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We are analyzing https://link.springer.com/article/10.1186/s12864-016-2727-x.

Title:
Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types | BMC Genomics
Description:
Background An important step towards personalizing cancer treatment is to integrate heterogeneous evidences to catalog mutational hotspots that are biologically and therapeutically relevant and thus represent where targeted therapy would likely be beneficial. However, existing methods do not sufficiently delineate varying functionality of individual mutations within the same genes. Results We observed a large discordancy of mutation rates across different mutation subtypes and tumor types, and nominated 702 hotspot mutations in 549 genes in the Catalog of Somatic Mutations in Cancer (COSMIC) by considering context specific mutation characteristics such as genes, cancer types, mutation rates, mutation subtypes and sequence contexts. We observed that hotspot mutations were highly prevalent in Non CpG-island C/G transition and transversion sequence contexts in 10 tumor types, and specific insertion hotspot mutations were enriched in breast cancer and deletion hotspot mutations in colorectal cancer. We found that the hotspot mutations nominated by our approach were significantly more conserved than non-hotspot mutations in the corresponding cancer genes. We also examined the biological significance and pharmacogenomics properties of these hotspot mutations using data in the Cancer Genome Atlas (TCGA) and the Cancer Cell-Line Encyclopedia (CCLE), and found that 53 hotspot mutations are independently associated with diverse functional evidences in 1) mRNA and protein expression, 2) pathway activity, or 3) drug sensitivity and 82 were highly enriched in specific tumor types. We highlighted the distinct functional indications of hotspot mutations under different contexts and nominated novel hotspot mutations such as MAP3K4 A1199 deletion, NR1H2 Q175 insertion, and GATA3 P409 insertion as potential biomarkers or drug targets. Conclusion We identified a set of hotspot mutations across 17 tumor types by considering the background mutation rate variations among genes, tumor subtypes, mutation subtypes, and sequence contexts. We illustrated the common and distinct mutational signatures of hotspot mutations among different tumor types and investigated their variable functional relevance under different contexts, which could potentially serve as a resource for explicitly selecting targets for diagnosis, drug development, and patient management.
Website Age:
28 years and 1 months (reg. 1997-05-29).

Matching Content Categories {๐Ÿ“š}

  • Science
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Content Management System {๐Ÿ“}

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Custom-built

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๐ŸŒ  Phenomenal Traffic: 5M - 10M visitors per month


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Keywords {๐Ÿ”}

mutations, hotspot, cancer, mutation, types, tumor, pubmed, samples, article, data, google, scholar, genes, additional, functional, mutational, expression, file, cas, sequence, protein, contexts, central, fig, gene, pikca, number, nonhotspot, drug, insertion, significantly, table, higher, cosmic, type, brca, context, found, missense, biological, subtypes, examined, signatures, deletion, sensitivity, analysis, specific, tcga, rate, genomic,

Topics {โœ’๏ธ}

cancer cell-line encyclopedia early-phase clinical trials org/tcpa/_design/basic/index mutational profile genomic profiles obtained cancer genome atlas millsย &ย ken chen kruskal-wallis h-test subtype-specific mutation rate tcga pan-cancer data remaining frame-shift insertion di-nucleotide sequence contexts /articles/supplements/volume-17-supplement article download pdf systematic pathway-aware algorithms g108 frame-shift deletion search patient-based cancer therapeutics observed subtype-specific mutations ken chen funda meric-bernstam outlier hyper-mutated samples specific sequence context full access privacy choices/manage cookies lower grade glioma selectively activate akt diverse functional evidences integrate heterogeneous evidences diverse cancer types cancer cell-lines article chen context-specific manner texas graduate school tumor specificity data developing predictive biomarkers targeting raf kinases creative commons license exhibit similar functions protein-protein interaction author information authors prevalent sequence context human cancer genomes pan-cancer catalogue insufficient sample size diverse functional relevance bmc genomics 17 background mutation rate central platform map3k4 a1199 deletion

Schema {๐Ÿ—บ๏ธ}

WebPage:
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         headline:Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types
         description:An important step towards personalizing cancer treatment is to integrate heterogeneous evidences to catalog mutational hotspots that are biologically and therapeutically relevant and thus represent where targeted therapy would likely be beneficial. However, existing methods do not sufficiently delineate varying functionality of individual mutations within the same genes. We observed a large discordancy of mutation rates across different mutation subtypes and tumor types, and nominated 702 hotspot mutations in 549 genes in the Catalog of Somatic Mutations in Cancer (COSMIC) by considering context specific mutation characteristics such as genes, cancer types, mutation rates, mutation subtypes and sequence contexts. We observed that hotspot mutations were highly prevalent in Non CpG-island C/G transition and transversion sequence contexts in 10 tumor types, and specific insertion hotspot mutations were enriched in breast cancer and deletion hotspot mutations in colorectal cancer. We found that the hotspot mutations nominated by our approach were significantly more conserved than non-hotspot mutations in the corresponding cancer genes. We also examined the biological significance and pharmacogenomics properties of these hotspot mutations using data in the Cancer Genome Atlas (TCGA) and the Cancer Cell-Line Encyclopedia (CCLE), and found that 53 hotspot mutations are independently associated with diverse functional evidences in 1) mRNA and protein expression, 2) pathway activity, or 3) drug sensitivity and 82 were highly enriched in specific tumor types. We highlighted the distinct functional indications of hotspot mutations under different contexts and nominated novel hotspot mutations such as MAP3K4 A1199 deletion, NR1H2 Q175 insertion, and GATA3 P409 insertion as potential biomarkers or drug targets. We identified a set of hotspot mutations across 17 tumor types by considering the background mutation rate variations among genes, tumor subtypes, mutation subtypes, and sequence contexts. We illustrated the common and distinct mutational signatures of hotspot mutations among different tumor types and investigated their variable functional relevance under different contexts, which could potentially serve as a resource for explicitly selecting targets for diagnosis, drug development, and patient management.
         datePublished:2016-06-23T00:00:00Z
         dateModified:2016-06-23T00:00:00Z
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            Sequence Context
            Reverse Phase Protein Array
            Cancer Cell Line Encyclopedia
            Mutation Subtype
            Life Sciences
            general
            Microarrays
            Proteomics
            Animal Genetics and Genomics
            Microbial Genetics and Genomics
            Plant Genetics and Genomics
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                     name:The University of Texas MD Anderson Cancer Center
                     address:
                        name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
                        type:PostalAddress
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                        name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
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      headline:Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types
      description:An important step towards personalizing cancer treatment is to integrate heterogeneous evidences to catalog mutational hotspots that are biologically and therapeutically relevant and thus represent where targeted therapy would likely be beneficial. However, existing methods do not sufficiently delineate varying functionality of individual mutations within the same genes. We observed a large discordancy of mutation rates across different mutation subtypes and tumor types, and nominated 702 hotspot mutations in 549 genes in the Catalog of Somatic Mutations in Cancer (COSMIC) by considering context specific mutation characteristics such as genes, cancer types, mutation rates, mutation subtypes and sequence contexts. We observed that hotspot mutations were highly prevalent in Non CpG-island C/G transition and transversion sequence contexts in 10 tumor types, and specific insertion hotspot mutations were enriched in breast cancer and deletion hotspot mutations in colorectal cancer. We found that the hotspot mutations nominated by our approach were significantly more conserved than non-hotspot mutations in the corresponding cancer genes. We also examined the biological significance and pharmacogenomics properties of these hotspot mutations using data in the Cancer Genome Atlas (TCGA) and the Cancer Cell-Line Encyclopedia (CCLE), and found that 53 hotspot mutations are independently associated with diverse functional evidences in 1) mRNA and protein expression, 2) pathway activity, or 3) drug sensitivity and 82 were highly enriched in specific tumor types. We highlighted the distinct functional indications of hotspot mutations under different contexts and nominated novel hotspot mutations such as MAP3K4 A1199 deletion, NR1H2 Q175 insertion, and GATA3 P409 insertion as potential biomarkers or drug targets. We identified a set of hotspot mutations across 17 tumor types by considering the background mutation rate variations among genes, tumor subtypes, mutation subtypes, and sequence contexts. We illustrated the common and distinct mutational signatures of hotspot mutations among different tumor types and investigated their variable functional relevance under different contexts, which could potentially serve as a resource for explicitly selecting targets for diagnosis, drug development, and patient management.
      datePublished:2016-06-23T00:00:00Z
      dateModified:2016-06-23T00:00:00Z
      pageStart:249
      pageEnd:262
      license:http://creativecommons.org/publicdomain/zero/1.0/
      sameAs:https://doi.org/10.1186/s12864-016-2727-x
      keywords:
         PIK3CA Mutation
         Sequence Context
         Reverse Phase Protein Array
         Cancer Cell Line Encyclopedia
         Mutation Subtype
         Life Sciences
         general
         Microarrays
         Proteomics
         Animal Genetics and Genomics
         Microbial Genetics and Genomics
         Plant Genetics and Genomics
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         name:BioMed Central
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            type:ImageObject
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      author:
            name:Tenghui Chen
            affiliation:
                  name:The University of Texas MD Anderson Cancer Center
                  address:
                     name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
                     type:PostalAddress
                  type:Organization
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                     name:Biostatistics, Bioinformatics and Systems Biology Program, The University of Texas Graduate School of Biomedical Sciences, Houston, USA
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            name:Zixing Wang
            affiliation:
                  name:The University of Texas MD Anderson Cancer Center
                  address:
                     name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Wanding Zhou
            affiliation:
                  name:The University of Texas MD Anderson Cancer Center
                  address:
                     name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Zechen Chong
            affiliation:
                  name:The University of Texas MD Anderson Cancer Center
                  address:
                     name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Funda Meric-Bernstam
            affiliation:
                  name:The University of Texas MD Anderson Cancer Center
                  address:
                     name:Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
                     type:PostalAddress
                  type:Organization
                  name:The University of Texas MD Anderson Cancer Center
                  address:
                     name:Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Gordon B. Mills
            affiliation:
                  name:The University of Texas MD Anderson Cancer Center
                  address:
                     name:Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
                     type:PostalAddress
                  type:Organization
                  name:The University of Texas MD Anderson Cancer Center
                  address:
                     name:Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
                     type:PostalAddress
                  type:Organization
                  name:The University of Texas Graduate School of Biomedical Sciences
                  address:
                     name:Biostatistics, Bioinformatics and Systems Biology Program, The University of Texas Graduate School of Biomedical Sciences, Houston, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Ken Chen
            affiliation:
                  name:The University of Texas MD Anderson Cancer Center
                  address:
                     name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
                     type:PostalAddress
                  type:Organization
                  name:The University of Texas Graduate School of Biomedical Sciences
                  address:
                     name:Biostatistics, Bioinformatics and Systems Biology Program, The University of Texas Graduate School of Biomedical Sciences, Houston, USA
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      name:The University of Texas MD Anderson Cancer Center
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         name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
         type:PostalAddress
      name:The University of Texas MD Anderson Cancer Center
      address:
         name:Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
         type:PostalAddress
      name:The University of Texas MD Anderson Cancer Center
      address:
         name:Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
         type:PostalAddress
      name:The University of Texas MD Anderson Cancer Center
      address:
         name:Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
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      address:
         name:Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
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            name:The University of Texas Graduate School of Biomedical Sciences
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               name:Biostatistics, Bioinformatics and Systems Biology Program, The University of Texas Graduate School of Biomedical Sciences, Houston, USA
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      name:Zixing Wang
      affiliation:
            name:The University of Texas MD Anderson Cancer Center
            address:
               name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
               type:PostalAddress
            type:Organization
      name:Wanding Zhou
      affiliation:
            name:The University of Texas MD Anderson Cancer Center
            address:
               name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
               type:PostalAddress
            type:Organization
      name:Zechen Chong
      affiliation:
            name:The University of Texas MD Anderson Cancer Center
            address:
               name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
               type:PostalAddress
            type:Organization
      name:Funda Meric-Bernstam
      affiliation:
            name:The University of Texas MD Anderson Cancer Center
            address:
               name:Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
               type:PostalAddress
            type:Organization
            name:The University of Texas MD Anderson Cancer Center
            address:
               name:Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
               type:PostalAddress
            type:Organization
      name:Gordon B. Mills
      affiliation:
            name:The University of Texas MD Anderson Cancer Center
            address:
               name:Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
               type:PostalAddress
            type:Organization
            name:The University of Texas MD Anderson Cancer Center
            address:
               name:Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
               type:PostalAddress
            type:Organization
            name:The University of Texas Graduate School of Biomedical Sciences
            address:
               name:Biostatistics, Bioinformatics and Systems Biology Program, The University of Texas Graduate School of Biomedical Sciences, Houston, USA
               type:PostalAddress
            type:Organization
      name:Ken Chen
      affiliation:
            name:The University of Texas MD Anderson Cancer Center
            address:
               name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
               type:PostalAddress
            type:Organization
            name:The University of Texas Graduate School of Biomedical Sciences
            address:
               name:Biostatistics, Bioinformatics and Systems Biology Program, The University of Texas Graduate School of Biomedical Sciences, Houston, USA
               type:PostalAddress
            type:Organization
      email:[email protected]
PostalAddress:
      name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
      name:Biostatistics, Bioinformatics and Systems Biology Program, The University of Texas Graduate School of Biomedical Sciences, Houston, USA
      name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
      name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
      name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
      name:Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
      name:Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
      name:Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
      name:Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, USA
      name:Biostatistics, Bioinformatics and Systems Biology Program, The University of Texas Graduate School of Biomedical Sciences, Houston, USA
      name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
      name:Biostatistics, Bioinformatics and Systems Biology Program, The University of Texas Graduate School of Biomedical Sciences, Houston, USA

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