Resultados de investigación

Method to identify genomic regions, both coding and non-coding, bearing mutations with significant shift towards high functional impact across a cohort of tumos (FMbias), which are candidates to function as cancer drivers, through a local test.

Python tab files parsing and validating schema tools.

OncodriveCLUST is a method aimed to identify genes whose mutations are biased towards a large spatial clustering. This method is designed to exploit the feature that mutations in cancer genes, especially oncogenes, often cluster in particular positions of the protein. We consider this as a sign that mutations in these regions change the function of these proteins in a manner that provides an adaptive advantage to cancer cells and consequently are positively selected during clonal evolution of tumours, and this property can thus be used to nominate novel candidate driver genes./nThe method does not assume that the baseline mutation probability is homogeneous across all gene positions but it creates a background model using silent mutations. Coding silent mutations are supposed to be under no positive selection and may reflect the baseline clustering of somatic mutations. Given recent evidences of non-random mutation processes along the genome, the assumption of homogenous mutation probabilities is likely an oversimplication introducing bias in the detection of meaningful events.

OncodriveFM detects candidate cancer driver genes and pathways from catalogs of somatic mutations in a cohort of tumors by computing the bias towards the accumulation of functional mutations (FM bias).This novel approach avoids some known limitations of recurrence-based approaches, such as the dif?culty to estimate background mutation rate, and the fact that they usually fail to identify lowly recurrently mutated driver genes.

Wok is a workflow management system implemented in Python that makes very easy to structure the workflows, parallelize their execution and monitor its progress among other things. It is designed in a modular way allowing to adapt it to different infraestructures./nFor the time being it is strongly focused on clusters implementing any DRMAA compatible resource manager (i.e. Oracle Grid Engine) which working nodes have a shared folder in common. Other, more flexible infrastructures (such as the Amazon EC2) are considered for future implementations.

Machine-learning based approach to classify cancer driver genes into to Activating or Loss of Function roles for cancer gene development.

HDAC7 is a repressor of myeloid genes whose downregulation in pre-B cells is required for transdifferentiation into macrophages.

Oncodrive-CIS is a method aimed to identify those copy number alterations (CNAs) leading to larger in cis expression changes that may be useful in elucidating the role of these aberrations in cancer. This is based on the hypothesis that a gene driving oncogenesis through copy number changes is more prone to bias towards overexpression (or underexpression) as compared to bystanders. The effect of the gene dosage is assessed by observing expression changes not only among tumors but also taking into account normal samples data, when available./nOncodrive-CIS has several potential benefits: first, it did not examine the frequency of the CNAs across samples and therefore the detection of low-recurrent driver alterations was not impaired. Second, amplifications and deletions were evaluated separately to obtain a fair ranking of genes, because the expression change measured in deletions was lower than the one obtained from multi-copy amplifications. Third, the expression of genes in tumor samples was analyzed according to the copy number status but was also compared to normal samples, thus better revealing the gene misregulation role of CNAs in cancer cells. And finally, it should be emphasized that the relationship between expression changes and their functional impact is complex, thus Oncodrive-CIS is proposed as a method to elucidate the role of CNAs in cancer which may be complementary to analyses based on other criteria.

The cyclin-cdk (cyclin-dependent kinase) inhibitor p27(Kip1) (p27) has a crucial negative role on cell cycle progression. In addition to its classical role as a cyclin-cdk inhibitor, it also performs cyclin-cdk-independent functions as the regulation of cytoskeleton rearrangements and cell motility. p27 deficiency has been associated with tumor aggressiveness and poor clinical outcome, although the mechanisms underlying this participation still remain elusive. We report here a new cellular function of p27 as a transcriptional regulator in association with p130/E2F4 complexes that could be relevant for tumorigenesis. We observed that p27 associates with specific promoters of genes involved in important cellular functions as processing and splicing of RNA, mitochondrial organization and respiration, translation and cell cycle. On these promoters p27 co-localizes with p130, E2F4 and co-repressors as histone deacetylases (HDACs) and mSIN3A. p27 co-immunoprecipitates with these proteins and by affinity chromatography, we demonstrated a direct interaction of p27 with p130 and E2F4 through its carboxyl-half. We have also shown that p130 recruits p27 on the promoters, and there p27 is needed for the subsequent recruitment of HDACs and mSIN3A. Expression microarrays and luciferase assays revealed that p27 behaves as transcriptional repressor of these p27-target genes (p27-TGs). Finally, in human tumors, we established a correlation with overexpression of p27-TGs and poor survival. Thus, this new function of p27 as a transcriptional repressor could have a role in the major aggressiveness of tumors with low levels of p27.

This database contains information on the genes identified as drivers in Rubio-Perez and Tamborero et al. (2015). It contains information on driver identification at mutational, CNA and gene fusion level. Additional ancillary information about the role and major clonality of drivers is also included. A table is also provided with the list of datasets used for mutational driver identification.