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Computational approaches for discovery of mutational signatures in cancer [article]

Adrian Baez-Ortega, Kevin Gori
2017 bioRxiv   pre-print
The study of these DNA fingerprints, termed mutational signatures, holds important potential for furthering our understanding of the causes and evolution of cancer, and can provide insights of relevance  ...  for cancer prevention and treatment.  ...  When used for refitting well-validated signatures in specific 540 the ones described here, both de novo inference and refitting of mutational 553 signatures are amenable to many other computational approaches  ... 
doi:10.1101/154716 fatcat:fzcjbvq5nra7dbeh33u7lqxvma

Computational approaches for discovery of mutational signatures in cancer

Adrian Baez-Ortega, Kevin Gori
2017 Briefings in Bioinformatics  
By contrast, the 134 simpler problem of signature refitting is characterised by both M and S being known a priori. 135 136 Computational approaches for mutational signature discovery 137  ...  This has 60 produced catalogues of signatures that operate in a variety of human neoplasias [2,28-31]. 61 While the development of methods for discovery of mutational signatures has achieved 62 considerable  ...  properties of 630 mutational signature discovery, the study of somatic mutation patterns will surely be extended • Alternative approaches include partly and fully probabilistic models, as well as NMF  ... 
doi:10.1093/bib/bbx082 pmid:28968631 fatcat:4ekqo4v4lzflphvtt62npktvh4

Biocomputing drug repurposing toward targeted therapies

Luca Cardone
2016 Aging  
Thus, the approach could be applied to every genetically targetable oncogene and tumour suppressor mutated in cancer for which pharmacological inhibitors might not be available.  ...  In the case of the PI3K pathway, the oncogene-induced signature was sufficient for the computational repurposing of novel pathway inhibitors.  ... 
doi:10.18632/aging.101135 pmid:27920407 pmcid:PMC5191858 fatcat:tscwu4ocp5fyfgyvfk3pf5b5gi

Cancer In Silico Drug Discovery: A Systems Biology Tool for Identifying Candidate Drugs to Target Specific Molecular Tumor Subtypes

F. A. San Lucas, J. Fowler, K. Chang, S. Kopetz, E. Vilar, P. Scheet
2014 Molecular Cancer Therapeutics  
We present Cancer in silico Drug Discovery (CiDD;, a computational drug discovery platform that addresses these challenges.  ...  We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF.  ...  Authors' Contributions Acknowledgments The authors thank TCGA research network for publicly sharing their data. The software and results published here are in large part based upon  ... 
doi:10.1158/1535-7163.mct-14-0260 pmid:25349306 pmcid:PMC4341901 fatcat:as2j23frmne5da2m6qeue2lnhq

Computational Approaches and Pharmacogenomics Data Resources for Drug Repositioning

Fuhai LI
2017 Medical Research Archives  
In this study, some widely used computational approaches and pharmacogenomics data resources for repositioning optimal drugs are introduced and discussed, which aims to provide a general overview of the  ...  Though a set of approaches and data resources have been reported to reposition FDA approved drugs and investigational drugs for specific diseases, novel and sophisticated computational approaches are needed  ...  Computational Approaches and Pharmacogenomics Data Resources for Drug Repositioning  ... 
doi:10.18103/mra.v5i6.1225 fatcat:yebpsd6u6bg35huknuh4fzyvpi

Data-driven approaches to advance research and clinical care for pediatric cancer

Alexander M. Gout, Sasi Arunachalam, David B. Finkelstein, Jinghui Zhang
2021 Biochimica et Biophysica Acta. CR. Reviews on Cancer  
In this review we present the major data resources of pediatric cancer and actionable insights into pediatric cancer etiology stemming from the identification of oncogenic gene fusions, mutational signature  ...  analysis, systems biology, cancer predisposition and survivorship studies - that have led to improved clinical diagnosis, discovery of new drug-targets, pharmacological therapy, and screening for genetic  ...  Stephanie Wiggins for their help in data preparation, proof-reading and design of figure 1 .  ... 
doi:10.1016/j.bbcan.2021.188571 pmid:34051287 fatcat:xr457oomkrfirm5lzkbn5nkgpy

HyperModules: identifying clinically and phenotypically significant network modules with disease mutations for biomarker discovery

Alvin Leung, Gary D. Bader, Jüri Reimand
2014 Computer applications in the biosciences : CABIOS  
Correlating disease mutations with clinical and phenotypic information such as drug response or patient survival is an important goal of personalized cancer genomics and a first step in biomarker discovery  ...  HyperModules is a network search algorithm that finds frequently mutated gene modules with significant clinical or phenotypic signatures from biomolecular interaction networks.  ...  ACKNOWLEDGEMENTS The authors thank Jason Montojo and Harold Rodriguez for Cytoscape help. Conflict of Interest: none declared.  ... 
doi:10.1093/bioinformatics/btu172 pmid:24713437 pmcid:PMC4103591 fatcat:howfy3q5x5blrnd6pmdmjefzyq

Characteristics of mutational signatures of unknown etiology

Xiaoju Hu, Zhuxuan Xu, Subhajyoti De
2020 NAR Cancer  
Nonetheless, remarkable progress in characterization of mutational signatures has provided fundamental insights into the biology of cancer, informed disease etiology and opened up new opportunities for  ...  Computational deconvolution of somatic mutation patterns and expert curation pan-cancer studies have identified a number of mutational signatures associated with point mutations, dinucleotide substitutions  ...  ACKNOWLEDGEMENTS The authors thank members of the Center for Systems and Computational Biology at Rutgers Cancer Institute for helpful discussions.  ... 
doi:10.1093/narcan/zcaa026 pmid:33015626 pmcid:PMC7520824 fatcat:wjquffgwgjhufh26tdlnkmv34u

Whole-Genome Sequencing in Cancer

Eric Y. Zhao, Martin Jones, Steven J.M. Jones
2018 Cold Spring Harbor Perspectives in Medicine  
Genome sequencing of cancer has fundamentally advanced our understanding of the underlying biology of this disease, and more recently has provided approaches to characterize and monitor tumors in the clinic  ...  This leads to a new paradigm in cancer management in which real-time analysis of an individual's disease can have a rapid and lasting impact on our understanding of how clinical practices need to change  ...  Meanwhile, the demand for genome-guided cancer therapy has motivated the development of N-of-One approaches to mutation signature characterization (Rosenthal et al. 2016) .  ... 
doi:10.1101/cshperspect.a034579 pmid:29844223 pmcid:PMC6396343 fatcat:liwpug46sjewfni3sgvyvm4jcq

De novo mutational signature discovery in tumor genomes using SparseSignatures

Avantika Lal, Keli Liu, Robert Tibshirani, Arend Sidow, Daniele Ramazzotti, Daniel Huebschmann
2021 PLoS Computational Biology  
Cancer is the result of mutagenic processes that can be inferred from tumor genomes by analyzing rate spectra of point mutations, or "mutational signatures".  ...  Our approach incorporates a user-specified background signature, employs regularization to reduce noise in non-background signatures, uses cross-validation to identify the number of signatures, and is  ...  List of 560 Breast cancer samples used for signature discovery.  ... 
doi:10.1371/journal.pcbi.1009119 pmid:34181655 fatcat:jpeepsddjbhjph2ddw23wntqy4

In silico frameworks for systematic pre-clinical screening of potential anti-leukemia therapeutics

Matthew H. Ung, Frederick S. Varn, Chao Cheng
2016 Expert Opinion on Drug Discovery  
Expert opinion-Today's data deluge presents novel opportunities to develop computational tools and pipelines to screen for likely therapeutic candidates in the treatment of leukemia.  ...  In particular, three approaches are discussed including molecular docking, transcriptomic integration, and network analysis.  ...  Acknowledgments Funding: This work was supported by American Cancer Society Research grant #IRG-82-003-30, the National Center for Advancing Translational Sciences of the National Institutes of Health  ... 
doi:10.1080/17460441.2016.1243524 pmid:27689915 pmcid:PMC5180445 fatcat:hkb5o4zforhd7kr4ywxc7lbum4

A mixture model for signature discovery from sparse mutation data

Itay Sason, Yuexi Chen, Mark D.M. Leiserson, Roded Sharan
2021 Genome Medicine  
In application to simulated and real gene-panel sequences, is shown to outperform current approaches and yield mutational signatures and patient stratifications that are in higher agreement with the literature  ...  AbstractMutational signatures are key to understanding the processes that shape cancer genomes, yet their analysis requires relatively rich whole-genome or whole-exome mutation data.  ...  A broad catalog of mutational signatures in cancer genomes was only recently revealed through computational analysis of mutations in thousands of tumors. Alexandrov et al.  ... 
doi:10.1186/s13073-021-00988-7 pmid:34724984 pmcid:PMC8559697 fatcat:b2xtgngi6ffdbpmdq4leyelp5e

In silico saturation mutagenesis of cancer genes [article]

Ferran Muinos, Francisco Martinez-Jimenez, Oriol Pich, Abel Gonzalez-Perez, Nuria Lopez-Bigas
2020 bioRxiv   pre-print
The number of potential driver mutations in a cancer gene roughly determines how many mutations are available for detection across newly sequenced tumors.  ...  Here, we present an in silico saturation mutagenesis approach to identify all drivermutations in 568 cancer genes across 66 tumor types.  ...  Acknowledgements We acknowledge important technical contributions to the development of the in silico saturation mutagenesis approach and to the manuscript by Loris Mularoni, Iker Reyes-Salazar, EIectra  ... 
doi:10.1101/2020.06.03.130211 fatcat:y3wnbdks3vbhlahkdsrvtpizjy

Looking beyond drivers and passengers in cancer genome sequencing data

S. De, S. Ganesan
2016 Annals of Oncology  
For instance, emerging findings show that mutational patterns in cancer genomes can help detect signatures of known and novel DNA damage and repair processes, provide a likely chronological account of  ...  In this review, we discuss these emerging approaches and unexpected breakthroughs, and their implications for basic cancer research and clinical practices.  ...  Acknowledgements We thank members of the laboratories of De and Ganesan, and also the members of the Center for Systems Biology at Rutgers Cancer Institute for comments and suggestions.  ... 
doi:10.1093/annonc/mdw677 pmid:27998972 fatcat:7dn33esmfbbd3eg6mknymo2ojm

A survey of current trends in computational drug repositioning

Jiao Li, Si Zheng, Bin Chen, Atul J. Butte, S. Joshua Swamidass, Zhiyong Lu
2015 Briefings in Bioinformatics  
Computational drug repositioning or repurposing is a promising and efficient tool for discovering new uses from existing drugs and holds the great potential for precision medicine in the age of big data  ...  In this review, we show recent advancements in the critical areas of computational drug repositioning from multiple aspects.  ...  Acknowledgment The authors would like to thank Dr Pankaj Agarwal for his helpful discussion.  ... 
doi:10.1093/bib/bbv020 pmid:25832646 pmcid:PMC4719067 fatcat:aogwknlldvhtxfct5wwmorqtk4
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