinarum, is one of the major aquaculture species in the world and a potential sentinel organism for monitoring the status of marine ecosystems. However, genomic resources for R. philippinarum are still extremely limited. Global analysis of gene expression profiles is increasingly used to evaluate the biological effects of various environmental stressors on aquatic animals under either artificial conditions or in the wild. Here, we report on the development of a transcriptomic platform for global gene expression profiling in the Manila clam. Results A normalized cDNA library representing a mixture of adult tissues was sequenced using a ultra high-throughput sequencing technology (Roche 454). A database consisting of 32,606 unique transcripts was constructed, 9,747 (30%) of which could be annotated by similarity. An oligo-DNA microarray platform was designed and applied to profile gene expression of digestive gland and gills. Functional annotation of differentially expressed genes between different tissues was performed by enrichment analysis. Expression of Natural Antisense Transcripts (NAT) analysis was also performed and bi-directional transcription appears a common phenomenon in the R. philippinarum transcriptome. A preliminary study on clam samples collected in a highly polluted area of the Venice Lagoon demonstrated the applicability of genomic tools to environmental monitoring. Conclusions The transcriptomic platform developed for the Manila clam confirmed the high level of reproducibility of current microarray technology. Next-generation sequencing provided a good representation of the clam transcriptome. Despite the known limitations in transcript annotation and sequence coverage for non model species, sufficient information was obtained to identify a large set of genes potentially involved in cellular response to environmental stress.This work was partially supported by a grant from European Union-funded Network of Excellence "Marine Genomics Europe". CS wishes to acknowledge additional funding from the Ministry of Education and Science (Spain) through grant AGL2007-60049. MM had a PhD scholarship from the University of Florence, Italy. RL was recipient of PhD fellowship SFRH/BD/30112/2006, from the Portuguese Science and Technology Foundation (FCT) and LC and RL acknowledge a grant from FCT project ISOPERK (PTDC/CVT/72083/2006).Peer Reviewe

Identification of a Kinase Profile that Predicts Chromosome Damage Induced by Small Molecule Kinase Inhibitors

Kinases are heavily pursued pharmaceutical targets because of their mechanistic role in many diseases. Small molecule kinase inhibitors (SMKIs) are a compound class that includes marketed drugs and compounds in various stages of drug development. While effective, many SMKIs have been associated with toxicity including chromosomal damage. Screening for kinase-mediated toxicity as early as possible is crucial, as is a better understanding of how off-target kinase inhibition may give rise to chromosomal damage. To that end, we employed a competitive binding assay and an analytical method to predict the toxicity of SMKIs. Specifically, we developed a model based on the binding affinity of SMKIs to a panel of kinases to predict whether a compound tests positive for chromosome damage. As training data, we used the binding affinity of 113 SMKIs against a representative subset of all kinases (290 kinases), yielding a 113×290 data matrix. Additionally, these 113 SMKIs were tested for genotoxicity in an in vitro micronucleus test (MNT). Among a variety of models from our analytical toolbox, we selected using cross-validation a combination of feature selection and pattern recognition techniques: Kolmogorov-Smirnov/T-test hybrid as a univariate filter, followed by Random Forests for feature selection and Support Vector Machines (SVM) for pattern recognition. Feature selection identified 21 kinases predictive of MNT. Using the corresponding binding affinities, the SVM could accurately predict MNT results with 85% accuracy (68% sensitivity, 91% specificity). This indicates that kinase inhibition profiles are predictive of SMKI genotoxicity. While in vitro testing is required for regulatory review, our analysis identified a fast and cost-efficient method for screening out compounds earlier in drug development. Equally important, by identifying a panel of kinases predictive of genotoxicity, we provide medicinal chemists a set of kinases to avoid when designing compounds, thereby providing a basis for rational drug design away from genotoxicity

Copy number signatures and mutational processes in ovarian carcinoma.

The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.NIHR, Ovarian Cancer Action, Cancer Research UK Cambridge Centre, Cambridge Experimental Cancer Medicine Centr

Centrosome – a promising anti-cancer target

Yainyrette Rivera-Rivera, Harold I Saavedra Department of Pharmacology, Ponce Health Sciences University-School of Medicine, Ponce Research Institute, Ponce, Puerto Rico Abstract: The centrosome, an organelle discovered >100 years ago, is the main microtubule-organizing center in mammalian organisms. The centrosome is composed of a pair of centrioles surrounded by the pericentriolar material (PMC) and plays a major role in the regulation of cell cycle transitions (G1-S, G2-M, and metaphase-anaphase), ensuring the normality of cell division. Hundreds of proteins found in the centrosome exert a variety of roles, including microtubule dynamics, nucleation, and kinetochore–microtubule attachments that allow correct chromosome alignment and segregation. Errors in these processes lead to structural (shape, size, number, position, and composition), functional (abnormal microtubule nucleation and disorganized spindles), and numerical (centrosome amplification [CA]) centrosome aberrations causing aneuploidy and genomic instability. Compelling data demonstrate that centrosomes are implicated in cancer, because there are important oncogenic and tumor suppressor proteins that are localized in this organelle and drive centrosome aberrations. Centrosome defects have been found in pre-neoplasias and tumors from breast, ovaries, prostate, head and neck, lung, liver, and bladder among many others. Several drugs/compounds against centrosomal proteins have shown promising results. Other drugs have higher toxicity with modest or no benefits, and there are more recently developed agents being tested in clinical trials. All of this emerging evidence suggests that targeting centrosome aberrations may be a future avenue for therapeutic intervention in cancer research. Keywords: centrosomes, cell cycle, mitosis, CA, CIN, cancer therap