Literature DB >> 26111056

Computational methods and resources for the interpretation of genomic variants in cancer.

Rui Tian, Malay K Basu, Emidio Capriotti.   

Abstract

The recent improvement of the high-throughput sequencing technologies is having a strong impact on the detection of genetic variations associated with cancer. Several institutions worldwide have been sequencing the whole exomes and or genomes of cancer patients in the thousands, thereby providing an invaluable collection of new somatic mutations in different cancer types. These initiatives promoted the development of methods and tools for the analysis of cancer genomes that are aimed at studying the relationship between genotype and phenotype in cancer. In this article we review the online resources and computational tools for the analysis of cancer genome. First, we describe the available repositories of cancer genome data. Next, we provide an overview of the methods for the detection of genetic variation and computational tools for the prioritization of cancer related genes and causative somatic variations. Finally, we discuss the future perspectives in cancer genomics focusing on the impact of computational methods and quantitative approaches for defining personalized strategies to improve the diagnosis and treatment of cancer.

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Year:  2015        PMID: 26111056      PMCID: PMC4480958          DOI: 10.1186/1471-2164-16-S8-S7

Source DB:  PubMed          Journal:  BMC Genomics        ISSN: 1471-2164            Impact factor:   3.969


  134 in total

1.  Discovering functional modules by identifying recurrent and mutually exclusive mutational patterns in tumors.

Authors:  Christopher A Miller; Stephen H Settle; Erik P Sulman; Kenneth D Aldape; Aleksandar Milosavljevic
Journal:  BMC Med Genomics       Date:  2011-04-14       Impact factor: 3.063

Review 2.  Lessons from the cancer genome.

Authors:  Levi A Garraway; Eric S Lander
Journal:  Cell       Date:  2013-03-28       Impact factor: 41.582

3.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Authors:  Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

4.  A comprehensive catalogue of somatic mutations from a human cancer genome.

Authors:  Erin D Pleasance; R Keira Cheetham; Philip J Stephens; David J McBride; Sean J Humphray; Chris D Greenman; Ignacio Varela; Meng-Lay Lin; Gonzalo R Ordóñez; Graham R Bignell; Kai Ye; Julie Alipaz; Markus J Bauer; David Beare; Adam Butler; Richard J Carter; Lina Chen; Anthony J Cox; Sarah Edkins; Paula I Kokko-Gonzales; Niall A Gormley; Russell J Grocock; Christian D Haudenschild; Matthew M Hims; Terena James; Mingming Jia; Zoya Kingsbury; Catherine Leroy; John Marshall; Andrew Menzies; Laura J Mudie; Zemin Ning; Tom Royce; Ole B Schulz-Trieglaff; Anastassia Spiridou; Lucy A Stebbings; Lukasz Szajkowski; Jon Teague; David Williamson; Lynda Chin; Mark T Ross; Peter J Campbell; David R Bentley; P Andrew Futreal; Michael R Stratton
Journal:  Nature       Date:  2009-12-16       Impact factor: 49.962

Review 5.  The cancer genome.

Authors:  Michael R Stratton; Peter J Campbell; P Andrew Futreal
Journal:  Nature       Date:  2009-04-09       Impact factor: 49.962

6.  Improving the prediction of disease-related variants using protein three-dimensional structure.

Authors:  Emidio Capriotti; Russ B Altman
Journal:  BMC Bioinformatics       Date:  2011-07-05       Impact factor: 3.169

7.  Cancer3D: understanding cancer mutations through protein structures.

Authors:  Eduard Porta-Pardo; Thomas Hrabe; Adam Godzik
Journal:  Nucleic Acids Res       Date:  2014-11-11       Impact factor: 16.971

8.  COSMIC: exploring the world's knowledge of somatic mutations in human cancer.

Authors:  Simon A Forbes; David Beare; Prasad Gunasekaran; Kenric Leung; Nidhi Bindal; Harry Boutselakis; Minjie Ding; Sally Bamford; Charlotte Cole; Sari Ward; Chai Yin Kok; Mingming Jia; Tisham De; Jon W Teague; Michael R Stratton; Ultan McDermott; Peter J Campbell
Journal:  Nucleic Acids Res       Date:  2014-10-29       Impact factor: 16.971

9.  PID: the Pathway Interaction Database.

Authors:  Carl F Schaefer; Kira Anthony; Shiva Krupa; Jeffrey Buchoff; Matthew Day; Timo Hannay; Kenneth H Buetow
Journal:  Nucleic Acids Res       Date:  2008-10-02       Impact factor: 16.971

10.  High-definition reconstruction of clonal composition in cancer.

Authors:  Andrej Fischer; Ignacio Vázquez-García; Christopher J R Illingworth; Ville Mustonen
Journal:  Cell Rep       Date:  2014-05-29       Impact factor: 9.423

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  9 in total

1.  VarI-SIG 2014--From SNPs to variants: interpreting different types of genetic variants.

Authors:  Yana Bromberg; Emidio Capriotti
Journal:  BMC Genomics       Date:  2015-06-18       Impact factor: 3.969

2.  VarI-SIG 2015: methods for personalized medicine - the role of variant interpretation in research and diagnostics.

Authors:  Yana Bromberg; Emidio Capriotti; Hannah Carter
Journal:  BMC Genomics       Date:  2016-06-23       Impact factor: 3.969

3.  Novel putative drivers revealed by targeted exome sequencing of advanced solid tumors.

Authors:  Antonio Pannuti; Aleksandra Filipovic; Chindo Hicks; Elliot Lefkowitz; Travis Ptacek; Justin Stebbing; Lucio Miele
Journal:  PLoS One       Date:  2018-03-23       Impact factor: 3.240

4.  Spatial distribution of disease-associated variants in three-dimensional structures of protein complexes.

Authors:  A Gress; V Ramensky; O V Kalinina
Journal:  Oncogenesis       Date:  2017-09-25       Impact factor: 7.485

Review 5.  Integrating molecular networks with genetic variant interpretation for precision medicine.

Authors:  Emidio Capriotti; Kivilcim Ozturk; Hannah Carter
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2018-12-12

6.  Genomic analysis of pancreatic juice DNA assesses malignant risk of intraductal papillary mucinous neoplasm of pancreas.

Authors:  Raúl N Mateos; Hidewaki Nakagawa; Seiko Hirono; Shinichi Takano; Mitsuharu Fukasawa; Akio Yanagisawa; Satoru Yasukawa; Kazuhiro Maejima; Aya Oku-Sasaki; Kaoru Nakano; Munmee Dutta; Hiroko Tanaka; Satoru Miyano; Nobuyuki Enomoto; Hiroki Yamaue; Kenta Nakai; Masashi Fujita
Journal:  Cancer Med       Date:  2019-06-21       Impact factor: 4.452

7.  A conjoined universal helper epitope can unveil antitumor effects of a neoantigen vaccine targeting an MHC class I-restricted neoepitope.

Authors:  Adam M Swartz; Kendra L Congdon; Smita K Nair; Qi-Jing Li; James E Herndon; Carter M Suryadevara; Katherine A Riccione; Gary E Archer; Pamela K Norberg; Luis A Sanchez-Perez; John H Sampson
Journal:  NPJ Vaccines       Date:  2021-01-18       Impact factor: 7.344

8.  Prostate cancer in omics era.

Authors:  Nasrin Gholami; Amin Haghparast; Iraj Alipourfard; Majid Nazari
Journal:  Cancer Cell Int       Date:  2022-09-05       Impact factor: 6.429

9.  PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions.

Authors:  Jaroslav Bendl; Miloš Musil; Jan Štourač; Jaroslav Zendulka; Jiří Damborský; Jan Brezovský
Journal:  PLoS Comput Biol       Date:  2016-05-25       Impact factor: 4.475

  9 in total

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