Bladder cancer is the 4th most common cancer among men in the U.S. We analyzed variant genotypes hypothesized to modify major biological processes involved in bladder carcinogenesis, including hormone regulation, apoptosis, DNA repair, immune surveillance, metabolism, proliferation, and telomere maintenance. Logistic regression was used to assess the relationship between genetic variation affecting these processes and susceptibility in 563 genotyped urothelial cell carcinoma cases and 863 controls enrolled in a case–control study of incident bladder cancer conducted in New Hampshire, U.S. We evaluated gene–gene interactions using Multifactor Dimensionality Reduction (MDR) and Statistical Epistasis Network analysis. The 3′UTR flanking variant form of the hormone regulation gene HSD3B2 was associated with increased bladder cancer risk in the New Hampshire population (adjusted OR 1.85 95%CI 1.31–2.62). This finding was successfully replicated in the Texas Bladder Cancer Study with 957 controls, 497 cases (adjusted OR 3.66 95%CI 1.06–12.63). The effect of this prevalent SNP was stronger among males (OR 2.13 95%CI 1.40–3.25) than females (OR 1.56 95%CI 0.83–2.95), (SNP-gender interaction P = 0.048). We also identified a SNP-SNP interaction between T-cell activation related genes GATA3 and CD81 (interaction P = 0.0003). The fact that bladder cancer incidence is 3–4 times higher in males suggests the involvement of hormone levels. This biologic process-based analysis suggests candidate susceptibility markers and supports the theory that disrupted hormone regulation plays a role in bladder carcinogenesis.

Lymphocytes are a key component of the immune system and their differentiation and function are directly influenced by cancer. We examined peripheral blood lymphocyte (PBL) gene expression as a biomarker of illness and treatment effect using the Affymetrix Human Gene ST1 platform in patients with metastatic renal cell carcinoma (mRCC) who received combined treatment with IL-2, interferon-?-2a and dendritic cell vaccine. We examined gene expression, cytokine levels in patient serum and lymphocyte subsets as determined by flow cytometry (FCM). Pre-treatment PBLs from patients with mRCC exhibit a gene expression profile and serum cytokine profile consistent with inflammation and proliferation not found in healthy donors (HD). PBL gene expression from patients with mRCC showed increased mRNA of genes involved with T-cell and TREG-cell activation pathways, which was also reflected in lymphocyte subset distribution. Overall, PBL gene expression post-treatment (POST) was not significantly different than pre-treatment (PRE). Nevertheless, treatment related changes in gene expression (post-treatment minus pre-treatment) revealed an increased expression of T-cell and B-cell receptor signaling pathways in responding (R) patients compared to non-responding (NR) patients. In addition, we observed down-regulation of TREG-cell pathways post-treatment in R vs. NR patients. While exploratory in nature, this study supports the hypothesis that enhanced inflammatory cytotoxic pathways coupled with blunting of the regulatory pathways is necessary for effective anti-cancer activity associated with immune therapy. This type of analysis can potentially identify additional immune therapeutic targets in patients with mRCC.

Purpose

To evaluate CD4+CD25+FOXP3+ T regulatory cells (TREG) and associated immune-regulatory pathways in peripheral blood lymphocytes (PBL) of metastatic renal cell carcinoma (mRCC) patients and healthy volunteers. We subsequently investigated the effects of immunotherapy on circulating TREG combining an extensive phenotype examination, DNA methylation analysis and global transcriptome analysis.

Design

Eighteen patients with mRCC and twelve volunteers (controls) were available for analysis. TREG phenotype was examined using flow cytometry (FCM). TREG were also quantified by analyzing the epigenetic status of the FOXP3 locus using methylation specific PCR. As a third approach, RNA of the PBL was hybridized to Affymetrix GeneChip Human Gene 1.0 ST Arrays and the gene signatures were explored using pathway analysis.

Results

We observed higher numbers of TREG in pre-treatment PBL of mRCC patients compared to controls. A significant increase in TREG was detected in all mRCC patients after the two cycles of immunotherapy. The expansion of TREG was significantly higher in non-responders than in responding patients. Methylation specific PCR confirmed the FCM data and circumvented the variability and subjectivity of the FCM method. Gene Set Enrichment Analysis (GSEA) of the microarray data showed significant enrichment of FOXP3 target genes, CTLA-4 and TGF-ß associated pathways in the patient cohort.

Conclusion

Immune monitoring of the peripheral blood and tumor tissue is important for a wide range of diseases and treatment strategies. Adoption of methodology for quantifying TREG with the least variability and subjectivity will enhance the ability to compare and interpret findings across studies.

The environmental agent 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD or dioxin) causes a multitude of human illnesses. In order to more fully understand the underlying biology of TCDD toxicity, we tested the hypothesis that new candidate genes could be identified using polysome RNA from TCDD-treated mouse Hepa-1c1c7 cells. We found that (i) differentially expressed whole cell and cytoplasm RNA levels are both poor predictors of polysome RNA levels; (ii) for a majority of RNAs, differential RNA levels are regulated independently in the nucleus, cytoplasm, and polysomes; (iii) for the remaining polysome RNAs, levels are regulated via several different mechanisms, including a “tagging” of mRNAs in the nucleus for immediate polysome entry; and (iv) most importantly, a gene list derived from differentially expressed polysome RNA generated new genes and cell pathways potentially related to TCDD biology.

Rapid and accurate retrospective dosimetry is of critical importance and strategic value for the emergency medical response to a large-scale radiological/nuclear event. One technique that has the potential for rapid and accurate dosimetry measurements is electron paramagnetic resonance (EPR) spectroscopy of relatively stable radiation-induced signals (RIS) in fingernails and toenails. Two approaches are being developed for EPR nail dosimetry. In the approach using ex vivo measurements on nail clippings, accurate estimation of the dose-dependent amplitude of the RIS is complicated by the presence of mechanically-induced signals (MIS) that are generated during the nail clipping. Recent developments in ex vivo nail dosimetry, including a thorough characterization of the MIS and an appreciation of the role of hydration and the development of effective analytic techniques, have led to improvements in the accuracy and precision of this approach. An in vivo nail dosimetry approach is also very promising, as it eliminates the problems of MIS from the clipping and it has the potential to be an effective and efficient approach for field deployment. Two types of EPR resonators are being developed for in vivo measurements of fingernails and toenails.

With the rapid development of biological technology, measurement of thousands of genes or SNPs can be carried out simultaneously. Improved procedures for multiple hypothesis testing when the number of tests is very large are critical for interpreting genomic data. In this paper, we review recent developments on three distinct but closely related methods involving p-value weighting to improve statistical power while also controlling for the false discovery rate or the family wise error rate.

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 (Treg) 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 Treg 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.

The widespread use of high-throughput methods of single nucleotide polymorphism (SNP) genotyping has created a number of computational and statistical challenges. The problem of identifying SNP–SNP interactions in case–control studies has been studied extensively, and a number of new techniques have been developed. Little progress has been made, however, in the analysis of SNP–SNP interactions in relation to time-to-event data, such as patient survival time or time to cancer relapse. 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 survival analysis. The proposed Survival MDR (Surv-MDR) method handles survival data by modifying MDR’s constructive induction algorithm to use the log-rank test. Surv-MDR replaces balanced accuracy with log-rank test statistics as the score to determine the best models. We simulated datasets with a survival outcome related to two loci in the absence of any marginal effects. We compared Surv-MDR with Cox-regression for their ability to identify the true predictive loci in these simulated data. We also used this simulation to construct the empirical distribution of Surv-MDR’s testing score. We then applied Surv-MDR to genetic data from a population-based epidemiologic study to find prognostic markers of survival time following a bladder cancer diagnosis. We identified several two-loci SNP combinations that have strong associations with patients’ survival outcome. Surv-MDR is capable of detecting interaction models with weak main effects. These epistatic models tend to be dropped by traditional Cox regression approaches to evaluating interactions. With improved efficiency to handle genome wide datasets, Surv-MDR will play an important role in a research strategy that embraces the complexity of the genotype–phenotype mapping relationship since epistatic interactions are an important component of the genetic basis of disease.

A central goal of human genetics is to identify and characterize susceptibility genes for common complex human diseases. An important challenge in this endeavor is the modeling of gene-gene interaction or epistasis that can result in non-additivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as machine learning alternative to parametric logistic regression for detecting interactions in absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modeling 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 Fisher’s Exact Test rather than a predetermined threshold. The advantage of this approach is that only those genotype combinations that are determined to be statistically significant are considered in the MDR analysis. We use two 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.

Background

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 among blood folate levels, and dietary and lifestyle factors with CpG island methylation in normal colorectal mucosa.

Methods

Subjects were enrolled in a multi-center chemoprevention trial of aspirin or folic acid for the prevention of large bowel adenomas. We collected 1000 biopsies 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.

Results

For both ERα and SFRP1, percent methylation was significantly higher in the rectum compared to 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 compared to Caucasians and Hispanics. Higher RBC folate levels were associated with higher levels of both ERα (p=0.03) and SFRP1 methylation (p=0.01).

Conclusions

Our results suggest that CpG island 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.

Purpose

To determine whether an autologous dendritic cell (DC) vaccine could induce anti-tumor 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 (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 ELISPOT 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 one week after vaccination had a markedly better recurrence free survival (RFS) at 5 years (63% vs. 18%, p=0.037) than non-responders. 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 affect 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 recurrence free survival. Activation of this DC vaccine with CD40L did not lead to increased immune responses.

Epistasis or gene-gene interaction is a fundamental component of the genetic architecture of complex traits such as disease susceptibility. Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free method to detect epistasis when there are no significant marginal genetic effects. However, in many studies of complex disease, other covariates like age of onset and smoking status could have a strong main effect and may potentially interfere with MDR's ability to achieve its goal. In this paper, we present a simple and computationally efficient sampling method to adjust for covariate effects in MDR. We use simulation to show that after adjustment, MDR has sufficient power to detect true gene-gene interactions. We also compare our method with the state-of-art technique in covariate adjustment. The results suggest that our proposed method performs similarly, but is more computationally efficient. We then apply this new method to an analysis of a population-based bladder cancer study in New Hampshire.

Exposure of fingernails and toenails to ionizing radiation creates radicals that are stable over a relatively long period (days to weeks) and characterized by an isotropic EPR signal at g = 2.003 (so-called radiation-induced signal, RIS). This signal in readily obtained fingernail parings has the potential to be used in screening a population for exposure to radiation and determining individual dose to guide medical treatment. However, the mechanical harvesting of fingernail parings also creates radicals and their EPR signals (so-called mechanically-induced signals, MIS) overlap the g ~ 2.0 region, interfering with efforts to quantify the RIS and, therefore, the radiation dose. Careful analysis of the time evolution and power-dependence of the EPR spectra of freshly cut fingernail parings has now resolved the MIS into three major components, including one that is described for the first time. It dominates the MIS soon after cutting, but decays within the first hour, and consists of a unique doublet that can be resolved from the RIS. The MIS obtained within the first few minutes after cutting is consistent among fingernail samples and provides an opportunity to achieve the two important dosimetry objectives. First, perturbation of the initial MIS by the presence of RIS in fingernails that have received a threshold dose of radiation leads to spectral signatures that can be used for rapid screening. Second, decomposition of the EPR spectra from irradiated fingernails into MIS and RIS components can be used to isolate and thus quantify the RIS for determining individual exposure dose.

Cyclooxygenase-2 (COX-2) catalyzes the rate-limiting step in the production of prostaglandins, potent mediators of inflammation. Chronic inflammation plays an important role in the development and progression of colorectal cancer. Aspirin inhibits COX-2 activity and lowers the risk of colorectal adenomas and cancer. We investigated whether common genetic variation in COX-2 influenced risk of colorectal adenoma recurrence among 979 participants in the Aspirin/Folate Polyp Prevention Study who were randomly assigned to placebo or aspirin and followed for 3 years for the occurrence of new adenomas. Of these participants, 44.2% developed at least one new adenoma during follow-up. Adjusted relative risks (RRs) and 95% confidence intervals (CIs) were calculated to test the association between genetic variation at six COX-2 single nucleotide polymorphisms (SNPs) and adenoma occurrence and interaction with aspirin treatment. Two SNPs were significantly associated with increased adenoma recurrence: for rs5277 homozygous carriers of the minor C allele had a 51% increased risk compared to GG homozygotes (RR=1.51, 95% CI=1.01–2.25), and for rs4648310 heterozygous carriers of the minor G allele had a 37% increased risk compared to AA homozygotes (RR=1.37, 95% CI=1.05–1.79). (There were no minor allele homozygotes.) In stratified analyses, there was suggestive evidence that rs4648319 modified the effect of aspirin. These results support the hypothesis that that COX-2 plays a role in the etiology of colon cancer and may be a target for aspirin chemoprevention and warrant further investigation in other colorectal adenoma and cancer populations.

Background

Lens regeneration in adult newts occurs via transdifferentiation of the pigment epithelial cells (PECs) of the dorsal iris. The same source of cells from the ventral iris is not able to undergo this process. In an attempt to understand this restriction we have studied in the past expression patterns of miRNAs. Among several miRNAs we have found that mir-148 shows an up-regulation in the ventral iris, while members of the let-7 family showed down-regulation in dorsal iris during dedifferentiation.

Methodology/Principal Findings

We have performed gain- and loss-of–function experiments of mir-148 and let-7b in an attempt to delineate their function. We find that up-regulation of mir-148 caused significant decrease in the proliferation rates of ventral PECs only, while up-regulation of let-7b affected proliferation of both dorsal and ventral PECs. Neither miRNA was able to affect lens morphogenesis or induction. To further understand how this effect of miRNA up-regulation is mediated we examined global expression of miRNAs after up-regulation of mir148 and let-7b. Interestingly, we identified a novel level of mirRNA regulation, which might indicate that miRNAs are regulated as a network.

Conclusion/Significance

The major conclusion is that different miRNAs can control proliferation in the dorsal or ventral iris possibly by a different mechanism. Of interest is that down-regulation of the let-7 family members has also been documented in other systems undergoing reprogramming, such as in stem cells or oocytes. This might indicate that reprogramming during newt regeneration shares common molecular signatures with reprogramming in stem or germ cells. On the other hand that miRNAs can regulate the levels of other miRNAs is a novel level of regulation, which might provide new insights on their function.

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.

Background

Frequent use of nonsteroidal anti-inflammatory drugs (NSAIDs) has been shown to reduce the risk of colorectal adenomas in randomized trials. We examined the persistence of the protective effect after the cessation of randomized aspirin treatment and whether it is affected by the duration and frequency of subsequent NSAID use.

Methods

We used data from the Aspirin/Folate Polyp Prevention Study (AFPPS), in which 1121 subjects were randomly assigned to receive placebo or aspirin (81 or 325 mg/d) for 3 years. After the end of treatment and a follow-up colonoscopy, AFPPS participants were invited to remain under follow-up until their next surveillance colonoscopies, scheduled 3–5 years later. Information regarding use of NSAIDs during posttreatment follow-up was gathered periodically via questionnaires. Average weekly NSAID use was classified as sporadic (<2 days per week), moderate (2 to <4 days per week), or frequent (≥4 days per week). The analysis was stratified according to randomized aspirin groups and posttreatment NSAID use; placebo subjects who later were sporadic NSAID users formed the reference group. The primary outcomes were all adenomas and advanced lesions. Adjusted relative risks and 95% confidence intervals were computed with generalized linear models. All statistical tests were two-sided.

Results

A total of 850 subjects underwent a posttreatment colonoscopy, on average 4 years after the end of study treatment. The protective effect of 81 mg of aspirin for colorectal adenomas persisted with continued posttreatment NSAID use. The risk of any adenoma among frequent NSAID users was 26.8% vs 39.9% among placebo subjects who later used NSAIDs sporadically (adjusted relative risk = 0.62, 95% confidence interval [CI] = 0.39 to 0.98; Ptrend with NSAID use frequency = .03). The unadjusted absolute risk reduction was 13.1 percentage points (95% CI = −0.3 to 26.5 percentage points) (P = .07). Results for 325 mg of aspirin were similar, although not statistically significant. For advanced lesions, small numbers of endpoints limited the analysis, but findings among subjects randomly assigned to 81 mg of aspirin suggested a protective association regardless of posttreatment NSAID use.

Conclusion

Long-term and frequent use of NSAIDs may enhance the chemopreventive effect of aspirin against colorectal neoplasia.

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 in 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 1000-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 1000-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 1000-fold permutation test.