TOP-OCC and TOP-OCD

2014/11/12 OPMD IRB:
基因檢測是以單核苷酸多態性(single nucleotide polymorphism, SNP)為主,特別是會影響酵素功能的功能性(functional)SNP與在亞洲人當中比較重要的SNP。SNP的檢測將採用Taqman allele discrimination的方式1
首先,把DNA的濃度標準化為15ng/µL。然後,在96孔盤裡分別加入84位不同研究對象的DNA與試劑的混合液(2µL=30ng DNA in a 25µL reaction)、8個陽性對照及4個陰性對照,預計共需要24個96孔盤來完成所有研究對象(N=2000)每一個SNP的檢測。接著,把96孔盤放置在Applied Biosystem 7500 real time PCR(Foster City, CA)進行資料的讀取。每一個SNP的檢測將會經過幾個步驟的品質管制:
a.    以對照組的檢測資料來評估Hardy-Weinberg disequilibrium,p值<0.01的SNP將被排除。
b.    Allele 的頻率將與the International Hapmap Project(www.hapmap.org)的中國人的基因資料來做比較。
c.    偵測頻率(call rate)< 95%的SNP將被排除。
d.    10%的DNA樣本將被重覆檢測來評估檢測的準確度。
1.    de Kok JB, Wiegerinck ET, Giesendorf BA, Swinkels DW. Rapid genotyping of single nucleotide polymorphisms using novel minor groove binding DNA oligonucleotides (MGB probes). Hum Mutat. 2002;19:554-559.
2.    The International HapMap Consortium. (2003) The International HapMap Project. Nature;426:789-796.
#1由 sufang 在 二, 10/06/2015 – 10:43 發表。

Genetic variants in one-carbon metabolism genes and breast

Int J Cancer. 2015 Aug 1;137(3):666-77. doi: 10.1002/ijc.29434. Epub 2015 Jan 29. 
Gong Z1, Yao S1, Zirpoli G1, David Cheng TY1, Roberts M1,2, Khoury T3, Ciupak G1, Davis W1, Pawlish K4, Jandorf L5, Bovbjerg DH6, Bandera EV7,8, Ambrosone CB1.
Author information
Abstract
Folate-mediated one-carbon metabolism plays critical roles in DNA synthesis, repair and DNA methylation. The impact of single nucleotide polymorphisms (SNPs) in folate-metabolizing enzymes has been investigated in risk of breast cancer among European or Asian populations, but not among women of African ancestry. We conducted a comprehensive analysis of SNPs in eleven genes involved in one-carbon metabolism and risk of breast cancer in 1,275 European-American (EA) and 1,299 African-American (AA) women who participated in the Women’s Circle of Health Study. Allele frequencies varied significantly between EA and AA populations. A number of these SNPs, specifically in genes including MTR, MTRR, SHMT1, TYMS and SLC19A1, were associated with overall breast cancer risk, as well as risk by estrogen receptor (ER) status, in either EA or AA women. Associations appeared to be modified by dietary folate intake. Although single-SNP associations were not statistically significant after correcting for multiple comparisons, polygenetic score analyses revealed significant associations with breast cancer risk. Per unit increase of the risk score was associated with a modest 19 to 50% increase in risk of breast cancer overall, ER positive or ER negative cancer (all p < 0.0005) in EAs or AAs. In summary, our data suggest that one-carbon metabolizing gene polymorphisms could play a role in breast cancer and that may differ between EA and AA women. PMID: 25598430

KEYWORDS:
African American; European American; breast cancer; one-carbon metabolism; polymorphisms

#2由 sufang 在 六, 09/05/2015 – 15:28 發表。

2015/08 ALDH2 Mini_symposium at Taipei

ALDH2缺乏率47%提高罹癌風險 睡前喝紅酒台灣人不適用 
http://www.ettoday.net/news/20150813/549091.htm
喝酒臉紅非肝好 罹癌風險增50倍
http://www.appledaily.com.tw/realtimenews/article/new/20150811/667750/

#3由 sufang 在 六, 09/05/2015 – 14:20 發表。

Taiwan Biobank v1
















#4由 sufang 在 一, 03/30/2015 – 09:41 發表。

Preliminary data 暫存區

2015/03/31 update on allele frequency

rs1801133/Chr1:11856378 – MTHFR  (C677T, A222V) [K6 (100%T); C8 (100%T); C9 (100%T), TW2.6 (100%T)] [K2 (100%C); OC3 (88%C, 13%T); OEC-M1 (80%C, 20%T)]

rs1801131: MTHFR (A1298C, E429A) [K2 (22%A, 78%C); OEC-M1(36%A, 64%C)[OC3 (63%A, 38%C); K6, C8, C9 and TW2.6 (100%A)]
rs2236225: MTHFD1 (G1958A; R653Q) [OC3 (46%G, 54%A); OEC-M1 (50%G, 49%A)TW2.6 (47%G, 53%A)] [K2 (68%G, 32%A); K6, C8 and C9 (100%G)]
rs671: ALDH2 (G1510A, E504K)
rs1229984/Chr4:100239319 – ADH1B (T143C, R48H)


#5由 sufang 在 一, 03/30/2015 – 09:30 發表。

MTHFR C677T Gene Polymorphism and Head and Neck Cancer Risk:

Dis Markers. 2015;2015:681313. Epub 2015 Jan 31.
Niu YM1, Deng MH2, Chen W3, Zeng XT4, Luo J5.
Author information
Abstract
Objective. Conflicting results on the association between MTHFR polymorphism and head and neck cancer (HNC) risk were reported. We therefore performed a meta-analysis to derive a more precise relationship between MTHFR C677T polymorphism and HNC risk. Methods. Three online databases of PubMed, Embase, and CNKI were researched on the associations between MTHFR C677T polymorphism and HNC risk. Twenty-three published case-control studies involving 4,955 cases and 8,805 controls were collected. Odds ratios (ORs) with 95% confidence interval (CI) were used to evaluate the relationship between MTHFR C677T polymorphism and HNC risk. Sensitivity analysis, cumulative analyses, and publication bias were conducted to validate the strength of the results. Results. Overall, no significant association between MTHFR C677T polymorphism and HNC risk was found in this meta-analysis (T versus C: OR = 1.04, 95% CI = 0.92-1.18; TT versus CC: OR = 1.15, 95% CI = 0.90-1.46; CT versus CC: OR = 1.00, 95% CI = 0.85-1.17; CT + TT versus CC: OR = 1.01, 95% CI = 0.87-1.18; TT versus CC + CT: OR = 1.11, 95% CI = 0.98-1.26). In the subgroup analysis by HWE, ethnicity, study design, cancer location, and negative significant associations were detected in almost all genetic models, except for few significant risks that were found in thyroid cancer. Conclusion. This meta-analysis demonstrates that MTHFR C677T polymorphism may not be a risk factor for the developing of HNC.   PMID: 25802478
#6由 sufang 在 五, 12/05/2014 – 14:59 發表。

Single nucleotide polymorphisms of one-carbon metabolism and can

One-carbon metabolism (folate metabolism) is considered important in carcinogenesis because of its involvement in DNA synthesis and biological methylation reactions. We investigated the associations of single nucleotide polymorphisms (SNPs) in folate metabolic pathway and the risk of three GI cancers in a population-based case-control study in Taixing City, China, with 218 esophageal cancer cases, 206 stomach cancer cases, 204 liver cancer cases, and 415 healthy population controls. Study participants were interviewed with a standardized questionnaire, and blood samples were collected after the interviews. We genotyped SNPs of the MTHFR, MTR, MTRR, DNMT1, and ALDH2 genes, using PCR-RFLP, SNPlex, or TaqMan assays. To account for multiple comparisons and reduce the chances of false reports, we employed semi-Bayes (SB) shrinkage analysis. After shrinkage and adjusting for potential confounding factors, we found positive associations between MTHFR rs1801133 and stomach cancer (any T versus C/C, SB odds-ratio [SBOR]: 1.79, 95% posterior limits: 1.18, 2.71) and liver cancer (SBOR: 1.51, 95% posterior limits: 0.98, 2.32). There was an inverse association between DNMT1 rs2228612 and esophageal cancer (any G versus A/A, SBOR: 0.60, 95% posterior limits: 0.39, 0.94). In addition, we detected potential heterogeneity across alcohol drinking status for ORs relating MTRR rs1801394 to esophageal (posterior homogeneity P = 0.005) and stomach cancer (posterior homogeneity P = 0.004), and ORs relating MTR rs1805087 to liver cancer (posterior homogeneity P = 0.021). Among non-alcohol drinkers, the variant allele (allele G) of these two SNPs was inversely associated with the risk of these cancers; while a positive association was observed among ever-alcohol drinkers. Our results suggest that genetic polymorphisms related to one-carbon metabolism may be associated with cancers of the esophagus, stomach, and liver. Heterogeneity across alcohol consumption status of the associations between MTR/MTRR polymorphisms and these cancers indicates potential interactions between alcohol drinking and one-carbon metabolic pathway.
#7由 sufang 在 四, 12/04/2014 – 12:55 發表。

Putative cis-regulatory drivers in colorectal cancer. (2014)

23    Ongen, H., C. L. Andersen, J. B. Bramsen, B. Oster, M. H. Rasmussen, P. G. Ferreira, J. Sandoval, E. Vidal, N. Whiffin, A. Planchon, I. Padioleau, D. Bielser, L. Romano, I. Tomlinson, R. S. Houlston, M. Esteller, T. F. Orntoft, and E. T. Dermitzakis. Putative cis-regulatory drivers in colorectal cancer. (2014). Nature. pdf 4129.    The cis-regulatory effects responsible for cancer development have not been as extensively studied as the perturbations of the protein coding genome in tumorigenesis. To better characterize colorectal cancer (CRC) development we conducted an RNA-sequencing experiment of 103 matched tumour and normal colon mucosa samples from Danish CRC patients, 90 of which were germline-genotyped. By investigating allele-specific expression (ASE) we show that the germline genotypes remain important determinants of allelic gene expression in tumours. Using the changes in ASE in matched pairs of samples we discover 71 genes with excess of somatic cis-regulatory effects in CRC, suggesting a cancer driver role. We correlate genotypes and gene expression to identify expression quantitative trait loci (eQTLs) and find 1,693 and 948 eQTLs in normal samples and tumours, respectively. We estimate that 36% of the tumour eQTLs are exclusive to CRC and show that this specificity is partially driven by increased expression of specific transcription factors and changes in methylation patterns. We show that tumour-specific eQTLs are more enriched for low CRC genome-wide association study (GWAS) P values than shared eQTLs, which suggests that some of the GWAS variants are tumour specific regulatory variants. Importantly, tumour-specific eQTL genes also accumulate more somatic mutations when compared to the shared eQTL genes, raising the possibility that they constitute germline-derived cancer regulatory drivers. Collectively the integration of genome and the transcriptome reveals a substantial number of putative somatic and germline cis-regulatory cancer changes that may have a role in tumorigenesis.
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A comparison of colorectal cancer and normal cells from 103 patients identifies dozens of genes that are differently expressed in tumour cells as a result of altered regulation of transcription.
How important for cancer incidence and progression is genetic variation that affects gene expression? This fundamental question has received remarkably little attention in recent studies of cancer genomes1, perhaps because of a prevailing view that the cancer-causing mutations that can be targeted by drugs are those that disrupt protein structure2. In a paper published on Nature’s website today, Ongen et al.3 demonstrate how simultaneous gene-expression profiling and whole-genome genotyping can be used to dissect the regulation of gene transcription in colorectal cancer3. The findings provide two thought-provoking insights: that cancer-driving changes may be identifiable among an excess of regulatory mutations, and that ‘cryptic’ regulatory genetic variation has the potential to modify cancer progression.
It is well established that gene expression is altered in cancer. Despite their independent derivation, tumours of the same type tend to converge on a common, new gene-expression profile. Various studies, primarily from The Cancer Genome Atlas project1, have noted differential transcription of tumour-driving and tumour-suppressing genes in advanced tumours, but so many gene transcripts are altered in these tumours that it is difficult to know which ones ‘drive’ the altered behaviour and which ones are ‘passengers’, just going along for the ride. Furthermore, epigenetic alterations — those that modify gene expression without involving sequence mutations — have been implicated in cancer, including colorectal cancer4, 5. Broad surveys of transcriptional and epigenetic changes in tumours have been conducted6, 7, but not on the scale and resolution achieved by Ongen and colleagues. They used a method known as RNA-Seq, in which the transcriptome of a cell (its whole complement of RNA molecules) is sequenced.
Over the past couple of years, sequencing of the exome of cancer cells (in essence, just the protein-coding regions) has suggested that around 250 genes are mutated in cancer cells significantly more often than expected by chance8, 9, 10. Many of these are pan-cancer genes, and some are tumour-type specific. It is less straightforward to perform similar analyses for regulatory DNA, for two reasons: we are just beginning to learn how to identify regulatory functions in the hundreds of kilobases that surround genes, and altered gene expression is often due to changes in genes located elsewhere in the genome. Ongen et al. overcome these limitations by focusing on changes in the ratio of expression of heterozygous alleles (sites at which the DNA sequence differs between the two copies of the sequence in a cell) between tumour and matched normal cells, as had also been done in another recent analysis of colorectal cancer11. They call the hundreds of instances of this phenomenon that they find per sample ‘genes with allelic dysregulation’ (GADs).
Although allele-specific expression can also be attributed to changes at other genes, it is highly likely that in many cases it is due to a locally acting regulatory mutation. Ongen et al. observe a significant correlation between the somatic (non-germline) mutation rate and altered allele-specific expression and, in each of the 103 matched normal–tumour pairs they analysed, approximately 200 transcripts showed a cancer-specific deviation in the allelic expression ratio at heterozygous sites. Their interpretation is that one allele is transcribed more than the other owing to the action of regulatory-sequence variation.
The authors show that some of this deviation can be attributed to familiar cancer-associated mutation types, including loss of heterozygosity and copy-number alteration, and that some is due to inferred (yet to be defined) regulatory mutations. Tallying these instances over all of the samples, and taking two approaches to controlling for statistical biases, they arrive at a list of 71 GADs that occur more frequently in tumours than in normal cells, 9 of which are shared with an existing list of pan-cancer driver mutations8. These observations provide a smoking gun for the idea that regulatory mutations can drive cancer. Perhaps there is no need to distinguish them with their own name, but the term ‘GPS mutations’ comes to mind, because they are instructing driver mutations on what to do, but it is not altogether clear that the cancer cells would not still attain a tumorous state without their help — much like a satellite-based navigation system instructing a driver on how to get somewhere.
A related term, ‘back-seat driver’, has been invoked to describe another class of mutation that probably has a role in mediating cancer progression or metastatic spread, and that is conditional on the status of other driver mutations12. Ongen and colleagues’ second major contribution is to suggest that, in addition to GPS mutations in GADs, another important source of cancer regulation is cryptic genetic variation (Fig. 1). These are genetic variants that are not relevant under normal circumstances, but become so only in a perturbed state13. They may play a key part in modifying the expression of cancer-driving genes. Specifically, when the authors looked for common variants that associate with differences in gene expression among individuals, they found that at least one-third of the expression-regulating variants (eSNPs) are tumour specific.
Figure 1: Cryptic regulation in tumour cells.
Cryptic regulation in tumour cells.
a, In normal cells, the two copies (alleles) of a gene in which the alleles are heterozygous, meaning that they contain a different nucleotide at a specific site (here, A and C), are both expressed at the same, low level. In this example, the alleles in the transcript are associated with a normally irrelevant, or ‘cryptic’, variant allele in a regulatory region of the gene (A with T and C with G). b, In a tumour cell that is characterized by enhanced expression of a transcription factor, this cryptic variant becomes relevant, because the transcription factor can bind to the T-containing allele but not to one containing G. This leads to enhanced transcription of the gene containing the A allele relative to that containing C, and thus an altered allelic-expression ratio.
    Full size image (104 KB)
Furthermore, these polymorphisms are enriched for binding sites for six known cancer-related transcription factors, all of which are upregulated in colorectal cancer. The idea is that when one of these factors (IRX3, E2F4, NFIL3, TFAP2A, CUX1 or LEF1) is in excess, polymorphisms that in normal cells do not influence the expression of the adjacent gene become relevant. Whether or not these are key back-seat modifiers of cancer progression is unclear, because there is only a mild enrichment for these polymorphisms in a genome-wide association study (GWAS) of colorectal cancers14. Perhaps they would be more enriched in a GWAS that assessed tumour progression.
Two words of caution about this study are in order. The first is that there has been no attempt to demonstrate functionality of any of the candidate mutations — the findings are all based on statistical association. The second is that anyone using RNA-Seq quickly realizes that there are many points at which the analysis can provide divergent results. Given recent interest in the repeatability of findings, it could be argued that it would be a good idea for journals to require independent parallel analyses from a different group, conducted blind, to corroborate such results before publication. This suggestion is not made to denigrate the careful and insightful analyses reported by Ongen et al., but is rather a generic comment on the inherent complexity of RNA-Seq, GWASs and enrichment analyses. Different analysts are likely to find quite different details. Yet the prospect that acquired variants drive cancer by controlling gene expression against a background of cryptic regulatory modifiers opens up a new perspective on cancer research. Similar analyses can now be performed on other data sets, and also on diseases other than cancer in which regulation of gene expression is altered15, 16. The next challenge is to establish the clinical utility of the identified regulatory variation.
References
    References•
    Author information
    The Cancer Genome Atlas Research Network. Nature Genet. 45, 1113–1120 (2013).
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    Hopkins, A. L. & Groom, C. R. Nature Rev. Drug Discov. 1, 727–730 (2002).
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    Ongen, H. et al. Nature http://dx.doi.org/10.1038/nature13602 (2014).
        Show context
    Bogaert, J. & Prenen, H. Ann. Gastroenterol. 27, 9–14 (2014). .

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