AmetaRisk

AmetaRisk quantifies colorectal cancer (CRC) metastasis risk by assessing local invasion potential from somatic and germline mutation data.


Key Features:

  • Local Invasion Power (LIP): A novel statistical parameter that quantitatively measures the potential of somatic and germline mutations to promote local invasion in CRC.
  • Germline versus somatic analysis: Emphasizes the role of innate germline mutations over somatic mutations in driving local invasion.
  • Exome-wide bioinformatic analyses: Performs exome-wide analyses using large datasets from public repositories to detect invasion-associated variants.
  • Identification of driver variants: Identifies ten potential driver variants associated with tumor cell invasion, including six genes newly associated with CRC metastasis.
  • Metastasis resister variant: Detects a variant that acts as a resister against metastasis.
  • Logistic regression model: Constructs a logistic regression model using the identified variants to assess risk of early metastasis.

Scientific Applications:

  • Mechanistic insights: Uses exome-wide mutation data and LIP to provide mechanistic insight into genetic drivers of local invasion and metastasis in CRC.
  • Clinical prioritization: Provides a variant-based risk assessment that can be used to prioritize therapeutic regimens according to individual patient mutation profiles.
  • Drug target discovery: Identifies genes and variants associated with metastasis that serve as candidates for novel drug target investigation.

Methodology:

Calculation of Local Invasion Power (LIP); exome-wide bioinformatic analyses of large public-repository datasets to identify driver variants (ten candidates, six novel gene associations and one metastasis-resister); and construction of a logistic regression model using the identified variants for early metastasis risk assessment.

Topics

Details

License:
Other
Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Added:
9/26/2022
Last Updated:
11/24/2024

Operations

Publications

Ding R, Zhang Y, Wu L, You P, Fang Z, Li Z, Zhang Z, Ji Z. Discovering Innate Driver Variants for Risk Assessment of Early Colorectal Cancer Metastasis. Frontiers in Oncology. 2022;12. doi:10.3389/fonc.2022.898117. PMID:35795065. PMCID:PMC9252167.