OncogenomicLandscapes

OncogenomicLandscapes maps cancer genomic profiles into two-dimensional landscapes and projects new samples onto 22 predefined landscapes derived from cancer cell line panels, organoids, patient-derived xenografts, and clinical tumor samples to enable comparison and interpretation of genetic heterogeneity across cohorts.

Key Features:

• 2D Visualization Framework: Generates two-dimensional representations of thousands of cancer genomic profiles to assess genetic heterogeneity across large cohorts.
• Use of Driver Genes as Landmarks: Uses driver genes as reference landmarks within landscapes to highlight critical genetic alterations that may influence cancer progression and treatment response.
• Mapping New Samples: Maps new samples and cohorts onto 22 predefined landscapes derived from cancer cell line panels, organoids, patient-derived xenografts, and clinical tumor samples to contextualize individual genomic profiles.
• Facilitating Research and Clinical Applications: Provides cohort-level genomic context to support identification of potential treatment opportunities, including experimental therapies for patients lacking standard options, and to inform basic cancer research.

Scientific Applications:

• Personalized Medicine: Supports personalized medicine by extrapolating cohort-derived findings to individual patients.
• Clinical Decision Support: Provides rationale for clinical decision-making by contextualizing individual tumor profiles within broader cohort landscapes.
• Cancer Biology and Target Discovery: Enables exploration of genetic diversity across cohorts and identification of novel therapeutic targets.

Methodology:

Integrates next-generation sequencing data with advanced computational algorithms to produce coherent two-dimensional representations of genomic profiles.