Daniel F. Pellatt

MicroRNAs and Colon and Rectal Cancer: Differential Expression by Tumor Location and Subtype

MicroRNAs are thought to have an impact on cell proliferation, apoptosis, stress responses, maintenance of stem cell potency, and metabolism and are, therefore, important in the carcinogenic process. In this study, we examined 40 colon tumors, 30 rectal tumors, and 30 normal tissue samples (10 proximal colon, 10 distal colon, and 10 rectal paired with cancer cases) to examine miRNA expression profiles in colon and rectal tumors. MiRNA expression levels were adjusted for multiple comparisons; tumor tissue was compared with noncancerous tissue from the same site. A comparison of normal tissue showed 287 unique miRNAs that were significantly differentially expressed at the 1.5‐fold level and 73 with over a two‐fold difference in expression between colon and rectal tissue. Examination of miRNAs that were significantly differentially expressed at the 1.5‐fold level by tumor phenotype showed 143 unique miRNAs differentially expression for microsatellite instability positive (MSI+) colon tumors; 129 unique miRNAs differentially expressed for CpG Island Methylator Phenotype positive (CIMP+) colon tumors; 135 miRNAs were differentially expressed for KRAS2‐mutated colon tumors, and 139 miRNAs were differentially expressed for TP53‐mutated colon tumors. Similar numbers of differentially expressed miRNAs were observed for rectal tumors, although the miRNAs differentially expressed differed. There were 129 unique miRNAs for CIMP+, 143 unique miRNAs for KRAS2‐mutated, and 136 unique miRNAs for TP53‐mutated rectal tumors. These results suggest the importance of miRNAs in colorectal cancer and the need for studies that can confirm these results and provide insight into the diet, lifestyle, and genetic factors that influence miRNA expression.

MicroRNA profiles in colorectal carcinomas, adenomas and normal colonic mucosa: variations in miRNA expression and disease progression

Summary Roughly 27% of miRNAs are commonly expressed in colonic tissue; of these, over 86% are dysregulated between carcinoma and normal tissue when applying a false discovery rate of 0.05. MiRNA expression from normal to adenoma to carcinoma varied by miRNA and its frequency of expression in the population.

Expression Profiles of miRNA Subsets Distinguish Human Colorectal Carcinoma and Normal Colonic Mucosa.

OBJECTIVES:MicroRNAs (miRNAs) are small, non-protein-coding RNA molecules that are commonly dysregulated in colorectal tumors. The objective of this study was to identify smaller subsets of highly predictive miRNAs.METHODS:Data come from population-based studies of colorectal cancer conducted in Utah and the Kaiser Permanente Medical Care Program. Tissue samples were available for 1,953 individuals, of which 1,894 had carcinoma tissue and 1,599 had normal mucosa available for statistical analysis. Agilent Human miRNA Microarray V.19.0 was used to generate miRNA expression profiles; validation of expression levels was carried out using quantitative PCR. We used random forest analysis and verified findings with logistic modeling in separate data sets. Important microRNAs are identified and bioinformatics tools are used to identify target genes and related biological pathways.RESULTS:We identified 16 miRNAs for colon and 17 miRNAs for rectal carcinoma that appear to differentiate between carcinoma and normal mucosa; of these, 12 were important for both colon and rectal cancer, hsa-miR-663b, hsa-miR-4539, hsa-miR-17-5p, hsa-miR-20a-5p, hsa-miR-21-5p, hsa-miR-4506, hsa-miR-92a-3p, hsa-miR-93-5p, hsa-miR-145-5p, hsa-miR-3651, hsa-miR-378a-3p, and hsa-miR-378i. Estimated misclassification rates were low at 4.83% and 2.5% among colon and rectal observations, respectively. Among independent observations, logistic modeling reinforced the importance of these miRNAs, finding the primary principal components of their variation statistically significant (P<0.001 among both colon and rectal observations) and again producing low misclassification rates. Repeating our analysis without those miRNAs initially identified as important identified other important miRNAs; however, misclassification rates increased and distinctions between remaining miRNAs in terms of classification importance were reduced.CONCLUSIONS:Our data support the hypothesis that while many miRNAs are dysregulated between carcinoma and normal mucosa, smaller subsets of these miRNAs are useful and informative in discriminating between these tissues.

Gene expression in colon cancer: A focus on tumor site and molecular phenotype

Hundreds to thousands of genes are differentially expressed in tumors when compared to nontumor colonic tissue samples. We evaluated gene expression patterns to better understand differences in colon cancer by tumor site and tumor molecular phenotype. We analyzed RNA‐seq data from tumor/normal paired samples from 175 colon cancer patients. We implemented a cross validation strategy with nonparametric tests to identify genes which displayed varying expression characteristics related to paired tumor/nontumor tissue across proximal and distal colon sites and by tumor molecular phenotypes, that is, TP53, KRAS, CpG Island Methylator Phenotype (CIMP), and microsatellite instability (MSI). We used Ingenuity Pathway Analysis (IPA) to determine networks associated with deregulated genes in our data. Genes showed significant differences in expression characteristics at the 0.01 level in both validation groups between tumor subsite (116 genes), CIMP high versus CIMP low (79 genes), MSI versus microsatellite stable (MSS) (49 genes), TP53‐mutated versus not mutated (17genes), and KRAS‐mutated versus not mutated (1 gene). Deregulated genes for CIMP high and MSI tumors were often down‐regulated. In contrast to CIMP high and MSI tumors, genes that were deregulated in TP53 were likely to be up‐regulated. ERK1, WNT, growth factors and inflammation‐related factors were focal points of both CIMP and MSI IPA networks. The MUC family of genes was up‐regulated MSI networks. Numerous genes showed differences in expression between proximal and distal tumors, nontumor proximal and distal tissue, and tumor molecular phenotype. Deregulated mucin genes appear to play an important role in MSI tumors.

Site-specific associations between miRNA expression and survival in colorectal cancer cases

Background MicroRNAs (miRNA) are small non-coding RNA involved in cellular processes, including cell proliferation and angiogenesis. Thus, miRNA expression may alter survival after diagnosis with colorectal cancer (CRC). Results Individuals diagnosed with stage 1 or stage 2 rectal cancer had worse survival than colon cancer cases diagnosed at stage 1 or stage 2. After adjustment for multiple comparisons, no miRNAs were significantly associated with disease stage. Two miRNAs infrequently expressed in the population and not previously reported were associated with survival after diagnosis with colon cancer (miR-1 HR 2.17 95% CI 1.41, 3.36; and miR-101-3p HR 3.51 95% CI 1.72, 7.15). Among those diagnosed with rectal cancer, 201 miRNAs were associated with survival when the FDR q value was < 0.05. Assessment of 105 previously reported miRNAs associated with prognosis showed that four miRNAs influenced colon cancer survival and 17 influenced survival after a diagnosis with rectal cancer when raw p values were considered. Patients and Methods This study includes data from population-based studies of CRC conducted in Utah and the Kaiser Permanente Medical Care Program. A total of 1893 carcinoma and normal paired colorectal mucosa tissue samples were run using the Agilent Human miRNA Microarray V19.0. We assessed miRNA differential expression between paired carcinoma and normal colonic mucosa tissue with CRC- specific survival evaluating stage and site-specific associations after adjusting for age, sex, microsatellite instability tumor status, and AJCC stage. Conclusions MiRNAs dysregulated for both colon and rectal cancer had a greater impact on survival after a diagnosis with rectal cancer.

Dietary intake alters gene expression in colon tissue: possible underlying mechanism for the influence of diet on disease.

Background Although the association between diet and disease is well documented, the biologic mechanisms involved have not been entirely elucidated. In this study, we evaluate how dietary intake influences gene expression to better understand the underlying mechanisms through which diet operates. Methods We used data from 144 individuals who had comprehensive dietary intake and gene expression data from RNAseq using normal colonic mucosa. Using the DESeq2 statistical package, we identified genes that showed statistically significant differences in expression between individuals in high-intake and low-intake categories for several dietary variables of interest adjusting for age and sex. We examined total calories, total fats, vegetable protein, animal protein, carbohydrates, trans-fatty acids, mutagen index, red meat, processed meat, whole grains, vegetables, fruits, fiber, folate, dairy products, calcium, and prudent and western dietary patterns. Results Using a false discovery rate of less than 0.1, meat-related foods were statistically associated with 68 dysregulated genes, calcium with three dysregulated genes, folate with four dysregulated genes, and nonmeat-related foods with 65 dysregulated genes. With a more stringent false discovery rate of less than 0.05, there were nine meat-related dysregulated genes and 23 nonmeat-related genes. Ingenuity pathway analysis identified three major networks among genes identified as dysregulated with respect to meat-related dietary variables and three networks among genes identified as dysregulated with respect to nonmeat-related variables. The top networks (Ingenuity Pathway Analysis network score >30) associated with meat-related genes were (i) cancer, organismal injury, and abnormalities, tumor morphology, and (ii) cellular function and maintenance, cellular movement, cell death, and survival. Among genes related to nonmeat consumption variables, the top networks were (i) hematological system development and function, nervous system development and function, tissue morphology and (ii) connective tissue disorders, organismal injury, and abnormalities. Conclusion Several dietary factors were associated with gene expression in our data. These findings provide insight into the possible mechanisms by which diet may influence disease processes.

Colorectal tumor molecular phenotype and miRNA: expression profiles and prognosis

MiRNAs regulate gene expression by post-transcriptionally suppressing mRNA translation or by causing mRNA degradation. It has been proposed that unique miRNAs influence specific tumor molecular phenotype. In this paper, we test the hypotheses that miRNA expression differs by tumor molecular phenotype and that those differences may influence prognosis. Data come from population-based studies of colorectal cancer conducted in Utah and the Northern California Kaiser Permanente Medical Care Program. A total of 1893 carcinoma samples were run on the Agilent Human miRNA Microarray V19.0 containing 2006 miRNAs. We assessed differences in miRNA expression between TP53-mutated and non-mutated, KRAS-mutated and non-mutated, BRAF-mutated and non-mutated, CpG island methylator phenotype (CIMP) high and CIMP low, and microsatellite instability (MSI) and microsatellite stable (MSS) colon and rectal tumors. Using a Cox proportional hazard model we evaluated if those miRNAs differentially expressed by tumor phenotype influenced survival after adjusting for age, sex, and AJCC stage. There were 22 differentially expressed miRNAs for TP53-mutated colon tumors and 5 for TP53-mutated rectal tumors with a fold change of >1.49 (or <0.67). Additionally, 13 miRNAS were differentially expressed for KRAS-mutated rectal tumors, 8 differentially expressed miRNAs for colon CIMP high tumors, and 2 differentially expressed miRNAs for BRAF-mutated colon tumors. The majority of differentially expressed miRNAS were observed between MSI and MSS tumors (94 differentially expressed miRNAs for colon; 41 differentially expressed miRNAs for rectal tumors). Of these miRNAs differentially expressed between MSI and MSS tumors, the majority were downregulated. Ten of the differentially expressed miRNAs were associated with survival; after adjustment for MSI status, five miRNAS, miR-196b-5p, miR-31-5p, miR-99b-5p, miR-636, and miR-192-3p, were significantly associated with survival. In summary, it appears that the majority of miRNAs that are differentially expressed by tumor molecular phenotype are MSI tumors. However, these miRNAs appear to have minimal effect on prognosis.

Differential Gene Expression in Colon Tissue Associated With Diet, Lifestyle, and Related Oxidative Stress

Several diet and lifestyle factors may impact health by influencing oxidative stress levels. We hypothesize that level of cigarette smoking, alcohol, anti-inflammatory drugs, and diet alter gene expression. We analyzed RNA-seq data from 144 colon cancer patients who had information on recent cigarette smoking, recent alcohol consumption, diet, and recent aspirin/non-steroidal anti-inflammatory use. Using a false discovery rate of 0.1, we evaluated gene differential expression between high and low levels of exposure using DESeq2. Ingenuity Pathway Analysis (IPA) was used to determine networks associated with de-regulated genes in our data. We identified 46 deregulated genes associated with recent cigarette use; these genes enriched causal networks regulated by TEK and MAP2K3. Different differentially expressed genes were associated with type of alcohol intake; five genes were associated with total alcohol, six were associated with beer intake, six were associated with wine intake, and four were associated with liquor consumption. Recent use of aspirin and/or ibuprofen was associated with differential expression of TMC06, ST8SIA4, and STEAP3 while a summary oxidative balance score (OBS) was associated with SYCP3, HDX, and NRG4 (all up-regulated with greater oxidative balance). Of the dietary antioxidants and carotenoids evaluated only intake of beta carotene (1 gene), Lutein/Zeaxanthine (5 genes), and Vitamin E (4 genes) were associated with differential gene expression. There were similarities in biological function of de-regulated genes associated with various dietary and lifestyle factors. Our data support the hypothesis that diet and lifestyle factors associated with oxidative stress can alter gene expression. However genes altered were unique to type of alcohol and type of antioxidant. Because of potential differences in associations observed between platforms these findings need replication in other populations.

Functional Generalized Autoregressive Conditional Heteroskedasticity

Heteroskedasticity is a common feature of financial time series and is commonly addressed in the model building process through the use of ARCH and GARCH processes. More recently multivariate variants of these processes have been in the focus of research with attention given to methods seeking an efficient and economic estimation of a large number of model parameters. Due to the need for estimation of many parameters, however, these models may not be suitable for modeling now prevalent high-frequency volatility data. One potentially useful way to bypass these issues is to take a functional approach. In this paper, theory is developed for a new functional version of the generalized autoregressive conditionally heteroskedastic process, termed fGARCH. The main results are concerned with the structure of the fGARCH(1,1) process, providing criteria for the existence of a strictly stationary solutions both in the space of square-integrable and continuous functions. An estimation procedure is introduced and its consistency verified. A small empirical study highlights potential applications to intraday volatility estimation.

Functional generalized autoregressive conditional heteroskedasticity

Heteroskedasticity is a common feature of financial time series and is commonly addressed in the model building process through the use of ARCH and GARCH processes. More recently multivariate variants of these processes have been in the focus of research with attention given to methods seeking an efficient and economic estimation of a large number of model parameters. Due to the need for estimation of many parameters, however, these models may not be suitable for modeling now prevalent high-frequency volatility data. One potentially useful way to bypass these issues is to take a functional approach. In this paper, theory is developed for a new functional version of the generalized autoregressive conditionally heteroskedastic process, termed fGARCH. The main results are concerned with the structure of the fGARCH(1,1) process, providing criteria for the existence of a strictly stationary solutions both in the space of square-integrable and continuous functions. An estimation procedure is introduced and its consistency verified. A small empirical study highlights potential applications to intraday volatility estimation.