Project description:We will explore the genetic (including APC, k-ras, p53, MSI, etc.) and environmental (including family history, life style, diet, nutritional status, DM, serum IGF-I, IGFBP-3, etc.) risk factors of colorectal tumorigenesis. We will accrue approximately 1000 patients as experimental group. The control group consists of 2000 individuals who were confirmed without colorectal cancer or polyps by colonoscopy. We estimated the statistical power of this study will reach more than 90%. In the second year, we will explore the association between various environmental risk factors with the epigenetic changes of various oncogenes and tumor suppressor genes. Firstly, we will study the correlation between hypermethylation of promoter region of hMLH1 gene with various environmental factors. Next, we will explore the genetic polymorphisms of promoter of E-cadherin gene. Recently, it has been reported that the C→A genetic polymorphism in the promoter region of E-cadherin gene in prostate cancer. Since this phenomenon has not been reported in colorectal cancer, it is mandatory for us to extend our research to the E-cadherin polymorphisms of colorectal cancer. Moreover, this project will focus on exploration of the association between the genetic polymorphisms of promoter of TS gene with chemosensitivity to 5-Fu-based therapy. We speculated that the better prognosis in colorectal tumors with MSI is related to their expression of TS gene. In summary, the second year of this project will extend our accumulated experience in the study of genetic polymorphisms to further clarify the association between genetic polymorphisms of TS gene with the prognosis of colorectal cancers after chemotherapy. We believe that this project will facilitate: (1) the further clarification of colorectal cancer tumorigenesis; (2) the establishment of domestic epidemiological data of colorectal cancer of Taiwan, and (3) the improvement of the quality of clinical management of patients with colorectal cancer.
Project description:We adapted the self-transcribing active regulatory region sequencing (Starr-seq) strategy to systematically identify the SNPs that affect gene expression by modulating activities of regulatory elements. Among 10,673 SNPs linked with 996 GWAS-identified cancer-risk SNPs, we found 70 regulatory variants for which the two alleles conferred different regulatory activities. We analyzed one of them in-depth and confirmed its target by CRIPSR-Cas9 technology. Our results will help the interpretation of GWAS results and better cancer risk assessment.
Project description:Precise identification of causal variants within credible intervals of eQTL associations is needed to identify regulatory GWAS variants. We show that CROPseq, namely multiplex CRISPR-Cas9 genome editing combined with single cell RNAseq, is a viable strategy for fine mapping regulatory SNPs. Mutations were induced nearby 67 SNPs in three genes, two of which, rs2251039 and rs17523802, significantly altered CISD1 and PARK7 expression, respectively, and overlap with chromatin accessibility peaks.
Project description:Most type 1 diabets (T1D) associated SNPs are located in non-coding regions, making it hard to understand their functional impact. We performed epigenomic profiling of two enhancer marks, H3K4me1 and H3K27ac, using primary TH1 and TREG cells from healthy and T1D subjects. By integrating enhancers predicted using these ChIP-Seq data, T1D associated SNPs and additional supporting data, we found and validated several novel risk SNPs for T1D.
Project description:Via a GWA study, several SNPs have been identified as markers capable of predicting prognosis of lung cancer patients receiving TKIs therapy as first-line treatment. In order to get insights into how these genetic variants are linked to traits of interest, we conducted a genome-wide eQTL study by integrated analyses of SNP genotyping array data and gene expression array data of 115 subjects of lung adenocarcinoma. Our study successfully identified several SNPs as eQTLs, whose genotype were significantly associated with expression levels of several already known genes related to lung cancer.
Project description:Genome-wide association studies (GWAS) have boosted our knowledge of genetic risk variants in autoimmune diseases (AIDs). Most of the risk variants are located within or near genes with immunological functions, and the majority is found to be non-coding, pointing towards a regulatory role. We have performed a cis expression quantitative trait locus (eQTL) screen to investigate whether single nucleotide polymorphisms (SNPs) associated with AIDs influence gene expression in thymus. Genotyping was performed using the Immunochip and 353 AID associated SNPs were tested against expression of surrounding genes (+/- 1 Mb) from human thymic tissue (N=42). We identified eight genes where the expression was associated with AID risk SNPs at a study-wide level of significance (P < 2.57x10-5). Five genes (FCRL3, RNASET2, C2orf74, SIRPG and SYS1) displayed cis eQTL signals also in other tissues, while for two loci (NPIPB8 and LOC388814), the eQTL signal appear to be thymus-specific. Since many AID risk variants from GWAS have been subsequently fine-mapped in recent Immunochip projects, we explored the overlap between these novel AID risk variants and the thymic eQTL regions. Moreover, we examined the functional annotation of the seven expression altering SNPs (eSNPs). Our study reveals autoimmune risk variants that act as eQTLs in thymus. We have highlighted functional variants within these genetic regions that potentially can represent causal autoimmune risk variants. Total RNA from 42 human thymic samples were obtained from children undergoing cardiac surgery.
Project description:Investigation of whole genome gene expression level changes in patients treated with cyclophosphamide We have studied the gene expression profile for 11 patients with different types of hematological malignancies but all of them have been treated with CP i.v.
Project description:This experiment was carried out in the context of a pharmacogenetic study of long-term (4-year follow-up) response to Interferon-beta treatment in two cohorts of Italian Multiple Sclerosis patients, to identify genetic variants (SNPs) that may influence response to IFN-beta. We integrated results from meta-analysis of the two cohorts with gene expression profiling of IFNβ stimulated PBMCs from 20 healthy controls and eQTL analyses, to look at possible enrichment of IFN-beta induced genes with genes mapped by top-ranking meta-analyzed SNPs.
Project description:Background: Expression quantitative trait loci (eQTL) studies are a valuable approach for identifying genetic variants correlated with gene expression. However, identifying the causal variants is challenging due to linkage disequilibrium amongst variants in the same haplotype block. In this study, we aim to identify functional SNPs in key regulatory regions that alter transcriptional regulation and thus, potentially impact cellular function. The majority of disease-associated single-nucleotide polymorphisms (SNPs) are located in regulatory regions, which can result in allele-specific binding (ASB) of transcription factors and differential expression of the target gene alleles. Here, we present regSNPs-ASB, a generalized linear model-based approach to accurately identify regulatory SNPs that are located in transcription factor binding sites from ATAC-seq data. Results: Using regSNPs-ASB, we identified 53 regulatory SNPs in human MCF-7 breast cancer cells and 125 regulatory SNPs in human mesenchymal stem cells (MSC). By integrating the regSNPs-ASB output with RNA-seq experimental data and publicly available chromatin interaction data from MCF-7 cells, we found that these 53 regulatory SNPs were associated with 74 potential target genes and that 32 (43%) of these genes showed significant allele-specific expression (ASE). By comparing all of the MCF-7 and MSC regulatory SNPs to the eQTLs in the Genome-Tissue Expression (GTEx) Project database, we found that 30% (16/53) of the regulatory SNPs in MCF-7 and 43% (52/122) of the regulatory SNPs in MSC were also eQTLs. The enrichment of regulatory SNPs in eQTLs indicated that many of them are likely responsible for allelic differences in gene expression (chi-square test, p-value < 0.01). In sum, we conclude that regSNPs-ASB is a useful tool for identifying causal variants from ATAC-seq data. This new computational tool will enable efficient prioritization of genetic variants identified as eQTL for further studies to validate their causal regulatory function. Ultimately, identifying causal genetic variants will further our understanding of the underlying molecular mechanisms of disease and the eventual development of potential therapeutic targets.
Project description:Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift (EMSA) and luciferase reporter assays. To identify binding of transcription factors and/or other nuclear proteins in an allele-determined manner, we employed pulldown using nuclear extract from Daudi cells and silver staining in SNPs that had exhibited allele-specific differential binding by EMSA. Each pulldown product for each allele of the five high-probability SNPs (rs2297550 C/G, rs13213604 C/G, rs276461 T/C, rs9907955 C/T, rs7302634 T/C) was evaluated by mass spectrometry (MS) to identify binding nuclear proteins, yielding a set of candidate proteins for each.