47 research outputs found
Fine-mapping using the weighted average method for a case-control study
We present a new method for fine-mapping a disease susceptibility locus using a case-control design. The new method, termed the weighted average (WA) statistic, averages the Cochran-Armitage (CA) trend test statistic and the difference between the Hardy-Weinberg disequilibrium test statistic for cases and controls (the HWD trend). The main characteristics of the WA statistic are that it improves on the weaknesses, and maintains the strengths, of both the CA trend test and the HWD trend test. Data from three different populations in the Genetic Analysis Workshop 14 (GAW14) simulated dataset (Aipotu, Karangar, and Danacaa) were first subjected to model-free linkage analysis to find regions exhibiting linkage. Then, for fine-scale mapping, 140 SNPs within the significant linkage regions were analyzed with the WA test statistic on replicates of the three populations, both separately and combined. The regions that were significant in the multipoint linkage analysis were also significant in this fine-scale mapping. The most significant regions that were obtained using the WA statistic were regions in chromosome 3 (B03T3056–B03T3058, p-value < 1 × 10(-10 )) and chromosome 9 (B09T8332–B09T8334, p-value 1 × 10(-6 )). Based on the results of the simulated GAW14 data, the WA test statistic showed good performance and could narrow down the region containing the susceptibility locus. However, the strength of the signal depends on both the strength of the linkage disequilibrium and the heterozygosity of the linked marker
Germline SDHx variants modify breast and thyroid cancer risks in Cowden and Cowden-like syndrome via FAD/NAD-dependant destabilization of p53
Cowden syndrome (CS), a Mendelian autosomal-dominant disorder, predisposes to breast, thyroid and other cancers. Germline mutations in phosphatase and tensin homolog (PTEN) have been recently reported in 23% of a large series of classic CS. Here, we validated our small (n = 10) pilot study in a large patient series that germline variations in succinate dehydrogenase genes (SDHx) occur in 8% (49/608) of PTEN mutation-negative CS and CS-like (CSL) individuals (SDHvar+). None of these SDHx variants was found in 700 population controls (P < 0.0001). We then found that SDHx variants also occur in 6% (26/444) of PTEN mutation-positive (PTENmut+) CS/CSL individuals (PTENmut+/SDHvar+). Of 22 PTENmut+/SDHvar+ females, 17 had breast cancers compared with 34/105 PTENmut+ (P < 0.001) or 27/47 SDHvar+ patients (P = 0.06). Notably, individuals with SDHvar+ alone had the highest thyroid cancer prevalence (24/47) compared with PTENmut+ patients (27/105, P = 0.002) or PTENmut+/SDHvar+ carriers (6/22, P = 0.038). Patient-derived SDHvar+ lymphoblastoid cells had elevated cellular reactive oxygen species, highest in PTENmut+/SDHvar+ cells, correlating with apoptosis resistance. SDHvar+ cells showed stabilized and hyperactivated hypoxia inducible factor (HIF)1α signaling. Most interestingly, we also observed the loss of steady-state p53 in the majority of SDHvar+ cells. This loss of p53 was regulated by MDM2-independent NADH quinone oxidoreductase 1-mediated protein degradation, likely due to the imbalance of flavin adenine dinucleotide/nicotinamide adenine dinucleotide in SDHvar+ cells. Our data suggest the potential regulation of HIF1α, p53 and PTEN signaling by mitochondrial metabolism in CS/CSL tumorigenesis. Together, our findings suggest the importance of considering SDHx as candidate predisposing and modifier genes for CS/CSL-related malignancy risks, and a mechanism which suggests ways of therapeutic reversal or prevention
Resveratrol regulates the PTEN/AKT pathway through androgen receptor-dependent and -independent mechanisms in prostate cancer cell lines
The tumor suppressor gene PTEN (phosphatase and tensin homolog deleted on chromosome 10) and the androgen receptor (AR) play important roles in tumor development and progression in prostate carcinogenesis. Among many functions, PTEN negatively regulates the cytoplasmic phosphatidylinositol-3-kinase/AKT anti-apoptotic pathway; and nuclear PTEN affects the cell cycle by also negatively regulating the MAPK pathway via cyclin D. Decreased PTEN expression is correlated with prostate cancer progression. Over-expression of AR and upregulation of AR transcriptional activity are often observed in the later stages of prostate cancer. Recent studies indicate that PTEN regulates AR activity and stability. However, the mechanism of how AR regulates PTEN has never been studied. Furthermore, resveratrol, a phytoalexin enriched in red grapes, strawberries and peanuts, has been shown to inhibit AR transcriptional activity in prostate cancer cells. In this study, we use prostate cancer cell lines to test the hypothesis that resveratrol inhibits cellular proliferation in both AR-dependent and -independent mechanisms. We show that resveratrol inhibits AR transcriptional activity in both androgen-dependent and -independent prostate cancer cells. Additionally, resveratrol stimulates PTEN expression through AR inhibition. In contrast, resveratrol directly binds epidermal growth factor receptor (EGFR) rapidly inhibiting EGFR phosphorylation, resulting in decreased AKT phosphorylation, in an AR-independent manner. Thus, resveratrol may act as potential adjunctive treatment for late-stage hormone refractory prostate cancer. More importantly, for the first time, our study demonstrates the mechanism by which AR regulates PTEN expression at the transcription level, indicating the direct link between a nuclear receptor and the PI3K/AKT pathway
Association of PARP1-specific polymorphisms and haplotypes with non-small cell lung cancer subtypes.
ObjectiveThe carcinogenesis role of PARP1 in lung cancer is still not clear. Analysis at allelic levels cannot fully explain the function of PARP1 on lung cancer. Our study aims to further explore the relation between PARP1 haplotypes and lung cancer.Materials and methodsDNA and RNA were extracted from non-small cell lung cancer (NSCLC) tumor and adjacent normal fresh frozen tissue. Five PARP1-SNPs were genotyped and PARP1-specific SNPs were imputed using IMPUTE and SHAPEIT software. The SNPs were subjected to allelic, haplotype and SNP-SNP interaction analyses. Correlation between SNPs and mRNA/protein expressions were performed.ResultsSNP imputation inferred the ungenotyped SNPs and increased the power for association analysis. Tumor tissue samples are more likely to carry rs1805414 (OR = 1.85; 95% CI: 1.12-3.06; P-value: 0.017) and rs1805404 (OR = 2.74; 95%CI 1.19-6.32; P-value: 0.015) compared to normal tissues. Our study is the first study to show that haplotypes comprising of 5 SNPs on PARP1 (rs1136410, rs3219073, rs1805414, rs1805404, rs1805415) is able to differentiate the NSCLC tumor from normal tissues. Interaction between rs3219073, rs1805415, and rs1805414 were significantly associated with the NSCLC tumor with OR ranging from 3.61-6.75; 95%CI from 1.82 to 19.9; P-valueConclusionPARP1 haplotypes may serve as a better predictor in lung cancer development and prognosis compared to single alleles
Using Machine Learning to Predict Progression in the Gastric Precancerous Process in a Population from a Developing Country Who Underwent a Gastroscopy for Dyspeptic Symptoms
Background. Gastric cancer is the fourth most common cancer and the third most common cause of cancer deaths worldwide. Morbidity and mortality from gastric cancer may be decreased by identification of those that are at high risk for progression in the gastric precancerous process so that they can be monitored over time for early detection and implementation of preventive strategies. Method. Using machine learning, we developed prediction models for gastric precancerous progression in a population from a developing country with a high rate of gastric cancer who underwent gastroscopies for dyspeptic symptoms. In the data imputed for completeness, we divided the data into a training and a validation test set. Using the training set, we used the random forest method to rank potential predictors based on their predictive importance. Using predictors identified by the random forest method, we conducted best subset linear regressions with the leave-one-out cross-validation approach to select predictors for overall progression and progression to dysplasia or cancer. We validated the models in the test set using leave-one-out cross-validation. Results. We observed for all models that complete intestinal metaplasia and incomplete intestinal metaplasia were the strongest predictors for further progression in the precancerous process. We also observed that a diagnosis of no gastritis, superficial gastritis, or antral diffuse gastritis at baseline was a predictor of no progression in the gastric precancerous process. The sensitivities and specificities were 86% and 79% for the general model and 100% and 82% for the location-specific model, respectively. Conclusion. We developed prediction models to identify gastroscopy patients that are more likely to progress in the gastric precancerous process, among whom routine follow-up gastroscopies can be targeted to prevent gastric cancer. Future external validation is needed
Using Machine Learning to Predict Progression in the Gastric Precancerous Process in a Population from a Developing Country Who Underwent a Gastroscopy for Dyspeptic Symptoms
Integrative Genomic Analysis Reveals Extended Germline Homozygosity with Lung Cancer Risk in the PLCO Cohort
<div><p>Susceptibility to common cancers is multigenic resulting from low-to-high penetrance predisposition-factors and environmental exposure. Genomic studies suggest germline homozygosity as a novel low-penetrance factor contributing to common cancers. We hypothesized that long homozygous regions (tracts-of-homozygosity [TOH]) harbor tobacco-dependent and independent lung-cancer predisposition (or protection) genes. We performed i<em>n silico</em> genome-wide SNP-array-based analysis of lung-cancer patients of European-ancestry from the PLCO screening-trial cohort to identify TOH regions amongst 788 cancer-cases and 830 ancestry-matched controls. Association analyses was then performed between presence of lung cancer and common(c)TOHs (operationally defined as 10 or more subjects sharing ≥100 identical homozygous calls), aTOHs (allelically-matched groups within a cTOH), demographics and tobacco-exposure. Finally, integration of significant c/aTOH with transcriptome was performed to functionally-map lung-cancer risk-genes. After controlling for demographics and smoking, we identified 7 cTOHs and 5 aTOHs associated with lung cancer (adjusted p<0.01). Three cTOHs were over-represented in cases over controls (OR = 1.75–2.06, p = 0.007–0.001), whereas 4 were under-represented (OR = 0.28–0.69, p = 0.006–0.001). Interaction between smoking status and cTOH3/aTOH2 (2p16.3–2p16.1) was observed (adjusted p<0.03). The remaining significant aTOHs have ORs 0.23–0.50 (p = 0.004–0.006) and 2.95–3.97 (p = 0.008–0.001). After integrating significant cTOH/aTOHs with publicly-available lung-cancer transcriptome datasets followed by filtering based on lung cancer and its relevant pathways revealed 9 putative predisposing genes (p<0.0001). In conclusion, differentially-distributed cTOH/aTOH genomic variants between cases and controls harbor sets of plausible differentially-expressed genes accounting for the complexity of lung-cancer predisposition.</p> </div
cgaTOH: extended approach for identifying tracts of homozygosity.
Identification of disease variants via homozygosity mapping and investigation of the effects of genome-wide homozygosity regions on traits of biomedical importance have been widely applied recently. Nonetheless, the existing methods and algorithms to identify long tracts of homozygosity (TOH) are not able to provide efficient and rigorous regions for further downstream association investigation. We expanded current methods to identify TOHs by defining "surrogate-TOH", a region covering a cluster of TOHs with specific characteristics. Our defined surrogate-TOH includes cTOH, viz a common TOH region where at least ten TOHs present; gTOH, whereby a group of highly overlapping TOHs share proximal boundaries; and aTOH, which are allelically-matched TOHs. Searching for gTOH and aTOH was based on a repeated binary spectral clustering algorithm, where a hierarchy of clusters is created and represented by a TOH cluster tree. Based on the proposed method of identifying different species of surrogate-TOH, our cgaTOH software was developed. The software provides an intuitive and interactive visualization tool for better investigation of the high-throughput output with special interactive navigation rings, which will find its applicability in both conventional association studies and more sophisticated downstream analyses. NCBI genome map viewer is incorporated into the system. Moreover, we discuss the choice of implementing appropriate empirical ranges of critical parameters by applying to disease models. This method identifies various patterned clusters of SNPs demonstrating extended homozygosity, thus one can observe different aspects of the multi-faceted characteristics of TOHs
Genotypic and allelic variability in CYP19A1 among populations of African and European ancestry.
CYP19A1 facilitates the bioconversion of estrogens from androgens. CYP19A1 intron single nucleotide polymorphisms (SNPs) may alter mRNA splicing, resulting in altered CYP19A1 activity, and potentially influencing disease susceptibility. Genetic studies of CYP19A1 SNPs have been well documented in populations of European ancestry; however, studies in populations of African ancestry are limited. In the present study, ten 'candidate' intronic SNPs in CYP19A1 from 125 African Americans (AA) and 277 European Americans (EA) were genotyped and their frequencies compared. Allele frequencies were also compared with HapMap and ASW 1000 Genomes populations. We observed significant differences in the minor allele frequencies between AA and EA in six of the ten SNPs including rs10459592 (p<0.0001), rs12908960 (p<0.0001), rs1902584 (p = 0.016), rs2470144 (p<0.0001), rs1961177 (p<0.0001), and rs6493497 (p = 0.003). While there were no significant differences in allele frequencies between EA and CEU in the HapMap population, a 1.2- to 19-fold difference in allele frequency for rs10459592 (p = 0.004), rs12908960 (p = 0.0006), rs1902584 (p<0.0001), rs2470144 (p = 0.0006), rs1961177 (p<0.0001), and rs6493497 (p = 0.0092) was observed between AA and the Yoruba (YRI) population. Linkage disequilibrium (LD) blocks and haplotype clusters that is unique to the EA population but not AA was also observed. In summary, we demonstrate that differences in the allele frequencies of CYP19A1 intron SNPs are not consistent between populations of African and European ancestry. Thus, investigations into whether CYP19A1 intron SNPs contribute to variations in cancer incidence, outcomes and pharmacological response seen in populations of different ancestry may prove beneficial
Lung cancer-associated cTOH1, cTOH2, cTOH5 and cTOH7 regions Single SNP association analysis was performed (independently of TOH analysis), after which the SNP association was compared to significant TOHs obtained with TOH analysis.
<p>The significant lung cancer-associated single SNPs, and TOH's namely cTOH1, cTOH2, cTOH5, and cTOH7, and their respective 95% CI are shown. The significant lung cancer association of aTOHs and SNPs in the region (top panel) and corresponding risk as odds ratios (lower panel) are shown in panels <b>A–D.</b> Below the lower panels are candidate genes which were prioritized after testing for association between lung cancer and differential expression of each of the genes within each significant TOH +/−250 kb TOH, stratified by smoking status (at p<0.0001; see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031975#s2" target="_blank">Methods</a> section).</p