1
|
Appe AJ, Aggerholm A, Hansen MC, Ebbesen LH, Hokland P, Bentzen HHN, Nyvold CG. Differential expression levels and methylation status of ROBO1 in mantle cell lymphoma and chronic lymphocytic leukaemia. Int J Lab Hematol 2017; 39:e70-e73. [PMID: 28004534 DOI: 10.1111/ijlh.12615] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
MESH Headings
- DNA Methylation
- DNA, Neoplasm/metabolism
- Female
- Gene Expression Regulation, Leukemic
- Humans
- Leukemia, Lymphocytic, Chronic, B-Cell/metabolism
- Leukemia, Lymphocytic, Chronic, B-Cell/pathology
- Lymphoma, Mantle-Cell/metabolism
- Lymphoma, Mantle-Cell/pathology
- Male
- Neoplasm Proteins/biosynthesis
- Nerve Tissue Proteins/biosynthesis
- Receptors, Immunologic/biosynthesis
- Roundabout Proteins
Collapse
Affiliation(s)
- A J Appe
- Department of Haematology, Aarhus University Hospital, Aarhus, Denmark
| | - A Aggerholm
- Department of Haematology, Aarhus University Hospital, Aarhus, Denmark
| | - M C Hansen
- Department of Haematology, Aarhus University Hospital, Aarhus, Denmark
| | - L H Ebbesen
- Department of Haematology, Aarhus University Hospital, Aarhus, Denmark
| | - P Hokland
- Department of Haematology, Aarhus University Hospital, Aarhus, Denmark
| | - H H N Bentzen
- Department of Haematology, Aarhus University Hospital, Aarhus, Denmark
| | - C G Nyvold
- Department of Haematology, Aarhus University Hospital, Aarhus, Denmark
| |
Collapse
|
2
|
do Valle ÍF, Giampieri E, Simonetti G, Padella A, Manfrini M, Ferrari A, Papayannidis C, Zironi I, Garonzi M, Bernardi S, Delledonne M, Martinelli G, Remondini D, Castellani G. Optimized pipeline of MuTect and GATK tools to improve the detection of somatic single nucleotide polymorphisms in whole-exome sequencing data. BMC Bioinformatics 2016; 17:341. [PMID: 28185561 PMCID: PMC5123378 DOI: 10.1186/s12859-016-1190-7] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Detecting somatic mutations in whole exome sequencing data of cancer samples has become a popular approach for profiling cancer development, progression and chemotherapy resistance. Several studies have proposed software packages, filters and parametrizations. However, many research groups reported low concordance among different methods. We aimed to develop a pipeline which detects a wide range of single nucleotide mutations with high validation rates. We combined two standard tools - Genome Analysis Toolkit (GATK) and MuTect - to create the GATK-LODN method. As proof of principle, we applied our pipeline to exome sequencing data of hematological (Acute Myeloid and Acute Lymphoblastic Leukemias) and solid (Gastrointestinal Stromal Tumor and Lung Adenocarcinoma) tumors. We performed experiments on simulated data to test the sensitivity and specificity of our pipeline. RESULTS The software MuTect presented the highest validation rate (90 %) for mutation detection, but limited number of somatic mutations detected. The GATK detected a high number of mutations but with low specificity. The GATK-LODN increased the performance of the GATK variant detection (from 5 of 14 to 3 of 4 confirmed variants), while preserving mutations not detected by MuTect. However, GATK-LODN filtered more variants in the hematological samples than in the solid tumors. Experiments in simulated data demonstrated that GATK-LODN increased both specificity and sensitivity of GATK results. CONCLUSION We presented a pipeline that detects a wide range of somatic single nucleotide variants, with good validation rates, from exome sequencing data of cancer samples. We also showed the advantage of combining standard algorithms to create the GATK-LODN method, that increased specificity and sensitivity of GATK results. This pipeline can be helpful in discovery studies aimed to profile the somatic mutational landscape of cancer genomes.
Collapse
Affiliation(s)
- Ítalo Faria do Valle
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
- CAPES Foundation, Ministry of Education of Brazil, Brasília, DF, Brazil
| | - Enrico Giampieri
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| | - Giorgia Simonetti
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Antonella Padella
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Marco Manfrini
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Anna Ferrari
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Cristina Papayannidis
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Isabella Zironi
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| | - Marianna Garonzi
- Department of Biotechnology, University of Verona, Verona, Italy
| | - Simona Bernardi
- Unit of Blood Diseases and Stem Cell Transplantation, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Massimo Delledonne
- Department of Biotechnology, University of Verona, Verona, Italy
- Personal Genomics, Verona, Italy
| | - Giovanni Martinelli
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Daniel Remondini
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy.
| | - Gastone Castellani
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| |
Collapse
|
3
|
Piñero J, Bravo À, Queralt-Rosinach N, Gutiérrez-Sacristán A, Deu-Pons J, Centeno E, García-García J, Sanz F, Furlong LI. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res 2016; 45:D833-D839. [PMID: 27924018 PMCID: PMC5210640 DOI: 10.1093/nar/gkw943] [Citation(s) in RCA: 1429] [Impact Index Per Article: 178.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 09/29/2016] [Accepted: 10/18/2016] [Indexed: 12/12/2022] Open
Abstract
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 involved 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.
Collapse
Affiliation(s)
- Janet Piñero
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Àlex Bravo
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Núria Queralt-Rosinach
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Alba Gutiérrez-Sacristán
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Jordi Deu-Pons
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Emilio Centeno
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Javier García-García
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Ferran Sanz
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Laura I Furlong
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| |
Collapse
|