Journal articles on the topic 'Mutational mechanisms'
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Antić, Željko, Stefan H. Lelieveld, Cédric G. van der Ham, Edwin Sonneveld, Peter M. Hoogerbrugge, and Roland P. Kuiper. "Unravelling the Sequential Interplay of Mutational Mechanisms during Clonal Evolution in Relapsed Pediatric Acute Lymphoblastic Leukemia." Genes 12, no. 2 (February 2, 2021): 214. http://dx.doi.org/10.3390/genes12020214.
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Pediatric acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy and is characterized by clonal heterogeneity. Genomic mutations can increase proliferative potential of leukemic cells and cause treatment resistance. However, mechanisms driving mutagenesis and clonal diversification in ALL are not fully understood. In this proof of principle study, we performed whole genome sequencing of two cases with multiple relapses in order to investigate whether groups of mutations separated in time show distinct mutational signatures. Based on mutation allele frequencies at diagnosis and subsequent relapses, we clustered mutations into groups and performed cluster-specific mutational profile analysis and de novo signature extraction. In patient 1, who experienced two relapses, the analysis unraveled a continuous interplay of aberrant activation induced cytidine deaminase (AID)/apolipoprotein B editing complex (APOBEC) activity. The associated signatures SBS2 and SBS13 were present already at diagnosis, and although emerging mutations were lost in later relapses, the process remained active throughout disease evolution. Patient 2 had three relapses. We identified episodic mutational processes at diagnosis and first relapse leading to mutations resembling ultraviolet light-driven DNA damage, and thiopurine-associated damage at first relapse. In conclusion, our data shows that investigation of mutational processes in clusters separated in time may aid in understanding the mutational mechanisms and discovery of underlying causes.
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Kim, Yoo-Ah, Mark D. M. Leiserson, Priya Moorjani, Roded Sharan, Damian Wojtowicz, and Teresa M. Przytycka. "Mutational Signatures: From Methods to Mechanisms." Annual Review of Biomedical Data Science 4, no. 1 (July 20, 2021): 189–206. http://dx.doi.org/10.1146/annurev-biodatasci-122320-120920.
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Mutations are the driving force of evolution, yet they underlie many diseases, in particular, cancer. They are thought to arise from a combination of stochastic errors in DNA processing, naturally occurring DNA damage (e.g., the spontaneous deamination of methylated CpG sites), replication errors, and dysregulation of DNA repair mechanisms. High-throughput sequencing has made it possible to generate large datasets to study mutational processes in health and disease. Since the emergence of the first mutational process studies in 2012, this field is gaining increasing attention and has already accumulated a host of computational approaches and biomedical applications.
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Dunson, David B., and Kenneth R. Tindall. "Bayesian Analysis of Mutational Spectra." Genetics 156, no. 3 (November 1, 2000): 1411–18. http://dx.doi.org/10.1093/genetics/156.3.1411.
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Abstract Studies that examine both the frequency of gene mutation and the pattern or spectrum of mutational changes can be used to identify chemical mutagens and to explore the molecular mechanisms of mutagenesis. In this article, we propose a Bayesian hierarchical modeling approach for the analysis of mutational spectra. We assume that the total number of independent mutations and the numbers of mutations falling into different response categories, defined by location within a gene and/or type of alteration, follow binomial and multinomial sampling distributions, respectively. We use prior distributions to summarize past information about the overall mutation frequency and the probabilities corresponding to the different mutational categories. These priors can be chosen on the basis of data from previous studies using an approach that accounts for heterogeneity among studies. Inferences about the overall mutation frequency, the proportions of mutations in each response category, and the category-specific mutation frequencies can be based on posterior distributions, which incorporate past and current data on the mutant frequency and on DNA sequence alterations. Methods are described for comparing groups and for assessing doserelated trends. We illustrate our approach using data from the literature.
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Rainey, P., and R. Moxon. "Unusual mutational mechanisms and evolution." Science 260, no. 5116 (June 25, 1993): 1958–60. http://dx.doi.org/10.1126/science.8316837.
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Hurst, L., and A. Grafen. "Unusual mutational mechanisms and evolution." Science 260, no. 5116 (June 25, 1993): 1959–60. http://dx.doi.org/10.1126/science.8316838.
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Watson, D. "Unusual mutational mechanisms and evolution." Science 260, no. 5116 (June 25, 1993): 1958–59. http://dx.doi.org/10.1126/science.8391167.
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Auerbach, Scott S., Miaofei Xu, B. Alex Merrick, Mark J. Hoenerhoff, Dhiral Phadke, Debra J. Taxman, Ruchir Shah, et al. "Exome Sequencing of Fresh-frozen or Formalin-fixed Paraffin-embedded B6C3F1/N Mouse Hepatocellular Carcinomas Arising Either Spontaneously or due to Chronic Chemical Exposure." Toxicologic Pathology 46, no. 6 (July 25, 2018): 706–18. http://dx.doi.org/10.1177/0192623318789398.
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Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide; however, the mutational properties of HCC-associated carcinogens remain largely uncharacterized. We hypothesized that mechanisms underlying chemical-induced HCC can be characterized by evaluating the mutational spectra of these tumors. To test this hypothesis, we performed exome sequencing of B6C3F1/N HCCs that arose either spontaneously in vehicle controls ( n = 3) or due to chronic exposure to gingko biloba extract (GBE; n = 4) or methyleugenol (MEG; n = 3). Most archived tumor samples are available as formalin-fixed paraffin-embedded (FFPE) blocks, rather than fresh-frozen (FF) samples; hence, exome sequencing from paired FF and FFPE samples was compared. FF and FFPE samples showed 63% to 70% mutation concordance. Multiple known (e.g., Ctnnb1T41A, BrafV637E) and novel (e.g., Erbb4C559S, Card10A700V, and Klf11P358L) mutations in cancer-related genes were identified. The overall mutational burden was greater for MEG than for GBE or spontaneous HCC samples. To characterize the mutagenic mechanisms, we analyzed the mutational spectra in the HCCs according to their trinucleotide motifs. The MEG tumors clustered closest to Catalogue of Somatic Mutations in Cancer signatures 4 and 24, which are, respectively, associated with benzo(a)pyrene- and aflatoxin-induced HCCs in humans. These results establish a novel approach for classifying liver carcinogens and understanding the mechanisms of hepatocellular carcinogenesis.
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Balamurugan, Kuppareddi, Martin L. Tracey, Uwe Heine, George C. Maha, and George T. Duncan. "Mutation at the Human D1S80 Minisatellite Locus." Scientific World Journal 2012 (2012): 1–8. http://dx.doi.org/10.1100/2012/917235.
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Little is known about the general biology of minisatellites. The purpose of this study is to examine repeat mutations from the D1S80 minisatellite locus by sequence analysis to elucidate the mutational process at this locus. This is a highly polymorphic minisatellite locus, located in the subtelomeric region of chromosome 1. We have analyzed 90,000 human germline transmission events and found seven (7) mutations at this locus. The D1S80 alleles of the parentage trio, the child, mother, and the alleged father were sequenced and the origin of the mutation was determined. Using American Association of Blood Banks (AABB) guidelines, we found a male mutation rate of1.04×10-4and a female mutation rate of5.18×10-5with an overall mutation rate of approximately7.77×10-5. Also, in this study, we found that the identified mutations are in close proximity to the center of the repeat array rather than at the ends of the repeat array. Several studies have examined the mutational mechanisms of the minisatellites according to infinite allele model (IAM) and the one-step stepwise mutation model (SMM). In this study, we found that this locus fits into the one-step mutation model (SMM) mechanism in six out of seven instances similar to STR loci.
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Pálinkás, Hajnalka Laura, Lőrinc Pongor, Máté Balajti, Ádám Nagy, Kinga Nagy, Angéla Békési, Giampaolo Bianchini, Beáta G. Vértessy, and Balázs Győrffy. "Primary Founder Mutations in the PRKDC Gene Increase Tumor Mutation Load in Colorectal Cancer." International Journal of Molecular Sciences 23, no. 2 (January 6, 2022): 633. http://dx.doi.org/10.3390/ijms23020633.
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The clonal composition of a malignant tumor strongly depends on cellular dynamics influenced by the asynchronized loss of DNA repair mechanisms. Here, our aim was to identify founder mutations leading to subsequent boosts in mutation load. The overall mutation burden in 591 colorectal cancer tumors was analyzed, including the mutation status of DNA-repair genes. The number of mutations was first determined across all patients and the proportion of genes having mutation in each percentile was ranked. Early mutations in DNA repair genes preceding a mutational expansion were designated as founder mutations. Survival analysis for gene expression was performed using microarray data with available relapse-free survival. Of the 180 genes involved in DNA repair, the top five founder mutations were in PRKDC (n = 31), ATM (n = 26), POLE (n = 18), SRCAP (n = 18), and BRCA2 (n = 15). PRKDC expression was 6.4-fold higher in tumors compared to normal samples, and higher expression led to longer relapse-free survival in 1211 patients (HR = 0.72, p = 4.4 × 10−3). In an experimental setting, the mutational load resulting from UV radiation combined with inhibition of PRKDC was analyzed. Upon treatments, the mutational load exposed a significant two-fold increase. Our results suggest PRKDC as a new key gene driving tumor heterogeneity.
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Walker, Brian A., Christopher P. Wardell, Lorenzo Melchor, Sanna Hulkki, Nicola E. Potter, David C. Johnson, Kerry Fenwick, et al. "Intraclonal heterogeneity and distinct molecular mechanisms characterize the development of t(4;14) and t(11;14) myeloma." Blood 120, no. 5 (August 2, 2012): 1077–86. http://dx.doi.org/10.1182/blood-2012-03-412981.
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Abstract We have used whole exome sequencing to compare a group of presentation t(4;14) with t(11;14) cases of myeloma to define the mutational landscape. Each case was characterized by a median of 24.5 exonic nonsynonymous single-nucleotide variations, and there was a consistently higher number of mutations in the t(4;14) group, but this number did not reach statistical significance. We show that the transition and transversion rates in the 2 subgroups are similar, suggesting that there was no specific mechanism leading to mutation differentiating the 2 groups. Only 3% of mutations were seen in both groups, and recurrently mutated genes include NRAS, KRAS, BRAF, and DIS3 as well as DNAH5, a member of the axonemal dynein family. The pattern of mutation in each group was distinct, with the t(4;14) group being characterized by deregulation of chromatin organization, actin filament, and microfilament movement. Recurrent RAS pathway mutations identified subclonal heterogeneity at a mutational level in both groups, with mutations being present as either dominant or minor subclones. The presence of subclonal diversity was confirmed at a single-cell level using other tumor-acquired mutations. These results are consistent with a distinct molecular pathogenesis underlying each subgroup and have important impacts on targeted treatment strategies. The Medical Research Council Myeloma IX trial is registered under ISRCTN68454111.
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Frieder, Darina, Mani Larijani, Ephraim Tang, Jahan-Yar Parsa, Wajiha Basit, and Alberto Martin. "Antibody Diversification: Mutational Mechanisms and Oncogenesis." Immunologic Research 35, no. 1-2 (2006): 75–88. http://dx.doi.org/10.1385/ir:35:1:75.
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Golding, G. Brian, Patricia J. Gearhart, and Barry W. Glickman. "Patterns of Somatic Mutations in Immunoglobulin Variable Genes." Genetics 115, no. 1 (January 1, 1987): 169–76. http://dx.doi.org/10.1093/genetics/115.1.169.
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ABSTRACT The mechanism responsible for somatic mutation in the variable genes of antibodies is unknown and may differ from previously described mechanisms that produce mutation in DNA. We have analyzed 421 somatic mutations from the rearranged immunoglobulin variable genes of mice to determine (1) if the nucleotide substitutions differ from those generated during meiosis and (2) if the presence of nearby direct and inverted repeated sequences could template mutations around the variable gene. The results reveal a difference in the pattern of substitutions obtained from somatic mutations vs. meiotic mutations. An increased frequency of T:A to C:G transitions and a decreased frequency of mutations involving a G in the somatic mutants compared to the meiotic mutants is indicated. This suggests that the mutational processes responsible for somatic mutation in antibody genes differs from that responsible for mutation during meiosis. An analysis of the local DNA sequences revealed many direct repeats and palindromic sequences that were capable of templating some of the known mutations. Although additional factors may be involved in targeting mutations to the variable gene, mistemplating by nearby repeats may provide a mechanism for the enhancement of somatic mutation.
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Coleman, W. B., and G. J. Tsongalis. "Multiple mechanisms account for genomic instability and molecular mutation in neoplastic transformation." Clinical Chemistry 41, no. 5 (May 1, 1995): 644–57. http://dx.doi.org/10.1093/clinchem/41.5.644.
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Abstract Neoplastic cells typically possess numerous genomic mutations and chromosomal aberrations, including point mutations, gene amplifications and deletions, and replication errors. Acquisition of such genomic instability may represent an early step in the process of carcinogenesis. Proteins involved in DNA replication, DNA repair, cell cycle progression, and others are all components of complex overlapping biochemical pathways that function to maintain cellular homeostasis. Therefore, mutational alteration of genes encoding proteins involved in these cellular processes could contribute to genomic instability. Loss of normal cellular mechanisms that guard against genomic mutation and the ensuing genomic instability might lead to accumulation of multiple stable mutations in the genome of affected cells, perhaps resulting in neoplastic transformation when some critical number of transformation-related target genes become damaged. Thus, interactions of fundamental cellular processes play significant roles in sustaining cellular normality, and alteration of any of these homeostatic processes could entrain cells to the progressive genomic instability and phenotypic evolution characteristic of carcinogenesis. Here, we discuss possible molecular mechanisms governing DNA mutation and genomic instability in genetically normal cells that might account for the acquisition of genomic instability in somatic cells, leading to the development of neoplasia. These include (a) molecular alteration of genes encoding DNA repair enzymes, (b) molecular alteration of genes responsible for cell-cycle control mechanisms, and (c) direct molecular alteration of dominantly transforming cellular protooncogenes. We also discuss normal cellular processes involved with DNA replication and repair that can contribute to the mutational alteration of critical genes: e.g., slow repair of damaged DNA in specific genes, and the timing of normal gene-specific replication.
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Hancock, R. L. "Theoretical mechanisms for synthesis of carcinogen-induced embryonic proteins: XIV mutational and non-mutational mechanisms as subsets of a more general mechanism. Part C — A defined cancer mutation." Medical Hypotheses 18, no. 3 (November 1985): 199–206. http://dx.doi.org/10.1016/0306-9877(85)90025-8.
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Blanco, Paula, Fernando Corona, and José Luis Martinez. "Mechanisms and phenotypic consequences of acquisition of tigecycline resistance by Stenotrophomonas maltophilia." Journal of Antimicrobial Chemotherapy 74, no. 11 (August 1, 2019): 3221–30. http://dx.doi.org/10.1093/jac/dkz326.
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Abstract Objectives To elucidate the potential mutation-driven mechanisms involved in the acquisition of tigecycline resistance by the opportunistic pathogen Stenotrophomonas maltophilia. The mutational trajectories and their effects on bacterial fitness, as well as cross-resistance and/or collateral susceptibility to other antibiotics, were also addressed. Methods S. maltophilia populations were submitted to experimental evolution in the presence of increasing concentrations of tigecycline for 30 days. The genetic mechanisms involved in the acquisition of tigecycline resistance were determined by WGS. Resistance was evaluated by performing MIC assays. Fitness of the evolved populations and individual clones was assessed by measurement of the maximum growth rates. Results All the tigecycline-evolved populations attained high-level resistance to tigecycline following different mutational trajectories, yet with some common elements. Among the mechanisms involved in low susceptibility to tigecycline, mutations in the SmeDEF efflux pump negative regulator smeT, changes in proteins involved in the biogenesis of the ribosome and modifications in the LPS biosynthesis pathway seem to play a major role. Besides tigecycline resistance, the evolved populations presented cross-resistance to other antibiotics, such as aztreonam and quinolones, and they were hypersusceptible to fosfomycin, suggesting a possible combination treatment. Further, we found that the selected resistance mechanisms impose a relevant fitness cost when bacteria grow in the absence of antibiotic. Conclusions Mutational resistance to tigecycline was easily selected during exposure to this antibiotic. However, the fitness cost may compromise the maintenance of S. maltophilia tigecycline-resistant populations in the absence of antibiotic.
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Otsubo, Yuki, Shoji Matsumura, Naohiro Ikeda, and Osamu Morita. "Hawk-Seq™ differentiates between various mutations in Salmonella typhimurium TA100 strain caused by exposure to Ames test-positive mutagens." Mutagenesis 36, no. 3 (February 16, 2021): 245–54. http://dx.doi.org/10.1093/mutage/geab006.
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Abstract A precise understanding of differences in genomic mutations according to the mutagenic mechanisms detected in mutagenicity data is required to evaluate the carcinogenicity of environmental mutagens. Recently, we developed a highly accurate genome sequencing method, ‘Hawk-Seq™’, that enables the detection of mutagen-induced genome-wide mutations. However, its applicability to detect various mutagens and identify differences in mutational profiles is not well understood. Thus, we evaluated DNA samples from Salmonella typhimurium TA100 exposed to 11 mutagens, including alkylating agents, aldehydes, an aromatic nitro compound, epoxides, aromatic amines and polycyclic aromatic hydrocarbons (PAHs). We extensively analysed mutagen-induced mutational profiles and studied their association with the mechanisms of mutagens. Hawk-Seq™ sensitively detected mutations induced by all 11 mutagens, including one that increased the number of revertants by approximately 2-fold in the Ames test. Although the sensitivity for less water-soluble mutagens was relatively low, we increased the sensitivity to obtain high-resolution spectra by modifying the exposure protocol. Moreover, two epoxides indicated similar 6- or 96-dimensional mutational patterns; likewise, three SN1-type alkylating agents indicated similar mutational patterns, suggesting that the mutational patterns are compound category specific. Meanwhile, an SN2 type alkylating agent exhibited unique mutational patterns compared to those of the SN1 type alkylating agents. Although the mutational patterns induced by aldehydes, the aromatic nitro compound, aromatic amines and PAHs did not differ substantially from each other, the maximum total base substitution frequencies (MTSFs) were similar among mutagens in the same structural groups. Furthermore, the MTSF was found to be associated with the carcinogenic potency of some direct-acting mutagens. These results indicate that our method can generate high-resolution mutational profiles to identify characteristic features of each mutagen. The detailed mutational data obtained by Hawk-Seq™ can provide useful information regarding mutagenic mechanisms and help identify its association with the carcinogenicity of mutagens without requiring carcinogenicity data.
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Zhang, Cheng-Zhong, and David Pellman. "From Mutational Mechanisms in Single Cells to Mutational Patterns in Cancer Genomes." Cold Spring Harbor Symposia on Quantitative Biology 80 (2015): 117–37. http://dx.doi.org/10.1101/sqb.2015.80.027623.
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Herzog, Mareike, Elisa Alonso-Perez, Israel Salguero, Jonas Warringer, David J. Adams, Stephen P. Jackson, and Fabio Puddu. "Mutagenic mechanisms of cancer-associated DNA polymerase ϵ alleles." Nucleic Acids Research 49, no. 7 (March 25, 2021): 3919–31. http://dx.doi.org/10.1093/nar/gkab160.
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Abstract A single amino acid residue change in the exonuclease domain of human DNA polymerase ϵ, P286R, is associated with the development of colorectal cancers, and has been shown to impart a mutator phenotype. The corresponding Pol ϵ allele in the yeast Saccharomyces cerevisiae (pol2-P301R), was found to drive greater mutagenesis than an entirely exonuclease-deficient Pol ϵ (pol2–4), an unexpected phenotype of ultra-mutagenesis. By studying the impact on mutation frequency, type, replication-strand bias, and sequence context, we show that ultra-mutagenesis is commonly observed in yeast cells carrying a range of cancer-associated Pol ϵ exonuclease domain alleles. Similarities between mutations generated by these alleles and those generated in pol2–4 cells indicate a shared mechanism of mutagenesis that yields a mutation pattern similar to cancer Signature 14. Comparison of POL2 ultra-mutator with pol2-M644G, a mutant in the polymerase domain decreasing Pol ϵ fidelity, revealed unexpected analogies in the sequence context and strand bias of mutations. Analysis of mutational patterns unique to exonuclease domain mutant cells suggests that backtracking of the polymerase, when the mismatched primer end cannot be accommodated in the proofreading domain, results in the observed insertions and T>A mutations in specific sequence contexts.
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Luo, Yue, Karen E. Hermetz, Jodi M. Jackson, Jennifer G. Mulle, Anne Dodd, Karen D. Tsuchiya, Blake C. Ballif, et al. "Diverse mutational mechanisms cause pathogenic subtelomeric rearrangements." Human Molecular Genetics 20, no. 19 (July 4, 2011): 3769–78. http://dx.doi.org/10.1093/hmg/ddr293.
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Helleday, Thomas, Saeed Eshtad, and Serena Nik-Zainal. "Mechanisms underlying mutational signatures in human cancers." Nature Reviews Genetics 15, no. 9 (July 1, 2014): 585–98. http://dx.doi.org/10.1038/nrg3729.
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Bayés, Mònica, Luis F. Magano, Núria Rivera, Raquel Flores, and Luis A. Pérez Jurado. "Mutational Mechanisms of Williams-Beuren Syndrome Deletions." American Journal of Human Genetics 73, no. 1 (July 2003): 131–51. http://dx.doi.org/10.1086/376565.
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Ota, Rissa, and David Penny. "Estimating Changes in Mutational Mechanisms of Evolution." Journal of Molecular Evolution 57 (August 1, 2003): S233—S240. http://dx.doi.org/10.1007/s00239-003-0032-1.
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Glickman, Barry W. "Mutational specificity and the influence of excision repair: insights into the mechanisms of error-avoidance and error-fixation." Genome 31, no. 2 (January 15, 1989): 584–89. http://dx.doi.org/10.1139/g89-108.
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The excision repair process controlled by the uvrABC gene in Escherichia coli is the major pathway for the repair of a diverse series of DNA damages. To achieve a better understanding of the mechanics of this repair pathway and its impact upon mutagenesis, we have applied a recently developed technology by which the nature of mutation is determined at the DNA sequence level. A comparison of the classes and distribution of mutation in excision–repair-proficient and excision–repair-deficient strains of E. coli reveals that the absence of excision repair can alter both the nature of the mutations recovered as well as their distribution. This can occur in one of several ways. For example, under some circumstances the action of the UvrABC pathway can lead to interruptions of DNA strand continuity and an enhancement of both frameshift and deletion events. Such an effect is seen following damage by psoralen plus near UV (PUVA) treatment that produces cross-links in the DNA. In comparison, several other treatments produce similar distributions within the classes of mutations recovered but demonstrate an alteration in site specificity. Such is the case following UV irradiation. In this case, the data indicate that while the premutagenic lesions may be the same, mutation fixation in the presence and absence of excision repair may involve different mechanisms. Similarly, evidence from the repair of damage by ethylating agents indicates that while the nature of the mutations recovered is not altered, the preferred location of these events is altered in the absence of excision repair. These results indicate that local DNA sequence can affect on the efficiency of excision repair. The described studies demonstrate the potential use of mutational specificity studies to better understand the mechanisms of mutation fixation and mutation avoidance.Key words: mutational specificity, excision repair, alkylation, mutagenesis, UV, PUVA treatment, DNA sequence context effects, neighbouring base inferences.
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Matsutani, Taro, Yuki Ueno, Tsukasa Fukunaga, and Michiaki Hamada. "Discovering novel mutation signatures by latent Dirichlet allocation with variational Bayes inference." Bioinformatics 35, no. 22 (April 16, 2019): 4543–52. http://dx.doi.org/10.1093/bioinformatics/btz266.
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Abstract Motivation A cancer genome includes many mutations derived from various mutagens and mutational processes, leading to specific mutation patterns. It is known that each mutational process leads to characteristic mutations, and when a mutational process has preferences for mutations, this situation is called a ‘mutation signature.’ Identification of mutation signatures is an important task for elucidation of carcinogenic mechanisms. In previous studies, analyses with statistical approaches (e.g. non-negative matrix factorization and latent Dirichlet allocation) revealed a number of mutation signatures. Nonetheless, strictly speaking, these existing approaches employ an ad hoc method or incorrect approximation to estimate the number of mutation signatures, and the whole picture of mutation signatures is unclear. Results In this study, we present a novel method for estimating the number of mutation signatures—latent Dirichlet allocation with variational Bayes inference (VB-LDA)—where variational lower bounds are utilized for finding a plausible number of mutation patterns. In addition, we performed cluster analyses for estimated mutation signatures to extract novel mutation signatures that appear in multiple primary lesions. In a simulation with artificial data, we confirmed that our method estimated the correct number of mutation signatures. Furthermore, applying our method in combination with clustering procedures for real mutation data revealed many interesting mutation signatures that have not been previously reported. Availability and implementation All the predicted mutation signatures with clustering results are freely available at http://www.f.waseda.jp/mhamada/MS/index.html. All the C++ source code and python scripts utilized in this study can be downloaded on the Internet (https://github.com/qkirikigaku/MS_LDA). Supplementary information Supplementary data are available at Bioinformatics online.
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Lambert, I. B., A. J. Gordon, B. W. Glickman, and D. R. McCalla. "The influence of local DNA sequence and DNA repair background on the mutational specificity of 1-nitroso-8-nitropyrene in Escherichia coli: inferences for mutagenic mechanisms." Genetics 132, no. 4 (December 1, 1992): 911–27. http://dx.doi.org/10.1093/genetics/132.4.911.
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Abstract We have examined the mutational specificity of 1-nitroso-8-nitropyrene (1,8-NONP), an activated metabolite of the carcinogen 1,8-dinitropyrene, in the lacI gene of Escherichia coli strains which differ with respect to nucleotide excision repair (+/- delta uvrB) and MucA/B-mediated error-prone translesion synthesis (+/- pKM101). Several different classes of mutation were recovered, of which frameshifts, base substitutions, and deletions were clearly induced by 1,8-NONP treatment. The high proportion of point mutations (> 92%) which occurred at G.C sites correlates with the percentage of 1,8-NONP-DNA adducts which occur at the C(8) position of guanine. The most prominent frameshift mutations were -(G.C) events, which were induced by 1,8-NONP treatment in all strains, occurred preferentially in runs of guanine residues, and whose frequency increased markedly with the length of the reiterated sequence. Of the base substitution mutations G.C-->T.A transversions were induced to the greatest extent by 1,8-NONP. The distribution of the G.C-->T.A transversions was not influenced by the nature of flanking bases, nor was there a strand preference for these events. The presence of plasmid pKM101 specifically increased the frequency of G.C-->T.A transversions by a factor of 30-60. In contrast, the -(G.C) frameshift mutation frequency was increased only 2-4-fold in strains harboring pKM101 as compared to strains lacking this plasmid. There was, however, a marked influence of pKM101 on the strand specificity of frameshift mutation; a preference was observed for -G events on the transcribed strand. The ability of the bacteria to carry out nucleotide excision repair had a strong effect on the frequency of all classes of mutation but did not significantly influence either the overall distribution of mutational classes or the strand specificity of G.C-->T.A transversions and -(G.C) frameshifts. Deletion mutations were induced in the delta uvr, pKM101 strain. The endpoints of the majority of the deletion mutations were G.C rich and contained regions of considerable homology. The specificity of 1,8-NONP-induced mutation suggests that DNA containing 1,8-NONP adducts can be processed through different mutational pathways depending on the DNA sequence context of the adduct and the DNA repair background of the cell.
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Olafsson, S., R. E. McIntyre, T. Coorens, T. Butler, P. Robinson, H. Lee-Six, M. Sanders, et al. "DOP50 The landscape of somatic mutations in non-neoplastic IBD-affected colon." Journal of Crohn's and Colitis 14, Supplement_1 (January 2020): S088—S089. http://dx.doi.org/10.1093/ecco-jcc/jjz203.089.
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Abstract Background Under normal physiological conditions, colonic crypts accrue ~40 somatic mutations for every year of life. That somatic mutations contribute to the development of cancer is well established, but their patterns, burden and functional consequences in diseases other than cancer have not been extensively studied and our understanding of the effects of chronic inflammation on the mutational profile and clonal structure of the colon is limited. Here, we investigated how the recurrent cycles of inflammation, ulceration and regeneration seen in IBD impact the mutational and clonal structure of intestinal epithelia. Methods We isolated and whole-genome sequenced ~400 individual colonic crypts from 46 IBD patients and compared these to ~400 crypts from 41 non-IBD controls. We compared the mutation burden, mutational signature exposure, clonal structure and cancer driver mutation landscape in crypts from actively and previously inflamed regions with crypts dissected from controls. Results We estimated the base substitution rate of affected colonic epithelial cells to be doubled after IBD onset. This change was primarily driven by acceleration of mutational processes ubiquitously observed in normal colon (Figure 1), and we did not detect an IBD-specific mutational process. In contrast to the normal colon, where clonal expansions outside the confines of the crypt are rare, we observed widespread millimetre-scale clonal expansions, even in the absence of mutations in KRAS, TP53 and APC (Figure 2). We discovered that mutations in ARID1A, PIGR and ZC3H12A, and genes in the interleukin 17 and Toll-like receptor pathways, were under positive selection in colonic crypts from IBD patients (Figure 3). With the exception of ARID1A, these genes and pathways have not been previously associated with cancer risk. A previously published mouse model of ZC3H12A suggests that LoF mutations in this gene may facilitate healing of affected mucosa without promoting tumorigenesis. This could make the encoded protein an attractive drug target. The observed enrichment of mutations in PIGR and IL17 and TLR pathways suggests that somatic mutations may initiate, maintain or perpetuate IBD pathogenesis through disruption of microbe-epithelial homeostasis. Conclusion Our results provide new insights into the consequences of chronic intestinal inflammation on the mutational profile and clonal structure of colonic epithelia. We identify the mutagens driving the increase in mutation burden and mutations which are under positive selection in the context of inflammation. Our results suggest that studying somatic mutations in the colon can reveal putative drug targets and pathogenic mechanisms for IBD.
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Verkhivker, Gennady. "Conformational Flexibility and Local Frustration in the Functional States of the SARS-CoV-2 Spike B.1.1.7 and B.1.351 Variants: Mutation-Induced Allosteric Modulation Mechanism of Functional Dynamics and Protein Stability." International Journal of Molecular Sciences 23, no. 3 (January 31, 2022): 1646. http://dx.doi.org/10.3390/ijms23031646.
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Structural and functional studies of the SARS-CoV-2 spike proteins have recently determined distinct functional states of the B.1.1.7 and B.1.351 spike variants, providing a molecular framework for understanding the mechanisms that link the effect of mutations with the enhanced virus infectivity and transmissibility. A detailed dynamic and energetic analysis of these variants was undertaken in the present work to quantify the effects of different mutations on functional conformational changes and stability of the SARS-CoV-2 spike protein. We employed the efficient and accurate coarse-grained (CG) simulations of multiple functional states of the D614G mutant, B.1.1.7 and B.1.351 spike variants to characterize conformational dynamics of the SARS-CoV-2 spike proteins and identify dynamic signatures of the functional regions that regulate transitions between the closed and open forms. By combining molecular simulations with full atomistic reconstruction of the trajectories and the ensemble-based mutational frustration analysis, we characterized how the intrinsic flexibility of specific spike regions can control functional conformational changes required for binding with the host-cell receptor. Using the residue-based mutational scanning of protein stability, we determined protein stability hotspots and identified potential energetic drivers favoring the receptor-accessible open spike states for the B.1.1.7 and B.1.351 spike variants. The results suggested that modulation of the energetic frustration at the inter-protomer interfaces can serve as a mechanism for allosteric couplings between mutational sites and the inter-protomer hinges of functional motions. The proposed mechanism of mutation-induced energetic frustration may result in greater adaptability and the emergence of multiple conformational states in the open form. This study suggested that SARS-CoV-2 B.1.1.7 and B.1.351 variants may leverage the intrinsic plasticity of functional regions in the spike protein for mutation-induced modulation of protein dynamics and allosteric regulation to control binding with the host cell receptor.
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Gowers, Kate H., Sarah E. Clarke, Ayu Hutami Syaraf, Kenichi Yoshida, Moritz J. Przybilla, Hugh Selway, Adam Pennycuick, Peter J. Campbell, and Sam M. Janes. "Abstract 3158: Defining the mechanisms that lead to mutational heterogeneity in the normal respiratory epithelium." Cancer Research 82, no. 12_Supplement (June 15, 2022): 3158. http://dx.doi.org/10.1158/1538-7445.am2022-3158.
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Abstract It is well established that tobacco smoking causes lung cancer and this is thought to be the result of a progressive accumulation of genomic mutations induced by tobacco smoke exposure; however, until recently a detailed understanding of the effects of smoke exposure on the genomes of cells in the normal bronchial epithelium was lacking. To address this, we defined the genomic architecture of normal airway basal cells in children and non-smoking, smoking and ex-smoking adults. We discovered two populations of basal cells in individuals with a smoking history: those with high mutational burden, driver gene mutations and tobacco-associated mutational signatures, and those with low mutational burden, similar to basal cells from never smokers and with an absence of mutational signatures associated with tobacco exposure. These cells expand preferentially in ex-smokers, accounting for 20-40% of basal cells compared with 2-5% in current smokers. We hypothesise that these cells are cancer-protective and their expansion reduces the risk of lung cancer development after smoking cessation. Understanding the functional differences between high- and low-mutant airway basal cells and the mechanisms by which some cells resist the accumulation of smoking-induced mutations will be crucial to understanding the earliest stages of lung carcinogenesis. To address this, we performed RNAseq on a subset of whole-genome sequenced airway basal cells. Preliminary data show that expression of markers of stemness is significantly different between high- and low-mutant basal cells. In addition, initial analysis shows that pathways such as carcinogen metabolism and MHC class I antigen presentation are higher in high-mutant basal cells. Further analysis in more patients is ongoing. To complement these data, we expanded whole-genome sequenced basal cell clones in culture and performed a range of assays to assess their progenitor and differentiation capacity. We assessed proliferation, colony-forming efficiency, longevity and differentiation and found no apparent differences between low- and high-mutant basal cells. Initial analysis suggests that carcinogen metabolism and MHC class I antigen presentation may be key pathways in establishing heterogeneity in mutational burden and clonal dynamics in the normal airway epithelium. Additional assays and analysis are ongoing and will be the focus of future research. Citation Format: Kate H. Gowers, Sarah E. Clarke, Ayu Hutami Syaraf, Kenichi Yoshida, Moritz J. Przybilla, Hugh Selway, Adam Pennycuick, Peter J. Campbell, Sam M. Janes. Defining the mechanisms that lead to mutational heterogeneity in the normal respiratory epithelium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3158.
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Shinagawa, Jun, Hideaki Moteki, Shin-ya Nishio, Yoshihiro Noguchi, and Shin-ichi Usami. "Haplotype Analysis of GJB2 Mutations: Founder Effect or Mutational Hot Spot?" Genes 11, no. 3 (February 27, 2020): 250. http://dx.doi.org/10.3390/genes11030250.
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The GJB2 gene is the most frequent cause of congenital or early onset hearing loss worldwide. In this study, we investigated the haplotypes of six GJB2 mutations frequently observed in Japanese hearing loss patients (i.e., c.235delC, p.V37I, p.[G45E; Y136X], p.R143W, c.176_191del, and c.299_300delAT) and analyzed whether the recurring mechanisms for each mutation are due to founder effects or mutational hot spots. Furthermore, regarding the mutations considered to be caused by founder effects, we also calculated the age at which each mutation occurred using the principle of genetic clock analysis. As a result, all six mutations were observed in a specific haplotype and were estimated to derive from founder effects. Our haplotype data together with their distribution patterns indicated that p.R143W and p.V37I may have occurred as multiple events, and suggested that both a founder effect and hot spot may be involved in some mutations. With regard to the founders’ age of frequent GJB2 mutations, each mutation may have occurred at a different time, with the oldest, p.V37I, considered to have occurred around 14,500 years ago, and the most recent, c.176_191del, considered to have occurred around 4000 years ago.
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Sepulveda Yanez, Julieta Haydee, Diego Alvarez, Jose Fernandez-Goycoolea, Cornelis A. M. van Bergen, Hendrik Veelken, and Marcelo A. Navarrete. "Differential Genome-Wide Mutational Patterns in Indolent B-Cell Lymphomas." Blood 132, Supplement 1 (November 29, 2018): 4102. http://dx.doi.org/10.1182/blood-2018-99-116174.
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Abstract Introduction: In recent years, strategies have been developed to identify specific mutation patterns within next-generation sequencing data. Distinct mutational patterns can be linked to underlying mutagenic processes in human cancer. One approach analyzes single base substitutions in the context of their neighboring bases as trinucleotides. The relative prevalence of all possible 96 altered trinucleotides defines distinctive mutational signatures. The activity of activation-induced cytidine deaminase (AID) initiates a specific mutational process in B cells. AID induces deamination of deoxycytidine into deoxyuridine. Subsequent mechanisms to repair the resulting mismatch lead to different genomic alterations that can be assigned to three mutational signatures: a canonical signature characterized by C>T/G transitions at WRCY motifs, a non-canonical signature defined by A>C transversions at WAN motifs, and a third AID signature characterized by C>T transitions at RCG motifs with preference for methylated CpG (W: A or T; R: purine; Y: pyrimidine, N: any nucleotide). The latter signature has specifically been designated as AID-mediated CpG-methylation-dependent mutagenesis. AID activity has been linked to the pathogenesis of several B-cell lymphomas, including follicular lymphoma (FL), chronic lymphocytic leukemia (CLL), and mantle cell lymphoma (MCL). Therefore, we searched for the contribution of different AID signatures in these B-cell malignancies. Methods: We analyzed the mutational landscape in whole exome (WES) and whole genome (WGS) sequencing data from 41 FL, 30 CLL, 2 MBL, and 43 MCL cases. Somatic variants were called by comparison of tumor and germline DNA with an in-house developed pipeline. Mutational signatures were defined according to the 96-base substitution model (Alexandrov et al. 2013) by an unsupervised machine learning with implementation of the SomaticSignatures R package (Gehring et al. 2015). In addition, MutationalPattern R package (Blokzijl et al. 2018) was executed for comparison to mutational signatures defined in COSMIC. Results: In unsupervised analyses of FL, CLL/MBL, and MCL cases, 77% of the mutation spectrum variance was attributable to four signatures (S1-4). In FL, the mutational landscape was dominated by S4 characterized by mutations in both canonical and non-canonical AID motifs (40%, 95% CI: 35-76%). The second most frequent signature (S2; 27%, 21-49%) was characterized by C>A transitions in the context of the non-canonical AID and the CpG hotspot motifs (RCG). The mutational landscape of CLL and MBL was strongly dominated by signature S3 (50%, 45-95%). S3 contains mutations in RCG motifs as well as mutations in non-canonical AID motifs (NTW), but with a lower contribution that in S4. In contrast, the mutational landscape of MCL was dominated by S1 (31%, 24-55%) characterized by C>T transitions in the RCG motif in addition to a striking prevalence of the TCT>TTT transition that is known to be associated with the activity of APOBEC enzymes. In comparison to the mutational signatures in COSMIC, the lymphomas analyzed here carry a strong similarity to the COSMIC signatures 1, 5, and 25. These signatures are observed across a wide spectrum of cancer types and are either of unknown etiology (S5 and S25) or associated with age (S1). Conclusions: The most common point mutations in CLL/MBL and FL are C>T transitions and indicate a strong influence of AID on their mutational landscape. In the indolent B-cell malignancies, all three known AID-related signatures, i.e. canonical, non-canonical, and CpG-methylation-dependent can be found. In contrast, the genomic landscape of MCL is dominated by variants in CpG-methylation-dependent mutagenesis sites and by an APOBEC-related motif. In addition to AID-related signatures, we also found consensus signatures described in COSMIC such as the age-related spontaneous deamination signature 1. Our work independently confirms the role of AID in B-cell lymphoma pathogenesis but points to disease-specific mechanisms that modulate AID in the respective lymphoma cell of origin. In addition, our data suggest that distinctive repair mechanisms operate in different entities. Disclosures No relevant conflicts of interest to declare.
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Huseby, Douglas L., Gerrit Brandis, Lisa Praski Alzrigat, and Diarmaid Hughes. "Antibiotic resistance by high-level intrinsic suppression of a frameshift mutation in an essential gene." Proceedings of the National Academy of Sciences 117, no. 6 (January 28, 2020): 3185–91. http://dx.doi.org/10.1073/pnas.1919390117.
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A fundamental feature of life is that ribosomes read the genetic code in messenger RNA (mRNA) as triplets of nucleotides in a single reading frame. Mutations that shift the reading frame generally cause gene inactivation and in essential genes cause loss of viability. Here we report and characterize a +1-nt frameshift mutation, centrally located in rpoB, an essential gene encoding the beta-subunit of RNA polymerase. Mutant Escherichia coli carrying this mutation are viable and highly resistant to rifampicin. Genetic and proteomic experiments reveal a very high rate (5%) of spontaneous frameshift suppression occurring on a heptanucleotide sequence downstream of the mutation. Production of active protein is stimulated to 61–71% of wild-type level by a feedback mechanism increasing translation initiation. The phenomenon described here could have broad significance for predictions of phenotype from genotype. Several frameshift mutations have been reported in rpoB in rifampicin-resistant clinical isolates of Mycobacterium tuberculosis (Mtb). These mutations have never been experimentally validated, and no mechanisms of action have been proposed. This work shows that frameshift mutations in rpoB can be a mutational mechanism generating antibiotic resistance. Our analysis further suggests that genetic elements supporting productive frameshifting could rapidly evolve de novo, even in essential genes.
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Lenski, Richard E., and John E. Mittler. "Response : Unusual Mutational Mechanisms and Evolution." Science 260, no. 5116 (June 25, 1993): 1959–60. http://dx.doi.org/10.1126/science.260.5116.1959.b.
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Lenski, Richard E., and John E. Mittler. "Response : Unusual Mutational Mechanisms and Evolution." Science 260, no. 5116 (June 25, 1993): 1959–60. http://dx.doi.org/10.1126/science.260.5116.1959-b.
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Chase, Andrew, Joannah Score, Feng Lin, Catherine Bryant, Katherine Waghorn, Sarah Yapp, Gonzalo Carreno-Tarragona, et al. "Mutational mechanisms of EZH2 inactivation in myeloid neoplasms." Leukemia 34, no. 12 (April 22, 2020): 3206–14. http://dx.doi.org/10.1038/s41375-020-0816-y.
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Ficht, Thomas A. "Discovery of Brucella virulence mechanisms using mutational analysis." Veterinary Microbiology 90, no. 1-4 (December 2002): 311–15. http://dx.doi.org/10.1016/s0378-1135(02)00216-x.
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Hancock, R. L. "Theoretical mechanisms for synthesis of carcinogen-induced embryonic proteins: XIII mutational and non-mutational mechanisms as subsets of a more general mechanism. Part B — Hereditary tyrosinemia." Medical Hypotheses 16, no. 2 (February 1985): 183–87. http://dx.doi.org/10.1016/0306-9877(85)90075-1.
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Piscosquito, Giuseppe, Paola Saveri, Stefania Magri, Claudia Ciano, Daniela Di Bella, Micaela Milani, Franco Taroni, and Davide Pareyson. "Mutational mechanisms in MFN2 -related neuropathy: compound heterozygosity for recessive and semidominant mutations." Journal of the Peripheral Nervous System 20, no. 4 (December 2015): 380–86. http://dx.doi.org/10.1111/jns.12145.
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Aldahmesh, Mohammed A., Arif O. Khan, Jawahir Mohamed, and Fowzan S. Alkuraya. "Novel recessive BFSP2 and PITX3 mutations: Insights into mutational mechanisms from consanguineous populations." Genetics in Medicine 13, no. 11 (November 2011): 978–81. http://dx.doi.org/10.1097/gim.0b013e31822623d5.
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Wienand, Kirsty, Bjoern Chapuy, Chip Stewart, Andrew J. Dunford, David Wu, Jaegil Kim, Atanas Kamburov, et al. "Genomic analyses of flow-sorted Hodgkin Reed-Sternberg cells reveal complementary mechanisms of immune evasion." Blood Advances 3, no. 23 (December 9, 2019): 4065–80. http://dx.doi.org/10.1182/bloodadvances.2019001012.
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Key Points Analyses of recurrent mutations, copy number alterations, and structural variants reveal complementary immune evasion mechanisms in cHL. The mutational burden in EBV– cHLs is among the highest reported, potentially contributing to the efficacy of PD-1 blockade.
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Levine, J. G., and R. M. Schaaper. "Complex Frameshift Mutations Medicated by Plasmid pKM101: Mutational Mechanisms Deduced from 4-aminobiphenyl-induced Mutation Spectra in Salmonella." Genetics 137, no. 1 (May 1, 1994): 337. http://dx.doi.org/10.1093/genetics/137.1.337.
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Levine, J. G., R. M. Schaaper, and D. M. DeMarini. "Complex frameshift mutations mediated by plasmid pKM101: mutational mechanisms deduced from 4-aminobiphenyl-induced mutation spectra in Salmonella." Genetics 136, no. 3 (March 1, 1994): 731–46. http://dx.doi.org/10.1093/genetics/136.3.731.
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Abstract We used colony probe hybridization and polymerase chain reaction/DNA sequence analysis to determine the mutations in approximately 2,400 4-aminobiphenyl (4-AB) +S9-induced revertants of the -1 frameshift allele hisD3052 and of the base-substitution allele hisG46 of Salmonella typhimurium. Most of the mutations occurred at sites containing guanine, which is the primary base at which 4-AB forms DNA adducts. A hotspot mutation involving the deletion of a CG or GC within the sequence CGCGCGCG accounted for 100 and 99.9%, respectively, of the reversion events at the hisD3052 allele in the pKM101 plasmid-minus strains TA1978 (uvr+) and TA1538 (delta uvrB). In strain TA98 (delta uvrB, pKM101), which contained the SOS DNA repair system provided by the pKM101 plasmid, approximately 85% of the revertants also contained the hotspot deletion; the remaining approximately 15% contained one of two types of mutations: (1) complex frameshifts that can be described as a -2 or +1 frameshift and an associated base substitution and (2) deletions of the CC or GG sequences that flank the hotspot site (CCGCGCGCGG). We propose a misincorporation/slippage model to account for these mutations in which (1) pKM101-mediated misincorporation and translesion synthesis occurs across a 4-AB-adducted guanine; (2) the instability of such a mispairing and/or the presence of the adduct leads to strand slippage in a run of repeated bases adjacent to the adducted guanine; and (3) continued DNA synthesis from the slipped intermediate produces a frameshift associated with a base substitution. This model readily accounts for the deletion of the CC or GG sequences flanking the hotspot site, indicating that these mutations are, in fact, complex mutations in disguise (i.e., cryptic complex frameshifts). The inferred base-substitution specificity associated with the complex frameshifts at the hisD3052 allele (primarily G.C-->T.A transversions) is consistent with the finding that 4-AB induced primarily G.C-->T.A transversions at the hisG46 base-substitution allele. The model also provides a framework for understanding the different relative mutagenic potencies of 4-AB at the two alleles in the various DNA repair backgrounds of Salmonella.
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Gladbach, Wiegele, Hamed, Merkenschläger, Fuellen, Junghanss, and Maletzki. "Unraveling the Heterogeneous Mutational Signature of Spontaneously Developing Tumors in MLH1−/− Mice." Cancers 11, no. 10 (October 2, 2019): 1485. http://dx.doi.org/10.3390/cancers11101485.
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Mismatch repair deficient (MMR-D) tumors exemplify the prototypic hypermutator phenotype. Owing to the high mutation rates, plenty of neo-antigens are present on the tumor cells’ surface, ideally shared among different cancer types. The MLH1 knock out mouse represents a preclinical model that resembles features of the human MMR-D counterpart. While these mice develop neoplasias in a sequential twin-peaked manner (lymphomas > gastrointestinal tumors (GIT)) we aimed at identification of underlying molecular mechanisms. Using whole-genome sequencing, we focused on (I) shared and (II) mutually exclusive mutations and describe the process of ongoing mutational events in tumor-derived cell cultures. The landscape of MLH1−/− tumors is heterogeneous with only a few shared mutations being detectable among different tumor entities (ARID1A and IDH2). With respect to coding microsatellite analysis of MMR-D-related target genes, partial overlap was detectable, yet recognizing shared antigens. The present study is the first reporting results of a comparison between spontaneously developing tumors in MMR-D driven tumorigenesis. Additionally to identifying ARID1A as potential causative mutation hotspot, this comprehensive characterization of the mutational landscape may be a good starting point to refine therapeutic concepts.
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Umbreit, Neil T., Cheng-Zhong Zhang, Luke D. Lynch, Logan J. Blaine, Anna M. Cheng, Richard Tourdot, Lili Sun, et al. "Mechanisms generating cancer genome complexity from a single cell division error." Science 368, no. 6488 (April 16, 2020): eaba0712. http://dx.doi.org/10.1126/science.aba0712.
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The chromosome breakage-fusion-bridge (BFB) cycle is a mutational process that produces gene amplification and genome instability. Signatures of BFB cycles can be observed in cancer genomes alongside chromothripsis, another catastrophic mutational phenomenon. We explain this association by elucidating a mutational cascade that is triggered by a single cell division error—chromosome bridge formation—that rapidly increases genomic complexity. We show that actomyosin forces are required for initial bridge breakage. Chromothripsis accumulates, beginning with aberrant interphase replication of bridge DNA. A subsequent burst of DNA replication in the next mitosis generates extensive DNA damage. During this second cell division, broken bridge chromosomes frequently missegregate and form micronuclei, promoting additional chromothripsis. We propose that iterations of this mutational cascade generate the continuing evolution and subclonal heterogeneity characteristic of many human cancers.
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Stenman, Adam, Samuel Backman, Klara Johansson, Johan O. Paulsson, Peter Stålberg, Jan Zedenius, and C. Christofer Juhlin. "Pan-genomic characterization of high-risk pediatric papillary thyroid carcinoma." Endocrine-Related Cancer 28, no. 5 (May 1, 2021): 337–51. http://dx.doi.org/10.1530/erc-20-0464.
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Pediatric papillary thyroid carcinomas (pPTCs) are often indolent tumors with excellent long-term outcome, although subsets of cases are clinically troublesome and recur. Although it is generally thought to exhibit similar molecular aberrancies as their counterpart tumors in adults, the pan-genomic landscape of clinically aggressive pPTCs has not been previously described. In this study, five pairs of primary and synchronously metastatic pPTC from patients with high-risk phenotypes were characterized using parallel whole-genome and -transcriptome sequencing. Primary tumors and their metastatic components displayed an exceedingly low number of coding somatic mutations and gross chromosomal alterations overall, with surprisingly few shared mutational events. Two cases exhibited one established gene fusion event each (SQSTM1-NTRK3 and NCOA4-RET) in both primary and metastatic tissues, and one case each was positive for a BRAF V600E mutation and a germline truncating CHEK2 mutation, respectively. One single case was without apparent driver events and was considered as a genetic orphan. Non-coding mutations in cancer-associated regions were generally not present. By expressional analyses, fusion-driven primary and metastatic pPTC clustered separately from the mutation-driven cases and the sole genetic orphan. We conclude that pPTCs are genetically indolent tumors with exceedingly stable genomes. Several mutations found exclusively in the metastatic samples which may represent novel genetic events that drive the metastatic behavior, and the differences in mutational compositions suggest early clonal divergence between primary tumors and metastases. Moreover, an overrepresentation of mutational and expressional dysregulation of immune regulatory pathways was noted among fusion-positive pPTC metastases, suggesting that these tumors might facilitate spread through immune evasive mechanisms.
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Bachar, Amit, Elad Itzhaki, Shmuel Gleizer, Melina Shamshoom, Ron Milo, and Niv Antonovsky. "Point mutations in topoisomerase I alter the mutation spectrum in E. coli and impact the emergence of drug resistance genotypes." Nucleic Acids Research 48, no. 2 (November 28, 2019): 761–69. http://dx.doi.org/10.1093/nar/gkz1100.
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Abstract Identifying the molecular mechanisms that give rise to genetic variation is essential for the understanding of evolutionary processes. Previously, we have used adaptive laboratory evolution to enable biomass synthesis from CO2 in Escherichia coli. Genetic analysis of adapted clones from two independently evolving populations revealed distinct enrichment for insertion and deletion mutational events. Here, we follow these observations to show that mutations in the gene encoding for DNA topoisomerase I (topA) give rise to mutator phenotypes with characteristic mutational spectra. Using genetic assays and mutation accumulation lines, we find that point mutations in topA increase the rate of sequence deletion and duplication events. Interestingly, we observe that a single residue substitution (R168C) results in a high rate of head-to-tail (tandem) short sequence duplications, which are independent of existing sequence repeats. Finally, we show that the unique mutation spectrum of topA mutants enhances the emergence of antibiotic resistance in comparison to mismatch-repair (mutS) mutators, and leads to new resistance genotypes. Our findings highlight a potential link between the catalytic activity of topoisomerases and the fundamental question regarding the emergence of de novo tandem repeats, which are known modulators of bacterial evolution.
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Zhang, Xu-Sheng, and William G. Hill. "Joint Effects of Pleiotropic Selection and Stabilizing Selection on the Maintenance of Quantitative Genetic Variation at Mutation-Selection Balance." Genetics 162, no. 1 (September 1, 2002): 459–71. http://dx.doi.org/10.1093/genetics/162.1.459.
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AbstractIn quantitative genetics, there are two basic “conflicting” observations: abundant polygenic variation and strong stabilizing selection that should rapidly deplete that variation. This conflict, although having attracted much theoretical attention, still stands open. Two classes of model have been proposed: real stabilizing selection directly on the metric trait under study and apparent stabilizing selection caused solely by the deleterious pleiotropic side effects of mutations on fitness. Here these models are combined and the total stabilizing selection observed is assumed to derive simultaneously through these two different mechanisms. Mutations have effects on a metric trait and on fitness, and both effects vary continuously. The genetic variance (VG) and the observed strength of total stabilizing selection (Vs,t) are analyzed with a rare-alleles model. Both kinds of selection reduce VG but their roles in depleting it are not independent: The magnitude of pleiotropic selection depends on real stabilizing selection and such dependence is subject to the shape of the distributions of mutational effects. The genetic variation maintained thus depends on the kurtosis as well as the variance of mutational effects: All else being equal, VG increases with increasing leptokurtosis of mutational effects on fitness, while for a given distribution of mutational effects on fitness, VG decreases with increasing leptokurtosis of mutational effects on the trait. The VG and Vs,t are determined primarily by real stabilizing selection while pleiotropic effects, which can be large, have only a limited impact. This finding provides some promise that a high heritability can be explained under strong total stabilizing selection for what are regarded as typical values of mutation and selection parameters.
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Verkhivker, Gennady. "Allosteric Determinants of the SARS-CoV-2 Spike Protein Binding with Nanobodies: Examining Mechanisms of Mutational Escape and Sensitivity of the Omicron Variant." International Journal of Molecular Sciences 23, no. 4 (February 16, 2022): 2172. http://dx.doi.org/10.3390/ijms23042172.
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Structural and biochemical studies have recently revealed a range of rationally engineered nanobodies with efficient neutralizing capacity against the SARS-CoV-2 virus and resilience against mutational escape. In this study, we performed a comprehensive computational analysis of the SARS-CoV-2 spike trimer complexes with single nanobodies Nb6, VHH E, and complex with VHH E/VHH V nanobody combination. We combined coarse-grained and all-atom molecular simulations and collective dynamics analysis with binding free energy scanning, perturbation-response scanning, and network centrality analysis to examine mechanisms of nanobody-induced allosteric modulation and cooperativity in the SARS-CoV-2 spike trimer complexes with these nanobodies. By quantifying energetic and allosteric determinants of the SARS-CoV-2 spike protein binding with nanobodies, we also examined nanobody-induced modulation of escaping mutations and the effect of the Omicron variant on nanobody binding. The mutational scanning analysis supported the notion that E484A mutation can have a significant detrimental effect on nanobody binding and result in Omicron-induced escape from nanobody neutralization. Our findings showed that SARS-CoV-2 spike protein might exploit the plasticity of specific allosteric hotspots to generate escape mutants that alter response to binding without compromising activity. The network analysis supported these findings showing that VHH E/VHH V nanobody binding can induce long-range couplings between the cryptic binding epitope and ACE2-binding site through a broader ensemble of communication paths that is less dependent on specific mediating centers and therefore may be less sensitive to mutational perturbations of functional residues. The results suggest that binding affinity and long-range communications of the SARS-CoV-2 complexes with nanobodies can be determined by structurally stable regulatory centers and conformationally adaptable hotspots that are allosterically coupled and collectively control resilience to mutational escape.
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Kuang, Shelley, Sally C. M. Lau, Kieran Sharma, Juehea Lee, Malcolm Isaiah Ryan, Sabine Schmid, Penelope Ann Bradbury, et al. "Impact of KRAS mutational variant on response to immunotherapy in metastatic NSCLC." Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021): e21127-e21127. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.e21127.
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e21127 Background: KRAS alterations constitute the most common driver mutations in metastatic non-small cell lung cancers (mNSCLC) and occur in approximately 30% of patients. KRAS mutational subtype as well as the presence of co-mutations has been associated with altered activation of downstream signaling pathways in preclinical models. We hypothesize that different KRAS G12C mutational subsets will be associated with variable clinical outcome and response to therapy. To this end, we have performed a retrospective analysis of survival and treatment outcomes by KRAS mutation subtype (G12C vs non-G12C). Methods: A review of KRAS-mutated mNSCLC patients treated with immunotherapy between 2013 and 2020 was conducted. Patient demographics, smoking status, KRAS mutational subtype, co-mutations and PD-L1 status were collected. Overall response rate (ORR) and progression-free survival (PFS) were analyzed in each subgroup. Results: 98 KRAS mutant mNSCLC patients were treated with immune checkpoint inhibitors (ICI): 37% with a KRAS G12C mutation, 62% with a non-G12C mutation. Patients with a G12C mutation were more likely to be of Caucasian ancestry (86% vs 56%; p = 0.01) whereas all other characteristics were similar between the groups including smoking history, PD-L1 expression ≥50% (61% vs 40%) and the presence of a TP53 co-mutation (48% vs. 54%); all p > 0.05. Treatment patterns were similar between the groups, with PD-1 inhibitor monotherapy given in 86% vs 79% of KRAS G12C and non-G12C patients. Overall response rate was 51% vs 27% in G12C vs non-G12C (p = 0.03). PFS was superior in G12C mutants (19.6 months vs 4.0 months), even after adjusting for smoking history, TP53 co-mutation status and PD-L1 expression (adjusted HR 0.51; p = 0.02). In subgroup analyses, the superiority in PFS was driven by the G12C mutants with high PD-L1 expression (n = 19): 26.8 months in G12C, PD-L1 high vs 4.7 months in G12C, PD-L1 low vs. 4.7 months in KRAS transversion mutations, PD-L1 high vs 4.0 months in transversion mutations, PD-L1 low vs. 3.0 months in transition mutations; p < 0.001. Conclusions: The presence of a KRAS G12C mutation is associated with improved ORR and PFS after treatment with ICI compared to non-G12C mutations in mNSCLC. The greatest benefit in PFS was observed in the subgroup with G12C mutation and high PD-L1 expression. Differential activation of downstream signaling associated with specific KRAS codon 12 mutation variants may modulate the composition of the tumor immune microenvironment thereby contributing to the variable response to immunotherapy. Further understanding on these molecular mechanisms may direct the development of new treatment strategies in KRAS mutant lung cancers.
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Grinshpun, Albert, Junko Tsuji, Tianyu Li, Douglas Russo, Leilani Anderson, Rebecca Rees, Carrie Cibulskis, et al. "Longitudinal circulating tumor DNA (ctDNA) whole-exome sequencing (WES) in the phase Ib/II trial of palbociclib and bazedoxifene reveals genomic dynamics and clonal evolution with the acquisition of treatment resistance in hormone receptor-positive, HER2-negative (HR+ HER2-), advanced breast cancer (ABC)." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): 1058. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.1058.
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1058 Background: Patients (pts) with HR+ HER2- ABC ultimately develop endocrine resistance. To gain insights into the genetic mechanisms of resistance we performed WES on serial plasma samples from endocrine resistant pts treated on a clinical trial (NCT02448771). Methods: Plasma samples were collected at baseline (n=36), day 1 of cycle 2 (n=33), and at the end of treatment (EOT, n=33). Samples were subjected to ultra-low passage (ULP, 0.19-0.57X) WGS to determine ctDNA tumor fraction (TF) for the selection of samples (TF>0.03) for subsequent WES (193X). Somatic single nucleotide variations, somatic copy number alteration (SCNA), phylogeny, tumor mutational burden, mutational signatures, and germline analyses were performed. Results: All 102 samples underwent successful ULP and 68 WES. Overall, most frequent pathogenic mutations were in ESR1 and PIK3CA. At baseline, 32% of pts had ESR1 mutation and 21% PIK3CA mutation. There was no association between ESR1 mutations and PFS. In contrast, baseline PIK3CA mutations were detected only in pts who did not have a clinical benefit, and were associated with worse PFS compared to pts with wild-type PIK3CA (1.8 vs. 3.9 months, respectively, HR=0.2, 95% CI 0.06-0.6, P=0.0019, log-rank test). Additionally, pts with a baseline truncating mutation, mostly in tumor suppressor genes ( TP53, MEN1, RB1, CDKN1B, NF1, TP53BP1, TP63, SMAD2/4, ARID1A, KMT2C), also had a significantly worse PFS (1.7 vs 3.8 months, HR=0.3, 95% CI 0.1-0.7, P=0.006, log-rank test). At EOT, 20% (4/20) of pts with matched baseline samples had newly acquired mutations that are suggestive of mechanisms of acquired resistance and offer potential therapeutic targets (e.g. ERBB2, PIK3CA). SCNA analysis showed that in all pts there were at least 2 SCNAs in cancer-related driver genes, most common in CCND1 and ELF3. Moreover, in all samples we identified at least 1 SCNA related to a potential mechanism of resistance. To better understand tumor heterogeneity and sub-clonal architecture we performed an evolutionary analysis (sufficient TF≥0.15, available in n=7). Phylogenetic analysis revealed sub-clonal dynamics that could explain the acquisition of resistance in at least three pts (3/7), and identified novel genes which might have role in endocrine resistance (e.g. DCAF13, ZFHX3). Conclusions: Our results demonstrate the feasibility and utility of serial WES in a clinical trial. Serial ctDNA WES and evolutionary studies enabled us to discover novel potential genomic mechanisms of tumor progression, and identified PIK3CA mutations as a candidate biomarker of resistance to the combination of palbociclib and bazedoxifene, which may apply to other next generation endocrine treatments. Clinical trial information: NCT02448771.
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Florian, Maria C., Kalpana J. Nattamai, Hartmut Geiger, and Medhanie A. Mulaw. "Clonality and Mixed Mutational Signature in Aged Hematopoietic Stem Cells Via Single Cell Variant Analysis." Blood 128, no. 22 (December 2, 2016): 570. http://dx.doi.org/10.1182/blood.v128.22.570.570.
Full textAbstract:
Abstract Genomic stability and integrity in Hematopoietic Stem Cells (HSCs) is maintained via DNA damage checkpoints, DNA proofreading and DNA repair (Moehrle et al., 2015; Cell Rep). Despite these mechanisms, recurring and non-recurring mutations accumulate in HSCs upon aging, which correlate with an elevated incidence of myeloproliferative diseases (Rossi, Bryder, and Weissman, Exp. Gerontol. 2007) as well as changes in clonality (Akunuru and Geiger, 2016; Trends in Mol. Med.). The rate at which such mutations accumulate in individual HSCs and the selection advantage/disadvantage that they provide is unclear and is an active area of investigation. Evolutionary theory supports a strong influence of the aged niche on the selection of HSCs clones upon aging (Rozhok, Salstrom, and DeGregori, 2014; Aging). We hypothesized that variant profiling of single HSCs based on RNA transcripts will reveal mutational signatures adapted to the selection pressure of the aging microenvironment. We performed Single cell RNA-seq of daughter cell pairs from young and aged murine HSCs (LSK, CD34-, flk2-). The Genome Analysis Toolkit (GATK; Broad Institute) RNA-seq variant/mutation calling algorithm pipeline was applied with some modifications. Only variants that were observed in both daughter cells of a given pair were selected, which significantly decreased our false discovery rate (tested by a Monte Carlo simulation). First and most interestingly, we observed no significant difference in the overall number of variants/mutations between young and aged HSCs, further supporting our recently published observations on the frequency of DNA mutations in HSCs upon aging (Moehrle et al., 2015; Cell Rep). We then used an approach that takes into account the 3' and 5' bases flanking a variant to generate motifs whose frequencies can be mathematically analyzed to deduce characteristic mutational patterns, termed as mutational signatures (Nik-Zainal et al., 2012; Cell). We employed a non-negative matrix factorization (nmf) and principal component analysis (pca) algorithms to generate 10 mutational signatures that explained > 95% of the variance in the dataset. We then analyzed the signatures in a pairwise fashion and selected two signatures with the highest discrimination score between young and aged HSC. Based on this, cells fell into two major groups: group 1 predominantly contained aged single cells (~90% of the cells in this group) whereas, interestingly, group 2 contained a mix of young and aged HSCs. The segregation of young and aged single HSCs counts between groups 1 and 2 was tested using Fisher's exact test and was statistically significant (p-value 0.0029). These data indicate that while the overall mutational load is not elevated, majority of aged HSCs acquire a mutational signature distinct from young HSCs, while a proportion of aged HSCs present with a young-like HSC signature. Furthermore, our results show that even those cells that have acquired an aging signature aren't homogeneous and show sub-clustering tendencies, providing the first hint that they may potentially evolve further into more distinct clones. In conclusion, our results show that individual HSCs reflect a mixed mutational profile reminiscent of a non-uniform accumulation of variants. As such signatures are a reflection of underlying mechanisms by which the mutations accumulate (Nik-Zainal et al., 2012; Cell), the proportion of aged HSCs sharing similar mutational signatures but distinct from the young HSCs reveal an aging signature that indicates specific mutational factors and selection pressure of the aging microenvironment. Disclosures Mulaw: NuGEN: Honoraria.