Cancer Risk and Integrated Susceptibility Evaluation
A global network decoding the rising incidence of early-onset cancers.
Uniting preclinical researchers, clinicians, and genetic counselors from Europe, South America, and Southwest Asia to redefine cancer susceptibility and clinical risk assessment.
The Challenge: Rising Incidence
* Data Visualization Source: Our World in Data (Cancer incidence rate by age group).
The incidence of early-onset cancers is rising worldwide, yet the mechanistic, biological, and genetic factors driving this trend remain poorly understood. This knowledge gap limits the development of effective prevention strategies, risk stratification, early detection approaches, and age-appropriate interventions for younger individuals.
Work Package 1 Blueprint
CanRISE Shared Knowledge Hub
An interactive environment detailing our framework for deciphering pleiotropic mechanisms for actionable biology in Early-Onset Cancers (EOCs).
Knowledge Source Pipeline
Integrated Multi-Ethnic Datasets
Click on any core element below to explore the data structures, secure harmonized ingestion protocols, and specific fields utilized by our multi-centric registry:
ACTIVE SCHEMA VIEWER
DB Structure: v1.0.4
Core Patient Demographics Anonymized Registry
To maintain complete security compliance across transnational borders, patient privacy is fortified at the ingestion point. Demographics are highly standardized to enable precise statistical modeling of early-onset trends.
Supports multi-modal, phenotype-driven queries across clinical profiles, tumor histologies, comorbidities, and genomic region classifications effortlessly.
02
Interactive Visualizations
Employs integrated dynamic tools like heatmaps, geospatial distribution maps, and interactive pedigree tools to visualize and study genomic susceptibility.
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Integrated Machine Learning
Houses dedicated statistical models and pathway assessment tools directly linked to international databases (KEGG, Reactome, Pathway Commons).
Our Mission
•Integrate multi-ethnic insights into cancer predisposition.
•Foster global technology and resource sharing.
•Identify novel pleiotropic genetic variants associated with diverse cancers.
•Improve the accuracy of genetic risk prediction for younger patients.
•Strengthen public engagement through collaboration with organizations like Cancer Patients Europe.
