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3. Design and methodological considerations for biomarker discovery and validation in the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Program

Author

Robbins, Hilary A., Alcala, Karine, Moez, Elham Khodayari, Guida, Florence, Thomas, Sera, Zahed, Hana, Warkentin, Matthew T., Smith-Byrne, Karl, Brhane, Yonathan, Muller, David, Feng, Xiaoshuang, Albanes, Demetrius, Aldrich, Melinda C., Arslan, Alan A., Bassett, Julie, Berg, Christine D., Cai, Qiuyin, Chen, Chu, Davies, Michael P.A., Diergaarde, Brenda, Field, John K., Freedman, Neal D., Huang, Wen-Yi, Johansson, Mikael, Jones, Michael, Koh, Woon-Puay, Lam, Stephen, Lan, Qing, Langhammer, Arnulf, Liao, Linda M., Liu, Geoffrey, Malekzadeh, Reza, Milne, Roger L., Montuenga, Luis M., Rohan, Thomas, Sesso, Howard D., Severi, Gianluca, Sheikh, Mahdi, Sinha, Rashmi, Shu, Xiao-Ou, Stevens, Victoria L., Tammemägi, Martin C., Tinker, Lesley F., Visvanathan, Kala, Wang, Ying, Wang, Renwei, Weinstein, Stephanie J., White, Emily, Wilson, David, Yuan, Jian-Min, Zhang, Xuehong, Zheng, Wei, Amos, Christopher I., Brennan, Paul, Johansson, Mattias, and Hung, Rayjean J.

Published
2023
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4. Epigenetic mechanisms of lung carcinogenesis involve differentially methylated CpG sites beyond those associated with smoking

Author

Petrovic, Dusan, Bodinier, Barbara, Dagnino, Sonia, Whitaker, Matthew, Karimi, Maryam, Campanella, Gianluca, Haugdahl Nøst, Therese, Polidoro, Silvia, Palli, Domenico, Krogh, Vittorio, Tumino, Rosario, Sacerdote, Carlotta, Panico, Salvatore, Lund, Eiliv, Dugué, Pierre-Antoine, Giles, Graham G., Severi, Gianluca, Southey, Melissa, Vineis, Paolo, Stringhini, Silvia, Bochud, Murielle, Sandanger, Torkjel M., Vermeulen, Roel C. H., Guida, Florence, and Chadeau-Hyam, Marc

Published
2022
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5. Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer

Author

Wade, Kaitlin H., Yarmolinsky, James, Giovannucci, Edward, Lewis, Sarah J., Millwood, Iona Y., Munafò, Marcus R., Meddens, Fleur, Burrows, Kimberley, Bell, Joshua A., Davies, Neil M., Mariosa, Daniela, Kanerva, Noora, Vincent, Emma E., Smith-Byrne, Karl, Guida, Florence, Gunter, Marc J., Sanderson, Eleanor, Dudbridge, Frank, Burgess, Stephen, Cornelis, Marilyn C., Richardson, Tom G., Borges, Maria Carolina, Bowden, Jack, Hemani, Gibran, Cho, Yoonsu, Spiller, Wes, Richmond, Rebecca C., Carter, Alice R., Langdon, Ryan, Lawlor, Deborah A., Walters, Robin G., Vimaleswaran, Karani Santhanakrishnan, Anderson, Annie, Sandu, Meda R., Tilling, Kate, Davey Smith, George, Martin, Richard M., and Relton, Caroline L.

Published
2022
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8. Blood-based DNA methylation markers for lung cancer prediction

Author

Onwuka, Justina Ucheojor, Guida, Florence, Langdon, Ryan, Johansson, Mikael, Severi, Gianluca, Milne, Roger L., Dugué, Pierre-Antoine, Southey, Melissa C., Vineis, Paolo, Sandanger, Torkjel, Nøst, Therese Haugdahl, Chadeau-Hyam, Marc, Relton, Caroline, Robbins, Hilary A., Suderman, Matthew, Johansson, Mattias, Onwuka, Justina Ucheojor, Guida, Florence, Langdon, Ryan, Johansson, Mikael, Severi, Gianluca, Milne, Roger L., Dugué, Pierre-Antoine, Southey, Melissa C., Vineis, Paolo, Sandanger, Torkjel, Nøst, Therese Haugdahl, Chadeau-Hyam, Marc, Relton, Caroline, Robbins, Hilary A., Suderman, Matthew, and Johansson, Mattias

Abstract

Objective: Screening high-risk individuals with low-dose CT reduces mortality from lung cancer, but many lung cancers occur in individuals who are not eligible for screening. Risk biomarkers may be useful to refine risk models and improve screening eligibility criteria. We evaluated if blood-based DNA methylation markers can improve a traditional lung cancer prediction model. Methods and analysis: This study used four prospective cohorts with blood samples collected prior to lung cancer diagnosis. The study was restricted to participants with a history of smoking, and one control was individually matched to each lung cancer case using incidence density sampling by cohort, sex, date of blood collection, age and smoking status. To train a DNA methylation-based risk score, we used participants from Melbourne Collaborative Cohort Study-Australia (n=648) and Northern Sweden Health and Disease Study-Sweden (n=380) based on five selected CpG sites. The risk discriminative performance of the methylation score was subsequently validated in participants from European Investigation into Cancer and Nutrition-Italy (n=267) and Norwegian Women and Cancer-Norway (n=185) and compared with that of the questionnaire-based PLCOm2012 lung cancer risk model. Results: The area under the receiver operating characteristic curve (AUC) for the PLCOm2012 model in the validation studies was 0.70 (95% CI: 0.65 to 0.75) compared with 0.73 (95% CI: 0.68 to 0.77) for the methylation score model (P difference =0.07). Incorporating the methylation score with the PLCOm2012 model did not improve the risk discrimination (AUC: 0.73, 95% CI: 0.68 to 0.77, P difference =0.73). Conclusions: This study suggests that the methylation-based risk prediction score alone provides similar lung cancer risk-discriminatory performance as the questionnaire-based PLCOm2012 risk model.

Published
2024
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9. Evaluation of risk prediction models to select lung cancer screening participants in Europe: a prospective cohort consortium analysis

Author

Planetary Health & Exposoom, Cancer, Circulatory Health, Feng, Xiaoshuang, Goodley, Patrick, Alcala, Karine, Guida, Florence, Kaaks, Rudolf, Vermeulen, Roel, Downward, George S, Bonet, Catalina, Colorado-Yohar, Sandra M, Albanes, Demetrius, Weinstein, Stephanie J, Goldberg, Marcel, Zins, Marie, Relton, Caroline, Langhammer, Arnulf, Skogholt, Anne Heidi, Johansson, Mattias, Robbins, Hilary A, Planetary Health & Exposoom, Cancer, Circulatory Health, Feng, Xiaoshuang, Goodley, Patrick, Alcala, Karine, Guida, Florence, Kaaks, Rudolf, Vermeulen, Roel, Downward, George S, Bonet, Catalina, Colorado-Yohar, Sandra M, Albanes, Demetrius, Weinstein, Stephanie J, Goldberg, Marcel, Zins, Marie, Relton, Caroline, Langhammer, Arnulf, Skogholt, Anne Heidi, Johansson, Mattias, and Robbins, Hilary A

Published
2024

10. Evaluation of risk prediction models to select lung cancer screening participants in Europe: a prospective cohort consortium analysis

Author

Feng, Xiaoshuang, Goodley, Patrick, Alcala, Karine, Guida, Florence, Kaaks, Rudolf, Vermeulen, Roel, Downward, George S, Bonet, Catalina, Colorado-Yohar, Sandra M, Albanes, Demetrius, Weinstein, Stephanie J, Goldberg, Marcel, Zins, Marie, Relton, Caroline, Langhammer, Arnulf, Skogholt, Anne Heidi, Johansson, Mattias, Robbins, Hilary A, Feng, Xiaoshuang, Goodley, Patrick, Alcala, Karine, Guida, Florence, Kaaks, Rudolf, Vermeulen, Roel, Downward, George S, Bonet, Catalina, Colorado-Yohar, Sandra M, Albanes, Demetrius, Weinstein, Stephanie J, Goldberg, Marcel, Zins, Marie, Relton, Caroline, Langhammer, Arnulf, Skogholt, Anne Heidi, Johansson, Mattias, and Robbins, Hilary A

Abstract

BACKGROUND: Lung cancer risk prediction models might efficiently identify individuals who should be offered lung cancer screening. However, their performance has not been comprehensively evaluated in Europe. We aimed to externally validate and evaluate the performance of several risk prediction models that predict lung cancer incidence or mortality in prospective European cohorts.METHODS: We analysed 240 137 participants aged 45-80 years with a current or former smoking history from nine European countries in four prospective cohorts from the pooled database of the Lung Cancer Cohort Consortium: the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (Finland), the Nord-Trøndelag Health Study (Norway), CONSTANCES (France), and the European Prospective Investigation into Cancer and Nutrition (Denmark, Germany, Italy, Spain, Sweden, the Netherlands, and Norway). We evaluated ten lung cancer risk models, which comprised the Bach, the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 model (PLCO m2012), the Lung Cancer Risk Assessment Tool (LCRAT), the Lung Cancer Death Risk Assessment Tool (LCDRAT), the Nord-Trøndelag Health Study (HUNT), the Optimized Early Warning Model for Lung Cancer Risk (OWL), the University College London-Death (UCLD), the University College London-Incidence (UCLI), the Liverpool Lung Project version 2 (LLP version 2), and the Liverpool Lung Project version 3 (LLP version 3) models. We quantified model calibration as the ratio of expected to observed cases or deaths and discrimination using the area under the receiver operating characteristic curve (AUC). For each model, we also identified risk thresholds that would screen the same number of individuals as each of the US Preventive Services Task Force 2021 (USPSTF-2021), the US Preventive Services Task Force 2013 (USPSTF-2013), and the Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON) criteria. FINDINGS: Among the participants, 1734 lung cancer ca

Published
2024

12. Epidemiology of 40 blood biomarkers of one-carbon metabolism, vitamin status, inflammation, and renal and endothelial function among cancer-free older adults

Author

Zahed, Hana, Johansson, Mattias, Ueland, Per M., Midttun, Øivind, Milne, Roger L., Giles, Graham G., Manjer, Jonas, Sandsveden, Malte, Langhammer, Arnulf, Sørgjerd, Elin Pettersen, Grankvist, Kjell, Johansson, Mikael, Freedman, Neal D., Huang, Wen-Yi, Chen, Chu, Prentice, Ross, Stevens, Victoria L., Wang, Ying, Le Marchand, Loic, Wilkens, Lynne R., Weinstein, Stephanie J., Albanes, Demetrius, Cai, Qiuyin, Blot, William J., Arslan, Alan A., Zeleniuch-Jacquotte, Anne, Shu, Xiao-Ou, Zheng, Wei, Yuan, Jian-Min, Koh, Woon-Puay, Visvanathan, Kala, Sesso, Howard D., Zhang, Xuehong, Gaziano, J. Michael, Fanidi, Anouar, Muller, David, Brennan, Paul, Guida, Florence, and Robbins, Hilary A.

Published
2021
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14. Exposure–Response Analyses of Asbestos and Lung Cancer Subtypes in a Pooled Analysis of Case–Control Studies

Author

Olsson, Ann C., Vermeulen, Roel, Schüz, Joachim, Kromhout, Hans, Pesch, Beate, Peters, Susan, Behrens, Thomas, Portengen, Lützen, Mirabelli, Dario, Gustavsson, Per, Kendzia, Benjamin, Almansa, Josue, Luzon, Veronique, Vlaanderen, Jelle, Stücker, Isabelle, Guida, Florence, Consonni, Dario, Caporaso, Neil, Landi, Maria Teresa, Field, John, Brüske, Irene, Wichmann, Heinz-Erich, Siemiatycki, Jack, Parent, Marie-Elise, Richiardi, Lorenzo, Merletti, Franco, Jöckel, Karl-Heinz, Ahrens, Wolfgang, Pohlabeln, Hermann, Plato, Nils, Tardón, Adonina, Zaridze, David, McLaughlin, John, Demers, Paul, Szeszenia-Dabrowska, Neonila, Lissowska, Jolanta, Rudnai, Peter, Fabianova, Eleonora, Dumitru, Rodica Stanescu, Bencko, Vladimir, Foretova, Lenka, Janout, Vladimir, Boffetta, Paolo, Bueno-de-Mesquita, Bas, Forastiere, Francesco, Brüning, Thomas, and Straif, Kurt

Published
2017

15. Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1·7 million men and women

Author

Alenius, Harri, Avendano, Mauricio, Barros, Henrique, Bochud, Murielle, Carmeli, Cristian, Carra, Luca, Castagné, Raphaele, Chadeau-Hyam, Marc, Clavel-Chapelon, Françoise, Costa, Giuseppe, Courtin, Emilie, Delpierre, Cyrille, D'Errico, Angelo, Dugué, Pierre-Antoine, Elliott, Paul, Fraga, Silvia, Gares, Valérie, Giles, Graham, Goldberg, Marcel, Greco, Dario, Hodge, Allison, Irving, Michelle Kelly, Karisola, Piia, Kivimäki, Mika, Krogh, Vittorio, Lang, Thierry, Layte, Richard, Lepage, Benoit, Mackenbach, Johan, Marmot, Michael, McCrory, Cathal, Milne, Roger, Muennig, Peter, Nusselder, Wilma, Panico, Salvatore, Petrovic, Dusan, Polidoro, Silvia, Preisig, Martin, Raitakari, Olli, Ribeiro, Ana Isabel, Ricceri, Fulvio, Robinson, Oliver, Valverde, Jose Rubio, Sacerdote, Carlotta, Satolli, Roberto, Severi, Gianluca, Shipley, Martin J, Stringhini, Silvia, Tumino, Rosario, Vineis, Paolo, Vollenweider, Peter, Zins, Marie, Jokela, Markus, Avendaño, Mauricio, Guida, Florence, d'Errico, Angelo, Giles, Graham G, Kelly-Irving, Michelle, Lasserre, Aurélie M, Marmot, Michael G, Kawachi, Ichiro, Steptoe, Andrew, and Mackenbach, Johan P

Published
2017
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16. The blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium

Author

Guida, Florence, Tan, Vanessa Y., Corbin, Laura J., Smith-Byrne, Karl, Alcala, Karine, Langenberg, Claudia, Stewart, Isobel D., Butterworth, Adam S., Surendran, Praveen, Achaintre, David, Adamski, Jerzy, Amiano Exezarreta, Pilar, Bergmann, Manuela M., Bull, Caroline J., Dahm, Christina C., Gicquiau, Audrey, Giles, Graham G., Gunter, Marc J., Haller, Toomas, Langhammer, Arnulf, Larose, Tricia L., Ljungberg, Börje, Metspalu, Andres, Milne, Roger L., Muller, David C., Nøst, Therese H., Pettersen Sørgjerd, Elin, Prehn, Cornelia, Riboli, Elio, Rinaldi, Sabina, Rothwell, Joseph A., Scalbert, Augustin, Schmidt, Julie A., Severi, Gianluca, Sieri, Sabina, Vermeulen, Roel, Vincent, Emma E., Waldenberger, Melanie, Timpson, Nicholas J., and Johansson, Mattias

Subjects
Kidney cancer -- Risk factors -- Development and progression -- Physiological aspects, Metabolites -- Health aspects -- Measurement, Body mass index, Biological sciences
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 x 10.sup.-8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 x 10.sup.-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 [ß.sub.BMI ] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 x 10.sup.-5). BMI was also associated with increased levels of glutamate (ß.sub.BMI : 0.12, p = 1.5 x 10.sup.-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., Author(s): Florence Guida 1, Vanessa Y. Tan 2,3, Laura J. Corbin 2,3, Karl Smith-Byrne 1, Karine Alcala 1, Claudia Langenberg 4, Isobel D. Stewart 4, Adam S. Butterworth 5,6,7,8, Praveen [...]

Published
2021
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17. Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools

Author

Feng, Xiaoshuang, primary, Wu, Wendy Yi-Ying, additional, Onwuka, Justina Ucheojor, additional, Haider, Zahra, additional, Alcala, Karine, additional, Smith-Byrne, Karl, additional, Zahed, Hana, additional, Guida, Florence, additional, Wang, Renwei, additional, Bassett, Julie K, additional, Stevens, Victoria, additional, Wang, Ying, additional, Weinstein, Stephanie, additional, Freedman, Neal D, additional, Chen, Chu, additional, Tinker, Lesley, additional, Nøst, Therese Haugdahl, additional, Koh, Woon-Puay, additional, Muller, David, additional, Colorado-Yohar, Sandra M, additional, Tumino, Rosario, additional, Hung, Rayjean J, additional, Amos, Christopher I, additional, Lin, Xihong, additional, Zhang, Xuehong, additional, Arslan, Alan A, additional, Sánchez, Maria-Jose, additional, Sørgjerd, Elin Pettersen, additional, Severi, Gianluca, additional, Hveem, Kristian, additional, Brennan, Paul, additional, Langhammer, Arnulf, additional, Milne, Roger L, additional, Yuan, Jian-Min, additional, Melin, Beatrice, additional, Johansson, Mikael, additional, Robbins, Hilary A, additional, and Johansson, Mattias, additional

Published
2023
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18. Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis

Author

Feng, Xiaoshuang, primary, Muller, David C., additional, Zahed, Hana, additional, Alcala, Karine, additional, Guida, Florence, additional, Smith-Byrne, Karl, additional, Yuan, Jian-Min, additional, Koh, Woon-Puay, additional, Wang, Renwei, additional, Milne, Roger L., additional, Bassett, Julie K., additional, Langhammer, Arnulf, additional, Hveem, Kristian, additional, Stevens, Victoria L., additional, Wang, Ying, additional, Johansson, Mikael, additional, Tjønneland, Anne, additional, Tumino, Rosario, additional, Sheikh, Mahdi, additional, Johansson, Mattias, additional, and Robbins, Hilary A., additional

Published
2023
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19. Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools

Author

Feng, Xiaoshuang, Wu, Wendy Yi-Ying, Onwuka, Justina Ucheojor, Haider, Zahra, Alcala, Karine, Smith-Byrne, Karl, Zahed, Hana, Guida, Florence, Wang, Renwei, Bassett, Julie K., Stevens, Victoria, Wang, Ying, Weinstein, Stephanie, Freedman, Neal D., Chen, Chu, Tinker, Lesley, Nøst, Therese Haugdahl, Koh, Woon-Puay, Muller, David, Colorado-Yohar, Sandra M., Tumino, Rosario, Hung, Rayjean J., Amos, Christopher I., Lin, Xihong, Zhang, Xuehong, Arslan, Alan A., Sánchez, Maria-Jose, Sørgjerd, Elin Pettersen, Severi, Gianluca, Hveem, Kristian, Brennan, Paul, Langhammer, Arnulf, Milne, Roger L., Yuan, Jian-Min, Melin, Beatrice S., Johansson, Mikael, Robbins, Hilary A., Johansson, Mattias, Feng, Xiaoshuang, Wu, Wendy Yi-Ying, Onwuka, Justina Ucheojor, Haider, Zahra, Alcala, Karine, Smith-Byrne, Karl, Zahed, Hana, Guida, Florence, Wang, Renwei, Bassett, Julie K., Stevens, Victoria, Wang, Ying, Weinstein, Stephanie, Freedman, Neal D., Chen, Chu, Tinker, Lesley, Nøst, Therese Haugdahl, Koh, Woon-Puay, Muller, David, Colorado-Yohar, Sandra M., Tumino, Rosario, Hung, Rayjean J., Amos, Christopher I., Lin, Xihong, Zhang, Xuehong, Arslan, Alan A., Sánchez, Maria-Jose, Sørgjerd, Elin Pettersen, Severi, Gianluca, Hveem, Kristian, Brennan, Paul, Langhammer, Arnulf, Milne, Roger L., Yuan, Jian-Min, Melin, Beatrice S., Johansson, Mikael, Robbins, Hilary A., and Johansson, Mattias

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.

Published
2023
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20. Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis

Author

Feng, Xiaoshuang, Muller, David C., Zahed, Hana, Alcala, Karine, Guida, Florence, Smith-Byrne, Karl, Yuan, Jian-Min, Koh, Woon-Puay, Wang, Renwei, Milne, Roger L., Bassett, Julie K., Langhammer, Arnulf, Hveem, Kristian, Stevens, Victoria L., Wang, Ying, Johansson, Mikael, Tjønneland, Anne, Tumino, Rosario, Sheikh, Mahdi, Johansson, Mattias, Robbins, Hilary A., Feng, Xiaoshuang, Muller, David C., Zahed, Hana, Alcala, Karine, Guida, Florence, Smith-Byrne, Karl, Yuan, Jian-Min, Koh, Woon-Puay, Wang, Renwei, Milne, Roger L., Bassett, Julie K., Langhammer, Arnulf, Hveem, Kristian, Stevens, Victoria L., Wang, Ying, Johansson, Mikael, Tjønneland, Anne, Tumino, Rosario, Sheikh, Mahdi, Johansson, Mattias, and Robbins, Hilary A.

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.

Published
2023
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21. Lung Cancer Among Firefighters : Smoking-Adjusted Risk Estimates in a Pooled Analysis of Case-Control Studies

Author

Bigert, Carolina, Gustavsson, Per, Straif, Kurt, Taeger, Dirk, Pesch, Beate, Kendzia, Benjamin, Schüz, Joachim, Stücker, Isabelle, Guida, Florence, Brüske, Irene, Wichmann, Heinz-Erich, Pesatori, Angela C., Landi, Maria Teresa, Caporaso, Neil, Tse, Lap Ah, Yu, Ignatius Tak-sun, Siemiatycki, Jack, Lavoué, Jérôme, Richiardi, Lorenzo, Mirabelli, Dario, Simonato, Lorenzo, Jöckel, Karl-Heinz, Ahrens, Wolfgang, Pohlabeln, Hermann, Tardón, Adonina, Zaridze, David, Field, John K., Mannetje, Andrea ’t, Pearce, Neil, McLaughlin, John, Demers, Paul, Szeszenia-Dabrowska, Neonila, Lissowska, Jolanta, Rudnai, Peter, Fabianova, Eleonora, Dumitru, Rodica Stanescu, Bencko, Vladimir, Foretova, Lenka, Janout, Vladimir, Boffetta, Paolo, Peters, Susan, Vermeulen, Roel, Kromhout, Hans, Brüning, Thomas, and Olsson, Ann C.

Published
2016

24. Welding, a risk factor of lung cancer: the ICARE study

Author

Matrat, Mireille, Guida, Florence, Mattei, Francesca, Cénée, Sylvie, Cyr, Diane, Févotte, Joëlle, Sanchez, Marie, Menvielle, Gwenn, Radoï, Loredana, Schmaus, Annie, Woronoff, Anne-Sophie, Luce, Danièle, and Stücker, Isabelle

Published
2016

26. Data from Prospective Identification of Elevated Circulating CDCP1 in Patients Years before Onset of Lung Cancer

Author

Dagnino, Sonia, primary, Bodinier, Barbara, primary, Guida, Florence, primary, Smith-Byrne, Karl, primary, Petrovic, Dusan, primary, Whitaker, Matthew D., primary, Haugdahl Nøst, Therese, primary, Agnoli, Claudia, primary, Palli, Domenico, primary, Sacerdote, Carlotta, primary, Panico, Salvatore, primary, Tumino, Rosario, primary, Schulze, Matthias B., primary, Johansson, Mikael, primary, Keski-Rahkonen, Pekka, primary, Scalbert, Augustin, primary, Vineis, Paolo, primary, Johansson, Mattias, primary, Sandanger, Torkjel M., primary, Vermeulen, Roel C.H., primary, and Chadeau-Hyam, Marc, primary

Published
2023
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27. Supplementary Data from Prospective Identification of Elevated Circulating CDCP1 in Patients Years before Onset of Lung Cancer

Author

Dagnino, Sonia, primary, Bodinier, Barbara, primary, Guida, Florence, primary, Smith-Byrne, Karl, primary, Petrovic, Dusan, primary, Whitaker, Matthew D., primary, Haugdahl Nøst, Therese, primary, Agnoli, Claudia, primary, Palli, Domenico, primary, Sacerdote, Carlotta, primary, Panico, Salvatore, primary, Tumino, Rosario, primary, Schulze, Matthias B., primary, Johansson, Mikael, primary, Keski-Rahkonen, Pekka, primary, Scalbert, Augustin, primary, Vineis, Paolo, primary, Johansson, Mattias, primary, Sandanger, Torkjel M., primary, Vermeulen, Roel C.H., primary, and Chadeau-Hyam, Marc, primary

Published
2023
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28. Lung cancer among coal miners, ore miners and quarrymen: smoking-adjusted risk estimates from the synergy pooled analysis of case–control studies

Author

Taeger, Dirk, Pesch, Beate, Kendzia, Benjamin, Behrens, Thomas, Jöckel, Karl-Heinz, Dahmann, Dirk, Siemiatycki, Jack, Kromhout, Hans, Vermeulen, Roel, Peters, Susan, Olsson, Ann, Brüske, Irene, Wichmann, Heinz-Erich, Stücker, Isabelle, Guida, Florence, Tardón, Adonina, Merletti, Franco, Mirabelli, Dario, Richiardi, Lorenzo, Pohlabeln, Hermann, Ahrens, Wolfgang, Landi, Maria Teresa, Caporaso, Neil, Pesatori, Angela Cecilia, Mukeriya, Anush, Szeszenia-Dabrowska, Neonila, Lissowska, Jolanta, Gustavsson, Per, Field, John, Marcus, Michael W, Fabianova, Eleonora, 't Mannetje, Andrea, Pearce, Neil, Rudnai, Peter, Bencko, Vladimir, Janout, Vladimir, Dumitru, Rodica Stanescu, Foretova, Lenka, Forastiere, Francesco, McLaughlin, John, Demers, Paul, Bueno-de-Mesquita, Bas, Schüz, Joachim, Straif, Kurt, and Brüning, Thomas

Published
2015

29. Lung Cancer Risk Among Cooks When Accounting for Tobacco Smoking : A Pooled Analysis of Case–Control Studies From Europe, Canada, New Zealand, and China

Author

Bigert, Carolina, Gustavsson, Per, Straif, Kurt, Pesch, Beate, Brüning, Thomas, Kendzia, Benjamin, Schüz, Joachim, Stücker, Isabelle, Guida, Florence, Brüske, Irene, Wichmann, Heinz-Erich, Pesatori, Angela C., Landi, Maria Teresa, Caporaso, Neil, Tse, Lap Ah, Yu, Ignatius Tak-sun, Siemiatycki, Jack, Pintos, Javier, Merletti, Franco, Mirabelli, Dario, Simonato, Lorenzo, Jöckel, Karl-Heinz, Ahrens, Wolfgang, Pohlabeln, Hermann, Tardón, Adonina, Zaridze, David, Field, John, ‘t Mannetje, Andrea, Pearce, Neil, McLaughlin, John, Demers, Paul, Szeszenia-Dabrowska, Neonila, Lissowska, Jolanta, Rudnai, Peter, Fabianova, Eleonora, Dumitru, Rodica Stanescu, Bencko, Vladimir, Foretova, Lenka, Janout, Vladimir, Boffetta, Paolo, Forastiere, Francesco, Bueno-de-Mesquita, Bas, Peters, Susan, Vermeulen, Roel, Kromhout, Hans, and Olsson, Ann C.

Published
2015

30. Coffee consumption and risk of lung cancer: the ICARE study

Author

Sanikini, Harinakshi, Radoï, Loredana, Menvielle, Gwenn, Guida, Florence, Mattei, Francesca, Cénée, Sylvie, Cyr, Diane, Sanchez, Marie, Velten, Michel, Carton, Matthieu, Schmaus, Annie, Luce, Danièle, and Stücker, Isabelle

Published
2015

34. Quantifying the mediating effects of smoking and occupational exposures in the relation between education and lung cancer: the ICARE study

Author

Menvielle, Gwenn, Franck, Jeanna-eve, Radoï, Loredana, Sanchez, Marie, Févotte, Joëlle, Guizard, Anne-Valérie, Stücker, Isabelle, Luce, Danièle, Woronoff, Anne-Sophie, Guizard, Anne-Valérie, Schmaus, Annie, Buemi, Antoine, Danzon, Arlette, Lapotre-Ledoux, Benedicte, Tretarre, Brigitte, Pilorget, Corinne, Luce, Danièle, Cyr, Diane, Marrer, Émilie, Lamkarkach, Farida, Guida, Florence, Molinie, Florence, Menvielle, Gwenn, Stücker, Isabelle, Févotte, Joëlle, Radoï, Loredana, Colonna, Marc, Sanchez, Marie, Carton, Matthieu, Velten, Michel, Raverdy, Nicole, Gaye, Oumar, Bercelli, Paolo, Delafosse, Patricia, Bara, Simona, Cénée, Sylvie, and ICARE study group

Published
2016
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35. Circulating Isovalerylcarnitine and Lung Cancer Risk: Evidence from Mendelian Randomization and Prediagnostic Blood Measurements

Author

Smith-Byrne, Karl, primary, Cerani, Agustin, additional, Guida, Florence, additional, Zhou, Sirui, additional, Agudo, Antonio, additional, Aleksandrova, Krasimira, additional, Barricarte, Aurelio, additional, Barranco, Miguel Rodríguez, additional, Bochers, Christoph H., additional, Gram, Inger Torhild, additional, Han, Jun, additional, Amos, Christopher I., additional, Hung, Rayjean J., additional, Grankvist, Kjell, additional, Nøst, Therese Haugdhal, additional, Imaz, Liher, additional, Chirlaque-López, María Dolores, additional, Johansson, Mikael, additional, Kaaks, Rudolf, additional, Kühn, Tilman, additional, Martin, Richard M., additional, McKay, James D., additional, Pala, Valeria, additional, Robbins, Hilary A., additional, Sandanger, Torkjel M., additional, Schibli, David, additional, Schulze, Matthias B., additional, Travis, Ruth C., additional, Vineis, Paolo, additional, Weiderpass, Elisabete, additional, Brennan, Paul, additional, Johansson, Mattias, additional, and Richards, J. Brent, additional

Published
2022
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37. Lung cancer risk among bakers, pastry cooks and confectionary makers: the SYNERGY study

Author

Behrens, Thomas, Kendzia, Benjamin, Treppmann, Tabea, Olsson, Ann, Jöckel, Karl-Heinz, Gustavsson, Per, Pohlabeln, Hermann, Ahrens, Wolfgang, Brüske, Irene, Wichmann, Hans-Erich, Merletti, Franco, Mirabelli, Dario, Richiardi, Lorenzo, Simonato, Lorenzo, Zaridze, David, Szeszenia-Dabrowska, Neonila, Rudnai, Peter, Lissowska, Jolanta, Fabianova, Eleonora, Tardón, Adonina, Field, John, Dumitru, Rodica Stanescu, Bencko, Vladimir, Foretova, Lenka, Janout, Vladimir, Siemiatycki, Jack, Parent, Marie-Elise, McLaughlin, John, Demers, Paul, Landi, Maria Teresa, Caporaso, Neil, Kromhout, Hans, Vermeulen, Roel, Peters, Susan, Benhamou, Simone, Stücker, Isabelle, Guida, Florence, Consonni, Dario, Bueno-de-Mesquita, Bas, Mannetje, Andrea 't, Pearce, Neil, Tse, Lap Ah, Yu, Ignatius Tak-sun, Plato, Nils, Boffetta, Paolo, Straif, Kurt, Schüz, Joachim, Pesch, Beate, and Brüning, Thomas

Published
2013
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39. Risk of Lung Cancer Associated With Occupational Exposure to Mineral Wools : Updating Knowledge From a French Population-Based Case–Control Study, the ICARE Study

Author

Guida, Florence, Paget-Bailly, Sophie, Lamkarkach, Farida, Gaye, Oumar, Ducamp, Stéphane, Menvielle, Gwenn, Papadopoulos, Alexandra, Matrat, Mireille, Févotte, Joëlle, Cénée, Sylvie, Cyr, Diane, Schmaus, Annie, Carton, Matthieu, Radoï, Loredana, Lapôtre-Ledoux, Bénédicte, Molinié, Florence, Luce, Danièle, and Stücker, Isabelle

Published
2013

42. Circulating Isovalerylcarnitine and Lung Cancer Risk : evidence from Mendelian Randomization and Prediagnostic Blood Measurements

Author

Smith-Byrne, Karl, Cerani, Agustin, Guida, Florence, Zhou, Sirui, Agudo, Antonio, Aleksandrova, Krasimira, Barricarte, Aurelio, Barranco, Miguel Rodríguez, Bochers, Christoph H., Gram, Inger Torhild, Han, Jun, Amos, Christopher I., Hung, Rayjean J., Grankvist, Kjell, Nøst, Therese Haugdhal, Imaz, Liher, Chirlaque-López, María Dolores, Johansson, Mikael, Kaaks, Rudolf, Kühn, Tilman, Martin, Richard M., McKay, James D., Pala, Valeria, Robbins, Hilary A., Sandanger, Torkjel M., Schibli, David, Schulze, Matthias B., Travis, Ruth C., Vineis, Paolo, Weiderpass, Elisabete, Brennan, Paul, Johansson, Mattias, Richards, J Brent, Smith-Byrne, Karl, Cerani, Agustin, Guida, Florence, Zhou, Sirui, Agudo, Antonio, Aleksandrova, Krasimira, Barricarte, Aurelio, Barranco, Miguel Rodríguez, Bochers, Christoph H., Gram, Inger Torhild, Han, Jun, Amos, Christopher I., Hung, Rayjean J., Grankvist, Kjell, Nøst, Therese Haugdhal, Imaz, Liher, Chirlaque-López, María Dolores, Johansson, Mikael, Kaaks, Rudolf, Kühn, Tilman, Martin, Richard M., McKay, James D., Pala, Valeria, Robbins, Hilary A., Sandanger, Torkjel M., Schibli, David, Schulze, Matthias B., Travis, Ruth C., Vineis, Paolo, Weiderpass, Elisabete, Brennan, Paul, Johansson, Mattias, and Richards, J Brent

Abstract

BACKGROUND: Tobacco exposure causes 8 of 10 lung cancers, and identifying additional risk factors is challenging due to confounding introduced by smoking in traditional observational studies. MATERIALS AND METHODS: We used Mendelian randomization (MR) to screen 207 metabolites for their role in lung cancer predisposition using independent genome-wide association studies (GWAS) of blood metabolite levels (n = 7,824) and lung cancer risk (n = 29,266 cases/56,450 controls). A nested case-control study (656 cases and 1,296 matched controls) was subsequently performed using prediagnostic blood samples to validate MR association with lung cancer incidence data from population-based cohorts (EPIC and NSHDS). RESULTS: An MR-based scan of 207 circulating metabolites for lung cancer risk identified that blood isovalerylcarnitine (IVC) was associated with a decreased odds of lung cancer after accounting for multiple testing (log10-OR = 0.43; 95% CI, 0.29-0.63). Molar measurement of IVC in prediagnostic blood found similar results (log10-OR = 0.39; 95% CI, 0.21-0.72). Results were consistent across lung cancer subtypes. CONCLUSIONS: Independent lines of evidence support an inverse association of elevated circulating IVC with lung cancer risk through a novel methodologic approach that integrates genetic and traditional epidemiology to efficiently identify novel cancer biomarkers. IMPACT: Our results find compelling evidence in favor of a protective role for a circulating metabolite, IVC, in lung cancer etiology. From the treatment of a Mendelian disease, isovaleric acidemia, we know that circulating IVC is modifiable through a restricted protein diet or glycine and L-carnatine supplementation. IVC may represent a modifiable and inversely associated biomarker for lung cancer.

Published
2022
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43. Epigenetic mechanisms of lung carcinogenesis involve differentially methylated CpG sites beyond those associated with smoking

Author

IRAS OH Epidemiology Chemical Agents, Petrovic, Dusan, Bodinier, Barbara, Dagnino, S., Whitaker, Matthew, Karimi, Maryam, Campanella, Gianluca, Nøst, Therese Haugdahl, Polidoro, Silvia, Krogh, Vittorio, Tumino, Rosario, Sacerdote, Carlotta, Panico, Salvatore, Lund, Eiliv, Dugué, Pierre-Antoine, Giles, Graham G., Severi, Gianluca, Southey, Melissa C., Vineis, Paolo, Stringhini, Silvia, Bochud, Murielle, Sandanger, Torkjel M, Vermeulen, Roel, Guida, Florence, Chadeau-Hyam, Marc, IRAS OH Epidemiology Chemical Agents, Petrovic, Dusan, Bodinier, Barbara, Dagnino, S., Whitaker, Matthew, Karimi, Maryam, Campanella, Gianluca, Nøst, Therese Haugdahl, Polidoro, Silvia, Krogh, Vittorio, Tumino, Rosario, Sacerdote, Carlotta, Panico, Salvatore, Lund, Eiliv, Dugué, Pierre-Antoine, Giles, Graham G., Severi, Gianluca, Southey, Melissa C., Vineis, Paolo, Stringhini, Silvia, Bochud, Murielle, Sandanger, Torkjel M, Vermeulen, Roel, Guida, Florence, and Chadeau-Hyam, Marc

Published
2022

44. Epigenetic mechanisms of lung carcinogenesis involve differentially methylated CpG sites beyond those associated with smoking

Author

Planetary Health & Exposoom, Cancer, Circulatory Health, Petrovic, Dusan, Bodinier, Barbara, Dagnino, Sonia, Whitaker, Matthew, Karimi, Maryam, Campanella, Gianluca, Haugdahl Nøst, Therese, Polidoro, Silvia, Palli, Domenico, Krogh, Vittorio, Tumino, Rosario, Sacerdote, Carlotta, Panico, Salvatore, Lund, Eiliv, Dugué, Pierre Antoine, Giles, Graham G., Severi, Gianluca, Southey, Melissa, Vineis, Paolo, Stringhini, Silvia, Bochud, Murielle, Sandanger, Torkjel M., Vermeulen, Roel C.H., Guida, Florence, Chadeau-Hyam, Marc, Planetary Health & Exposoom, Cancer, Circulatory Health, Petrovic, Dusan, Bodinier, Barbara, Dagnino, Sonia, Whitaker, Matthew, Karimi, Maryam, Campanella, Gianluca, Haugdahl Nøst, Therese, Polidoro, Silvia, Palli, Domenico, Krogh, Vittorio, Tumino, Rosario, Sacerdote, Carlotta, Panico, Salvatore, Lund, Eiliv, Dugué, Pierre Antoine, Giles, Graham G., Severi, Gianluca, Southey, Melissa, Vineis, Paolo, Stringhini, Silvia, Bochud, Murielle, Sandanger, Torkjel M., Vermeulen, Roel C.H., Guida, Florence, and Chadeau-Hyam, Marc

Published
2022

46. The blood proteome of imminent lung cancer diagnosis.

Author

The Lung Cancer Cohort Consortium (LC3), Albanes, Demetrius, Alcala, Karine, Alcala, Nicolas, Amos, Christopher I., Arslan, Alan A., Bassett, Julie K., Brennan, Paul, Cai, Qiuyin, Chen, Chu, Feng, Xiaoshuang, Freedman, Neal D., Guida, Florence, Hung, Rayjean J., Hveem, Kristian, Johansson, Mikael, Johansson, Mattias, Koh, Woon-Puay, Langhammer, Arnulf, and Milne, Roger L.

Subjects
LUNG cancer, CANCER diagnosis, BLOOD proteins, GROWTH factors, EARLY detection of cancer
Abstract

Identification of risk biomarkers may enhance early detection of smoking-related lung cancer. We measured between 392 and 1,162 proteins in blood samples drawn at most three years before diagnosis in 731 smoking-matched case-control sets nested within six prospective cohorts from the US, Europe, Singapore, and Australia. We identify 36 proteins with independently reproducible associations with risk of imminent lung cancer diagnosis (all p < 4 × 10−5). These include a few markers (e.g. CA-125/MUC-16 and CEACAM5/CEA) that have previously been reported in studies using pre-diagnostic blood samples for lung cancer. The 36 proteins include several growth factors (e.g. HGF, IGFBP-1, IGFP-2), tumor necrosis factor-receptors (e.g. TNFRSF6B, TNFRSF13B), and chemokines and cytokines (e.g. CXL17, GDF-15, SCF). The odds ratio per standard deviation range from 1.31 for IGFBP-1 (95% CI: 1.17–1.47) to 2.43 for CEACAM5 (95% CI: 2.04–2.89). We map the 36 proteins to the hallmarks of cancer and find that activation of invasion and metastasis, proliferative signaling, tumor-promoting inflammation, and angiogenesis are most frequently implicated. Lung cancer screening could enhance early diagnosis and treatment. Here, the authors used proteomic analysis of pre-diagnosis samples across 6 cohorts to identify 36 proteins associated with imminent lung cancer diagnosis. [ABSTRACT FROM AUTHOR]

Published
2023
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49. Design and methodological considerations for biomarker discovery and validation in the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Program

Author

Robbins, Hilary A, primary, Alcala, Karine, additional, Khodayari Moez, Elham, additional, Guida, Florence, additional, Thomas, Sera, additional, Zahed, Hana, additional, Warkentin, Matthew, additional, Smith-Byrne, Karl, additional, Brhane, Yonathan, additional, Muller, David, additional, Albanes, Demetrius, additional, Aldrich, Melinda C, additional, Arslan, Alan A, additional, Bassett, Julie, additional, Berg, Christine D, additional, Cai, Qiuyin, additional, Chen, Chu, additional, Davies, Michael PA, additional, Diergaarde, Brenda, additional, Field, John K, additional, Freedman, Neal D, additional, Huang, Wen-Yi, additional, Johansson, Mikael, additional, Jones, Michael, additional, Koh, Woon-Puay, additional, Lam, Stephen, additional, Lan, Qing, additional, Langhammer, Arnulf, additional, Liao, Linda M, additional, Liu, Geoffrey, additional, Malekzadeh, Reza, additional, Milne, Roger L, additional, Montuenga, Luis M, additional, Rohan, Thomas, additional, Sesso, Howard D, additional, Severi, Gianluca, additional, Sheikh, Mahdi, additional, Sinha, Rashmi, additional, Shu, Xiao-Ou, additional, Stevens, Victoria L, additional, Tammemägi, Martin C, additional, Tinker, Lesley F, additional, Visvanathan, Kala, additional, Wang, Ying, additional, Wang, Renwei, additional, Weinstein, Stephanie J, additional, White, Emily, additional, Wilson, David, additional, Yuan, Jian-Min, additional, Zhang, Xuehong, additional, Zheng, Wei, additional, Amos, Christopher I, additional, Brennan, Paul, additional, Johansson, Mattias, additional, and Hung, Rayjean J, additional

Published
2022
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50. The joint effect of asbestos exposure, tobacco smoking and alcohol drinking on laryngeal cancer risk: evidence from the French population-based case–control study, ICARE

Author

Menvielle, Gwenn, Fayossé, Aurore, Radoï, Loredana, Guida, Florence, Sanchez, Marie, Carton, Matthieu, Cyr, Diane, Schmaus, Annie, Cénée, Sylvie, Fevotte, Joëlle, Delafosse, Patricia, Stücker, Isabelle, Luce, Danièle, Guizard, Anne-Valérie, Danzon, Arlette, Woronoff, Anne-Sophie, Michel, Velten, Buemi, Antoine, Marrer, Émilie, Tretarre, Brigitte, Colonna, Marc, Bercelli, Paolo, Molinie, Florence, Bara, Simona, Lapotre-Ledoux, Benedicte, Raverdy, Nicole, Gaye, Oumar, and Lamkarkach, Farida

Published
2016
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