Wellcome Connecting Science Course Run Website Link
Course Time Table 2026
Course Informatics Guide
Cancer remains a leading cause of death worldwide, with rising incidence and significant disparities in outcomes across populations. While advances in genomics have transformed our understanding of tumour biology, translating this knowledge into effective prevention strategies remains challenging. Genomic epidemiology, including the study of mutational signatures, offers powerful tools to investigate how inherited and acquired genetic changes interact with environmental exposures to influence cancer risk. These insights are critical for identifying carcinogens, refining risk assessment, and informing population-level interventions. With growing access to genomic data from diverse populations, there is an urgent need to equip researchers and public health professionals with the skills to apply genomic epidemiology in support of equitable cancer prevention.
What will this course cover?
This immersive workshop will explore the intersection of cancer genomics and epidemiology to deepen our understanding of cancer causation and prevention with a public health perspective. Participants will engage with the latest analytical and experimental approaches to uncover how genetic and environmental factors combine to drive cancer onset. Through a combination of lectures, case studies, group discussions, and interactive sessions, the programme will cover:
- Computational approaches for mutational signature analysis
- In vivo and in vitro models for mechanistic studies of carcinogens associated with environmental exposures
- Use of large-scale genomic and exposure data from diverse populations to refine the assessment of cancer risk
- Multidisciplinary approaches to assess environmental contributions to cancer risk
- Applications of genomic epidemiology to public health and cancer prevention programmes
This course is aimed at scientists working in genomics, epidemiology, clinical, and public health fields who are seeking to enhance their ability to investigate cancer causation using genomic and population-level approaches. We welcome applicants at early- and mid-career stages, and encourage participation from diverse geographic, institutional, and interdisciplinary backgrounds.
By the end of this course, participants will be able to:
- Apply computational methods to analyse mutational signatures and investigate cancer-related genomic alterations.
- Use experimental and epidemiological approaches to assess the link between environmental exposures and cancer mechanisms.
- Interpret and integrate evidence from genomics, epidemiology, and exposure data to infer carcinogenic processes.
- Evaluate the application of genomic epidemiology in cancer prevention, including hazard identification, population diversity, and the use of open science resources.
This course will run from 10:00 on Monday 16 February and end at 16:00 on Wednesday 18 February 2026.
The programme will include lectures, seminars, and hands-on analysis sessions on the following topics:
- Mutational signatures
- Experimental models
- Genomic & exposure data
- Environmental risk assessment
- Public health applications
Course Instructors
- Sandra Perdomo, International Agency for Research on Cancer (WHO IARC), France
- Sarah Moody, Wellcome Sanger Institute, United Kingdom
- Ferriol Calvet, Institute for Research in Biomedicine (IRB Barcelona), Spain
- Jose Antonio Seoane, Vall d'Hebron Institute of Oncology (VHIO), Spain
- Linda Kachuri, Stanford University, United States of America
- Sonia Dagnino , University of Cote d'Azur, France
- Talya Dayton, European Molecular Biology Laboratory (EMBL) Barcelona, Spain
- Andrew Biankin, University of Glasgow, United Kingdom
- Mary Schubauer-Berigan, International Agency for Research on Cancer (WHO IARC), France
- Silvia Balbo, University of Minnesota, United States of America
Wellcome Connecting Science Team
- Liã Barbara Arruda, Education Developer
- Lucy Criddle, Event and Logistics
The course data are free to reuse and adapt with appropriate attribution. All course data in these repositories are licensed under the Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
Each course landing page is assigned a DOI via Zenodo, providing a stable and citable reference. These DOIs can be found on the respective course landing pages and can be included in CVs or research publications, offering a professional record of the course contributions.
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