| 1. |
- Campa, Daniele, et al.
(författare)
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Genetic variability of the forkhead box O3 and prostate cancer risk in the European Prospective Investigation on Cancer
- 2011
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Ingår i: Oncology Reports. - Athen : National Hellenic Research Foundation. - 1021-335X .- 1791-2431. ; 26:4, s. 979-986
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Tidskriftsartikel (refereegranskat)abstract
- Forkhead box O3 (FOXO3) has a wide range of functions: it promotes tumor suppression, cell cycle arrest, repair of damaged DNA, detoxification of reactive oxygen species, apoptosis and plays a pivotal role in promoting longevity. FOXO3 is a key downstream target of the PI3K-Akt pathway in response to cellular stimulation by growth factors or insulin and has been proposed as a bridge between ageing and tumor suppression. Three SNPs in the FOXO3 gene (rs3800231, rs9400239 and rs479744) that have been shown to be strongly and consistently associated with longevity, were examined in relation to PC risk in a case control study of 1571 incident PC cases and 1840 controls nested within the European Prospective Investigation into Cancer and Nutrition (EPIC). There was no statistically significant association between the SNPs and PC risk regardless of the model of inheritance (dominant, codominant and recessive). The associations were not modified by disease aggressiveness, circulating levels of steroid sex hormones, or IGFs or BMI. We conclude that polymorphisms in the FOXO3 gene that are associated with longevity are not major risk factors for PC risk, in this population of Caucasian men.
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| 2. |
- Fortner, Renee T., et al.
(författare)
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Correlates of circulating ovarian cancer early detection markers and their contribution to discrimination of early detection models : results from the EPIC cohort
- 2017
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Ingår i: Journal of Ovarian Research. - : Springer Science and Business Media LLC. - 1757-2215. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background: Ovarian cancer early detection markers CA125, CA15.3, HE4, and CA72.4 vary between healthy women, limiting their utility for screening.Methods: We evaluated cross-sectional relationships between lifestyle and reproductive factors and these markers among controls (n = 1910) from a nested case-control study in the European Prospective Investigation into Cancer and Nutrition (EPIC). Improvements in discrimination of prediction models adjusting for correlates of the markers were evaluated among postmenopausal women in the nested case-control study (n = 590 cases). Generalized linear models were used to calculate geometric means of CA125, CA15.3, and HE4. CA72.4 above vs. below limit of detection was evaluated using logistic regression. Early detection prediction was modeled using conditional logistic regression.Results: CA125 concentrations were lower, and CA15.3 higher, in post- vs. premenopausal women (p ≤ 0.02). Among postmenopausal women, CA125 was higher among women with higher parity and older age at menopause (ptrend ≤ 0.02), but lower among women reporting oophorectomy, hysterectomy, ever use of estrogen-only hormone therapy, or current smoking (p < 0.01). CA15.3 concentrations were higher among heavier women and in former smokers (p ≤ 0.03). HE4 was higher with older age at blood collection and in current smokers, and inversely associated with OC use duration, parity, and older age at menopause (≤ 0.02). No associations were observed with CA72.4. Adjusting for correlates of the markers in prediction models did not improve the discrimination.Conclusions: This study provides insights into sources of variation in ovarian cancer early detection markers in healthy women and informs about the utility of individualizing marker cutpoints based on epidemiologic factors.
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| 3. |
- Guida, Florence, et al.
(författare)
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Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins
- 2018
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Ingår i: JAMA Oncology. - : American Medical Association (AMA). - 2374-2437 .- 2374-2445. ; 4:10
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Tidskriftsartikel (refereegranskat)abstract
- Importance There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases.Objective To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria.Design, Setting, and Participants Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS).Main Outcomes and Measures Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity).Results In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity of 0.83, based on the US Preventive Services Task Force screening criteria, the sensitivity of the integrated risk prediction (biomarker) model was 0.63 compared with 0.43 for the smoking model. Conversely, at an overall sensitivity of 0.42, based on the US Preventive Services Task Force screening criteria, the integrated risk prediction model yielded a specificity of 0.95 compared with 0.86 for the smoking model.Conclusions and Relevance This study provided a proof of principle in showing that a panel of circulating protein biomarkers may improve lung cancer risk assessment and may be used to define eligibility for computed tomography screening.
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