Jiang Gui

The Association of Lifestyle and Dietary Factors with the Risk for Serrated Polyps of the Colorectum

Some serrated polyps of the colorectum are likely preinvasive lesions, evolving through a newly recognized serrated pathway to colorectal cancer. To assess possible risk and protective factors for serrated polyps and particularly to explore differences in risk factors between polyps in the right and left colorectum, we pooled data from three large multicenter chemoprevention trials. A serrated polyp was defined broadly as any serrated lesion (hyperplastic, sessile serrated adenoma, “traditional” serrated adenoma, mixed adenoma) diagnosed during each trials main treatment period of ∼3 to 4 years. Using generalized linear regression, we computed risk ratios and 95% confidence intervals as measures of the association between risk for serrated polyps and demographic, lifestyle, and dietary variables. Of the 2,830 subjects that completed at least one follow-up exam after randomization, 675 (23.9%) had at least one left-sided serrated polyp and 261 (9.2%) had at least one right-sided lesion. In the left colorectum, obesity, cigarette smoking, dietary fat, total energy intake, and red meat intake were associated with an increased risk for serrated polyps. In the right colon, aspirin treatment was associated with a reduced risk and family history of polyps and folate treatment were associated with an increased risk for serrated polyps. Our results suggest that several common lifestyle and dietary variables are associated with risk for serrated polyps, and some of these may differ for the right and left colorectum. (Cancer Epidemiol Biomarkers Prev 2009;18(8):2310–7)

Immune response in patients with newly diagnosed glioblastoma multiforme treated with intranodal autologous tumor lysate-dendritic cell vaccination after radiation chemotherapy.

Patients with glioblastoma multiforme (GBM) are profoundly immunosuppressed and may benefit from restoration of an antitumor immune response in combination with conventional radiation therapy and temozolomide (TMZ). The optimal strategies to evaluate clinically relevant immune responses to treatment have yet to be determined. The primary objective of our study was to determine immunologic response to cervical intranodal vaccination with autologous tumor lysate-loaded dendritic cells (DCs) in patients with GBM after radiation therapy and TMZ. We used a novel hierarchical clustering analysis of immune parameters measured before and after vaccination. Secondary objectives were to assess treatment feasibility and to correlate immune response with progression-free survival (PFS) and overall survival. Ten eligible patients received vaccination. Tumor-specific cytotoxic T-cell response measured after vaccination was enhanced for the precursor frequency of CD4+ T and CD4+ interferon &ggr;-producing cells. Hierarchical clustering analysis of multiple functional outcomes discerned 2 groups of patients according to their immune response, and additionally showed that patients in the top quintile for at least one immune function parameter had improved survival. There were no serious adverse events related to DC vaccination. All patients were alive at 6 months after diagnosis and the 6-month PFS was 90%. The median PFS was 9.5 months and overall survival was 28 months. In patients with GBM, immune therapy with DC vaccination after radiation and TMZ resulted in tumor-specific immune responses that were associated with prolonged survival. Our data suggest that DC vaccination in combination with radiation and chemotherapy in patients with GBM is feasible, safe, and may induce tumor-specific immune responses.

Association between folate levels and CpG Island hypermethylation in normal colorectal mucosa.

Gene-specific promoter methylation of several genes occurs in aging normal tissues and may predispose to tumorigenesis. In the present study, we investigate the association of blood folate levels and dietary and lifestyle factors with CpG island (CGI) methylation in normal colorectal mucosa. Subjects were enrolled in a multicenter chemoprevention trial of aspirin or folic acid for the prevention of large bowel adenomas. We collected 1,000 biopsy specimens from 389 patients, 501 samples from the right colon and 499 from the rectum at the follow-up colonoscopy. We measured DNA methylation of estrogen receptor alpha (ERα) and secreted frizzled related protein-1 (SFRP1), using bisulfite pyrosequencing. We used generalized estimating equations regression analysis to examine the association between methylation and selected variables. For both ERα and SFRP1, percentage methylation was significantly higher in the rectum than in the right colon (P = 0.001). For each 10 years of age, we observed a 1.7% increase in methylation level for ERα and a 2.9% increase for SFRP1 (P < 0.0001). African Americans had a significantly lower level of ERα and SFRP1 methylation than Caucasians and Hispanics. Higher RBC folate levels were associated with higher levels of both ERα (P = 0.03) and SFRP1 methylation (P = 0.01). Our results suggest that CGI methylation in normal colorectal mucosa is related to advancing age, race, rectal location, and RBC folate levels. These data have important implications regarding the safety of supplementary folate administration in healthy adults, given the hypothesis that methylation in normal mucosa may predispose to colorectal neoplasia. Cancer Prev Res; 3(12); 1552–64. ©2010 AACR.

A computationally efficient hypothesis testing method for epistasis analysis using multifactor dimensionality reduction.

Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model‐free data mining method for detecting, characterizing, and interpreting epistasis in the absence of significant main effects in genetic and epidemiologic studies of complex traits such as disease susceptibility. The goal of MDR is to change the representation of the data using a constructive induction algorithm to make nonadditive interactions easier to detect using any classification method such as naïve Bayes or logistic regression. Traditionally, MDR constructed variables have been evaluated with a naïve Bayes classifier that is combined with 10‐fold cross validation to obtain an estimate of predictive accuracy or generalizability of epistasis models. Traditionally, we have used permutation testing to statistically evaluate the significance of models obtained through MDR. The advantage of permutation testing is that it controls for false positives due to multiple testing. The disadvantage is that permutation testing is computationally expensive. This is an important issue that arises in the context of detecting epistasis on a genome‐wide scale. The goal of the present study was to develop and evaluate several alternatives to large‐scale permutation testing for assessing the statistical significance of MDR models. Using data simulated from 70 different epistasis models, we compared the power and type I error rate of MDR using a 1,000‐fold permutation test with hypothesis testing using an extreme value distribution (EVD). We find that this new hypothesis testing method provides a reasonable alternative to the computationally expensive 1,000‐fold permutation test and is 50 times faster. We then demonstrate this new method by applying it to a genetic epidemiology study of bladder cancer susceptibility that was previously analyzed using MDR and assessed using a 1,000‐fold permutation test. Genet. Epidemiol. 2008.

Bladder cancer SNP panel predicts susceptibility and survival

Bladder cancer is the fourth most common malignancy in men and the eighth most common in women in western countries. Single nucleotide polymorphisms (SNPs) in genes that regulate telomere maintenance, mitosis, inflammation, and apoptosis have not been assessed extensively for this disease. Using a population-based study with 832 bladder cancer cases and 1,191 controls, we assessed genetic variation in relation to cancer susceptibility or survival. Findings included an increased risk associated with variants in the methyl-metabolism gene, MTHFD2 (OR 1.7 95% CI 1.3–2.3), the telomerase TEP1 (OR 1.8 95% CI 1.2–2.6) and decreased risk associated with the inflammatory response gene variant IL8RB (OR 0.6 95% CI 0.5–0.9) compared to wild-type. Shorter survival was associated with apoptotic gene variants, including CASP9 (HR 1.8 95% CI 1.1–3.0). Variants in the detoxification gene EPHX1 experienced longer survival (HR 0.4 (95% CI 0.2–0.8). These genes can now be assessed in multiple study populations to identify and validate SNPs appropriate for clinical use.

A Randomized Trial of Ex vivo CD40L Activation of a Dendritic Cell Vaccine in Colorectal Cancer Patients: Tumor-Specific Immune Responses Are Associated with Improved Survival

Purpose: To determine whether an autologous dendritic cell (DC) vaccine could induce antitumor immune responses in patients after resection of colorectal cancer metastases and whether these responses could be enhanced by activating DCs with CD40L. Experimental Design: Twenty-six patients who had undergone resection of colorectal metastases were treated with intranodal injections of an autologous tumor lysate– and control protein [keyhole limpet hemocyanin (KLH)]–pulsed DC vaccine. Patients were randomized to receive DCs that had been either activated or not activated with CD40L. All patients were followed for a minimum of 5.5 years. Results: Immunization induced an autologous tumor-specific T-cell proliferative or IFNγ enzyme-linked immunospot response in 15 of 24 assessable patients (63%) and a tumor-specific DTH response in 61%. Patients with evidence of a vaccine-induced, tumor-specific T-cell proliferative or IFNγ response 1 week after vaccination had a markedly better recurrence-free survival (RFS) at 5 years (63% versus 18%, P = 0.037) than nonresponders. In contrast, no association was observed between induction of KLH-specific immune responses and RFS. CD40L maturation induced CD86 and CD83 expression on DCs but had no effect on immune responses or RFS. Conclusion: Adjuvant treatment of patients after resection of colorectal metastases with an autologous tumor lysate–pulsed, DC vaccine–induced, tumor-specific immune responses in a high proportion of patients. There was an association between induction of tumor-specific immune responses and RFS. Activation of this DC vaccine with CD40L did not lead to increased immune responses. Clin Cancer Res; 16(22); 5548–56. ©2010 AACR.

Immune modulation effects of concomitant temozolomide and radiation therapy on peripheral blood mononuclear cells in patients with glioblastoma multiforme

Concomitant radiation therapy (RT) and temozolomide (TMZ) therapy after surgery is the standard treatment for glioblastoma multiforme (GBM). Radiation and chemotherapy can affect the immune system with implications on subsequent immune therapy. Therefore, we examined the phenotype and function of peripheral blood mononuclear cells in 25 patients with GBM prior to and 4 weeks after treatment with RT-TMZ using multicolor flow cytometry, as well as in vitro CD4(+) regulatory T cell (T(reg)) suppressor and dendritic cell maturation assays. RT-TMZ induced significant lymphopenia, with a decrease in total CD4(+) T cells, but did not significantly change monocyte counts. The proportion of functional T(reg) cells increased after treatment, whereas their absolute numbers remained stable. There was also a measurable decrease in the proportion of CD8(+)CD56(+) and absolute number of CD3(-)CD56(+) effector cells. Posttherapy monocytes retained the ability to mature into dendritic cells. Treatment with RT-TMZ is associated with changes in regulatory and effector peripheral blood mononuclear cells that tilt the balance towards an immune suppressive state. This shift can affect the outcome of immune therapy following RT-TMZ treatment and should be considered in the design of future combination therapy regimens.

A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility

A central goal of human genetics is to identify susceptibility genes for common human diseases. An important challenge is modelling gene–gene interaction or epistasis that can result in nonadditivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as a machine learning alternative to parametric logistic regression for detecting interactions in the absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modelling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fishers Exact Test rather than a predetermined threshold. The advantage of this approach is that only statistically significant genotype combinations are considered in the MDR analysis. We use simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case‐control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene–gene interactions in genotype data from a population‐based study of bladder cancer in New Hampshire.

Symbolic Modeling of Epistasis

The workhorse of modern genetic analysis is the parametric linear model. The advantages of the linear modeling framework are many and include a mathematical understanding of the model fitting process and ease of interpretation. However, an important limitation is that linear models make assumptions about the nature of the data being modeled. This assumption may not be realistic for complex biological systems such as disease susceptibility where nonlinearities in the genotype to phenotype mapping relationship that result from epistasis, plastic reaction norms, locus heterogeneity, and phenocopy, for example, are the norm rather than the exception. We have previously developed a flexible modeling approach called symbolic discriminant analysis (SDA) that makes no assumptions about the patterns in the data. Rather, SDA lets the data dictate the size, shape, and complexity of a symbolic discriminant function that could include any set of mathematical functions from a list of candidates supplied by the user. Here, we outline a new five step process for symbolic model discovery that uses genetic programming (GP) for coarse-grained stochastic searching, experimental design for parameter optimization, graphical modeling for generating expert knowledge, and estimation of distribution algorithms for fine-grained stochastic searching. Finally, we introduce function mapping as a new method for interpreting symbolic discriminant functions. We show that function mapping when combined with measures of interaction information facilitates statistical interpretation by providing a graphical approach to decomposing complex models to highlight synergistic, redundant, and independent effects of polymorphisms and their composite functions. We illustrate this five step SDA modeling process with a real case-control dataset.

A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR’s constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR’s testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study.