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      HotSpotAnnotations—a database for hotspot mutations and annotations in cancer

      research-article
      Database: The Journal of Biological Databases and Curation
      Oxford University Press

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          Abstract

          Hotspots, recurrently mutated DNA positions in cancer, are thought to be oncogenic drivers because random chance is unlikely and the knowledge of clear examples of oncogenic hotspots in genes like BRAF, IDH1, KRAS and NRAS among many other genes. Hotspots are attractive because provide opportunities for biomedical research and novel treatments. Nevertheless, recent evidence, such as DNA hairpins for APOBEC3A, suggests that a considerable fraction of hotspots seem to be passengers rather than drivers. To document hotspots, the database HotSpotsAnnotations is proposed. For this, a statistical model was implemented to detect putative hotspots, which was applied to TCGA cancer datasets covering 33 cancer types, 10 182 patients and 3 175 929 mutations. Then, genes and hotspots were annotated by two published methods (APOBEC3A hairpins and dN/dS ratio) that may inform and warn researchers about possible false functional hotspots. Moreover, manual annotation from users can be added and shared. From the 23 198 detected as possible hotspots, 4435 were selected after false discovery rate correction and minimum mutation count. From these, 305 were annotated as likely for APOBEC3A whereas 442 were annotated as unlikely. To date, this is the first database dedicated to annotating hotspots for possible false functional hotspots.

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          Most cited references13

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          The genomic landscapes of human breast and colorectal cancers.

          Human cancer is caused by the accumulation of mutations in oncogenes and tumor suppressor genes. To catalog the genetic changes that occur during tumorigenesis, we isolated DNA from 11 breast and 11 colorectal tumors and determined the sequences of the genes in the Reference Sequence database in these samples. Based on analysis of exons representing 20,857 transcripts from 18,191 genes, we conclude that the genomic landscapes of breast and colorectal cancers are composed of a handful of commonly mutated gene "mountains" and a much larger number of gene "hills" that are mutated at low frequency. We describe statistical and bioinformatic tools that may help identify mutations with a role in tumorigenesis. These results have implications for understanding the nature and heterogeneity of human cancers and for using personal genomics for tumor diagnosis and therapy.
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            Pan-Cancer Network Analysis Identifies Combinations of Rare Somatic Mutations across Pathways and Protein Complexes

            Cancers exhibit extensive mutational heterogeneity and the resulting long tail phenomenon complicates the discovery of the genes and pathways that are significantly mutated in cancer. We perform a Pan-Cancer analysis of mutated networks in 3281 samples from 12 cancer types from The Cancer Genome Atlas (TCGA) using HotNet2, a novel algorithm to find mutated subnetworks that overcomes limitations of existing single gene and pathway/network approaches.. We identify 14 significantly mutated subnetworks that include well-known cancer signaling pathways as well as subnetworks with less characterized roles in cancer including cohesin, condensin, and others. Many of these subnetworks exhibit co-occurring mutations across samples. These subnetworks contain dozens of genes with rare somatic mutations across multiple cancers; many of these genes have additional evidence supporting a role in cancer. By illuminating these rare combinations of mutations, Pan-Cancer network analyses provide a roadmap to investigate new diagnostic and therapeutic opportunities across cancer types.
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              Regulated functional alternative splicing in Drosophila

              Alternative splicing expands the coding capacity of metazoan genes, and it was largely genetic studies in the fruit-fly Drosophila melanogaster that established the principle that regulated alternative splicing results in tissue- and stage-specific protein isoforms with different functions in development. Alternative splicing is particularly prominent in germ cells, muscle and the central nervous system where it modulates the expression of various proteins including cell-surface molecules and transcription factors. Studies in flies have given us numerous insights into alternative splicing in terms of upstream regulation, the exquisite diversity of their forms and the key differential cellular functions of alternatively spliced gene products. The current inundation of transcriptome sequencing data from Drosophila provides an unprecedented opportunity to gain a comprehensive view of alternative splicing.
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                Author and article information

                Journal
                Database (Oxford)
                Database (Oxford)
                databa
                Database: The Journal of Biological Databases and Curation
                Oxford University Press
                1758-0463
                2020
                08 May 2020
                08 May 2020
                : 2020
                : baaa025
                Affiliations
                [1] Tecnologico de Monterrey , Escuela de Medicina, Cátedra de Bioinformática, Morones Prieto No. 3000, Colonia Los Doctores, Monterrey, Nuevo León 64710, Mexico
                Author notes
                Corresponding author: Tecnologico de Monterrey, Escuela de Medicina, Cátedra de Bioinformática. Av. Morones Prieto No. 3000, Colonia Los Doctores, Monterrey Nuevo León, Mexico 64710. Tel: (52) 81 8888 2045, 81 8888 2000; E-mail: vtrevino@ 123456tec.mx
                Article
                baaa025
                10.1093/database/baaa025
                7211031
                32386297
                aa35cde3-9cd9-4ab2-b664-9da6fc400bdd
                © The Author(s) 2020. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 6 September 2019
                : 20 February 2020
                : 11 March 2020
                Page count
                Pages: 08
                Categories
                Database Tool

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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