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- Campa, Daniele, et al.
(författare)
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Genetic variation in genes of the fatty acid synthesis pathway and breast cancer risk.
- 2009
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Ingår i: Breast Cancer Research and Treatment. - : Springer Science and Business Media LLC. - 0167-6806 .- 1573-7217. ; 118:3, s. 565-574
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Tidskriftsartikel (refereegranskat)abstract
- Fatty acid synthase (FAS) is the major enzyme of lipogenesis. It catalyzes the NADPH-dependent condensation of acetyl-CoA and malonyl-CoA to produce palmitic acid. Transcription of the FAS gene is controlled synergistically by the transcription factors ChREBP (carbohydrate response element-binding protein), which is induced by glucose, and SREBP-1 (sterol response element-binding protein-1), which is stimulated by insulin through the PI3K/Akt signal transduction pathway. We investigated whether the genetic variability of the genes encoding for ChREBP, SREBP and FAS (respectively, MLXIPL, SREBF1 and FASN) is related to breast cancer risk and body-mass index (BMI) by studying 1,294 breast cancer cases and 2,452 controls from the European Prospective Investigation on Cancer (EPIC). We resequenced the FAS gene and combined information of SNPs found by resequencing and SNPs from public databases. Using a tagging approach and selecting 20 SNPs, we covered all the common genetic variation of these genes. In this study we were not able to find any statistically significant association between the SNPs in the FAS, ChREBP and SREPB-1 genes and an increased risk of breast cancer overall and by subgroups of age, menopausal status, hormone replacement therapy (HRT) use or BMI. On the other hand, we found that two SNPs in FASN were associated with BMI.
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| 2. |
- Campa, Daniele, et al.
(författare)
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The INSIG2 rs7566605 polymorphism is not associated with body mass index and breast cancer risk
- 2010
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Ingår i: BMC Cancer. - : BioMed Central. - 1471-2407 .- 1471-2407. ; 10, s. 563-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The single nucleotide polymorphism rs7566605, located in the promoter of the INSIG2 gene, has been the subject of a strong scientific effort aimed to elucidate its possible association with body mass index (BMI). The first report showing that rs7566605 could be associated with body fatness was a genome-wide association study (GWAS) which used BMI as the primary phenotype. Many follow-up studies sought to validate the association of rs7566605 with various markers of obesity, with several publications reporting inconsistent findings. BMI is considered to be one of the measures of choice to evaluate body fatness and there is evidence that body fatness is related with an increased risk of breast cancer (BC).METHODS: we tested in a large-scale association study (3,973 women, including 1,269 invasive BC cases and 2,194 controls), nested within the EPIC cohort, the involvement of rs7566605 as predictor of BMI and BC risk.RESULTS AND CONCLUSIONS: In this study we were not able to find any statistically significant association between this SNP and BMI, nor did we find any significant association between the SNP and an increased risk of breast cancer overall and by subgroups of age, or menopausal status.
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| 3. |
- Hoggart, Clive, et al.
(författare)
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A Risk Model for Lung Cancer Incidence
- 2012
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Ingår i: Cancer Prevention Research. - Philadelphia : American Association for Cancer Research. - 1940-6207 .- 1940-6215. ; 5:6, s. 834-846
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Tidskriftsartikel (refereegranskat)abstract
- Risk models for lung cancer incidence would be useful for prioritising individuals for screening and participation in clinical trials of chemoprevention. We present a risk model for lung cancer built using prospective cohort data from a general population which predicts individual incidence in a given time period.We build separate risk models for current and former smokers utilising 169,035 ever smokers from the multicentre European Prospective Investigation into Cancer and Nutrition (EPIC) and considered a model for never smokers. The data set was split into independent training and test sets. Lung cancer incidence was modelled using survival analysis, stratifying by age started smoking, and for former smokers, also smoking duration. Other risk factors considered were smoking intensity, ten occupational/environmental exposures previously implicated with lung cancer, and SNPs at two loci identified by genome-wide association studies of lung cancer. Individual risk in the test set was measured by the predicted probability of lung cancer incidence in the year preceding last follow-up time, predictive accuracy was measured by the area under the receiver operator characteristic curve (AUC).Utilising smoking information alone gave good predictive accuracy: the AUC and 95% confidence interval in ever smokers was 0.843 (0.810, 0.875), the Bach model applied to the same data gave an AUC of 0.775 (0.737, 0.813). Other risk factors had negligible effect on the AUC, including never smokers for whom prediction was poor.Our model is generalisable and straightforward to implement. Its accuracy can be attributed to its modelling of lifetime exposure to smoking.
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| 4. |
- Xun, Wei Wei, et al.
(författare)
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Single-nucleotide polymorphisms (5p15.33, 15q25.1, 6p22.1, 6q27 and 7p15.3) and lung cancer survival in the European Prospective Investigation into Cancer and Nutrition (EPIC).
- 2011
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Ingår i: Mutagenesis. - : Oxford University Press (OUP). - 0267-8357 .- 1464-3804. ; 26:5, s. 657-666
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Tidskriftsartikel (refereegranskat)abstract
- The single-nucleotide polymorphisms (SNPs) rs402710 (5p15.33), rs16969968 and rs8034191 (15q25.1) have been consistently identified by genome-wide association studies (GWAS) as significant predictors of lung cancer risk, while rs4324798 (6p22.1) was previously found to influence survival time in small-cell lung cancer (SCLC) patients. Using the same population of one of the original GWAS, we investigated whether the selected SNPs and 31 others (also identified in GWAS) influence survival time, assuming an additive model. The effect of each polymorphism on all cause survival was estimated in 1094 lung cancer patients, and lung cancer-specific survival in 763 patients, using Cox regression adjusted for a priori confounders and competing causes of death where appropriate. Overall, after 1558 person-years of post-diagnostic follow-up, 874 deaths occurred from all causes, including 690 from lung cancer. In the lung cancer-specific survival analysis (1102 person-years), only rs7452888 (6q27) and rs2710994 (7p15.3) modified survival, with adjusted hazard ratios of 1.19 (P = 0.009) and 1.32 (P = 0.011) respectively, taking competing risks into account. Some weak associations were identified in subgroup analysis for rs16969968 and rs8034191 (15q25.1) and rs4324798 (6p22.1) and survival in never-smokers, as well as for rs402710 in current smokers and SCLC patients. In conclusion, rs402710 (5p15.33), rs16969968 and rs8034191 (both 15q25.1) and rs4324798 (6p22.1) were found to be unrelated to survival times in this large cohort of lung cancer patients, regardless of whether the cause of death was from lung cancer or not. However, rs7452888 (6q27) was identified as a possible candidate SNP to influence lung cancer survival, while stratified analysis hinted at a possible role for rs8034191, rs16969968 (15q25.1) and rs4324798 (6p22.1) in influencing survival time in lung cancer patients who were never-smokers, based on a small sample.
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