A proteomics approach to identify changes in protein profiles in pre-cancerous colon

The development of colon cancer is characterised by alterations in multiple genetic and epigenetic pathways in colon tissue leading ultimately to deregulation of colon epithelial cells. Early detection is an important factor in decreasing colon cancer deaths. Proteomic techniques were used to identify potential early markers in colon tissue exhibiting pre-cancerous activity that may characterise pathological changes in a chemically induced colon cancer rat model. Protein profiles were assessed in soluble and insoluble fractions prepared from distal colon of rats treated with the colonotropic carcinogen, dimethylhydrazine. Alterations in protein profiles were associated with the presence of aberrant crypt foci, hyperplasia and dysplasia, microanatomical changes, and metabolic changes in rat colon. These changes may have a potential role in the identification of pre-pathological features preceding colon tumorigenesis.     

Early lesions induced in rat colon epithelium by N-methyl-N′-nitro-N-nitrosoguanidine

The development of ACF (aberrant crypt foci), adenoma and cancer following intrarectal administration of the alkylating agent N-methyl-N′-nitro-N-nitrosoguanidine (MNNG) has been described. However, microscopic lesions not previously reported were observed as soon as two weeks following carcinogen treatment. These lesions protrude slightly over the epithelial lining of the colon, with a micropolyp-like appearance. Oriented sections show that the centre of these lesions present pseudo-“cystic” appearance, with disorganized crypts made of normal cells. The chorion of the lesion is invaded by numerous inflammatory cells and some ACF may be present nearby. The epithelium lining the cysts and the distorted crypts shows expression of gastric mucin M1/MUC5AC, an early marker of colonic carcinogenesis which is not present in normal colon. This mucin is retained within the “cysts” together with some inflammatory cells.The micropolyps observed contain in a minute form some histological elements described in ulcerative colitis or short-term radiotherapy (distortion of crypts, crypt abscesses, increase of chorion cellularity, infiltration by immune cells). In addition, the presence of bifid crypts nearby suggests mucosal regeneration.Our hypothesis is that these modifications are steps in a normal healing pathway that may in some cases degenerate into precancerous lesions and cancer.     

The melatonin action on stromal stem cells within pericryptal area in colon cancer model under constant light

Constant light (LL) is associated with high incidence of colon cancer. MLT supplementation was related to the significant control of preneoplastic patterns. We sought to analyze preneoplastic patterns in colon tissue from animals exposed to LL environment (14 days; 300 lx), MLT-supplementation (10 mg/kg/day) and DMH-treatment (1,2 dimethylhydrazine; 125 mg/kg). Rodents were sacrificed and MLT serum levels were measured by radioimmunoassay. Our results indicated that LL induced ACF development (p < 0.001) with a great potential to increase the number of CD133(+) and CD68(+) cells (p < 0.05 and p < 0.001). LL also increased the proliferative process (PCNA-Li; p < 0.001) as well as decreased caspase-3 protein (p < 0.001), related to higher COX-2 protein expression (p < 0.001) within pericryptal colonic stroma (PCCS). However, MLT-supplementation controlled the development of dysplastic ACF (p < 0.001) diminishing preneoplastic patterns into PCCS as CD133 and CD68 (p < 0.05 and p < 0.001). These events were relative to decreased PCNA-Li index and higher expression of caspase-3 protein. Thus, MLT showed a great potential to control the preneoplastic patterns induced by LL.     

Comparison of maximum statistics for hypothesis testing when a nuisance parameter is present only under the alternative

In many practical problems, a hypothesis testing involves a nuisance parameter which appears only under the alternative hypothesis. Davies (1977, Biometrika 64, 247-254) proposed the maximum of the score statistics over the whole range of the nuisance parameter as a test statistic for this type of hypothesis testing. Freidlin, Podgor, and Gastwirth (1999, Biometrics 55, 883-886) studied two other simpler maximum test statistics, the maximum of the score statistics at two extreme points of the nuisance parameter, and the maximum of the score statistics at three points of the nuisance parameter including the two extreme points. In this article, we compare the powers of these three maximum-type statistics in the context of three genetic problems.     

A computer model of oxygen dynamics in human colon mucosa: implications in normal physiology and early tumor development

Based on the geometry of the colon mucosa, we built a model to compute the oxygen supply, the oxygen diffusion across the interstitial matrix, and the oxygen consumption by cryptal and stromal cells. By using an iterative algorithm, we have been able to solve a set of discretized (time and space) oxygen balance equations and determine the three-dimensional distribution of pO₂ in the mucosa. Although significant longitudinal and radial pO₂ variations were found, cells appeared to operate at their maximum respiratory capacity, regardless of their location in the tissue. The estimated oxygen extraction fraction was 47%, while the capillary oxygen permeability was 1.57×10⁻⁵ cm m s⁻¹. We concluded that cellular metabolism in normal colon mucosa is not limited by oxygen supply, thus prompting the idea that oxygenation does not determine the characteristic microenvironments occurring along the normal Lieberkhün crypts. In an extended model, simulation of an aberrant crypt focus (ACF)—the earliest stage in the adenomatous polyp-carcinoma sequence—showed instead that respiratory activity decreased when the capillary array symmetry is disrupted due to the ACF growth. A unified explanation about the alternative of a hypoxic-independent and/or a hypoxic-dependent early angiogenic response associated to the development of ACF is proposed.     

A stochastic carcinogenesis model incorporating multiple types of genomic instability fitted to colon cancer data

A generalization of the two-mutation stochastic carcinogenesis model of Moolgavkar, Venzon and Knudson and certain models constructed by Little [Little, M.P. (1995). Are two mutations sufficient to cause cancer? Some generalizations of the two-mutation model of carcinogenesis of Moolgavkar, Venzon, and Knudson, and of the multistage model of Armitage and Doll. Biometrics 51, 1278-1291] and Little and Wright [Little, M.P., Wright, E.G. (2003). A stochastic carcinogenesis model incorporating genomic instability fitted to colon cancer data. Math. Biosci. 183, 111-134] is developed; the model incorporates multiple types of progressive genomic instability and an arbitrary number of mutational stages. The model is fitted to US Caucasian colon cancer incidence data. On the basis of the comparison of fits to the population-based data, there is little evidence to support the hypothesis that the model with more than one type of genomic instability fits better than models with a single type of genomic instability. Given the good fit of the model to this large dataset, it is unlikely that further information on presence of genomic instability or of types of genomic instability can be extracted from age-incidence data by extensions of this model.     

A stochastic carcinogenesis model incorporating genomic instability fitted to colon cancer data

A generalization of the two-mutation stochastic carcinogenesis model of Moolgavkar, Venzon and Knudson and certain models constructed by Little is developed; the model incorporates progressive genomic instability and an arbitrary number of mutational stages. This model is shown to have the property that, at least in the case when the parameters of the model are eventually constant, the excess relative and absolute cancer rates following changes in any of the parameters will eventually tend to zero. It is also shown that when the parameters governing the processes of cell division, death, or additional mutation (whether of the normal sort or that resulting in genomic destabilization) at the penultimate stage are subject to perturbations, there are relatively large fluctuations in the hazard function for the model, which start almost as soon as the parameters are changed. The model is fitted to US Caucasian colon cancer incidence data. A model with five stages and two levels of genomic destabilization fits the data well. Comparison with patterns of excess risk in the Japanese atomic bomb survivor colon cancer incidence data indicate that radiation might act on early mutation rates in the model; a major role for radiation in initiating genomic destabilization is less likely.     

Hypothesis testing in semiparametric additive mixed models

We consider testing whether the nonparametric function in a semiparametric additive mixed model is a simple fixed degree polynomial, for example, a simple linear function. This test provides a goodness-of-fit test for checking parametric models against nonparametric models. It is based on the mixed-model representation of the smoothing spline estimator of the nonparametric function and the variance component score test by treating the inverse of the smoothing parameter as an extra variance component. We also consider testing the equivalence of two nonparametric functions in semiparametric additive mixed models for two groups, such as treatment and placebo groups. The proposed tests are applied to data from an epidemiological study and a clinical trial and their performance is evaluated through simulations.     

Testing the correlation for clustered categorical and censored discrete time-to-event data when covariates are measured without/with errors

In the analysis of clustered categorical data, it is of common interest to test for the correlation within clusters, and the heterogeneity across different clusters. We address this problem by proposing a class of score tests for the null hypothesis that the variance components are zero in random effects models, for clustered nominal and ordinal categorical responses. We extend the results to accommodate clustered censored discrete time-to-event data. We next consider such tests in the situation where covariates are measured with errors. We propose using the SIMEX method to construct the score tests for the null hypothesis that the variance components are zero. Key advantages of the proposed score tests are that they can be easily implemented by fitting standard polytomous regression models and discrete failure time models, and that they are robust in the sense that no assumptions need to be made regarding the distributions of the random effects and the unobserved covariates. The asymptotic properties of the proposed tests are studied. We illustrate these tests by analyzing two data sets and evaluate their performance with simulations.     

A Bayesian analysis of colonic crypt structure and coordinated response to carcinogen exposure incorporating missing crypts

This paper is concerned with modeling the architecture of colonic crypts and the implications of this modeling for understanding possible coordinated response of carcinogen-induced DNA damage between various regions of the colon. The methods we develop to address these two issues are applied to a particular important example in colon carcinogenesis. We cast the problem as an unusual and not previously studied hierarchical mixed-effects model characterized by completely missing covariates in units at a structurally base level, except for some randomly selected units. Information concerning the missing covariates is available through certain known ordering constraints and surrogate measures. Our methods use Bayesian machinery. We exploit the biological structure of this problem to generate the missing covariates simultaneously and efficiently at the base levels, as opposed to the naive practice of generating units at the base levels one-at-a-time with Metropolis-Hastings steps. We apply our methods to show that different regions of the colon have different architectures, and to estimate an important but non-standard function that measures the interrelationship of DNA damage mechanisms in different regions of the colon.     

A score test for the linkage analysis of qualitative and quantitative traits based on identity by descent data from sib-pairs

We propose a general likelihood-based approach to the linkage analysis of qualitative and quantitative traits using identity by descent (IBD) data from sib-pairs. We consider the likelihood of IBD data conditional on phenotypes and test the null hypothesis of no linkage between a marker locus and a gene influencing the trait using a score test in the recombination fraction theta between the two loci. This method unifies the linkage analysis of qualitative and quantitative traits into a single inferential framework, yielding a simple and intuitive test statistic. Conditioning on phenotypes avoids unrealistic random sampling assumptions and allows sib-pairs from differing ascertainment mechanisms to be incorporated into a single likelihood analysis. In particular, it allows the selection of sib-pairs based on their trait values and the analysis of only those pairs having the most informative phenotypes. The score test is based on the full likelihood, i.e. the likelihood based on all phenotype data rather than just differences of sib-pair phenotypes. Considering only phenotype differences, as in Haseman and Elston (1972) and Kruglyak and Lander (1995), may result in important losses in power. The linkage score test is derived under general genetic models for the trait, which may include multiple unlinked genes. Population genetic assumptions, such as random mating or linkage equilibrium at the trait loci, are not required. This score test is thus particularly promising for the analysis of complex human traits. The score statistic readily extends to accommodate incomplete IBD data at the test locus, by using the hidden Markov model implemented in the programs MAPMAKER/SIBS and GENEHUNTER (Kruglyak and Lander, 1995; Kruglyak et al., 1996). Preliminary simulation studies indicate that the linkage score test generally matches or outperforms the Haseman-Elston test, the largest gains in power being for selected samples of sib-pairs with extreme phenotypes.