Genetic and metabolomics screening: towards precision medicine in cancer prevention
We assess the association of known and unknown factors with cancer to estimate the risk of developing cancer and improve prevention.
Fundación Científica de la Asociación Española contra el Cáncer (AECC)
has awarded a grant of 500,000 € to the consortium of 15 translational groups coordinated by Dr. Victor Moreno.
is also a subprogram of
CIBER de Epidemiología y Salud Pública (CIBERESP).
We are an established consortium of cancer research institutes through 12 Spanish provinces, coordinated by CIBERESP. A large epidemiological study has been performed in Spain,
that has recruited 6,008 subjects with common cancers (colorectal, breast, stomach, prostate and chronic lymphocytic leukemia) and 4,098 population controls. In addition to epidemiological and dietary data, biological samples have been obtained which now will be analyzed to determine genetics and metabolomics from subjects.
The project aims to improve prevention of the studied cancers, through personalized strategies. Acting before the cancer appears or is at its early stage will diminish the morbidity and its social impact, and will reduce health cost in demographically shifting western world. Screening programs have already proven as successful direction towards lowering mortality from breast, colorectal and cervical cancer. However, screening today is done using only age to select population. With our project we want to move forward, towards personalized prevention so that genetics and lifestyle data will help to define how cancer prevention must be performed for each person.
With samples and data from 10,000 participants, predictive models of cancer risk and prognostic will be developed and validated, using innovative bioinformatics methodology.
Risk models will be developed using genomics, metabolomics and lifestyle data to identify population at high risk of developing cancer.
Improve prognosis and reduce cancer recurrence using prognostic models based on genetics, metabolomics and epidemiological data.
Genetic analysis of all participants
Blood molecules that provide information about metabolism, nutrition or energetic status
Relationship of cancer, genome and metabolome with:
- physical exercise
- alcohol and smoking
Evaluate whether a factor causes cancer or if this factor is altered after cancer onset
Models to predict cancer risk for the studied tumors
Models to predict which patients will have a better survival
Cost-effectiveness models to evaluate personalized screening strategies
Verification in independent studies that the models are valid and useful