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      Subclonal phylogenetic structures in cancer revealed by ultra-deep sequencing

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          Abstract

          During the clonal expansion of cancer from an ancestral cell with an initiating oncogenic mutation to symptomatic neoplasm, the occurrence of somatic mutations (both driver and passenger) can be used to track the on-going evolution of the neoplasm. All subclones within a cancer are phylogenetically related, with the prevalence of each subclone determined by its evolutionary fitness and the timing of its origin relative to other subclones. Recently developed massively parallel sequencing platforms promise the ability to detect rare subclones of genetic variants without a priori knowledge of the mutations involved. We used ultra-deep pyrosequencing to investigate intraclonal diversification at the Ig heavy chain locus in 22 patients with B-cell chronic lymphocytic leukemia. Analysis of a non-polymorphic control locus revealed artifactual insertions and deletions resulting from sequencing errors and base substitutions caused by polymerase misincorporation during PCR amplification. We developed an algorithm to differentiate genuine haplotypes of somatic hypermutations from such artifacts. This proved capable of detecting multiple rare subclones with frequencies as low as 1 in 5000 copies and allowed the characterization of phylogenetic interrelationships among subclones within each patient. This study demonstrates the potential for ultra-deep resequencing to recapitulate the dynamics of clonal evolution in cancer cell populations.

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          Characterization of mutation spectra with ultra-deep pyrosequencing: application to HIV-1 drug resistance.

          The detection of mutant spectra within a population of microorganisms is critical for the management of drug-resistant infections. We performed ultra-deep pyrosequencing to detect minor sequence variants in HIV-1 protease and reverse transcriptase (RT) genes from clinical plasma samples. We estimated empirical error rates from four HIV-1 plasmid clones and used them to develop a statistical approach to distinguish authentic minor variants from sequencing errors in eight clinical samples. Ultra-deep pyrosequencing detected an average of 58 variants per sample compared with an average of eight variants per sample detected by conventional direct-PCR dideoxynucleotide sequencing. In the clinical sample with the largest number of minor sequence variants, all 60 variants present in > or =3% of genomes and 20 of 35 variants present in <3% of genomes were confirmed by limiting dilution sequencing. With appropriate analysis, ultra-deep pyrosequencing is a promising method for characterizing genetic diversity and detecting minor yet clinically relevant variants in biological samples with complex genetic populations.
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            Bcr-Abl kinase domain mutations, drug resistance, and the road to a cure for chronic myeloid leukemia.

            Mutations in the kinase domain (KD) of BCR-ABL are the most prevalent mechanism of acquired imatinib resistance in patients with chronic myeloid leukemia (CML). Here we examine predisposing factors underlying acquisition of KD mutations, evidence for acquisition of mutations before and during therapy, and whether the detection of a KD mutation universally implies resistance. We also provide a perspective on how the second-line Abl inhibitors dasatinib and nilotinib are faring in the treatment of imatinib-resistant CML, especially in relation to specific KD mutations. We discuss the growing importance of the multi-inhibitor-resistant 315T>I mutant and the therapeutic potential that a 315T>I inhibitor would have. Last, we assess the potential of Abl kinase inhibitor combinations to induce stable responses even in advanced CML and interpret the emerging data in the context of CML pathogenesis.
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              Methods for determining spontaneous mutation rates.

              Spontaneous mutations arise as a result of cellular processes that act upon or damage DNA. Accurate determination of spontaneous mutation rates can contribute to our understanding of these processes and the enzymatic pathways that deal with them. The methods that are used to calculate mutation rates are based on the model for the expansion of mutant clones originally described by Luria and Delbrück (1943) and extended by Lea and Coulson (1949). The accurate determination of mutation rates depends on understanding the strengths and limitations of these methods and how to optimize a fluctuation assay for a given method. This chapter describes the proper design of a fluctuation assay, several of the methods used to calculate mutation rates, and ways to evaluate the results statistically.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                September 02 2008
                September 02 2008
                August 22 2008
                September 02 2008
                : 105
                : 35
                : 13081-13086
                Article
                10.1073/pnas.0801523105
                2529122
                18723673
                0bd9c1c6-f7b9-4006-b967-0575b24d93b9
                © 2008
                History

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