Mutational landscape of RNA-binding proteins in human cancers

RNA Binding Proteins (RBPs) are a class of post-transcriptional regulatory molecules which are increasingly documented to be dysfunctional in cancer genomes. However, our current understanding of these alterations is limited. Here, we delineate the mutational landscape of ∼1300 RBPs in ∼6000 cancer genomes. Our analysis revealed that RBPs have an average of ∼3 mutations per Mb across 26 cancer types. We identified 281 RBPs to be enriched for mutations (GEMs) in at least one cancer type. GEM RBPs were found to undergo frequent frameshift and inframe deletions as well as missense, nonsense and silent mutations when compared to those that are not enriched for mutations. Functional analysis of these RBPs revealed the enrichment of pathways associated with apoptosis, splicing and translation. Using the OncodriveFM framework, we also identified more than 200 candidate driver RBPs that were found to accumulate functionally impactful mutations in at least one cancer. Expression levels of 15% of these driver RBPs exhibited significant difference, when transcriptome groups with and without deleterious mutations were compared. Functional interaction network of the driver RBPs revealed the enrichment of spliceosomal machinery, suggesting a plausible mechanism for tumorogenesis while network analysis of the protein interactions between RBPs unambiguously revealed the higher degree, betweenness and closeness centrality for driver RBPs compared to non-drivers. Analysis to reveal cancer-specific Ribonucleoprotein (RNP) mutational hotspots showed extensive rewiring even among common drivers between cancer types. Knockdown experiments on pan-cancer drivers such as SF3B1 and PRPF8 in breast cancer cell lines, revealed cancer subtype specific functions like selective stem cell features, indicating a plausible means for RBPs to mediate cancer-specific phenotypes. Hence, this study would form a foundation to uncover the contribution of the mutational spectrum of RBPs in dysregulating the post-transcriptional regulatory networks in different cancer types

Las simulaciones, una alternativa para el estudio de los protocolos P2P

Resumen: La arquitectura y funcionalidad de las redes P2P hacen que sean atractivas para ser utilizadas en ambientes distribuidos locales y aplicaciones de amplia distribución, el análisis de sus protocolos de ruteo bajo diferentes ataques como son los de negación de existencia y de servicio, así como su análisis estadístico, hacen que las simulaciones cobren gran importancia, y sean una alternativa adecuada para su estudio, pues existen varios protocolosde esta categoría como Pastry o Chord, los cuales son de gran importancia dada su amplia utilización en diferentes aplicaciones para el envío y recuperación satisfactoria de información tanto en la nube como en aplicaciones distribuidas, razón por la cual su análisis es importante, este trabajo se centra en Pastry dado que es utilizado en la versión Azure de Microsoft Windows. Palabras clave: Redes P2P, DoS, simulaciones, cómputo en la nube

研究課題

An Excel file containing information on lncRNAs probed for FM bias. The first sheet contains a README file with details on the contents of the other two sheets. The second sheet contains the list of all lncRNAs probed, a summary of their biological function, and the original source from which we extracted them. The third sheet contains the FM bias p value computed for each significantly FM biased lncRNA in each cohort. (ODS 13 kb

Variabilidad genética, diversidad fenotípica e identificación de poblaciones sobresalientes de maíz cacahuacintle

En el año 2001 se hizo un estudio con el objetivo de estimar variabilidad genética, diversidad fenotípica e identificar poblaciones sobresalientes de Cacahuacintle. El material genético, consistente en 34 poblaciones, fue evaluado en un diseño experimental de bloques completos al azar con tres repeticiones por localidad. Los resultados indicaron lo siguiente: 1) Hubo poca variabilidad genética entre Cacahuacintles. 2) Hubo cuatro grupos de variables independientes: a) rendimiento de grano, diámetro de mazorca y alturas de planta y mazorca, b) longitud, peso de olote y de grano por mazorca, c) número de hileras de grano, y d) peso volumétrico del grano. 3) El análisis de conglomerados clasificó a los 34 Cacahuacintles en tres grupos; el grupo 3 estuvo integrado por las poblaciones con rendimientos entre 5.04 y 5.38 t ha-1En el año 2001 se hizo un estudio con el objetivo de estimar variabilidad genética, diversidad fenotípica e identiÀcar poblaciones sobresalientes de Cacahuacintle. El material genético, consistente en 34 poblaciones, fue evaluado en un diseño experimental de bloques completos al azar con tres repeticiones por localidad. Los resultados indicaron lo siguiente: 1) Hubo poca variabilidad genética entre Cacahuacintles. 2) Hubo cuatro grupos de variables independientes: a) rendimiento de grano, diámetro de mazorca y alturas de planta y mazorca, b) longitud, peso de olote y de grano por mazorca, c) número de hileras de grano, y d) peso volumétrico del grano. 3) El análisis de conglomerados clasiÀcó a los 34 Cacahuacintles en tres grupos; el grupo 3 estuvo integrado por las poblaciones con rendimientos entre 5.04 y 5.38 t ha-1

A compendium of mutational cancer driver genes

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer

Divergent mutational processes distinguish hypoxic and normoxic tumours

Many primary tumours have low levels of molecular oxygen (hypoxia), and hypoxic tumours respond poorly to therapy. Pan-cancer molecular hallmarks of tumour hypoxia remain poorly understood, with limited comprehension of its associations with specific mutational processes, non-coding driver genes and evolutionary features. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we quantify hypoxia in 1188 tumours spanning 27 cancer types. Elevated hypoxia associates with increased mutational load across cancer types, irrespective of underlying mutational class. The proportion of mutations attributed to several mutational signatures of unknown aetiology directly associates with the level of hypoxia, suggesting underlying mutational processes for these signatures. At the gene level, driver mutations in TP53, MYC and PTEN are enriched in hypoxic tumours, and mutations in PTEN interact with hypoxia to direct tumour evolutionary trajectories. Overall, hypoxia plays a critical role in shaping the genomic and evolutionary landscapes of cancer

Integrative pathway enrichment analysis of multivariate omics data

Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations

High p16 expression and heterozygous RB1 loss are biomarkers for CDK4/6 inhibitor resistance in ER+ breast cancer

Breast cancer; Cancer models; Predictive markersCáncer de mama; Modelos de cáncer; Marcadores predictivosCàncer de pulmó; Models de càncer; Marcadors predictiusCDK4/6 inhibitors combined with endocrine therapy have demonstrated higher antitumor activity than endocrine therapy alone for the treatment of advanced estrogen receptor-positive breast cancer. Some of these tumors are de novo resistant to CDK4/6 inhibitors and others develop acquired resistance. Here, we show that p16 overexpression is associated with reduced antitumor activity of CDK4/6 inhibitors in patient-derived xenografts (n = 37) and estrogen receptor-positive breast cancer cell lines, as well as reduced response of early and advanced breast cancer patients to CDK4/6 inhibitors (n = 89). We also identified heterozygous RB1 loss as biomarker of acquired resistance and poor clinical outcome. Combination of the CDK4/6 inhibitor ribociclib with the PI3K inhibitor alpelisib showed antitumor activity in estrogen receptor-positive non-basal-like breast cancer patient-derived xenografts, independently of PIK3CA, ESR1 or RB1 mutation, also in drug de-escalation experiments or omitting endocrine therapy. Our results offer insights into predicting primary/acquired resistance to CDK4/6 inhibitors and post-progression therapeutic strategies

Beyond the standard seesaw: neutrino masses from Kahler operators and broken supersymmetry

We investigate supersymmetric scenarios in which neutrino masses are generated by effective d=6 operators in the Kahler potential, rather than by the standard d=5 superpotential operator. First, we discuss some general features of such effective operators, also including SUSY-breaking insertions, and compute the relevant renormalization group equations. Contributions to neutrino masses arise at low energy both at the tree level and through finite threshold corrections. In the second part we present simple explicit realizations in which those Kahler operators arise by integrating out heavy SU(2)_W triplets, as in the type II seesaw. Distinct scenarios emerge, depending on the mechanism and the scale of SUSY-breaking mediation. In particular, we propose an appealing and economical picture in which the heavy seesaw mediators are also messengers of SUSY breaking. In this case, strong correlations exist among neutrino parameters, sparticle and Higgs masses, as well as lepton flavour violating processes. Hence, this scenario can be tested at high-energy colliders, such as the LHC, and at lower energy experiments that measure neutrino parameters or search for rare lepton decays.Comment: LaTeX, 34 pages; some corrections in Section