Dataset Information

Genes, environment and gene expression in colon tissue: a pathway approach to determining functionality.

ABSTRACT: Genetic and environmental factors have been shown to work together to alter cancer risk. In this study we evaluate previously identified gene and lifestyle interactions in a candidate pathway that were associated with colon cancer risk to see if these interactions altered gene expression. We analyzed non-tumor RNA-seq data from 144 colon cancer patients who had genotype, recent cigarette smoking, diet, body mass index (BMI), and recent aspirin/non-steroidal anti-inflammatory use data. Using a false discovery rate of 0.1, we evaluated differential gene expression between high and low levels of lifestyle exposure and genotypes using DESeq2. Thirteen pathway genes and 17 SNPs within those genes were associated with altered expression of other genes in the pathway. BMI, NSAIDs use and dietary components of the oxidative balance score (OBS) also were associated with altered gene expression. SNPs previously identified as interacting with these lifestyle factors, altered expression of pathway genes. NSAIDs interacted with 10 genes (15 SNPs) within those genes to alter expression of 28 pathway genes; recent cigarette smoking interacted with seven genes (nine SNPs) to alter expression of 27 genes. BMI interacted with FLT1, KDR, SEPN1, TERT, TXNRD2, and VEGFA to alter expression of eight genes. Three genes (five SNPs) interacted with OBS to alter expression of 12 genes. These data provide support for previously identified lifestyle and gene interactions associated with colon cancer in that they altered expression of key pathway genes. The need to consider lifestyle factors in conjunction with genetic factors is illustrated.

SUBMITTER: Slattery ML

PROVIDER: S-EPMC4858616 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Genes, environment and gene expression in colon tissue: a pathway approach to determining functionality.

Slattery Martha L ML Pellatt Daniel F DF Wolff Roger K RK Lundgreen Abbie A

International journal of molecular epidemiology and genetics 20160323 1

Genetic and environmental factors have been shown to work together to alter cancer risk. In this study we evaluate previously identified gene and lifestyle interactions in a candidate pathway that were associated with colon cancer risk to see if these interactions altered gene expression. We analyzed non-tumor RNA-seq data from 144 colon cancer patients who had genotype, recent cigarette smoking, diet, body mass index (BMI), and recent aspirin/non-steroidal anti-inflammatory use data. Using a fa ...[more]

PMID: 27186328

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Project description:Personalizing treatment regimes based on gene expression profiles of individual tumors will facilitate management of cancer. Although many methods have been developed to identify pathways perturbed in tumors, the results are often not generalizable across independent datasets due to the presence of platform/batch effects. There is a need to develop methods that are robust to platform/batch effects and able to identify perturbed pathways in individual samples.We present Gene-Ranking Analysis of Pathway Expression (GRAPE) as a novel method to identify abnormal pathways in individual samples that is robust to platform/batch effects in gene expression profiles generated by multiple platforms. GRAPE first defines a template consisting of an ordered set of pathway genes to characterize the normative state of a pathway based on the relative rankings of gene expression levels across a set of reference samples. This template can be used to assess whether a sample conforms to or deviates from the typical behavior of the reference samples for this pathway. We demonstrate that GRAPE performs well versus existing methods in classifying tissue types within a single dataset, and that GRAPE achieves superior robustness and generalizability across different datasets. A powerful feature of GRAPE is the ability to represent individual gene expression profiles as a vector of pathways scores. We present applications to the analyses of breast cancer subtypes and different colonic diseases. We perform survival analysis of several TCGA subtypes and find that GRAPE pathway scores perform well in comparison to other methods.GRAPE templates offer a novel approach for summarizing the behavior of gene-sets across a collection of gene expression profiles. These templates offer superior robustness across distinct experimental batches compared to existing methods. GRAPE pathway scores enable identification of abnormal gene-set behavior in individual samples using a non-competitive approach that is fundamentally distinct from popular enrichment-based methods. GRAPE may be an appropriate tool for researchers seeking to identify individual samples displaying abnormal gene-set behavior as well as to explore differences in the consensus gene-set behavior of groups of samples. GRAPE is available in R for download at https://CRAN.R-project.org/package=GRAPE .

Dataset Information

Genes, environment and gene expression in colon tissue: a pathway approach to determining functionality.

Publications

Genes, environment and gene expression in colon tissue: a pathway approach to determining functionality.

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