CanSeer

CanSeer employs patient-specific genetic alterations and RNA-seq data to annotate in silico models and performs dynamical network analyses to assess treatment responses and identify potential drug combinations for personalized cancer therapeutics.

Key Features:

• Patient-Specific Model Annotation: Utilizes patient-specific genetic alterations and RNA-seq data to annotate in silico biomolecular network models.
• Dynamical Network Analysis: Performs dynamical network analyses to assess treatment responses including efficacy and cytotoxic effect.
• Drug Repositioning: Repositions FDA-approved drugs for personalized cancer treatment.
• Drug Combination Identification: Identifies novel drug combinations such as Afuresertib + Palbociclib, Dinaciclib + Trametinib, Afatinib + Oxaliplatin, and Ulixertinib + Olaparib.
• Actionable Target Identification: Ascertains actionable targets for personalized therapy design.

Scientific Applications:

• Lung Squamous Cell Carcinoma (LUSC) Treatment: Exemplified through three use cases involving paired samples, unpaired samples, and cancer samples only to reveal effectiveness of repositioned drugs and identify novel treatment combinations.
• Personalized Cancer Therapeutic Development: Provides quantitative cues on therapy responses for designing individualized cancer treatments.

Methodology:

CanSeer employs patient-specific genetic alterations and RNA-seq data to annotate in silico models followed by dynamical network analyses.