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Nucleotide excision repair is impaired by binding of transcription factors to DNA
[article]
2015
bioRxiv
pre-print
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Somatic mutations are the driving force of cancer genome evolution. The rate of somatic mutations appears in great variability across the genome due to chromatin organization, DNA accessibility and replication timing. However, other variables that may influence the mutation rate locally, such as DNA-binding proteins, are unknown. Here we demonstrate that the rate of somatic mutations in melanoma tumors is highly increased at active Transcription Factor binding sites (TFBS) and nucleosome
doi:10.1101/028886
fatcat:gm4qhnajzjcwjadwjkv6qg2op4
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... d DNA, compared to their flanking regions. Using recently available excision-repair sequencing (XR-seq) data, we show that the higher mutation rate at these sites is caused by a decrease of the levels of nucleotide excision repair (NER) activity. Therefore, our work demonstrates that DNA-bound proteins interfere with the NER machinery, which results in an increased rate of mutations at their binding sites. This finding has important implications in our understanding of mutational and DNA repair processes and in the identification of cancer driver mutations.
Rational design of cancer gene panels with OncoPaD
2016
Genome Medicine
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Profiling the somatic mutations of genes which may inform about tumor evolution, prognostics and treatment is becoming a standard tool in clinical oncology. Commercially available cancer gene panels rely on manually gathered cancer-related genes, in a "one-size-fits-many" solution. The design of new panels requires laborious search of literature and cancer genomics resources, with their performance on cohorts of patients difficult to estimate. Results: We present OncoPaD, to our knowledge the
doi:10.1186/s13073-016-0349-1
pmid:27716338
pmcid:PMC5047348
fatcat:xr6o25bxa5bsjd5lrglls7pbay
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... rst tool aimed at the rational design of cancer gene panels. OncoPaD estimates the cost-effectiveness of the designed panel on a cohort of tumors and provides reports on the importance of individual mutations for tumorigenesis or therapy. With a friendly interface and intuitive input, OncoPaD suggests researchers relevant sets of genes to be included in the panel, because prior knowledge or analyses indicate that their mutations either drive tumorigenesis or function as biomarkers of drug response. OncoPaD also provides reports on the importance of individual mutations for tumorigenesis or therapy that support the interpretation of the results obtained with the designed panel. We demonstrate in silico that OncoPaD designed panels are more cost-effective-i.e. detect a maximum fraction of tumors in the cohort by sequencing a minimum quantity of DNA-than available panels. Conclusions: With its unique features, OncoPaD will help clinicians and researchers design tailored next-generating sequencing (NGS) panels to detect circulating tumor DNA or biopsy specimens, thereby facilitating early and accurate detection of tumors, genomics informed therapeutic decisions, patient follow-up and timely identification of resistance mechanisms to targeted agents. OncoPaD may be accessed through http://www.intogen.org/oncopad.
Cancer Genome Interpreter Annotates The Biological And Clinical Relevance Of Tumor Alterations
[article]
2017
bioRxiv
pre-print
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While tumor genome sequencing has become widely available in clinical and research settings, the interpretation of tumor somatic variants remains an important bottleneck. Most of the alterations observed in tumors, including those in well-known cancer genes, are of uncertain significance. Moreover, the information on tumor genomic alterations shaping the response to existing therapies is fragmented across the literature and several specialized resources. Here we present the Cancer Genome
doi:10.1101/140475
fatcat:ldia2r6fcnb47o3grupfavh6xi
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... eter (http://www.cancergenomeinterpreter.org), an open access tool that we have implemented to annotate genomic alterations and interpret their possible role in tumorigenesis and in the response to anti-cancer therapies.
Nucleotide excision repair is impaired by binding of transcription factors to DNA
2016
Nature
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Somatic mutations are the driving force of cancer genome evolution 1 . The rate of somatic mutations appears in great variability across the genome due to variations in chromatin organization, DNA accessibility and replication timing 2-5 . However, other variables that may influence the mutation rate locally, such as DNA-binding proteins, are unknown. Here, we demonstrate that the rate of somatic mutations in melanomas is highly increased at active Transcription Factor binding sites (TFBS) and
doi:10.1038/nature17661
pmid:27075101
fatcat:rfgz6hhys5gizjiu3lquh4o5se
more »
... ucleosome embedded DNA, compared to their flanking regions. Using recently available excision-repair sequencing (XR-seq) data 6 , we show that the higher mutation rate at these sites is caused by a decrease of the levels of nucleotide excision repair (NER) activity. Therefore, our work demonstrates that DNA-bound proteins interfere with the NER machinery, which results in an increased rate of mutations at their binding sites. This finding has important implications in our understanding of mutational and DNA repair processes and in the identification of cancer driver mutations. The accumulation of somatic mutations in cells results from the interplay of mutagenic processes, both internal and exogenous, and mechanisms of DNA repair. Detailed early biochemical studies 7,8 and recent efforts to sequence the genomes of tumors from different cancer types 9,10 have shed light on this interplay. Mutational signatures associated to various tumorigenic mechanisms have been identified across cancer types 11 , and genomic features such as chromatin organization, DNA accessibility, and DNA replication timing 2-5 have been associated to the variation of somatic mutation rates at the megabase scale. Two recent studies proposed a causal relationship between the accessibility of chromosomal areas to the DNA repair machinery and their mutational burden. Supek and Lehner, 2015 12 pointed to variable repair of DNA mismatches as the basis of the megabase scale variation of somatic mutation rates across the human genome. Polak et al. 2014 4 attributed lower somatic mutation rates at
Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation
2012
Genome Medicine
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High-throughput prioritization of cancer-causing mutations (drivers) is a key challenge of cancer genome projects, due to the number of somatic variants detected in tumors. One important step in this task is to assess the functional impact of tumor somatic mutations. A number of computational methods have been employed for that purpose, although most were originally developed to distinguish disease-related nonsynonymous single nucleotide variants (nsSNVs) from polymorphisms. Our new method,
doi:10.1186/gm390
pmid:23181723
pmcid:PMC4064314
fatcat:2cbveb2kgvdntnhallvanjvu7y
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... sformed Functional Impact score for Cancer (transFIC), improves the assessment of the functional impact of tumor nsSNVs by taking into account the baseline tolerance of genes to functional variants.
IntOGen-mutations identifies cancer drivers across tumor types
2013
Nature Methods
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The results can be browsed through intoGen-mutations identifies cancer drivers across tumor types Abel Gonzalez-Perez 1 , Christian Perez-Llamas 1 , Jordi Deu-Pons 1 , David Tamborero 1 , Michael P Schroeder ...
Gonzalez-Perez, A., Deu-Pons, J. & Lopez-Bigas, N. Genome med. 4, 89 (2012). 15. Perez-Llamas, C. & Lopez-Bigas, N. ...
doi:10.1038/nmeth.2642
pmid:24037244
pmcid:PMC5758042
fatcat:qmkcw5et6zhqxciby2gmvlh44a
Cancer Genome Interpreter annotates the biological and clinical relevance of tumor alterations
2018
Genome Medicine
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While tumor genome sequencing has become widely available in clinical and research settings, the interpretation of tumor somatic variants remains an important bottleneck. Most of the alterations observed in tumors, including those in well-known cancer genes, are of uncertain significance. Moreover, the information on tumor genomic alterations shaping the response to existing therapies is fragmented across the literature and several specialized resources. Here we present the Cancer Genome
doi:10.1186/s13073-018-0531-8
pmid:29592813
pmcid:PMC5875005
fatcat:edrki7mj6ncmlilbxmzhacpcnq
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... eter (http://www.cancergenomeinterpreter.org), an open access tool that we have implemented to annotate genomic alterations and interpret their possible role in tumorigenesis and in the response to anti-cancer therapies. New computational tools to support the interpretation of tumor genomes are needed Cancer is predominantly a genetic disease, caused by the accumulation of so-called "driver" genomic alterations that confer cells tumorigenic capabilities 1 . Thousands of tumor genomes are sequenced every year in research projects and clinical settings around the world. In some cases the whole-genome is sequenced while other focus on the exome or a panel of selected genes. In all cases, the sequencing is followed by the necessity to annotate which of the somatic mutations identified have a possible role in tumorigenesis and treatment response. We call this process 'the interpretation of cancer genomes' and it is currently a tedious .
In Silico Prescription of Anticancer Drugs to Cohorts of 28 Tumor Types Reveals Targeting Opportunities
2015
Cancer Cell
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OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations
2016
Genome Biology
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Distinguishing the driver mutations from somatic mutations in a tumor genome is one of the major challenges of cancer research. This challenge is more acute and far from solved for non-coding mutations. Here we present OncodriveFML, a method designed to analyze the pattern of somatic mutations across tumors in both coding and non-coding genomic regions to identify signals of positive selection, and therefore, their involvement in tumorigenesis. We describe the method and illustrate its
doi:10.1186/s13059-016-0994-0
pmid:27311963
pmcid:PMC4910259
fatcat:whg3hamnbjgq5d23kuztyr2pdq
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... s to identify protein-coding genes, promoters, untranslated regions, intronic splice regions, and lncRNAs-containing driver mutations in several malignancies.
Comprehensive identification of mutational cancer driver genes across 12 tumor types
2013
Scientific Reports
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Deu-Pons, Cyriac Kandoth, Jüri Reimand, Michael S. ...
SCIENTIFIC REPORTS | 3 : 2650 | DOI: 10.1038/srep02650
Comprehensive identification of mutational cancer driver genes across 12 tumor types David Tamborero, Abel Gonzalez-Perez, Christian Perez-Llamas, Jordi ...
doi:10.1038/srep02650
pmid:24084849
pmcid:PMC3788361
fatcat:tdh5r4cwcvf6fnmxlyrpaoy2cu
DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants
2016
Nucleic Acids Research
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The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants
doi:10.1093/nar/gkw943
pmid:27924018
pmcid:PMC5210640
fatcat:5lwyn7r5hnd6bbmbesjjomtmm4
more »
... d in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.
The whole-genome panorama of cancer drivers
[article]
2017
bioRxiv
pre-print
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The advance of personalized cancer medicine requires the accurate identification of the mutations driving each patient's tumor. However, to date, we have only been able to obtain partial insights into the contribution of genomic events to tumor development. Here, we design a comprehensive approach to identify the driver mutations in each patient's tumor and obtain a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and
doi:10.1101/190330
fatcat:ioafttojhfbf5oa5zv3nwhpvdu
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... -coding point mutations, copy number alterations and other genomic rearrangements of somatic origin, and potentially predisposing germline variants. We demonstrate that genomic events are at the root of virtually all tumors, with each carrying on average 4.6 driver events. Most individual tumors harbor a unique combination of drivers, and we uncover the most frequent co-occurring driver events. Half of all cancer genes are affected by several types of driver mutations. In summary, the panorama described here provides answers to fundamental questions in cancer genomics and bridges the gap between cancer genomics and personalized cancer medicine.
A harmonized meta-knowledgebase of clinical interpretations of cancer genomic variants
[article]
2018
bioRxiv
pre-print
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Precision oncology relies on the accurate discovery and interpretation of genomic variants to enable individualized therapy selection, diagnosis, or prognosis. However, knowledgebases containing clinical interpretations of somatic cancer variants are highly disparate in interpretation content, structure, and supporting primary literature, reducing consistency and impeding consensus when evaluating variants and their relevance in a clinical setting. With the cooperation of experts of the Global
doi:10.1101/366856
fatcat:tgvcvhikdngoxpanenq2wtnzgy
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... lliance for Genomics and Health (GA4GH) and of six prominent cancer variant knowledgebases, we developed a framework for aggregating and harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations covering 3,437 unique variants in 415 genes, 357 diseases, and 791 drugs. We demonstrated large gains in overlapping terms between resources across variants, diseases, and drugs as a result of this harmonization. We subsequently demonstrated improved matching between patients of the GENIE cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 34% to 57% in aggregate. We developed an open and freely available web interface for exploring the harmonized interpretations from these six knowledgebases at search.cancervariants.org.
A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer
2020
Nature Genetics
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Precision oncology relies on accurate discovery and interpretation of genomic variants, enabling individualized diagnosis, prognosis and therapy selection. We found that six prominent somatic cancer variant knowledgebases were highly disparate in content, structure and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. We developed a framework for harmonizing variant interpretations to produce a meta-knowledgebase of 12,856
doi:10.1038/s41588-020-0603-8
pmid:32246132
pmcid:PMC7127986
fatcat:dqjp676phvfg5luj7ndow4ndp4
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... gate interpretations. We demonstrated large gains in overlap between resources across variants, diseases and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 57% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide a freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.
Correction to: Complex multiple risk intervention to promote healthy behaviours in people between 45 to 75 years attended in primary health care (EIRA study): study protocol for a hybrid trial
2018
BMC Public Health
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Author details 1 details Institut Universitarid'Investigació en AtencióPrimària Jordi Gol (IDIAP Jordi Gol), Gran Via Corts Catalanes 587 àtic, 08007 Barcelona, Spain. 2 Gerència Territorial de Barcelona ...
, Institut de Recerca Sant Joan de Déu, C/Santa Rosa 39-57, 08950 Esplugues de Llobregat, Spain. 10 Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain. ...
doi:10.1186/s12889-018-5905-8
pmid:30103723
pmcid:PMC6088411
fatcat:lltr4w2zr5dabjgtzlzuahq2iq
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