Guanine Holes Are Prominent Targets for Mutation in Cancer and Inherited Disease

Single base substitutions constitute the most frequent type of human gene mutation and are a leading cause of cancer and inherited disease. These alterations occur non-randomly in DNA, being strongly influenced by the local nucleotide sequence context. However, the molecular mechanisms underlying such sequence context-dependent mutagenesis are not fully understood. Using bioinformatics, computational and molecular modeling analyses, we have determined the frequencies of mutation at G•C bp in the context of all 64 5′-NGNN-3′ motifs that contain the mutation at the second position. Twenty-four datasets were employed, comprising >530,000 somatic single base substitutions from 21 cancer genomes, >77,000 germline single-base substitutions causing or associated with human inherited disease and 16.7 million benign germline single-nucleotide variants. In several cancer types, the number of mutated motifs correlated both with the free energies of base stacking and the energies required for abstracting an electron from the target guanines (ionization potentials). Similar correlations were also evident for the pathological missense and nonsense germline mutations, but only when the target guanines were located on the non-transcribed DNA strand. Likewise, pathogenic splicing mutations predominantly affected positions in which a purine was located on the non-transcribed DNA strand. Novel candidate driver mutations and tissue-specific mutational patterns were also identified in the cancer datasets. We conclude that electron transfer reactions within the DNA molecule contribute to sequence context-dependent mutagenesis, involving both somatic driver and passenger mutations in cancer, as well as germline alterations causing or associated with inherited disease.     

MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing

We have developed a novel machine-learning approach, MutPred Splice, for the identification of coding region substitutions that disrupt pre-mRNA splicing. Applying MutPred Splice to human disease-causing exonic mutations suggests that 16% of mutations causing inherited disease and 10 to 14% of somatic mutations in cancer may disrupt pre-mRNA splicing. For inherited disease, the main mechanism responsible for the splicing defect is splice site loss, whereas for cancer the predominant mechanism of splicing disruption is predicted to be exon skipping via loss of exonic splicing enhancers or gain of exonic splicing silencer elements. MutPred Splice is available at http://mutdb.org/mutpredsplice.     

Genes causing inherited cancer as beacons to identify the mechanisms of chemoresistance

Mechanisms of resistance to cancer chemotherapy are poorly understood. Molecular pathways involving genes associated with inherited cancer syndromes could represent mechanisms of chemoresistance. Microarray techniques can identify simultaneous alterations in the mRNA expression of multiple genes, but identification of the exact mechanism responsible for a particular phenotype, including resistance to a specific drug, remains problematic. Genes in which mutations cause inherited cancers play vital roles in apoptosis, growth arrest and/or DNA repair, and are inactivated by somatic mutations, deletions or hypermethylation in most cancer tissues. Similarities between carcinogenic injury and cell damage created by chemotherapeutics suggests that somatic inactivation of such genes is crucially important to drug sensitivity.     

Mitochondrial DNA mutations in diseases of energy metabolism

A variety of degenerative diseases involving deficiencies in mitochondrial bioenergetics have been associated with mitochondrial DNA (mtDNA) mutations. Maternally inherited mtDNA nucleotide substitutions range from neutral polymorphisms to lethal mutations. Neutral polymorphisms are ancient, having accumulated along mtDNA lineages, and thus correlate with ethnic and geographic origin. Mildly deleterious base substitutions have also occurred along mtDNA lineages and have been associated with familial deafness and some cases of Alzheimer's Disease and Parkinson's Disease. Moderately deleterious nucleotide substitutions are more recent and cause maternally-inherited diseases such as Leber's Hereditary Optic Neuropathy (LHON) and Myoclonic Epilepsy and Ragged-Red Fiber Disease (MERRF). Severe nucleotide substitutions are generally new mutations that cause pediatric diseases such as Leigh's Syndrome and dystonia. MtDNA rearrangements also cause a variety of phenotypes. The milder rearrangements generally involve duplications and can cause maternally-inherited adult-onset diabetes and deafness. More severe rearrangements frequently involving detetions have been associated with adult-onset Chronic Progressive External Ophthalmoplegia (CPEO) and Kearns-Sayre Syndrome (KSS) or the lethal childhood disorder, Pearson's Marrow/Pancreas Syndrome. Defects in nuclear-cytoplasmic interaction have also been observed, and include an autosomal dominant mutation causing multiple muscle mtDNA deletions and a genetically complex disease resulting in the tissue depletion of mtDNAs. MtDNA nucleotide substitution and rearrangement mutations also accumulate with age in quiescent tissues. These somatic mutations appear to degrade cellular bioenergetic capacity, exacerbate inherited mitochondrial defects and contribute to tissue senescence. Thus, bioenergetic defects resulting from mtDNA mutations may be a common cause of human degenerative disease.     

Overview: genes that predispose to cancer

Heredity and environment both operate in the origin of cancer. Dominantly heritable cancer is caused by 'cancer' genes that impart high relative risks but account for only a small part of the incidence of cancer; they are usually recessive in oncogenesis, mutation or loss of the second allele being necessary. Non-hereditary forms of cancer may involve the same genes. Other genes interact with environment in carcinogenesis; these may impart relatively small relative risks, but because their frequencies may be high, the attributable risks can be great, as probably is the case with lung cancer. The process of carcinogenesis is thought to involve 2 or more somatic genetic events in most cases. The genes whose germline mutations cause dominantly inherited cancer can also be mutated somatically to cause non-hereditary cancer. Other genes may influence the numbers of target cells, or the proliferation of once-hit stem cells, without being critical events on the path to cancer. However, such genes could greatly influence the incidence of a cancer. Other genes, such as that for Bloom's syndrome, may affect the rates at which first and second events occur. Finally, other genes may influence the occurrence of events critical for progression and metastasis, such as vascularization of a small tumor.     

Statistical analysis of pathogenicity of somatic mutations in cancer

Recent large-scale sequencing studies have revealed that cancer genomes contain variable numbers of somatic point mutations distributed across many genes. These somatic mutations most likely include passenger mutations that are not cancer causing and pathogenic driver mutations in cancer genes. Establishing a significant presence of driver mutations in such data sets is of biological interest. Whereas current techniques from phylogeny are applicable to large data sets composed of singly mutated samples, recently exemplified with a p53 mutation database, methods for smaller data sets containing individual samples with multiple mutations need to be developed. By constructing distinct models of both the mutation process and selection pressure upon the cancer samples, exact statistical tests to examine this problem are devised. Tests to examine the significance of selection toward missense, nonsense, and splice site mutations are derived, along with tests assessing variation in selection between functional domains. Maximum-likelihood methods facilitate parameter estimation, including levels of selection pressure and minimum numbers of pathogenic mutations. These methods are illustrated with 25 breast cancers screened across the coding sequences of 518 kinase genes, revealing 90 base substitutions in 71 genes. Significant selection pressure upon truncating mutations was established. Furthermore, an estimated minimum of 29.8 mutations were pathogenic.     

Germline and somatic mutation profile in Cancer patients revealed by a medium-sized pan-Cancer panel

Gene mutation detection and the resulted precision-medicine therapy is transforming clinical practice. Here, we report the use of a custom-developed, medium-sized, pan-cancer probe panel for the detection of somatic and germline mutations. We used a hybridization capture-based NGS assay for targeted deep sequencing of all exons and selected introns of 181 key cancer driver genes, covering both inherited risks and somatic mutations. We performed paired-variant calling on tumor samples and their matched normal samples. We processed clinical patient samples of formalin-fixed, paraffin embedded tumors (FFPE samples) and cell-free peripheral blood (cfDNA samples). We found germline mutations of inherited cancer risk at 9%; and discovered a novel germline mutation in BRCA1. Somatic mutation rate in driver genes is at 73.1%, much higher than previously reported. On recommending precision-medicine therapeutics, we achieved 91.6% for patients with FFPE samples.     

Integrative Analysis of Somatic Mutations Altering MicroRNA Targeting in Cancer Genomes

Determining the functional impact of somatic mutations is crucial to understanding tumorigenesis and metastasis. Recent sequences of several cancers have provided comprehensive lists of somatic mutations across entire genomes, enabling investigation of the functional impact of somatic mutations in non-coding regions. Here, we study somatic mutations in 3′UTRs of genes that have been identified in four cancers and computationally predict how they may alter miRNA targeting, potentially resulting in dysregulation of the expression of the genes harboring these mutations. We find that somatic mutations create or disrupt putative miRNA target sites in the 3′UTRs of many genes, including several genes, such as MITF, EPHA3, TAL1, SCG3, and GSDMA, which have been previously associated with cancer. We also integrate the somatic mutations with germline mutations and results of association studies. Specifically, we identify putative miRNA target sites in the 3′UTRs of BMPR1B, KLK3, and SPRY4 that are disrupted by both somatic and germline mutations and, also, are in linkage disequilibrium blocks with high scoring markers from cancer association studies. The somatic mutation in BMPR1B is located in a target site of miR-125b; germline mutations in this target site have previously been both shown to disrupt regulation of BMPR1B by miR-125b and linked with cancer.     

Somatic immunoglobulin sequence divergence and its implications for studies of evolutionary divergence

The divergence of immunoglobulin genes due to somatic mutation provides a natural example of DNA sequence divergence. This divergence was examined to gain insight into the processes of evolution and the determinants of the variance-to-mean ratio of sequence divergence. Normally, this ratio is found to be larger than expected (1.0 under Poisson assumptions) for the evolutionary divergence or most genes. Although not significantly less than one, all seven groups of immunoglobulin amino acid sequences have ratios smaller than expected, contrary to the evolutionary pattern generally observed. The substitutions in the immunoglobulin genes appear to be highly nonrandom and an excess of parallel changes (the major nonrandom feature of these mutations) is shown to cause smaller ratios. Because convergent or parallel mutations are often observed in the evolutionary divergence of genes, this suggests that forces causing the large observed ratios may actually have to be more powerful than previously expected. Further, since selection is one of the likely causes of parallel mutations, it should be noted that selection could significantly decrease the variance-to-mean ratio. The high frequency of parallel mutations and their resulting effects, as observed in the immunoglobulin genes, suggest that only poor inferences of sequence divergence can be made without actual knowledge of the ancestral sequence.     

Patterns of Somatic Mutations in Immunoglobulin Variable Genes

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 if the nucleotide substitutions differ from those generated during meiosis and 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 mutations 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.     

Point mutation of the p53 gene resulting in splicing inhibition in small cell lung carcinoma

The p53 gene is functionally inactivated mostly by point mutations resulting in amino acid substitutions in a wide variety of human cancers. We found a novel mutation of the p53 gene in a small cell lung carcinoma cell line, Lu-143. One of the allelic p53 genes was lost accompanied by loss of heterozygosity for chromosome 17. In the remaining allelic p53 gene, there was a single-base substitution of G to T at position 1 within the splice donor site of intron 7, and the mutated intron was not spliced out during the mRNA maturation process. As a result of this mutation, larger sized p53 mRNA was expressed and no p53 specific protein was detected in this cell line. These results suggest that mutations causing splicing abnormalities are one of the molecular mechanisms for the p53 gene inactivation in human cancer.     

Somatic mosaicism and cancer: inference based on a conditional Luria-Delbrück distribution

Somatic mosaicism for mutations in disease-causing genes has been reported in several recent studies. Examples include hemophilia A, many skin disorders, and several cancers such as retinoblastoma and familial adenomatous polyposis. Many of these disorders require multiple mutations in order to express the disease phenotype. For example, two recessive mutations to the retinoblastoma locus are required to initiate retinoblastomal tumors. I develop a mathematical framework for somatic mosaicism in which two recessive mutations cause disease. With my framework, I analyse the following question: Given an observed frequency of cells with two mutations and an easily scored aberrant phenotype, what is the conditional frequency distribution of cells carrying one mutation and therefore susceptible to transformation by a second mutation? This question is important because a high frequency of carrier cells can cause genetic counselors to misdiagnose a mosaic as an inherited heterozygote carrier and because widespread mosaicism can lead to some germline transmission. As more data accumulate, the observed distribution of mosaics can be compared against my predicted distribution. These sorts of studies will contribute to a broader understanding of the distribution of somatic mutations, a central topic in the study of cancer.     

Somatic hypermutagenesis in immunoglobulin genes. II. Influence of neighbouring base sequences on mutagenesis.

A new approach for the analysis of hotspots of mutations is described. It is based on the classification of hotspot site sequences. Using this approach, the consensuses RGYW and TAA of hotspot sites were revealed in the V gene. Correlation between somatic mutations and these consensuses is investigated by the statistical weight method in 323 somatic substitutions in 14 V genes. Assuming the absence of any correlation, the probability of observing such data in the sample would be very low (0.0003). These results support the idea that emergence of somatic mutation is significantly influenced by neighbouring base sequences. This idea was also supported by the analysis of 296 somatic mutations in flanking sequences of V genes. It is supposed that this influence is an important feature of somatic hypermutagenesis.     

Disentangling the perturbational effects of amino acid substitutions in the DNA-binding domain of p53

The spectrum of somatic cancer-associated missense mutations in the human TP53 gene was studied in order to assess the potential structural and functional importance of various intra-molecular properties associated with these substitutions. Relating the observed frequency of particular amino acid substitutions in the p53 DNA-binding domain to their expected frequency, as calculated from DNA sequence-dependent mutation rates, yielded estimates of their relative clinical observation likelihood (RCOL). Several biophysical properties were found to display significant covariation with RCOL values. Thus RCOL values were observed to decrease with increasing solvent accessibility of the substituted residue and with increasing distance from the p53 DNA-binding and Zn²⁺-binding sites. The number of adverse steric interactions introduced by an amino acid replacement was found to be positively correlated with its RCOL value, irrespective of the magnitude of the interactions. A gain in hydrogen bond number was found to be only half as likely to come to clinical attention as mutations involving either a reduction or no change in hydrogen bond number. When the difference in potential energy between the wild-type and mutant DNA-binding domains was considered, RCOL values exhibited a minimum around changes of zero. Finally, classification of mutated residues in terms of their protein/solvent environment yielded, for somatic p53 mutations, RCOL values that resembled those previously determined for inherited mutations of human factor IX causing haemophilia B, suggesting that similar mechanisms may be responsible for the mutation-related perturbation of biological function in different protein folds. Received: 31 August 1998 / Accepted: 26 October 1998     

Missense mutations in hMLH1 associated with colorectal cancer

One of the most prevalent hereditary syndromes associated with colorectal cancer is hereditary nonpolyposis colorectal cancer (HNPCC). The inherited gene defects in HNPCC have been shown to reside in DNA mismatch repair genes, mostly hMSH2 or hMLH1. Most HNPCC patients are heterozygous with regard to the relevant mismatch repair gene; they have one normal and one mutated allele, and mismatch repair in normal somatic cells is functional. Cancer predisposition in HNPCC is believed to be associated with the loss of the wild-type allele in somatic cells, resulting in defective DNA mismatch repair. This gives rise to DNA microsatellite instability (MSI), an increased somatic mutation rate, and eventually, to the accumulation of mutations in genes involved in colorectal carcinogenesis. In support of this theory, colorectal tumors in HNPCC patients and in mice deficient for hMSH2 or hMLH1 show MSI. Here, we describe two missense mutations in hMLH1 exon 16 associated with colorectal cancer. Interestingly, the tumors do not show MSI. This raises some potentially important issues. First, even microsatellite-negative colorectal tumors can be associated with germline mutations and these will be missed if an MSI test is used to select patients for mutation screening. Second, the lack of MSI in these cases suggests that the mechanism involved in carcinogenesis could be different from that generally hypothesized.     

Germline fitness-based scoring of cancer mutations

A key goal in cancer research is to find the genomic alterations that underlie malignant cells. Genomics has proved successful in identifying somatic variants at a large scale. However, it has become evident that a typical cancer exhibits a heterogenous mutation pattern across samples. Cases where the same alteration is observed repeatedly seem to be the exception rather than the norm. Thus, pinpointing the key alterations (driver mutations) from a background of variations with no direct causal link to cancer (passenger mutations) is difficult. Here we analyze somatic missense mutations from cancer samples and their healthy tissue counterparts (germline mutations) from the viewpoint of germline fitness. We calibrate a scoring system from protein domain alignments to score mutations and their target loci. We show first that this score predicts to a good degree the rate of polymorphism of the observed germline variation. The scoring is then applied to somatic mutations. We show that candidate cancer genes prone to copy number loss harbor mutations with germline fitness effects that are significantly more deleterious than expected by chance. This suggests that missense mutations play a driving role in tumor suppressor genes. Furthermore, these mutations fall preferably onto loci in sequence neighborhoods that are high scoring in terms of germline fitness. In contrast, for somatic mutations in candidate onco genes we do not observe a statistically significant effect. These results help to inform how to exploit germline fitness predictions in discovering new genes and mutations responsible for cancer.     

Application of Rigidity Theory to the Thermostabilization of Lipase A from Bacillus subtilis

Protein thermostability is a crucial factor for biotechnological enzyme applications. Protein engineering studies aimed at improving thermostability have successfully applied both directed evolution and rational design. However, for rational approaches, the major challenge remains the prediction of mutation sites and optimal amino acid substitutions. Recently, we showed that such mutation sites can be identified as structural weak spots by rigidity theory-based thermal unfolding simulations of proteins. Here, we describe and validate a unique, ensemble-based, yet highly efficient strategy to predict optimal amino acid substitutions at structural weak spots for improving a protein’s thermostability. For this, we exploit the fact that in the majority of cases an increased structural rigidity of the folded state has been found as the cause for thermostability. When applied prospectively to lipase A from Bacillus subtilis, we achieved both a high success rate (25% over all experimentally tested mutations, which raises to 60% if small-to-large residue mutations and mutations in the active site are excluded) in predicting significantly thermostabilized lipase variants and a remarkably large increase in those variants’ thermostability (up to 6.6°C) based on single amino acid mutations. When considering negative controls in addition and evaluating the performance of our approach as a binary classifier, the accuracy is 63% and increases to 83% if small-to-large residue mutations and mutations in the active site are excluded. The gain in precision (predictive value for increased thermostability) over random classification is 1.6-fold (2.4-fold). Furthermore, an increase in thermostability predicted by our approach significantly points to increased experimental thermostability (p < 0.05). These results suggest that our strategy is a valuable complement to existing methods for rational protein design aimed at improving thermostability.     

The Cancer Mutation D83V Induces an α-Helix to β-Strand Conformation Switch in MEF2B

MEF2B is a major target of somatic mutations in non-Hodgkin lymphoma. Most of these mutations are non-synonymous substitutions of surface residues in the MADS-box/MEF2 domain. Among them, D83V is the most frequent mutation found in tumor cells. The link between this hotspot mutation and cancer is not well understood. Here we show that the D83V mutation induces a dramatic α-helix to β-strand switch in the MEF2 domain. Located in an α-helix region rich in β-branched residues, the D83V mutation not only removes the extensive helix stabilization interactions but also introduces an additional β-branched residue that further shifts the conformation equilibrium from α-helix to β-strand. Cross-database analyses of cancer mutations and chameleon sequences revealed a number of well-known cancer targets harboring β-strand favoring mutations in chameleon α-helices, suggesting a commonality of such conformational switch in certain cancers and a new factor to consider when stratifying the rapidly expanding cancer mutation data.     

The functional importance of disease-associated mutation

Background  

For many years, scientists believed that point mutations in genes are the genetic switches for somatic and inherited diseases such as cystic fibrosis, phenylketonuria and cancer. Some of these mutations likely alter a protein's function in a manner that is deleterious, and they should occur in functionally important regions of the protein products of genes. Here we show that disease-associated mutations occur in regions of genes that are conserved, and can identify likely disease-causing mutations.