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1.
EBioMedicine ; 48: 203-211, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31629678

RESUMO

BACKGROUND: We previously conducted a systematic field synopsis of 1059 breast cancer candidate gene studies and investigated 279 genetic variants, 51 of which showed associations. The major limitation of this work was the small sample size, even pooling data from all 1059 studies. Thereafter, genome-wide association studies (GWAS) have accumulated data for hundreds of thousands of subjects. It's necessary to re-evaluate these variants in large GWAS datasets. METHODS: Of these 279 variants, data were obtained for 228 from GWAS conducted within the Asian Breast Cancer Consortium (24,206 cases and 24,775 controls) and the Breast Cancer Association Consortium (122,977 cases and 105,974 controls of European ancestry). Meta-analyses were conducted to combine the results from these two datasets. FINDINGS: Of those 228 variants, an association was observed for 12 variants in 10 genes at a Bonferroni-corrected threshold of P < 2·19 × 10-4. The associations for four variants reached P < 5 × 10-8 and have been reported by previous GWAS, including rs6435074 and rs6723097 (CASP8), rs17879961 (CHEK2) and rs2853669 (TERT). The remaining eight variants were rs676387 (HSD17B1), rs762551 (CYP1A2), rs1045485 (CASP8), rs9340799 (ESR1), rs7931342 (CHR11), rs1050450 (GPX1), rs13010627 (CASP10) and rs9344 (CCND1). Further investigating these 10 genes identified associations for two additional variants at P < 5 × 10-8, including rs4793090 (near HSD17B1), and rs9210 (near CYP1A2), which have not been identified by previous GWAS. INTERPRETATION: Though most candidate gene variants were not associated with breast cancer risk, we found 14 variants showing an association. Our findings warrant further functional investigation of these variants. FUND: National Institutes of Health.

2.
J Natl Cancer Inst ; 2019 May 29.
Artigo em Inglês | MEDLINE | ID: mdl-31143935

RESUMO

BACKGROUND: DNA methylation plays a critical role in breast cancer development. Previous studies have identified DNA methylation marks in white blood cells as promising biomarkers for breast cancer. However, these studies were limited by low statistical power and potential biases. Utilizing a new methodology, we investigated DNA methylation marks for their associations with breast cancer risk. METHODS: Statistical models were built to predict levels of DNA methylation marks using genetic data and DNA methylation data from HumanMethylation450 BeadChip from the Framingham Heart Study (N=1,595). The prediction models were validated using data from the Women's Health Initiative (N=883). We applied these models to genome-wide association study (GWAS) data of 122,977 breast cancer cases and 105,974 controls to evaluate if the genetically predicted DNA methylation levels at CpGs are associated with breast cancer risk. All statistical tests were two-sided. RESULTS: Of the 62,938 CpG sites (CpGs) investigated, statistically significant associations with breast cancer risk were observed for 450 CpGs at a Bonferroni-corrected threshold of P<7.94 × 10-7, including 45 CpGs residing in 18 genomic regions which have not previously been associated with breast cancer risk. Of the remaining 405 CpGs located within 500 kilobase flaking regions of 70 GWAS-identified breast cancer risk variants, the associations for 11 CpGs were independent of GWAS-identified variants. Integrative analyses of genetic, DNA methylation and gene expression data found that 38 CpGs may affect breast cancer risk through regulating expression of 21 genes. CONCLUSION: Our new methodology can identify novel DNA methylation biomarkers for breast cancer risk and can be applied to other diseases.

3.
Nat Neurosci ; 22(5): 691-699, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30988527

RESUMO

Genome-wide association studies (GWAS) have identified more than 100 schizophrenia (SCZ)-associated loci, but using these findings to illuminate disease biology remains a challenge. Here we present integrative risk gene selector (iRIGS), a Bayesian framework that integrates multi-omics data and gene networks to infer risk genes in GWAS loci. By applying iRIGS to SCZ GWAS data, we predicted a set of high-confidence risk genes, most of which are not the nearest genes to the GWAS index variants. High-confidence risk genes account for a significantly enriched heritability, as estimated by stratified linkage disequilibrium score regression. Moreover, high-confidence risk genes are predominantly expressed in brain tissues, especially prenatally, and are enriched for targets of approved drugs, suggesting opportunities to reposition existing drugs for SCZ. Thus, iRIGS can leverage accumulating functional genomics and GWAS data to advance our understanding of SCZ etiology and potential therapeutics.


Assuntos
Redes Reguladoras de Genes , Predisposição Genética para Doença , Genômica/métodos , Esquizofrenia/genética , Animais , Teorema de Bayes , Modelos Animais de Doenças , Estudo de Associação Genômica Ampla , Humanos , Camundongos , Fatores de Risco
4.
Curr Protoc Hum Genet ; 101(1): e83, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30849219

RESUMO

With the advent of Next Generation Sequencing (NGS) technologies, whole genome and whole exome DNA sequencing has become affordable for routine genetic studies. Coupled with improved genotyping arrays and genotype imputation methodologies, it is increasingly feasible to obtain rare genetic variant information in large datasets. Such datasets allow researchers to gain a more complete understanding of the genetic architecture of complex traits caused by rare variants. State-of-the-art statistical methods for the statistical genetics analysis of sequence-based association, including efficient algorithms for association analysis in biobank-scale datasets, gene-association tests, meta-analysis, fine mapping methods that integrate functional genomic dataset, and phenome-wide association studies (PheWAS), are reviewed here. These methods are expected to be highly useful for next generation statistical genetics analysis in the era of precision medicine. © 2019 by John Wiley & Sons, Inc.


Assuntos
Predisposição Genética para Doença , Genoma Humano/genética , Herança Multifatorial/genética , Algoritmos , Estudo de Associação Genômica Ampla/métodos , Genótipo , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Fenótipo , Polimorfismo de Nucleotídeo Único/genética , Sequenciamento Completo do Exoma/métodos , Sequenciamento Completo do Genoma/métodos
5.
Mol Cancer Res ; 17(5): 1024-1035, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-30683671

RESUMO

Aberrant activation of the Hedgehog signaling pathway has been linked to the formation of numerous cancer types, including the myogenic soft tissue sarcoma, embryonal rhabdomyosarcoma (eRMS). Here, we report PCG2, a novel mouse model in which human GLI2A, a constitutive activator of Hedgehog signaling, induced undifferentiated sarcomas that were phenotypically divergent from eRMS. Rather, sarcomas arising in PCG2 mice featured some characteristics that were reminiscent of Ewing sarcoma. Even though it is widely understood that Ewing sarcoma formation is driven by EWS-ETS gene fusions, a genetically defined mouse model is not well-established. While EWS-ETS gene fusions were not present in PCG2 sarcomas, precluding their designation as Ewing sarcoma, we did find that GLI2A induced expression of known EWS-ETS gene targets essential to Ewing pathogenesis, most notably, Nkx2.2. Moreover, we found that naïve mesenchymal progenitors originate tumors in PCG2 mice. Altogether, our work provides a novel genetic mouse model, which directly connects oncogenic Hedgehog activity to the etiology of undifferentiated soft tissue sarcomas for the first time. IMPLICATIONS: The finding that activation of Gli2 transcription factor is sufficient to induce Ewing-like sarcomas provides a direct transformative role of the Hedgehog signaling pathway in undifferentiated soft tissue sarcoma.

6.
Gastroenterology ; 156(5): 1455-1466, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30529582

RESUMO

BACKGROUND & AIMS: Genome-wide association studies (GWASs) have associated approximately 50 loci with risk of colorectal cancer (CRC)-nearly one third of these loci were initially associated with CRC in studies conducted in East Asian populations. We conducted a GWAS of East Asians to identify CRC risk loci and evaluate the generalizability of findings from GWASs of European populations to Asian populations. METHODS: We analyzed genetic data from 22,775 patients with CRC (cases) and 47,731 individuals without cancer (controls) from 14 studies in the Asia Colorectal Cancer Consortium. First, we performed a meta-analysis of 7 GWASs (10,625 cases and 34,595 controls) and identified 46,554 promising risk variants for replication by adding them to the Multi-Ethnic Global Array (MEGA) for genotype analysis in 6445 cases and 7175 controls. These data were analyzed, along with data from an additional 5705 cases and 5961 controls genotyped using the OncoArray. We also obtained data from 57,976 cases and 67,242 controls of European descent. Variants at identified risk loci were functionally annotated and evaluated in correlation with gene expression levels. RESULTS: A meta-analyses of all samples from people of Asian descent identified 13 loci and 1 new variant at a known locus (10q24.2) associated with risk of CRC at the genome-wide significance level of P < 5 × 10-8. We did not perform experiments to replicate these associations in additional individuals of Asian ancestry. However, the lead risk variant in 6 of these loci was also significantly associated with risk of CRC in European descendants. A strong association (44%-75% increase in risk per allele) was found for 2 low-frequency variants: rs201395236 at 1q44 (minor allele frequency, 1.34%) and rs77969132 at 12p11.21 (minor allele frequency, 1.53%). For 8 of the 13 associated loci, the variants with the highest levels of significant association were located inside or near the protein-coding genes L1TD1, EFCAB2, PPP1R21, SLCO2A1, HLA-G, NOTCH4, DENND5B, and GNAS. For other intergenic loci, we provided evidence for the possible involvement of the genes ALDH7A1, PRICKLE1, KLF5, WWOX, and GLP2R. We replicated findings for 41 of 52 previously reported risk loci. CONCLUSIONS: We showed that most of the risk loci previously associated with CRC risk in individuals of European descent were also associated with CRC risk in East Asians. Furthermore, we identified 13 loci significantly associated with risk for CRC in Asians. Many of these loci contained genes that regulate the immune response, Wnt signaling to ß-catenin, prostaglandin E2 catabolism, and cell pluripotency and proliferation. Further analyses of these genes and their variants is warranted, particularly for the 8 loci for which the lead CRC risk variants were not replicated in persons of European descent.


Assuntos
Grupo com Ancestrais do Continente Asiático/genética , Biomarcadores Tumorais/genética , Neoplasias Colorretais/genética , Loci Gênicos , Polimorfismo de Nucleotídeo Único , Ásia/epidemiologia , Estudos de Casos e Controles , Neoplasias Colorretais/diagnóstico , Neoplasias Colorretais/etnologia , Neoplasias Colorretais/imunologia , Frequência do Gene , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Fenótipo , Medição de Risco , Fatores de Risco
7.
Cancer Res ; 79(3): 505-517, 2019 02 01.
Artigo em Inglês | MEDLINE | ID: mdl-30559148

RESUMO

DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P < 7.94 × 10-7. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. SIGNIFICANCE: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.

8.
Eur J Cancer ; 106: 133-143, 2019 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-30528798

RESUMO

BACKGROUND: Both circulating tumour cell (CTC) and total circulating cell-free DNA (ccfDNA) predict cancer patient prognosis. However, no study has explored the prognostic value of the combined use of CTC and ccfDNA. We aimed to investigate individual and joint effects of CTC and ccfDNA on clinical outcomes of metastatic breast cancer (MBC) patients. METHODS: We collected 227 blood samples from 117 MBC patients. CTCs were enumerated using the CellSearch System. ccfDNAs were quantified by quantitative real-time polymerase chain reaction and Qubit fluorometer. The individual and joint effects of CTC and ccfDNA levels on patient progression-free survival (PFS) and overall survival (OS) were analysed using Cox proportional hazards models. RESULTS: Compared to patients with <5 CTCs, patients with ≥5 CTCs had a 2.58-fold increased risk of progression and 3.63-fold increased risk of death. High level of ccfDNA was associated with a 2.05-fold increased risk of progression and 3.56-fold increased risk of death. These associations remained significant after adjusting for other important clinical covariates and CTC/ccfDNA levels. CTC and ccfDNA levels had a joint effect on patient outcomes. Compared to patients with low levels of both CTC and ccfDNA, those with high levels of both markers exhibited a >17-fold increased death risk (P < 0.001). Moreover, longitudinal analysis of 132 samples from 22 patients suggested that the inconsistency between CTC level and outcome in some patients could possibly be explained by ccfDNA level. CONCLUSIONS: CTC and total ccfDNA levels were individually and jointly associated with PFS and OS in MBC patients.

9.
J Natl Compr Canc Netw ; 16(10): 1183-1192, 2018 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-30323088

RESUMO

Background: Use of chemotherapy in stage II colorectal cancer (CRC) is controversial because it improves survival only in some patients. We aimed to develop a statistical model using routine and readily available blood tests to predict the prognosis of patients with stage II CRC and to identify which patients are likely to benefit from chemotherapy. Methods: We divided 422 patients with stage II CRC into a training and a testing set. The association of routine laboratory variables and disease-free survival (DFS) was analyzed. A prognostic model was developed incorporating clinically relevant laboratory variables with demographic and tumor characteristics. A prognostic score was derived by calculating the sum of each variable weighted by its regression coefficient in the model. Model performance was evaluated by constructing receiver operating characteristic curves and calculating the area under the curve (AUC). Results: Significant associations were seen between 5 laboratory variables and patient DFS in univariate analyses. After stepwise selection, 3 variables (carcinoembryonic antigen, hemoglobin, creatinine) were retained in the multivariate model with an AUC of 0.75. Compared with patients with a low prognostic score, those with a medium and high prognostic score had a 1.99- and 4.78-fold increased risk of recurrence, respectively. The results from the training set were validated in the testing set. Moreover, chemotherapy significantly improved DFS in high-risk patients, but not in low- and medium-risk patients. Conclusions: A routine laboratory variable-based model may help predict DFS of patients with stage II CRC and identify high-risk patients more likely to benefit from chemotherapy.

10.
Hum Mol Genet ; 2018 10 10.
Artigo em Inglês | MEDLINE | ID: mdl-30307499

RESUMO

E-selectin mediates the rolling of circulating leukocytes during inflammatory processes. Previous genome-wide association studies (GWAS) in European and Asian individuals have identified the ABO locus associated with E-selectin levels. Using Trans-Omics for Precision Medicine (TOPMed) whole-genome sequencing (WGS) data in 2,249 African Americans (AAs) from the Jackson Heart Study (JHS), we examined genome-wide associations with soluble E-selectin levels. In addition to replicating known signals at ABO, we identified a novel association of a common loss-of-function, missense variant in FUT6 (rs17855739,p.Glu274Lys, p=9.02 x 10-24) with higher soluble E-selectin levels. This variant is considerably more common in populations of African-ancestry compared to non-African ancestry populations. We replicated the association of FUT6 p.Glu274Lys with higher soluble E-selectin in an independent population of 748 AAs from the Women's Health Initiative and identified an additional pleiotropic association with vitamin B12 levels. Despite the broad role of both selectins and fucosyltransferases in various inflammatory, immune and cancer-related processes, we were unable to identify any additional disease associations of the FUT6 p.Glu274Lys variant in an EMR-based phenome-wide association scan of over 9,000 African Americans.

11.
Bioinformatics ; 2018 Sep 26.
Artigo em Inglês | MEDLINE | ID: mdl-30256891

RESUMO

Motivation: Given the complexity of genome regions, prioritize the functional effects of noncoding variants remains a challenge. Although several frameworks have been proposed for the evaluation of the functionality of noncoding variants, most of them used "black boxes" methods that simplify the task as the pathogenicity/benign classification problem, which ignores the distinct regulatory mechanisms of variants and leads to less desirable performance. In this study, we developed DVAR, an unsupervised framework that leverage various biochemical and evolutionary evidence to distinguish the gene regulatory categories of variants and assess their comprehensive functional impact simultaneously. Results: DVAR performed de novo pattern discovery in high-dimensional data and identified five regulatory clusters of noncoding variants. Leveraging the new insights into the multiple functional patterns, it measures both the between-class and the within-class functional implication of the variants to achieve accurate prioritization. Compared to other two-class learning methods, it showed improved performance in identification of clinically significant variants, fine-mapped GWAS variants, eQTLs and expression-modulating variants. Moreover, it has superior performance on disease causal variants verified by genome editing (like CRISPR-Cas9), which could provide a pre-selection strategy for genome editing technologies across the whole genome. Finally, evaluated in BioVU and UK Biobank, two large-scale DNA biobanks linked to complete electronic health records (EHR), DVAR demonstrated its effectiveness in prioritizing noncoding variants associated with medical phenotypes. Availability: The C++ and Python source codes, the pre-computed DVAR-cluster labels and DVAR scores across the whole genome are available at https://www.vumc.org/cgg/dvar. Supplementary information: Supplementary data are available at Bioinformatics online.

12.
World J Pediatr ; 14(6): 585-593, 2018 12.
Artigo em Inglês | MEDLINE | ID: mdl-30155617

RESUMO

BACKGROUND: Wilms tumor (WT) is the most common childhood kidney cancer worldwide, yet its incidence and clinical behavior vary according to race and access to adequate healthcare resources. To guide and streamline therapy in the war-torn and resource-constrained city of Baghdad, Iraq, we conducted a first-ever molecular analysis of 20 WT specimens to characterize the biological features of this lethal disease within this challenged population. METHODS: Next-generation sequencing of ten target genes associated with WT development and treatment resistance (WT1, CTNNB1, WTX, IGF2, CITED1, SIX2, p53, N-MYC, CRABP2, and TOP2A) was completed. Immunohistochemistry was performed for 6 marker proteins of WT (WT1, CTNNB1, NCAM, CITED1, SIX2, and p53). Patient outcomes were compiled. RESULTS: Mutations were detected in previously described WT "hot spots" (e.g., WT1 and CTNNB1) as well as novel loci that may be unique to the Iraqi population. Immunohistochemistry showed expression domains most typical of blastemal-predominant WT. Remarkably, despite the challenges facing families and care providers, only one child, with combined WT1 and CTNNB1 mutations, was confirmed dead from disease. Median clinical follow-up was 40.5 months (range 6-78 months). CONCLUSIONS: These data suggest that WT biology within a population of Iraqi children manifests features both similar to and unique from disease variants in other regions of the world. These observations will help to risk stratify WT patients living in this difficult environment to more or less intensive therapies and to focus treatment on cell-specific targets.

13.
Cancer Res ; 78(18): 5419-5430, 2018 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-30054336

RESUMO

Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10-6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419-30. ©2018 AACR.

14.
Nat Genet ; 50(7): 968-978, 2018 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-29915430

RESUMO

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10-6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

15.
Reprod Sci ; : 1933719118776788, 2018 May 30.
Artigo em Inglês | MEDLINE | ID: mdl-29848177

RESUMO

OBJECTIVE: To identify novel susceptibility genes for age at natural menopause (ANM). METHODS: Using transcription data generated in tissues from normal hypothalami (n = 73) and ovaries (n = 68) and high-density genotyping data provided by the Genotype-Tissue Expression (GTEx) database, we built 16 164 genetic models to predict gene expression across the transcriptome in these tissues. We used these models and summary statistics data from genome-wide association studies (GWAS) of ANM generated in 69 360 women of European ancestry to identify genes with their predicted expression related to ANM. RESULTS: We found the predicted expression of 34 genes to be significantly associated with ANM at a Bonferroni-corrected threshold of P < 3.09 ×10-6. These include 4 genes located more than 1 Mb away from any previously GWAS-identified ANM-associated variants, 24 genes that reside in known GWAS-identified loci but have not been previously implicated, and 6 genes previously implicated as ANM-associated genes. CONCLUSION: Results from this transcriptome-wide association study, which integrated Expression quantitative trait loci (eQTL) data with summary statistics of GWAS of ANM, improves our understanding of the genetics and biology of female reproductive aging.

16.
AMIA Jt Summits Transl Sci Proc ; 2017: 237-246, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29888080

RESUMO

Drug repositioning for available medications can be preferred over traditional drug development, which requires substantially more effort to uncover new insights into medications and diseases. Genome-Wide Association Studies (GWAS) and Phenome-Wide Association Studies (PheWAS) are two complimentary methods for finding novel associations between genes and diseases. We hypothesize that discoveries from these studies could be leveraged to find new targets for existing drugs. Thus, we propose a framework to learn opportunities for inferring such relationships via overlapped genes between disease-associated genes (e.g. GWAS and PheWAS findings) and drugtargeted genes. We use drug indications found in Medication Indication Resource (MEDI) as a gold standard to evaluate if drug indications learned from GWAS and PheWAS findings have clinical indications. We examined 151,011 pairs from 987 drugs across 153 diseases and 763 pairs were statistically significant. Out of these 763 pairs, 16 of them were found to have clinical indications.

17.
Am J Hum Genet ; 102(5): 890-903, 2018 05 03.
Artigo em Inglês | MEDLINE | ID: mdl-29727689

RESUMO

Genome-wide association studies (GWASs) have identified more than 150 common genetic loci for breast cancer risk. However, the target genes and underlying mechanisms remain largely unknown. We conducted a cis-expression quantitative trait loci (cis-eQTL) analysis using normal or tumor breast transcriptome data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), The Cancer Genome Atlas (TCGA), and the Genotype-Tissue Expression (GTEx) project. We identified a total of 101 genes for 51 lead variants after combing the results of a meta-analysis of METABRIC and TCGA, and the results from GTEx at a Benjamini-Hochberg (BH)-adjusted p < 0.05. Using luciferase reporter assays in both estrogen-receptor positive (ER+) and negative (ER-) cell lines, we showed that alternative alleles of potential functional single-nucleotide polymorphisms (SNPs), rs11552449 (DCLRE1B), rs7257932 (SSBP4), rs3747479 (MRPS30), rs2236007 (PAX9), and rs73134739 (ATG10), could significantly change promoter activities of their target genes compared to reference alleles. Furthermore, we performed in vitro assays in breast cancer cell lines, and our results indicated that DCLRE1B, MRPS30, and ATG10 played a vital role in breast tumorigenesis via certain disruption of cell behaviors. Our findings revealed potential target genes for associations of genetic susceptibility risk loci and provided underlying mechanisms for a better understanding of the pathogenesis of breast cancer.

19.
Int J Cancer ; 143(5): 1143-1152, 2018 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-29569724

RESUMO

Recent studies have revealed significant intratumor heterogeneity (ITH) of nuclear genome mutations and highlighted its function in tumor progression and treatment resistance. However, the ITH of somatic mitochondrial DNA (mtDNA) mutations detected in cancers remains unknown. In this study, we performed multiregional mtDNA sequencing of tumor and paratumor tissue samples from 12 hepatocellular carcinoma (HCC) and 13 colorectal cancer (CRC) patients. A substantial level of mtDNA mutations was found in paired non-HCC inflammatory tissues, suggesting that these tissues might not be mtDNA-genetically "normal." Moreover, our data indicated that the ITH of somatic mtDNA mutations was a common feature in HCC and CRC patients. In addition, we found that shared mutations which were observed in at least 2 samples in each patient exhibited a significantly higher heteroplasmic level than mutations that were private to a specific tumor region from both HCC (p = 0.039) and CRC patients (p = 0.001). The heteroplasmic level of shared mutations was positively correlated with intratumoral recurrence of mtDNA mutations. We also found that shared mutations in tumor tissues with a higher degree of pathogenicity risk exhibited a higher heteroplasmic level and intratumoral recurrence in both HCC and CRC patients. These findings suggest that some mtDNA mutations may undergo positive selection during the clonal expansion. Taken together, our analyses identified various levels of ITH of somatic mtDNA mutations in HCC and CRC patients and provided evidence supporting the positive selection working on some somatic mtDNA mutations in tumor tissues.

20.
J Exp Clin Cancer Res ; 36(1): 168, 2017 11 28.
Artigo em Inglês | MEDLINE | ID: mdl-29179728

RESUMO

BACKGROUND: Previous studies have indicated that tumor mitochondrial DNA (mtDNA) mutations are primarily shaped by relaxed negative selection, which is contradictory to the critical roles of mtDNA mutations in tumorigenesis. Therefore, we hypothesized that site-specific selection may influence tumor mtDNA mutations. METHODS: To test our hypothesis, we developed the largest collection of tumor mtDNA mutations to date and evaluated how natural selection shaped mtDNA mutation patterns. RESULTS: Our data demonstrated that both positive and negative selections acted on specific positions or functional units of tumor mtDNAs, although the landscape of these mutations was consistent with the relaxation of negative selection. In particular, mutation rate (mutation number in a region/region bp length) in complex V and tRNA coding regions, especially in ATP8 within complex V and in loop and variable regions within tRNA, were significantly lower than those in other regions. While the mutation rate of most codons and amino acids were consistent with the expectation under neutrality, several codons and amino acids had significantly different rates. Moreover, the mutations under selection were enriched for changes that are predicted to be deleterious, further supporting the evolutionary constraints on these regions. CONCLUSION: These results indicate the existence of site-specific selection and imply the important role of the mtDNA mutations at some specific sites in tumor development.


Assuntos
DNA Mitocondrial/genética , Mitocôndrias/genética , Neoplasias/genética , Mutação Puntual , Aminoácidos/genética , Códon/genética , DNA Mitocondrial/química , Bases de Dados Genéticas , Humanos , Mitocôndrias/química , Taxa de Mutação , Seleção Genética
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