Validation of an RNA cell cycle progression score for predicting death from prostate cancer in a conservatively managed needle biopsy cohort.

BACKGROUND: The natural history of prostate cancer is highly variable and difficult to predict accurately. Better markers are needed to guide management and avoid unnecessary treatment. In this study, we validate the prognostic value of a cell cycle progression score (CCP score) independently and in a prespecified linear combination with standard clinical variables, that is, a clinical-cell-cycle-risk (CCR) score. METHODS: Paraffin sections from 761 men with clinically localized prostate cancer diagnosed by needle biopsy and managed conservatively in the United Kingdom, mostly between 2000 and 2003. The primary end point was prostate cancer death. Clinical variables consisted of centrally reviewed Gleason score, baseline PSA level, age, clinical stage, and extent of disease; these were combined into a single predefined risk assessment (CAPRA) score. Full data were available for 585 men who formed a fully independent validation cohort. RESULTS: In univariate analysis, the CCP score hazard ratio was 2.08 (95% CI (1.76, 2.46), P<10(-13)) for one unit change of the score. In multivariate analysis including CAPRA, the CCP score hazard ratio was 1.76 (95% CI (1.44, 2.14), P<10(-6)). The predefined CCR score was highly predictive, hazard ratio 2.17 (95% CI (1.83, 2.57), χ(2)=89.0, P<10(-20)) and captured virtually all available prognostic information. CONCLUSIONS: The CCP score provides significant pretreatment prognostic information that cannot be provided by clinical variables and is useful for determining which patients can be safely managed conservatively, avoiding radical treatment.

Patterns of genomic loss of heterozygosity predict homologous recombination repair defects in epithelial ovarian cancer.

BACKGROUND: Defects in BRCA1, BRCA2, and other members of the homologous recombination pathway have potential therapeutic relevance when used to support agents that introduce or exploit double-stranded DNA breaks. This study examines the association between homologous recombination defects and genomic patterns of loss of heterozygosity (LOH). METHODS: Ovarian tumours from two independent data sets were characterised for defects in BRCA1, BRCA2, and RAD51C, and LOH profiles were generated. Publically available data were downloaded for a third independent data set. The same analyses were performed on 57 cancer cell lines. RESULTS: Loss of heterozygosity regions of intermediate size were observed more frequently in tumours with defective BRCA1 or BRCA2 (P=10(-11)). The homologous recombination deficiency (HRD) score was defined as the number of these regions observed in a tumour sample. The association between HRD score and BRCA deficiency was validated in two independent ovarian cancer data sets (P=10(-5) and 10(-29)), and identified breast and pancreatic cell lines with BRCA defects. CONCLUSION: The HRD score appears capable of detecting homologous recombination defects regardless of aetiology or mechanism. This score could facilitate the use of PARP inhibitors and platinum in breast, ovarian, and other cancers.

Prognostic value of a cell cycle progression signature for prostate cancer death in a conservatively managed needle biopsy cohort.

BACKGROUND: The natural history of prostate cancer is highly variable and it is difficult to predict. We showed previously that a cell cycle progression (CCP) score was a robust predictor of outcome in a conservatively managed cohort diagnosed by transurethral resection of the prostate. A greater need is to predict outcome in patients diagnosed by needle biopsy. METHODS: Total RNA was extracted from paraffin specimens. A CCP score was calculated from expression levels of 31 genes. Clinical variables consisted of centrally re-reviewed Gleason score, baseline prostate-specific antigen level, age, clinical stage, and extent of disease. The primary endpoint was death from prostate cancer. RESULTS: In univariate analysis (n=349), the hazard ratio (HR) for death from prostate cancer was 2.02 (95% CI (1.62, 2.53), P<10(-9)) for a one-unit increase in CCP score. The CCP score was only weakly correlated with standard prognostic factors and in a multivariate analysis, CCP score dominated (HR for one-unit increase=1.65, 95% CI (1.31, 2.09), P=3 × 10(-5)), with Gleason score (P=5 × 10(-4)) and prostate-specific antigen (PSA) (P=0.017) providing significant additional contributions. CONCLUSION: For conservatively managed patients, the CCP score is the strongest independent predictor of cancer death outcome yet described and may prove valuable in managing clinically localised prostate cancer.

Evidence for HTR1A and LHPP as interacting genetic risk factors in major depression.

The HTR1A -1019C>G genotype was associated with major depression in the Utah population. Linkage analysis on Utah pedigrees with strong family histories of major depression including only cases with the HTR1A -1019G allele revealed a linkage peak on chromosome 10 (maximum HLOD=4.4). Sequencing of all known genes in the linkage region revealed disease-segregating single-nucleotide polymorphisms (SNPs) in LHPP. LHPP SNPs were also associated with major depression in both Utah and Ashkenazi populations. Consistent with the linkage evidence, LHPP associations depended on HTR1A genotype. Lhpp or a product of a collinear brain-specific transcript, therefore, may interact with Htr1a in the pathogenesis of major depression.

Genomic DNA pooling for whole-genome association scans in complex disease: empirical demonstration of efficacy in rheumatoid arthritis.

A pragmatic approach that balances the benefit of a whole-genome association (WGA) experiment against the cost of individual genotyping is to use pooled genomic DNA samples. We aimed to determine the feasibility of this approach in a WGA scan in rheumatoid arthritis (RA) using the validated human leucocyte antigen (HLA) and PTPN22 associations as test loci. A total of 203 269 single-nucleotide polymorphisms (SNPs) on the Affymetrix 100K GeneChip and Illumina Infinium microarrays were examined. A new approach to the estimation of allele frequencies from Affymetrix hybridization intensities was developed involving weighting for quality signals from the probe quartets. SNPs were ranked by z-scores, combined from United Kingdom and New Zealand case-control cohorts. Within a 1.7 Mb HLA region, 33 of the 257 SNPs and at PTPN22, 21 of the 45 SNPs, were ranked within the top 100 associated SNPs genome wide. Within PTPN22, individual genotyping of SNP rs1343125 within MAGI3 confirmed association and provided some evidence for association independent of the PTPN22 620W variant (P=0.03). Our results emphasize the feasibility of using genomic DNA pooling for the detection of association with complex disease susceptibility alleles. The results also underscore the importance of the HLA and PTPN22 loci in RA aetiology.

Analysis of missense variation in human BRCA1 in the context of interspecific sequence variation.

INTRODUCTION: Interpretation of results from mutation screening of tumour suppressor genes known to harbour high risk susceptibility mutations, such as APC, BRCA1, BRCA2, MLH1, MSH2, TP53, and PTEN, is becoming an increasingly important part of clinical practice. Interpretation of truncating mutations, gene rearrangements, and obvious splice junction mutations, is generally straightforward. However, classification of missense variants often presents a difficult problem. From a series of 20,000 full sequence tests of BRCA1 carried out at Myriad Genetic Laboratories, a total of 314 different missense changes and eight in-frame deletions were observed. Before this study, only 21 of these missense changes were classified as deleterious or suspected deleterious and 14 as neutral or of little clinical significance. METHODS: We have used a combination of a multiple sequence alignment of orthologous BRCA1 sequences and a measure of the chemical difference between the amino acids present at individual residues in the sequence alignment to classify missense variants and in-frame deletions detected during mutation screening of BRCA1. RESULTS: In the present analysis we were able to classify an additional 50 missense variants and two in-frame deletions as probably deleterious and 92 missense variants as probably neutral. Thus we have tentatively classified about 50% of the unclassified missense variants observed during clinical testing of BRCA1. DISCUSSION: An internal test of the analysis is consistent with our classification of the variants designated probably deleterious; however, we must stress that this classification is tentative and does not have sufficient independent confirmation to serve as a clinically applicable stand alone method.

Linkage of body mass index to chromosome 20 in Utah pedigrees.

Several linkage studies have hinted at the existence of an obesity predisposition locus on chromosome 20, but none of these studies has produced conclusive results. Therefore, we analyzed 48 genetic markers on chromosome 20 for linkage to severe obesity (BMI> or =35) in 103 extended Utah pedigrees (1,711 individuals), all of which had strong aggregation of severe obesity. A simple dominant model produced a maximum multipoint heterogeneity LOD score of 3.5 at D20S438 (55.1 cM). Two additional analyses were performed. First, a one-gene, two-mutation model (with one dominant mutation and one recessive mutation) increased the LOD score to 4.2. Second, a two-locus model (with one locus dominant and one recessive) generated a multipoint LOD score of 4.9. We conclude that one or more severe obesity predisposing genes lie within an interval of approx. 10 cM on chromosome 20. This study generated significant LOD scores which confirm suggestive linkage reports from previous studies. In addition, our analyses suggest that the predisposing gene(s) is localized very near the chromosome 20 centromere.

A new nonparametric linkage statistic for mapping both qualitative and quantitative trait loci.

We describe an alternative nonparametric linkage (NPL) statistic to that of Kruglyak et al. [Am. J. Hum. Genet. 58:1347-63, 1996] that can be used with qualitative phenotypes, and is easily extended for use with quantitative phenotypes. We analyzed the Genetic Analysis Workshop 12 simulated isolated population data, replicate 1, using two phenotypes; affected status (AFF) a dichotomous phenotype and quantitative trait Q5, which was chosen since it was the most strongly associated with AFF. One false positive significant NPL score was observed for the AFF phenotype. For Q5 a single region on chromosome 1 reached genome-wide significance. The peak of this signal was for marker D01G137 at 135.1 cM with a quantitative trait locus (QTL)-NPL score of 4.19. The nearest marker to the true location of the major gene (MG5 at 137.1 cM) was D01G139 at position 135.8 cM, where the QTL-NPL score was still high at 4.08.

A robust multipoint linkage statistic (tlod) for mapping complex trait loci.

Classical parametric two-point linkage analysis is a powerful analysis tool, however there are clear disadvantages too, including the sensitivity to allele frequency mis-specification. Conversely, multipoint linkage analysis is not sensitive to allele frequency mis-specification, but it is sensitive to genetic model mis-specification. Göring and Terwilliger [Am J Hum Genet 66:1095-106, 2000] proposed a new robust multipoint statistic that increased the robustness of multipoint analyses. In this paper we have referred to this new statistic as the tlod. We applied this new statistic to the Genetic Analysis Workshop (GAW) 12 data using affected status (AFF) as the phenotype of interest. The heterogeneity tlod and two-point hlod scores correlated highly across the genome (p < 0.0001), as expected, but the het-tlod had a lower number false positives. In addition, the tlod analysis handled missing data better, as would be expected for a multipoint method. When one-third of the genotype data was removed (dead people) the tlod analysis was less affected than the two-point analysis. When tlod scores were compared with multipoint lod scores in true gene locations, the robustness of the tlod to model mis-specification was clearly evident. When the "best" replicate from the general population was analyzed, a borderline genome-wide significant two-point hlod result (3.6) was found 4 cM from MG6 and MG7 on chromosome 6. The heterogeneity tlod score was lower than the two-point hlod score (1.8), but greater than the heterogeneity multipoint lod score (0.4). However, when replicate 1 of the isolated population was analyzed none of the true gene locations were identified with either statistic.

Allelic association in large pedigrees.

We subjected the first replication of the simulated isolated population data set to a novel analysis for association between marker alleles and either disease phenotypes or quantitative variable. The analysis depends on being able to reliably reconstruct all haplotypes in the pedigree. This was achieved using the MCLINK blocked Gibbs sampling program. We observed a highly significant association between the variable Q5 and marker D01G138, and suggestive associations between the disease trait and markers D03G056 and D07G004.

Evidence of linkage of familial hypoalphalipoproteinemia to a novel locus on chromosome 11q23.

Coronary heart disease (CHD) accounts for half of the 1 million deaths annually ascribed to cardiovascular disease and for almost all of the 1.5 million acute myocardial infarctions. Within families affected by early and apparently heritable CHD, dyslipidemias have a much higher prevalence than in the general population; 20%-30% of early familial CHD has been ascribed to primary hypoalphalipoproteinemia (low HDL-C). This study assesses the evidence for linkage of low HDL-C to chromosomal region 11q23 in 105 large Utah pedigrees ascertained with closely related clusters of early CHD and expanded on the basis of dyslipidemia. Linkage analysis was performed by use of 22 STRP markers in a 55-cM region of chromosome 11. Two-point analysis based on a general, dominant-phenotype model yielded LODs of 2.9 for full pedigrees and 3.5 for 167 four-generation split pedigrees. To define a localization region, model optimization was performed using the heterogeneity, multipoint LOD score (mpHLOD). This linkage defines a region on 11q23.3 that is approximately 10 cM distal to-and apparently distinct from-the ApoAI/CIII/AIV gene cluster and thus represents a putative novel localization for the low HDL-C phenotype.

Theory of kinetic partitioning in protein folding with possible applications to prions.

This study focuses of the phenomenon of kinetic partitioning when a polypeptide chain has two ground-state conformations, one of which is kinetically more reachable than the other. We designed sequences for lattice model proteins with two different conformations of equal energy corresponding to the global energy minimum. Folding simulations revealed that one of these conformations was indeed much more kinetically accessible than the other. We found that the number and strength of local contacts in the ground-state conformation are the major factors that determine which conformation is reached faster; the greater the number of local contacts, the more kinetically reachable a conformation is. We present simple statistical-mechanical arguments to explain these findings. Our results may be relevant in explaining the phenomenology of such proteins as human plasminogen activator inhibitor-1 (PAI-1), photosystem II, and prions.

A protein engineering analysis of the transition state for protein folding: simulation in the lattice model.

BACKGROUND: Protein engineering has been used extensively to evaluate the properties of transition states in protein folding. Although the method has proved useful, its limitations and the details of interpretation of the obtained results remain largely unexplored. RESULTS: Lattice model simulations are used to test and verify the protein engineering analysis of the transition state in protein folding. It is shown that in some cases - but not always - this method is able to determine the transition state with reasonable accuracy. Limitations of protein engineering are revealed and analyzed. In particular, the change in non-native interactions as a result of mutations is shown to influence the results of the protein engineering analysis. Furthermore, the temperature dependencies of phi values (which are a measure of the participation of a residue in the transition state) and the character of the transition state ensemble are studied. It is shown that as a general trend phi values decrease when the temperature decreases, a finding consistent with recent experimental results. Our analysis suggests that this trend results primarily from the formation of some contacts (native and non-native) in the unfolded state at a lower temperature, when the barrier for folding is energetic. CONCLUSIONS: Our analysis helps to interpret the results of protein engineering and allows observed φ values to be directly related to structural features of the unfolded state, the transition state and the native state.

Computer simulations of prebiotic evolution.

This paper is a review of our previous work on the field of possible ways of prebiotic evolution. We propose an algorithm providing sequences of model proteins with rapid folding into a given native conformation. Thermodynamical analysis shows that the increase in speed is matched by an increase in stability: the evolved sequences are much more stable in their native conformation than the initial random sequence. We discuss a possible origin of the first biopolymers, having stable unique structure. We suggest that at the prebiotic stage of evolution, long organic polymers had to be compact in order to avoid hydrolysis and had to be soluble and thus must not be exceedingly hydrophobic. We present an algorithm that generates such sequences of model proteins. The evolved sequences turn out to have a stable unique structure, into which they quickly fold. This result illustrates the idea that the unique three-dimensional native structure of first biopolymers could have evolved as a side effect of a nonspecific physico-chemical factors acting at the prebiotic stage of evolution.

Improved design of stable and fast-folding model proteins.

BACKGROUND: A number of approaches to design stable and fast-folding sequences for model polypeptide chains have been based on the premise that optimization of the relative energy of the native conformation (or Z-score) is sufficient to yield stable and fast-folding sequences. Although this approach has been successful, for longer chains it often yielded sequences that failed to fold cooperatively, instead having multidomain folding behavior. RESULTS: We show that one of the factors determining single-domain or multidomain folding behavior is the dispersion of energies of native contacts. So, we study folding of sequences optimized to have the same native conformation as a global energy minimum but having different dispersion of native contact energies. Our results suggest that under conditions at which native conformation is stable, the best-folding proteins are those that have smaller heterogeneity of native contact energies. For them, the folding transition is all-or-none. On the other hand, proteins with greater heterogeneity of native contact energies have more gradual multidomain folding transition and fold into stable native conformation much slower than those proteins with small dispersion of native contact energies.

How the first biopolymers could have evolved.

In this work, we discuss a possible origin of the first biopolymers with stable unique structures. We suggest that at the prebiotic stage of evolution, long organic polymers had to be compact to avoid hydrolysis and had to be soluble and thus must not be exceedingly hydrophobic. We present an algorithm that generates such sequences for model proteins. The evolved sequences turn out to have a stable unique structure, into which they quickly fold. This result illustrates the idea that the unique three-dimensional native structures of first biopolymers could have evolved as a side effect of nonspecific physicochemical factors acting at the prebiotic stage of evolution.

Simulations of chaperone-assisted folding.

We investigated a chaperone mechanism of protein folding using a 36-mer model on a cubic lattice. The mechanism simulates folding, which proceeds with repetitive cycles of binding, unfolding, and releasing of misfolded metastable states. We measured the yield enhancement due to this mechanism for sequences selected by evolutionary design and showed that the binding and releasing mechanism is efficient for the yield enhancement of folding for sequences that are poorly designed, i.e., where selection is not adequately strong. From this it follows that the chaperone mechanism can be considered as the evolutionary alternative to compensate for poor sequence design. On the other hand, random sequences show a decrease in yield and no effect on the total mean first passage time when the proposed chaperone mechanism is implemented, thus implying that sequence optimization is a necessary condition for the efficiency of the proposed mechanism. We qualitatively reproduced experimental results for folding in the presence of GroEL/GroES, fit our results with the aid of a double-exponential model of folding kinetics, and characterized the conditions under which this mechanism of chaperone action affects folding.

Why do protein architectures have Boltzmann-like statistics?

A theoretical study has shown that the occurrence of various structural elements in stable folds of random copolymers is exponentially dependent on the own energy of the element. A similar occurrence-on-energy dependence is observed in globular proteins from the level of amino acid conformations to the level of overall architectures. Thus, the structural features stabilized by many random sequences are typical of globular proteins while the features rarely observed in proteins are those which are stabilized by only a minor part of the random sequences.

Perfect temperature for protein structure prediction and folding.

We have investigated the influence of the "noise" of inevitable errors in energetic parameters on protein structure prediction. Because of this noise, only a part of all the interactions operating in a protein chain can be taken into account, and therefore a search for the energy minimum becomes inadequate for protein structure prediction. One can rather rely on statistical mechanics: a calculation carried out at a temperature T* somewhat below that of protein melting gives the best possible, though always approximate prediction. The early stages of protein folding also "take into account" only a part of all the interactions; consequently, the same temperature T* is favorable for the self-organization of native-like intermediates in protein folding.

Impact of local and non-local interactions on thermodynamics and kinetics of protein folding.

To address the question of how the geometry of a protein's native conformation affects its folding and stability, we studied three model 36-mers on a cubic lattice. The native structure of one of these model 36-mers consisted mostly of local contacts, while that of a second consisted mostly of non-local contacts. The third native structure had a typical compact native conformation, and served as our reference. For each protein, the amino acid sequence was designed to have a pronounced energy minimum at its native conformation. We observed dramatic differences in folding, dependent on the presence or absence of non-local contacts. For the proteins with a typical large number of non-local contacts, the folding transition was all-or-none, whereas for the one with mostly local contacts, it was not. Although the maximum rate of folding was similar for all three proteins, we found that under conditions at which each native conformation was stable, the structure with mostly non-local contacts folded two orders of magnitude faster than the one with mostly local contacts. The statistical analysis of protein structure agrees fully with the implications of the theory. We discuss the importance of cooperativity in protein folding for its stability.