Literature DB >> 34411908

Significance and limitations of the use of next-generation sequencing technologies for detecting mutational signatures.

Ammal Abbasi1, Ludmil B Alexandrov2.   

Abstract

Next generation sequencing technologies (NGS) have been critical in characterizing the genomic landscape and untangling the genetic heterogeneity of human cancer. Since its advent, NGS has played a pivotal role in identifying the patterns of somatic mutations imprinted on cancer genomes and in deciphering the signatures of the mutational processes that have generated these patterns. Mutational signatures serve as phenotypic molecular footprints of exposures to environmental factors as well as deficiency and infidelity of DNA replication and repair pathways. Since the first roadmap of mutational signatures in human cancer was generated from whole-genome and whole-exome sequencing data, there has been a growing interest to extract mutational signatures from other NGS technologies such as targeted panel sequencing, RNA sequencing, single-cell sequencing, duplex sequencing, reduced representation sequencing, and long-read sequencing. Many of these technologies have their inherent sequencing biases and produce technical artifacts that can confound the extraction of reliable and interpretable mutational signatures. In this review, we highlight the relevance, limitations, and prospects of using different NGS technologies for examining mutational patterns and for deciphering mutational signatures.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cancer genomics; Mutational signatures; Next generation sequencing

Mesh:

Year:  2021        PMID: 34411908      PMCID: PMC9478565          DOI: 10.1016/j.dnarep.2021.103200

Source DB:  PubMed          Journal:  DNA Repair (Amst)        ISSN: 1568-7856


  98 in total

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Authors:  Isaac Kinde; Jian Wu; Nick Papadopoulos; Kenneth W Kinzler; Bert Vogelstein
Journal:  Proc Natl Acad Sci U S A       Date:  2011-05-17       Impact factor: 11.205

2.  Characterizing Mutational Signatures in Human Cancer Cell Lines Reveals Episodic APOBEC Mutagenesis.

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Journal:  Cell       Date:  2019-03-07       Impact factor: 41.582

3.  p53 mutation in hepatocellular carcinoma after aflatoxin exposure.

Authors:  M Ozturk
Journal:  Lancet       Date:  1991-11-30       Impact factor: 79.321

4.  Ultra-deep sequencing detects ovarian cancer cells in peritoneal fluid and reveals somatic TP53 mutations in noncancerous tissues.

Authors:  Jeffrey D Krimmel; Michael W Schmitt; Maria I Harrell; Kathy J Agnew; Scott R Kennedy; Mary J Emond; Lawrence A Loeb; Elizabeth M Swisher; Rosa Ana Risques
Journal:  Proc Natl Acad Sci U S A       Date:  2016-05-05       Impact factor: 11.205

5.  signeR: an empirical Bayesian approach to mutational signature discovery.

Authors:  Rafael A Rosales; Rodrigo D Drummond; Renan Valieris; Emmanuel Dias-Neto; Israel T da Silva
Journal:  Bioinformatics       Date:  2016-09-01       Impact factor: 6.937

6.  Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance.

Authors:  Lovelace J Luquette; Craig L Bohrson; Max A Sherman; Peter J Park
Journal:  Nat Commun       Date:  2019-08-29       Impact factor: 14.919

Review 7.  Mutational signatures: experimental design and analytical framework.

Authors:  Gene Koh; Xueqing Zou; Serena Nik-Zainal
Journal:  Genome Biol       Date:  2020-02-14       Impact factor: 13.583

8.  Breast tumours maintain a reservoir of subclonal diversity during expansion.

Authors:  Darlan C Minussi; Michael D Nicholson; Hanghui Ye; Alexander Davis; Kaile Wang; Toby Baker; Maxime Tarabichi; Emi Sei; Haowei Du; Mashiat Rabbani; Cheng Peng; Min Hu; Shanshan Bai; Yu-Wei Lin; Aislyn Schalck; Asha Multani; Jin Ma; Thomas O McDonald; Anna Casasent; Angelica Barrera; Hui Chen; Bora Lim; Banu Arun; Funda Meric-Bernstam; Peter Van Loo; Franziska Michor; Nicholas E Navin
Journal:  Nature       Date:  2021-03-24       Impact factor: 69.504

9.  Single-cell analysis reveals different age-related somatic mutation profiles between stem and differentiated cells in human liver.

Authors:  K Brazhnik; S Sun; O Alani; M Kinkhabwala; A W Wolkoff; A Y Maslov; X Dong; J Vijg
Journal:  Sci Adv       Date:  2020-01-31       Impact factor: 14.136

10.  Pan-cancer landscape of homologous recombination deficiency.

Authors:  Luan Nguyen; John W M Martens; Arne Van Hoeck; Edwin Cuppen
Journal:  Nat Commun       Date:  2020-11-04       Impact factor: 14.919

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  2 in total

Review 1.  An overview of mutational and copy number signatures in human cancer.

Authors:  Christopher D Steele; Nischalan Pillay; Ludmil B Alexandrov
Journal:  J Pathol       Date:  2022-05-20       Impact factor: 9.883

2.  Two subtypes of cutaneous melanoma with distinct mutational signatures and clinico-genomic characteristics.

Authors:  Yoon-Seob Kim; Minho Lee; Yeun-Jun Chung
Journal:  Front Genet       Date:  2022-09-29       Impact factor: 4.772

  2 in total

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