SwePub
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Le Marchand Loic) srt2:(2015-2019)"

Sökning: WFRF:(Le Marchand Loic) > (2015-2019)

  • Resultat 1-10 av 61
  • [1]234567Nästa
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  • Hollestelle, Antoinette, et al. (författare)
  • No clinical utility of KRAS variant rs61764370 for ovarian or breast cancer
  • 2016
  • Ingår i: Gynecologic Oncology. - : Academic Press. - 0090-8258. ; 141:2, s. 386-401
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3′ UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370. Methods Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers). Results We found no association with risk of ovarian cancer (OR = 0.99, 95% CI 0.94-1.04, p = 0.74) or breast cancer (OR = 0.98, 95% CI 0.94-1.01, p = 0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR = 1.09, 95% CI 0.97-1.23, p = 0.14, breast cancer HR = 1.04, 95% CI 0.97-1.12, p = 0.27; BRCA2, ovarian cancer HR = 0.89, 95% CI 0.71-1.13, p = 0.34, breast cancer HR = 1.06, 95% CI 0.94-1.19, p = 0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR = 0.94, 95% CI 0.83-1.07, p = 0.38), breast cancer (HR = 0.96, 95% CI 0.87-1.06, p = 0.38), and all other previously-reported associations. Conclusions rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.
  •  
2.
  • Lawrenson, Kate, et al. (författare)
  • Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus
  • 2016
  • Ingår i: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 7
  • Tidskriftsartikel (refereegranskat)abstract
    • A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.
  •  
3.
  • Locke, Adam E, et al. (författare)
  • Genetic studies of body mass index yield new insights for obesity biology.
  • 2015
  • Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 518:7538, s. 197-401
  • Tidskriftsartikel (refereegranskat)abstract
    • Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
  •  
4.
  • Phelan, Catherine M, et al. (författare)
  • Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.
  • 2017
  • Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 49:5, s. 680-691
  • Tidskriftsartikel (refereegranskat)abstract
    • To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.
  •  
5.
  • Shungin, Dmitry, et al. (författare)
  • New genetic loci link adipose and insulin biology to body fat distribution.
  • 2015
  • Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 518:7538, s. 187-378
  • Tidskriftsartikel (refereegranskat)abstract
    • Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
  •  
6.
  • Barrdahl, Myrto, et al. (författare)
  • A comprehensive analysis of polymorphic variants in steroid hormone and insulin-like growth factor-1 metabolism and risk of in situ breast cancer : Results from the Breast and Prostate Cancer Cohort Consortium
  • 2018
  • Ingår i: International Journal of Cancer. - : John Wiley & Sons Inc.. - 0020-7136. ; 142:6, s. 1182-1188
  • Tidskriftsartikel (refereegranskat)abstract
    • We assessed the association between 1,414 single nucleotide polymorphisms (SNPs) in genes involved in synthesis and metabolism of steroid hormones and insulin-like growth factor 1, and risk of breast cancer in situ (BCIS), with the aim of determining whether any of these were disease specific. This was carried out using 1,062 BCIS cases and 10,126 controls as well as 6,113 invasive breast cancer cases from the Breast and Prostate Cancer Cohort Consortium (BPC3). Three SNPs showed at least one nominally significant association in homozygous minor versus homozygous major models. ACVR2A-rs2382112 (ORhom=3.05, 95%CI=1.72-5.44, Phom=1.47 × 10-4), MAST2-rs12124649 (ORhom=1.73, 95% CI =1.18-2.54, Phom=5.24 × 10-3), and INSR-rs10500204 (ORhom=1.96, 95% CI=1.44-2.67, Phom=1.68 × 10-5) were associated with increased risk of BCIS; however, only the latter association was significant after correcting for multiple testing. Furthermore, INSR-rs10500204 was more strongly associated with the risk of BCIS than invasive disease in case-only analyses using the homozygous minor versus homozygous major model (ORhom=1.78, 95% CI=1.30-2.44, Phom=3.23 × 10-4). The SNP INSR-rs10500204 is located in an intron of the INSR gene and is likely to affect binding of the promyelocytic leukemia (PML) protein. The PML gene is known as a tumor suppressor and growth regulator in cancer. However, it is not clear on what pathway the A-allele of rs10500204 could operate to influence the binding of the protein. Hence, functional studies are warranted to investigate this further.
  •  
7.
  • Barrdahl, Myrto, et al. (författare)
  • Association of breast cancer risk loci with breast cancer survival
  • 2015
  • Ingår i: International Journal of Cancer. - : Wiley-Blackwell. - 0020-7136 .- 1097-0215. ; 137:12, s. 2837-2845
  • Tidskriftsartikel (refereegranskat)abstract
    • The survival of breast cancer patients is largely influenced by tumor characteristics, such as TNM stage, tumor grade and hormone receptor status. However, there is growing evidence that inherited genetic variation might affect the disease prognosis and response to treatment. Several lines of evidence suggest that alleles influencing breast cancer risk might also be associated with breast cancer survival. We examined the associations between 35 breast cancer susceptibility loci and the disease over-all survival (OS) in 10,255 breast cancer patients from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) of which 1,379 died, including 754 of breast cancer. We also conducted a meta-analysis of almost 35,000 patients and 5,000 deaths, combining results from BPC3 and the Breast Cancer Association Consortium (BCAC) and performed in silico analyses of SNPs with significant associations. In BPC3, the C allele of LSP1-rs3817198 was significantly associated with improved OS (HRper-allele=0.70; 95% CI: 0.58-0.85; ptrend=2.84 x 10-4; HRheterozygotes=0.71; 95% CI: 0.55-0.92; HRhomozygotes=0.48; 95% CI: 0.31-0.76; p2DF=1.45 x 10-3). In silico, the C allele of LSP1-rs3817198 was predicted to increase expression of the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C). In the meta-analysis, TNRC9-rs3803662 was significantly associated with increased death hazard (HRMETA =1.09; 95% CI: 1.04-1.15; ptrend=6.6 x 10-4; HRheterozygotes=0.96 95% CI: 0.90-1.03; HRhomozygotes=1.21; 95% CI: 1.09-1.35; p2DF=1.25 x 10-4). In conclusion, we show that there is little overlap between the breast cancer risk single nucleotide polymorphisms (SNPs) identified so far and the SNPs associated with breast cancer prognosis, with the possible exceptions of LSP1-rs3817198 and TNRC9-rs3803662.What's new? Genetic factors are known to influence the risk of breast cancer, but inherited genetic variation may also affect disease prognosis and response to treatment. In this study, the we investigated whether single nucleotide polymorphisms (SNPs) that are known to be associated with breast cancer risk might also influence the survival of breast-cancer patients. While two of the investigated SNPs may influence survival, there was otherwise no indication that SNP alleles related to breast cancer risk also play a role in the survival of breast cancer patients.
  •  
8.
  •  
9.
  • Bien, Stephanie A., et al. (författare)
  • Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer
  • 2019
  • Ingår i: Human Genetics. - : Springer. - 0340-6717 .- 1432-1203. ; 138:4, s. 307-326
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide association studies have reported 56 independently associated colorectal cancer (CRC) risk variants, most of which are non-coding and believed to exert their effects by modulating gene expression. The computational method PrediXcan uses cis-regulatory variant predictors to impute expression and perform gene-level association tests in GWAS without directly measured transcriptomes. In this study, we used reference datasets from colon (n=169) and whole blood (n=922) transcriptomes to test CRC association with genetically determined expression levels in a genome-wide analysis of 12,186 cases and 14,718 controls. Three novel associations were discovered from colon transverse models at FDR0.2 and further evaluated in an independent replication including 32,825 cases and 39,933 controls. After adjusting for multiple comparisons, we found statistically significant associations using colon transcriptome models with TRIM4 (discovery P=2.2x10(-4), replication P=0.01), and PYGL (discovery P=2.3x10(-4), replication P=6.7x10(-4)). Interestingly, both genes encode proteins that influence redox homeostasis and are related to cellular metabolic reprogramming in tumors, implicating a novel CRC pathway linked to cell growth and proliferation. Defining CRC risk regions as one megabase up- and downstream of one of the 56 independent risk variants, we defined 44 non-overlapping CRC-risk regions. Among these risk regions, we identified genes associated with CRC (P<0.05) in 34/44 CRC-risk regions. Importantly, CRC association was found for two genes in the previously reported 2q25 locus, CXCR1 and CXCR2, which are potential cancer therapeutic targets. These findings provide strong candidate genes to prioritize for subsequent laboratory follow-up of GWAS loci. This study is the first to implement PrediXcan in a large colorectal cancer study and findings highlight the utility of integrating transcriptome data in GWAS for discovery of, and biological insight into, risk loci.
  •  
10.
  • Brenner, Darren R, et al. (författare)
  • Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia
  • 2015
  • Ingår i: Carcinogenesis. - : Oxford University Press. - 0143-3334 .- 1460-2180. ; 36:11, s. 1314-1326
  • Tidskriftsartikel (refereegranskat)abstract
    • Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10−8) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10−7) and MTMR2 at 11q21 (rs10501831, P = 3.1×10−6) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10−7) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10−4 for KCNIP4, represented by rs9799795) and AC (P = 2.16×10−4 for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range.
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-10 av 61
  • [1]234567Nästa

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy