A coalescent analysis for modeling the mutation process in colorectal cancer

Colorectal cancer is the forth most common diagnosed cancer in the United States. Every year about a hundred forty-seven thousand people will be diagnosed with colorectal cancer and fifty-six thousand people lose their lives due to this disease. Most of the hereditary nonpolyposis colorectal cancer (HNPCC) and 12% of the sporadic colorectal cancer show microsatellite instability. Colorectal cancer is a multistep progressive disease. It starts from a mutation in a normal colorectal cell and grows into a clone of cells that further accumulates mutations and finally develops into a malignant tumor. In terms of molecular evolution, the process of colorectal tumor progression represents the acquisition of sequential mutations. ^ Clinical studies use biomarkers such as microsatellite or single nucleotide polymorphisms (SNPs) to study mutation frequencies in colorectal cancer. Microsatellite data obtained from single genome equivalent PCR or small pool PCR can be used to infer tumor progression. Since tumor progression is similar to population evolution, we used an approach known as coalescent, which is well established in population genetics, to analyze this type of data. Coalescent theory has been known to infer the sample's evolutionary path through the analysis of microsatellite data. ^ The simulation results indicate that the constant population size pattern and the rapid tumor growth pattern have different genetic polymorphic patterns. The simulation results were compared with experimental data collected from HNPCC patients. The preliminary result shows the mutation rate in 6 HNPCC patients range from 0.001 to 0.01. The patients' polymorphic patterns are similar to the constant population size pattern which implies the tumor progression is through multilineage persistence instead of clonal sequential evolution. The results should be further verified using a larger dataset. ^

Genotypic spectrum and genotype-phenotype correlation of trimethylaminuria

Trimethylaminuria (TMAU) or Fish odor syndrome is an autosomal recessive disease that is characterized by pungent body odor with subsequent psychosocial complications. There are limited studies of the sequence variants causing TMAU in the literature with most studies describing only one or two patients and lacking genotype-phenotype correlations. Also to date, there is no laboratory in the US or Europe that offers TMA genetic testing on a clinical basis. We have recently validated genetic testing in the University of Colorado DNA Diagnostic Laboratory. We have a database of a few dozen patients with a biochemical diagnosis of TMA at the University of Colorado at Denver Health Sciences Center (UCDHSC) which includes a few patients with the classical form of the disease. We have used the newly established clinical test in our institution to attempt to characterize the genotype (sequence variants including mutations and polymorphisms) of classical TMAU patients and to establish a genotype-phenotype (biochemical and clinical) association. The questionnaire results confirmed most of the previously reported epidemiological findings of TMAU and also indicated that TMAU patients use multiple intervention measures in attempt to control their symptoms with dietary control being most effective. Despite the complexity of intervention, most patients did not have any medical follow up and there was underutilization of specialist care. In a set of our patients, two deleterious mutations were identified in 4/12 patients including a novel T237P sequence variant, while the majority of our patients (8/12) did not reveal any mutations. Some of the latter were double heterozygous for the E158K and E308G polymorphisms which could explain a mild phenotype while others had only the E158K variant which raised the question of undetected mutations. These results indicate that further experiments are needed to further delineate the full mutational spectrum of the FMO3 gene. ^

NRAS and BRAF mutations in primary cutaneous melanoma: A comparison of mutation rates between radial and vertical growth phases in individual tumors

Primary cutaneous melanoma is a cancer arising from melanocytes in the skin. In recent decades the incidence of this malignancy has increased significantly. Mortality rates are high for patients with tumors measuring over a few millimeters in thickness. Response rates to conventional radiation and chemotherapy are very low in patients with metastatic melanoma. New therapies targeting melanoma’s aberrant cell signaling pathways such as the MAP Kinase pathway are being developed. Mutations of NRAS and BRAF genes are quite common in cutaneous melanoma and lead to constitutive activation of the MAP Kinase pathway. This study tests the hypothesis that NRAS and BRAF mutations increase as a tumor progresses from the noninvasive radial growth phase (RGP) to the invasive vertical growth phase (VGP). Laser capture microdissection was used to obtain separate, pure tumor DNA samples from the RGP and VGP of thirty primary cutaneous melanomas. PCR was used to amplify NRAS exon 2 and BRAF exon 15 tumor DNA. The amplified DNA was sequenced and analyzed for mutations. An overall mutation rate of 74% was obtained for the twenty-three melanomas in which there were complete sequence results. With the exception of one melanoma NRAS and BRAF mutations were mutually exclusive. All seven NRAS exon 2 mutations involved codon 61. Three of these melanomas had mutations in both the RGP and VGP. The remaining four tumors were wild type for NRAS exon 2 in the RGP but mutated in the VGP. Of the fifteen BRAF exon 15 mutated melanomas all but one involved codon 600. Twelve of the fifteen BRAF exon 15 mutations were the T1799A type. Nine of the fifteen BRAF mutated tumors had the same mutation in both the RGP and VGP. Five of fifteen melanomas had wild type RGP DNA and BRAF exon 15 mutated VGP DNA. A single melanoma had BRAF exon 15 mutated DNA in the RGP and wild type DNA in the VGP. Overall, these results suggest a trend toward the acquisition of NRAS and BRAF mutations as cutaneous melanomas change from a noninvasive to an invasive, potentially deadly cancer.^

The effect of genotype-by-environment interaction on longitudinal triglyceride profiles in the Bogalusa Heart Study

Triglyceride levels are a component of plasma lipids that are thought to be an important risk factor for coronary heart disease and are influenced by genetic and environmental factors, such as single nucleotide polymorphisms (SNPs), alcohol intake, and smoking. This study used longitudinal data from the Bogalusa Heart Study, a biracial community-based survey of cardiovascular disease risk factors. A sample of 1191 individuals, 4 to 38 years of age, was measured multiple times from 1973 to 2000. The study sample consisted of 730 white and 461 African American participants. Individual growth models were developed in order to assess gene-environment interactions affecting plasma triglycerides over time. After testing for inclusion of significant covariates and interactions, final models, each accounting for the effects of a different SNP, were assessed for fit and normality. After adjustment for all other covariates and interactions, LIPC -514C/T was found to interact with age3, age2, and age and a non-significant interaction of CETP -971G/A genotype with smoking status was found (p = 0.0812). Ever-smokers had higher triglyceride levels than never smokers, but persons heterozygous at this locus, about half of both races, had higher triglyceride levels after smoking cessation compared to current smokers. Since tobacco products increase free fatty acids circulating in the bloodstream, smoking cessation programs have the potential to ultimately reduce triglyceride levels for many persons. However, due to the effect of smoking cessation on the triglyceride levels of CETP -971G/A heterozygotes, the need for smoking prevention programs is also demonstrated. Both smoking cessation and prevention programs would have a great public health impact on minimizing triglyceride levels and ultimately reducing heart disease. ^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

EFFECTS OF THE ACTA2 R258C MUTATION ON VASCULAR SMOOTH MUSCLE CELL PHENOTYPE AND PROPERTIES

Thoracic Aortic Aneurysms and Dissections (TAAD) are the fifteenth leading cause of death in the United States. About 15% of TAAD patients have family history of the disease. The most commonly mutated gene in these families is ACTA2, encoding smooth muscle-specific α-actin. ACTA2 missense mutations predispose individuals both to TAAD and to vascular occlusive disease of small, muscular arteries. Mice carrying an Acta2 R258C mutant transgene with a wildtype Acta2 promoter were generated and bred with Acta2-/- mice to decrease the wildtype: mutant Acta2 ratio. Acta2+/+ R258C TGmice have decreased aortic contractility without aortic disease. Acta2+/- R258C TG mice, however, have significant aortic dilatations by 12 weeks of age and a hyperproliferative response to injury. We characterized smooth muscle cells (SMCs) from bothmouse models under the hypothesis that mutant α-actin has a dominant negative effect, leading to impaired contractile filament formation/stability, improper focal adhesion maturation and increased proliferation. Explanted aortic SMCs from Acta2+/+ R258C TG mice are differentiated - they form intact filaments, express higher levels of contractile markers compared to wildtype SMCs and have predominantly nuclear Myocardin-Related Transcription Factor A (MRTF-A) localization. However, ultracentrifugation assays showed large unpolymerized actin fractions, suggesting that the filaments are brittle. In contrast, Acta2+/- R258C TG SMCs are less well-differentiated, with pools of unpolymerized actin, more cytoplasmic MRTF-A and decreased contractile protein expression compared to wildtype cells. Ultracentrifugation assays after treating Acta2+/- R258C TGSMCs with phalloidin showed actin filament fractions, indicating that mutant α-actin can polymerize into filaments. Both Acta2+/+ R258C TGand Acta2+/- R258C TGSMCs have larger and more peripheral focal adhesions compared to wildtype SMCs. Rac1 was more activated in Acta2+/+ R258C TGSMCs; both Rac1 and RhoA were less activated in Acta2+/- R258C TG SMCs, and FAK was more activated in both transgenic SMC lines compared to wildtype. Proliferation in both cell lines was significantly increased compared to wildtype cells and could be partially attenuated by inhibition of FAK or PDGFRβ. These data support a dominant negative effect of the Acta2 R258C mutation on the SMC phenotype, with increasing phenotypic severity when wildtype: mutant α-actin levels are decreased.

DETERMINING THE GENOTYPE-PHENOTYPE CONNECTION IN SYNTHETIC INDUCIBLE GENE EXPRESSION SYSTEMS

Introduction Gene expression is an important process whereby the genotype controls an individual cell’s phenotype. However, even genetically identical cells display a variety of phenotypes, which may be attributed to differences in their environment. Yet, even after controlling for these two factors, individual phenotypes still diverge due to noisy gene expression. Synthetic gene expression systems allow investigators to isolate, control, and measure the effects of noise on cell phenotypes. I used mathematical and computational methods to design, study, and predict the behavior of synthetic gene expression systems in S. cerevisiae, which were affected by noise. Methods I created probabilistic biochemical reaction models from known behaviors of the tetR and rtTA genes, gene products, and their gene architectures. I then simplified these models to account for essential behaviors of gene expression systems. Finally, I used these models to predict behaviors of modified gene expression systems, which were experimentally verified. Results Cell growth, which is often ignored when formulating chemical kinetics models, was essential for understanding gene expression behavior. Models incorporating growth effects were used to explain unexpected reductions in gene expression noise, design a set of gene expression systems with “linear” dose-responses, and quantify the speed with which cells explored their fitness landscapes due to noisy gene expression. Conclusions Models incorporating noisy gene expression and cell division were necessary to design, understand, and predict the behaviors of synthetic gene expression systems. The methods and models developed here will allow investigators to more efficiently design new gene expression systems, and infer gene expression properties of TetR based systems.

Functional analysis of p53 phosphorylation and a p53 hot spot mutation

The tumor suppressor p53 is a phosphoprotein which functions as a transcriptional activator. By monitoring the transcriptional activity, we studied how p53 functions is regulated in relation to cell growth and contact inhibition. When cells were arrested at G1 phase of the cell cycle by contact inhibition, we found that p53 transactivation function was suppressed. When contact inhibition was overridden by cyclin E overexpression which stimulates cell cycle progression, p53 function was restored. This observation led to the development of a cell density assay to study the regulation of p53 function during cell cycle for the functional significance of p53 phosphorylation. The murine p53 is phosphorylated at serines 7, 9, 12, 18, 37, 312 and 389. To understand the role of p53 phosphorylation, we generated p53 constructs encoding serine-to-alanine or serine-to-glutamate mutations at these codons. The transcriptional activity were measured in cells capable of contact inhibition. In low-density cycling cells, no difference in transcriptional activity was found between wild type p53 and any of the mutants. In contact-inhibited cells, however, only mutations of p53 at serine 389 resulted in altered responses to cell cycle arrest and to cyclin E overexpression. The mutant with serine-to-glutamate substitution at codon 389 retained its function in contact inhibited cells. Cyclin E overexpression in these cells induced p53 phosphorylation at serine 389. Furthermore, we showed that phosphorylation at serine 389 regulates p53 DNA binding activity. Our findings implicate that phosphorylation is an important mechanism for p53 activation.^ p53 is the most frequently mutated gene in human tumors. To study the mechanism of p53 inactivation by mutations, we carried out detailed analysis of a murine p53 mutation with an arginine-to-tryptophane substitution at codon 245. The corresponding human p53 mutation at amino acid 248 is the most frequently mutated codon in tumors. We showed that this mutant is inactive in suppressing focus formation, binding to DNA and transactivation. Structural analysis revealed that this mutant assumes the wild type protein conformation. These findings define a novel class of p53 mutations and help to understand structure-function relationship of p53. ^

Gain-of-function of the p53R172H mutation in a mouse model of Li -Fraumeni syndrome

Missense mutations in the p53 tumor-suppressor gene are the most common alterations of p53 in somatic tumors and in patients with Li-Fraumeni syndrome. p53 missense mutations occur in the DNA binding region and disrupt the ability of p53 to activate transcription. In vitro studies have shown that some p53 missense mutants have a gain-of-function or dominant-negative activity. ^ The p53 175 Arg-to-His (p53 R175H) mutation in humans has been shown to have dominant-negative and gain-of-function properties in vitro. This mutation is observed in the germline of individuals with Li-Fraumeni syndrome. To accurately model Li-Fraumeni syndrome and to examine the mechanistic nature of a gain-of-function missense mutation on in vivo tumorigenesis, we generated and characterized a mouse with the corresponding mutation, p53 R172H. p53R172H homozygous and heterozygous mice developed similar tumor spectra and survival curves as p53 −/− and p53+/− mice, respectively. However, tumors in p53+/R172H mice metastasized to various organs with high frequency, suggesting a gain-of-function phenotype by p53R172H in vivo. Mouse embryonic fibroblasts (MEFs) from p53R172H mice also showed gain-of-function phenotypes in cell proliferation, DNA synthesis, and transformation potential, while cells from p53+/− and p53−/− mice did not. ^ To mechanistically characterize the gain-of-function phenotype of the p53R172H mutant, the role of p53 family members, p63 and p73, was analyzed. Disruption of p63 and p73 by siRNAs in p53 −/− MEFs increased transformation potential and reinitiated DNA synthesis to levels observed in p53R172H/R172H cells. Additionally, p63 and p73 were bound and functionally inactivated by p53R172H in metastatic p53 R172H tumor-derived cell lines, indicating a role for the p53 family members in the gain-of-function phenotype. This study provides in vivo evidence for the gain-of-function effect of p53 missense mutations and more accurately models the Li-Fraumeni syndrome. ^