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Methodological Innovations Teams
Integrative Epidemiology Team (IET)

Starting date: July 2021

Work Programme

The Integrative Epidemiology Team (IET) carries out translational epidemiological research spanning from discovery to implementation. IET’s ambition is to lead research with strong potential for long-term impact in reducing the impact of cancer.

The vision of IET is:
  • to inform primary prevention by advancing the understanding of cancer risk and etiology; and
  • to inform secondary prevention by optimizing early detection strategies.

IET specializes in organizing large international collaborations to study risk factors, develop risk prediction tools, and identify and evaluate early detection biomarkers. IET leverages the specific strengths of different conceptual, design, and analytical approaches to reach conclusive answers to important research questions, often leveraging the rich data resources generated by consortium studies.

A specific objective is to evaluate the importance of evolving risk factors in cancer etiology among populations in transition, including opioid and tobacco use and obesity. IET approaches this by organizing collaborative projects with investigators around the world to measure risk factors directly using traditional observational methods, and using instrumental variable methods by leveraging large genomic studies.

Another objective is to develop methods for improved early detection of cancer. A key strategy in this field is to improve cancer-specific risk assessment by incorporating novel risk indicators, frequently biomarkers, and to validate existing risk prediction tools in diverse populations. A guiding principle is to design studies that mimic the target use population to directly motivate implementation studies of biomarkers for early cancer detection.

IET focuses on several cancer types, with a particular emphasis on lung cancer, kidney cancer, and human papillomavirus (HPV)-associated cancers. All IET projects involve international collaborations, and many include the coordination of large consortia.

Team Composition

Team Leaders: Dr Mattias Johansson and Dr Hilary Robbins, Genomic Epidemiology Branch (GEM), IARC
Emails: JohanssonM@iarc.who.int; RobbinsH@iarc.who.int

Team members:
Ms Karine Alcala (Senior Research Assistant, Data Management/Analysis, GEM)
Dr Shayma Alwaheidi (Project Officer, GEM)
Dr Xiaoshuang Feng (Postdoctoral Scientist, GEM)
Dr Aida Ferreiro (Scientist, GEM)
Dr Justina Onwuka (Postdoctoral Scientist, GEM)
Dr Mahdi Sheikh (Scientist, GEM)
Ms Andreea Spanu (Project Assistant, GEM)
Ms Hana Zahed (Doctoral Student, GEM)
Ms Natalia Alves De Oliviera Vaz (Project Assistant, GEM)
Dr Allison Domingues (Postdoctoral Scientist, GEM)
Dr Ryan Langdon (Postdoctoral Scientist, GEM)
Dr Saeed Nemati (Visiting Scientist, GEM)
Dr Jifang Zhou (Visiting Scientist, GEM)

Key networks: Lung Cancer Cohort Consortium (LC3), International Lung Cancer Consortium (ILCCO), MetKid Consortium, Integrative Cancer Epidemiology Programme (ICEP), HPV Cancer Cohort Consortium (HPVC3), Opioid Cohort Consortium (OPICO)

Key funding: United States National Cancer Institute (NCI), World Cancer Research Fund (WCRF), Lung Cancer Research Foundation (LCRF), Institut national du Cancer (INCa), Cancer Research UK (CRUK)

Key publications

  1. Albanes D, Alcala K, Alcala N, Amos CI, Arslan AA, Bassett JK, et al.; Lung Cancer Cohort Consortium (LC3) (2023). The blood proteome of imminent lung cancer diagnosis. Nat Commun. 14(1):3042. https://doi.org/10.1038/s41467-023-37979-8 PMID:37264016
  2. Feng X, Wu WYY, Onwuka JU, Haider Z, Alcala K, Smith-Byrne K, et al. (2023). Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools. J Natl Cancer Inst. 115(9):1050–9. https://doi.org/10.1093/jnci/djad071 PMID:37260165
  3. Sheikh M, Mukeriya A, Zahed H, Feng X, Robbins HA, Shangina O, et al. (2023). Smoking cessation after diagnosis of kidney cancer is associated with reduced risk of mortality and cancer progression: a prospective cohort study. J Clin Oncol. 41(15):2747–55. https://doi.org/10.1200/JCO.22.02472 PMID:36989465
  4. Robbins HA, Ferreiro-Iglesias A, Waterboer T, Brenner N, Nygard M, Bender N, et al. (2022). Absolute risk of oropharyngeal cancer after an HPV16-E6 serology test and potential implications for screening: results from the Human Papillomavirus Cancer Cohort Consortium. J Clin Oncol. 40(31):3613–22. https://doi.org/10.1200/JCO.21.01785 PMID:35700419
  5. Zahed H, Feng X, Sheikh M, Bray F, Ferlay J, Ginsburg O, et al. (2024). Age at diagnosis for lung, colon, breast and prostate cancers: an international comparative study. Int J Cancer. 154(1):28–40. https://doi.org/10.1002/ijc.34671 PMID:37615573
  6. Alcala K, Zahed H, Cortez Cardoso Penha R, Alcala N, Robbins HA, Smith-Byrne K, et al. (2023). Kidney function and risk of renal cell carcinoma. Cancer Epidemiol Biomarkers Prev. 32(11):1644–50. https://doi.org/10.1158/1055-9965.EPI-23-0558 PMID:37668600
  7. Kachuri L, Graff RE, Smith-Byrne K, Meyers TJ, Rashkin SR, Ziv E, et al. (2020). Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction. Nat Commun. 11(1):6084. https://doi.org/10.1038/s41467-020-19600-4 PMID:33247094


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