scholarly journals Arginine Depletion in Human Cancers

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6274
Author(s):  
Devi D. Nelakurti ◽  
Tiffany Rossetti ◽  
Aman Y. Husbands ◽  
Ruben C. Petreaca
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Base Pair ◽  
Somatic Mutations ◽  
Purifying Selection ◽  
Mutational Bias ◽  
Cancer Tissue ◽  
Driver Genes ◽  
Cancer Driver ◽  
Substitution Bias

Arginine is encoded by six different codons. Base pair changes in any of these codons can have a broad spectrum of effects including substitutions to twelve different amino acids, eighteen synonymous changes, and two stop codons. Four amino acids (histidine, cysteine, glutamine, and tryptophan) account for over 75% of amino acid substitutions of arginine. This suggests that a mutational bias, or “purifying selection”, mechanism is at work. This bias appears to be driven by C > T and G > A transitions in four of the six arginine codons, a signature that is universal and independent of cancer tissue of origin or histology. Here, we provide a review of the available literature and reanalyze publicly available data from the Catalogue of Somatic Mutations in Cancer (COSMIC). Our analysis identifies several genes with an arginine substitution bias. These include known factors such as IDH1, as well as previously unreported genes, including four cancer driver genes (FGFR3, PPP6C, MAX, GNAQ). We propose that base pair substitution bias and amino acid physiology both play a role in purifying selection. This model may explain the documented arginine substitution bias in cancers.

scholarly journals Non-coding mutations reveal cancer driver cistromes in luminal breast cancer

2021 ◽  
Author(s):  
Samah El Ghamrasni ◽  
Rene Quevedo ◽  
James R Hawley ◽  
Parisa Mazrooei ◽  
Youstina Hanna ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcription Factors ◽  
Somatic Mutations ◽  
Breast Tumors ◽  
Regulatory Elements ◽  
Luminal Breast Cancer ◽  
Breast Cancers ◽  
Driver Genes ◽  
Cancer Driver ◽  
Personalized Cancer

Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and non-coding cancer driver plexuses from somatic mutations. However, differentiating driver and passenger events among non-coding genetic variants remains a challenge to understand the etiology of cancer and inform the delivery of personalized cancer medicine. Herein, we reveal an enrichment of non-coding mutations in cis-regulatory elements that cover a subset of transcription factors linked to tumor progression in luminal breast cancers. Using a cohort of 26 primary luminal ER+PR+ breast tumors, we compiled a catalogue of ~100,000 unique cis-regulatory elements from ATACseq data. Integrating this catalogue with somatic mutations from 350 publicly available breast tumor whole genomes, we identified four recurrently mutated individual cis-regulatory elements. By then partitioning the non-coding genome into cistromes, defined as the sum of binding sites for a transcription factor, we uncovered cancer driver cistromes for ten transcription factors in luminal breast cancer, namely CTCF, ELF1, ESR1, FOSL2, FOXA1, FOXM1 GATA3, JUND, TFAP2A, and TFAP2C in luminal breast cancer. Nine of these ten transcription factors were shown to be essential for growth in breast cancer, with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of non-coding mutations over cis-regulatory elements concatenated into a functional unit drawn from an accessible chromatin catalogue derived from primary cancer tissues.

IDENTIFY CANCER DRIVER GENES THROUGH SHARED MENDELIAN DISEASE PATHOGENIC VARIANTS AND CANCER SOMATIC MUTATIONS

2016 ◽  
Author(s):  
MENG MA ◽  
CHANGCHANG WANG ◽  
BENJAMIN S. GLICKSBERG ◽  
ERIC E. SCHADT ◽  
SHUYU D. LI ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Mendelian Disease ◽  
Driver Genes ◽  
Cancer Driver ◽  
Pathogenic Variants ◽  
Cancer Driver Genes

Somatic mutations in triple-negative breast carcinoma and high-grade serous ovarian carcinoma from young women.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e12561-e12561
Author(s):  
Pedro Adolpho MP Serio ◽  
Glaucia Fernanda Lima Pereira ◽  
Maria Lucia Hirata Katayama ◽  
Simone Maistro ◽  
Rossana Veronica Mendoza Lopez ◽  
...  
Keyword(s):  
Ovarian Carcinoma ◽  
Somatic Mutations ◽  
Triple Negative ◽  
Young Patients ◽  
High Grade ◽  
Cancer Gene ◽  
Sequencing Data ◽  
Driver Genes ◽  
Cancer Driver ◽  
Serous Ovarian Carcinoma

e12561 Background: High grade serous ovarian carcinoma (HGSOvCa) and triple negative breast cancer (TNBC) share characteristics, such as poor prognosis, BRCA1 germline mutations and TP53 somatic mutations. Our aim was to analyze somatic mutations from HGS-OvCa and TNBC from young patients aged ≤ 40 years. Methods: Whole genome or exome sequencing data for TNBC (n = 83) or HGS-OvCa (n = 21) was recovered from COSMIC or cBioPortal. Data was searched for cancer driver genes catalogued in Cancer Gene Census (CGC) or Candidate Cancer Gene Database rank A or B (CCGD) and for DNA repair genes. Results: TNBC mainly consisted of ductal carcinomas (78/83). A median of two cancer causing genes was affected in both TNBC and HGS-OvCa and TP53 was mutated in at least 2/3 of the samples. Only 7/83 and 2/19 of TNBC and HGS-OvCa samples, respectively, did not present variants in known cancer causing genes. C > T substitutions were the most frequent events in both TNBC and HGS-OvCa, however transversions were more frequently detected in TNBC. Besides TP53, another 33 genes were mutated in both tumor types, including PIK3CA, RYR2, TARBP1, CSMD3, DNAH11, MYO3A, NF1, TNRC6A, CACNA1E, HCMN1, PRKDC. Conclusions: Although many similarities were detected, TNBC in young patients presents a higher number of transversions and almost 25% of HGSOvCa present somatic mutations in HR genes. [Table: see text]

scholarly journals VARIATION OF MUTAGENIC ACTION ON NONSENSE MUTANTS AT DIFFERENT SITES IN THE ISO-1-CYTOCHROME c GENE OF YEAST

Genetics ◽  
1974 ◽  
Vol 78 (1) ◽  
pp. 97-113
Author(s):  
Fred Sherman ◽  
John W Stewart
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Cytochrome C ◽  
Base Pair ◽  
Nitrous Acid ◽  
Nucleotide Sequences ◽  
Mutagenic Action ◽  
Base Pairs ◽  
Wide Range ◽  
Cytochromes C

ABSTRACT Three ochre and two amber mutants in yeast have been definitively identified by the amino acid replacements in iso-1-cytochromes c from intragenic revertants. Except for rare and sometimes unusual changes, all of the replacements were single amino acids whose codons differed from UAA or UAG by one base. These assignments, which were based on the absence of tryptophan replacements in ochre revertants, could be corroborated from the studies of two groups of suppressors that were shown to act on either the ochre or amber mutants. All five nonsense mutants are located at different sites in the cyc1 gene and all are at sites that can be occupied by amino acids having a wide range of structures. The relative frequencies of the amino acid replacements indicate that identical codons located at different sites may respond differently to a mutagenic agent. Notably glutamine replacements occurred almost exclusively in UV-induced revertants of only one ochre mutant cyc1-9, but not at all or at reduced proportions in the others. Similarly, lysine replacements occurred almost exclusively in the NA-induced revertants of only the ochre mutant cyc1-72, but not at all in the others. These and other results reveal that mutation of A·T base pairs by UV and nitrous acid are dependent upon the location of the codon within the gene as well as the location of the base pair within the codon. From these findings, it appears as if the type of base-pair changes induced by UV and nitrous acid are strongly influenced by adjacent nucleotide sequences.

scholarly journals Mutational likeliness and entropy help to identify driver mutations and their functional role in cancer

2018 ◽  
Author(s):  
Giorgio Mattiuz ◽  
Salvatore Di Giorgio ◽  
Lorenzo Tofani ◽  
Antonio Frandi ◽  
Francesco Donati ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Somatic Mutations ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Loss Of Function ◽  
Driver Genes ◽  
Cancer Driver ◽  
Cancer Genomes ◽  
Passenger Mutations ◽  
Mutational Processes

AbstractAlterations in cancer genomes originate from mutational processes taking place throughout oncogenesis and cancer progression. We show that likeliness and entropy are two properties of somatic mutations crucial in cancer evolution, as cancer-driver mutations stand out, with respect to both of these properties, as being distinct from the bulk of passenger mutations. Our analysis can identify novel cancer driver genes and differentiate between gain and loss of function mutations.

scholarly journals DNA Methylation, Deamination, and Translesion Synthesis Combine to Generate Footprint Mutations in Cancer Driver Genes in B-Cell Derived Lymphomas and Other Cancers

2021 ◽  
Vol 12 ◽  
Author(s):  
Igor B. Rogozin ◽  
Abiel Roche-Lima ◽  
Kathrin Tyryshkin ◽  
Kelvin Carrasquillo-Carrión ◽  
Artem G. Lada ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Dna Polymerases ◽  
Affinity Maturation ◽  
Immunoglobulin Genes ◽  
Sequence Profile ◽  
Driver Genes ◽  
Cancer Driver ◽  
Sequence Variations ◽  
Matrix Sequence ◽  
Activation Induced Deaminase

Cancer genomes harbor numerous genomic alterations and many cancers accumulate thousands of nucleotide sequence variations. A prominent fraction of these mutations arises as a consequence of the off-target activity of DNA/RNA editing cytosine deaminases followed by the replication/repair of edited sites by DNA polymerases (pol), as deduced from the analysis of the DNA sequence context of mutations in different tumor tissues. We have used the weight matrix (sequence profile) approach to analyze mutagenesis due to Activation Induced Deaminase (AID) and two error-prone DNA polymerases. Control experiments using shuffled weight matrices and somatic mutations in immunoglobulin genes confirmed the power of this method. Analysis of somatic mutations in various cancers suggested that AID and DNA polymerases η and θ contribute to mutagenesis in contexts that almost universally correlate with the context of mutations in A:T and G:C sites during the affinity maturation of immunoglobulin genes. Previously, we demonstrated that AID contributes to mutagenesis in (de)methylated genomic DNA in various cancers. Our current analysis of methylation data from malignant lymphomas suggests that driver genes are subject to different (de)methylation processes than non-driver genes and, in addition to AID, the activity of pols η and θ contributes to the establishment of methylation-dependent mutation profiles. This may reflect the functional importance of interplay between mutagenesis in cancer and (de)methylation processes in different groups of genes. The resulting changes in CpG methylation levels and chromatin modifications are likely to cause changes in the expression levels of driver genes that may affect cancer initiation and/or progression.

Profile of somatic mutations in young adults with pancreatic cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15790-e15790
Author(s):  
Livia Munhoz Rodrigues ◽  
Simone Maistro ◽  
Maria Lucia Hirata Katayama ◽  
Rosimeire Aparecida Roela ◽  
Maria A. A. Koike Folgueira
Keyword(s):  
Pancreatic Cancer ◽  
Young Adults ◽  
Somatic Mutations ◽  
Cancer Gene ◽  
Driver Genes ◽  
Cancer Driver ◽  
Three Samples ◽  
Candidate Cancer Gene ◽  
Gene Database ◽  
Carcinogenic Process

e15790 Background: Most pancreatic carcinomas (PC) occur in older people, however a few cases are detected in young adults. In this age group, the carcinogenic process is less well understood. Our goal was to identify and to characterize cancer driver genes in early age onset PC. Methods: Somatic variants of individuals affected by PC aged ≤45 years were searched in the COSMIC and CBioPortal databases. The variants were annotated using Oncotator, excluding the silent and intronic variants. Implication in cancer causality was evaluated in the Cancer Gene Census (CGC) and the Candidate Cancer Gene Database (CCGD). The most frequently mutated genes were identified and investigated to determine if they configured FrequentLy mutAted GeneS (FLAGs). Results: Whole genome (4) or exome (29) sequencing was available from 33 individuals (14 females and 19 males). A median of 31 (7-102) alterations per tumor, mainly represented by C > T substitutions (median 16, 2-71), was detected. A median of 3 (0-11) truncated alterations, 4 (1-13) genes cataloged as CGC and 8 (1-22) genes cataloged as CCGD rank A or B was identified per tumor. The most frequently affected genes were those characteristic of tumor promotion in pancreatic cancer carcinogenesis, such as KRAS (79%), TP53 (64%), SMAD4 (18%), followed by RYR1 (15%) and TTN (12%) genes, the latter two classified as FLAGs and, finally, HERC2, GREB1 and DMBT1 (9%). Seventeen samples presented variants in both TP53 and KRAS (17/33), 9 and 4 presented only KRAS or TP53 variants, respectively. Three samples with mutations in neither of these genes presented mutations in genes such as BCLAF1, DCC, BRAF, CDH11 and CDKN2A, both CGCs. Three out of 9 samples carrying KRAS but not TP53 mutations presented variants in DNA homologous repair (HHR) genes. Among all the altered genes, the main biological processes were cell adhesion (139 genes involved) and anatomical structure formation involved in morphogenesis (127), while the most enriched pathways were Wnt (45) and Cadherin (30). Conclusions: TP53 and KRAS are the somatic mutations most frequently detected in PC. 10% of the samples showed no change in these genes, but showed changes in other CGCs. HERC2, GREB1 and DMBT1 are potential cancer drivers in young adult PCs.

Comprehensive analysis reveals distinct mutational signature and its mechanistic insights of alcohol consumption in human cancers

2020 ◽  
Author(s):  
Ran Wei ◽  
Pengcheng Li ◽  
Funan He ◽  
Gang Wei ◽  
Zhan Zhou ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Somatic Mutations ◽  
Alcohol Exposure ◽  
Environment Interaction ◽  
Mutational Signatures ◽  
Driver Genes ◽  
Cancer Driver ◽  
Mutational Signature ◽  
Oncogenic Mutations ◽  
A Genome

Abstract Alcohol consumption is a critical risk factor for multiple types of cancer. A genome can be attacked and acquire numerous somatic mutations in the environment of alcohol exposure. Mutational signature has the capacity illustrating the complex somatic mutation patterns in cancer genome. Recent studies have discovered distinct mutational signatures associating with alcohol consumption in liver and esophageal cancers. However, their prevalence among diverse cancers, impact of genetic background and origin of alcohol-induced mutational signatures remain unclear. By a comprehensive bioinformatics analysis on somatic mutations from patients of four cancer types with drinking information, we identified nine mutational signatures (signatures B–J), among which signature J (similar to COSMIC signature 16) was distinctive to alcohol drinking. Signature J was associated with HNSC, ESCA and LIHC but not PAAD. Interestingly, patients with mutated allele rs1229984 in ADH1B had lower level of signature J while mutated allele rs671 in ALDH2 exhibited higher signature J abundance, suggesting acetaldehyde is one cause of signature J. Intriguingly, somatic mutations of three potential cancer driver genes (TP53, CUL3 and NSD1) were found the critical contributors for increased mutational load of signature J in alcohol consumption patients. Furthermore, signature J was enriched with early accumulated clonal mutations compared to mutations derived from late tumor growth. This study systematically characterized alcohol-related mutational signature and indicated mechanistic insights into the prevalence, origin and gene–environment interaction regarding the risk oncogenic mutations associated with alcohol intake.

scholarly journals Evaluating the evaluation of cancer driver genes

2016 ◽  
Vol 113 (50) ◽  
pp. 14330-14335 ◽  
Author(s):  
Collin J. Tokheim ◽  
Nickolas Papadopoulos ◽  
Kenneth W. Kinzler ◽  
Bert Vogelstein ◽  
Rachel Karchin
Keyword(s):  
Somatic Mutations ◽  
Gene Prediction ◽  
Gene Mutations ◽  
Evaluation Framework ◽  
Mutation Rates ◽  
Driver Gene ◽  
Driver Genes ◽  
Cancer Driver ◽  
Bona Fide ◽  
Cancer Driver Genes

Sequencing has identified millions of somatic mutations in human cancers, but distinguishing cancer driver genes remains a major challenge. Numerous methods have been developed to identify driver genes, but evaluation of the performance of these methods is hindered by the lack of a gold standard, that is, bona fide driver gene mutations. Here, we establish an evaluation framework that can be applied to driver gene prediction methods. We used this framework to compare the performance of eight such methods. One of these methods, described here, incorporated a machine-learning–based ratiometric approach. We show that the driver genes predicted by each of the eight methods vary widely. Moreover, the P values reported by several of the methods were inconsistent with the uniform values expected, thus calling into question the assumptions that were used to generate them. Finally, we evaluated the potential effects of unexplained variability in mutation rates on false-positive driver gene predictions. Our analysis points to the strengths and weaknesses of each of the currently available methods and offers guidance for improving them in the future.

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