| 1. |
- Alcala, Karine, et al.
(författare)
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The relationship between blood pressure and risk of renal cell carcinoma
- 2022
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Ingår i: International Journal of Epidemiology. - : Oxford University Press (OUP). - 1464-3685 .- 0300-5771. ; 51:4, s. 1317-1327
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The relation between blood pressure and kidney cancer risk is well established but complex and different study designs have reported discrepant findings on the relative importance of diastolic blood pressure (DBP) and systolic blood pressure (SBP). In this study, we sought to describe the temporal relation between diastolic and SBP with renal cell carcinoma (RCC) risk in detail.METHODS: Our study involved two prospective cohorts: the European Prospective Investigation into Cancer and Nutrition study and UK Biobank, including >700 000 participants and 1692 incident RCC cases. Risk analyses were conducted using flexible parametric survival models for DBP and SBP both separately as well as with mutuality adjustment and then adjustment for extended risk factors. We also carried out univariable and multivariable Mendelian randomization (MR) analyses (DBP: ninstruments = 251, SBP: ninstruments = 213) to complement the analyses of measured DBP and SBP.RESULTS: In the univariable analysis, we observed clear positive associations with RCC risk for both diastolic and SBP when measured ≥5 years before diagnosis and suggestive evidence for a stronger risk association in the year leading up to diagnosis. In mutually adjusted analysis, the long-term risk association of DBP remained, with a hazard ratio (HR) per standard deviation increment 10 years before diagnosis (HR10y) of 1.20 (95% CI: 1.10-1.30), whereas the association of SBP was attenuated (HR10y: 1.00, 95% CI: 0.91-1.10). In the complementary multivariable MR analysis, we observed an odds ratio for a 1-SD increment (ORsd) of 1.34 (95% CI: 1.08-1.67) for genetically predicted DBP and 0.70 (95% CI: 0.56-0.88) for genetically predicted SBP.CONCLUSION: The results of this observational and MR study are consistent with an important role of DBP in RCC aetiology. The relation between SBP and RCC risk was less clear but does not appear to be independent of DBP.
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| 2. |
- Feng, Xiaoshuang, et al.
(författare)
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Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis
- 2023
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 92
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Tidskriftsartikel (refereegranskat)abstract
- Background: To evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis.Methods: We measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only.Findings: There were 86 proteins nominally associated with mortality (p < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10–1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61–0.66), compared with 0.62 (95% CI: 0.59–0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: −0.003 to 0.035).Interpretation: Blood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information.
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| 3. |
- Feng, Xiaoshuang, et al.
(författare)
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Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools
- 2023
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 115:9, s. 1050-1059
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: We sought to develop a proteomics-based risk model for lung cancer and evaluate its risk-discriminatory performance in comparison with a smoking-based risk model (PLCOm2012) and a commercially available autoantibody biomarker test.METHODS: We designed a case-control study nested in 6 prospective cohorts, including 624 lung cancer participants who donated blood samples at most 3 years prior to lung cancer diagnosis and 624 smoking-matched cancer free participants who were assayed for 302 proteins. We used 470 case-control pairs from 4 cohorts to select proteins and train a protein-based risk model. We subsequently used 154 case-control pairs from 2 cohorts to compare the risk-discriminatory performance of the protein-based model with that of the Early Cancer Detection Test (EarlyCDT)-Lung and the PLCOm2012 model using receiver operating characteristics analysis and by estimating models' sensitivity. All tests were 2-sided.RESULTS: The area under the curve for the protein-based risk model in the validation sample was 0.75 (95% confidence interval [CI] = 0.70 to 0.81) compared with 0.64 (95% CI = 0.57 to 0.70) for the PLCOm2012 model (Pdifference = .001). The EarlyCDT-Lung had a sensitivity of 14% (95% CI = 8.2% to 19%) and a specificity of 86% (95% CI = 81% to 92%) for incident lung cancer. At the same specificity of 86%, the sensitivity for the protein-based risk model was estimated at 49% (95% CI = 41% to 57%) and 30% (95% CI = 23% to 37%) for the PLCOm2012 model.CONCLUSION: Circulating proteins showed promise in predicting incident lung cancer and outperformed a standard risk prediction model and the commercialized EarlyCDT-Lung.
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| 4. |
- Guida, Florence, et al.
(författare)
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The blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium
- 2021
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Ingår i: PLoS Medicine. - : Public Library of Science (PLOS). - 1549-1277 .- 1549-1676. ; 18:9
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Tidskriftsartikel (refereegranskat)abstract
- Background: Excess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI).Methods and findings: We assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case–control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10−8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10−5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some—but not all—metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., −0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10−5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10−3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds.Conclusions: This study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI - the principal modifiable risk factor of kidney cancer.
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| 5. |
- Huang, Joyce Y., et al.
(författare)
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Circulating markers of cellular immune activation in prediagnostic blood sample and lung cancer risk in the Lung Cancer Cohort Consortium (LC3)
- 2020
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Ingår i: International Journal of Cancer. - : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 146:9, s. 2394-2405
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Tidskriftsartikel (refereegranskat)abstract
- Cell-mediated immune suppression may play an important role in lung carcinogenesis. We investigated the associations for circulating levels of tryptophan, kynurenine, kynurenine:tryptophan ratio (KTR), quinolinic acid (QA) and neopterin as markers of immune regulation and inflammation with lung cancer risk in 5,364 smoking-matched case-control pairs from 20 prospective cohorts included in the international Lung Cancer Cohort Consortium. All biomarkers were quantified by mass spectrometry-based methods in serum/plasma samples collected on average 6 years before lung cancer diagnosis. Odds ratios (ORs) and 95% confidence intervals (CIs) for lung cancer associated with individual biomarkers were calculated using conditional logistic regression with adjustment for circulating cotinine. Compared to the lowest quintile, the highest quintiles of kynurenine, KTR, QA and neopterin were associated with a 20-30% higher risk, and tryptophan with a 15% lower risk of lung cancer (all p(trend) < 0.05). The strongest associations were seen for current smokers, where the adjusted ORs (95% CIs) of lung cancer for the highest quintile of KTR, QA and neopterin were 1.42 (1.15-1.75), 1.42 (1.14-1.76) and 1.45 (1.13-1.86), respectively. A stronger association was also seen for KTR and QA with risk of lung squamous cell carcinoma followed by adenocarcinoma, and for lung cancer diagnosed within the first 2 years after blood draw. This study demonstrated that components of the tryptophan-kynurenine pathway with immunomodulatory effects are associated with risk of lung cancer overall, especially for current smokers. Further research is needed to evaluate the role of these biomarkers in lung carcinogenesis and progression.
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| 6. |
- Robbins, Hilary A., et al.
(författare)
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Design and methodological considerations for biomarker discovery and validation in the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Program
- 2023
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Ingår i: Annals of Epidemiology. - : Elsevier. - 1047-2797 .- 1873-2585. ; 77, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize low-dose CT (LDCT) lung cancer screening. Here, we describe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1161 proteins in a nested-case control study within 2 prospective cohorts (n = 252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n = 479 cases and 479 controls). Eligible participants had a current or former history of smoking and cases were diagnosed up to 3 years following blood draw. The Nodule Malignancy project measured 1078 proteins among participants with a heavy smoking history within four LDCT screening studies (n = 425 cases diagnosed up to 5 years following blood draw, 430 benign-nodule controls, and 398 nodule-free controls). The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its performance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n = 1696 cases and 2926 subcohort representatives), and in the Nodule Malignancy project within five LDCT screening studies (n = 675 cases, 680 benign-nodule controls, and 648 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies.
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