Unraveling Tumor Profiles Using an HRD-Enabled CGP Assay and Exome Sequencing with AI-Driven Data Analysis

Tumor molecular characterization is key for advancing precision oncology. Two Agilent collaborators present approaches to detect somatic variants from cancer samples for large-scale data analyses. First is a whole exome sequencing method based on Agilent SureSelect technology paired with AI-driven best-in-class analytics. Utilizing this AI-driven approach enables identification of SNVs, indels, CNAs, TMB, MSI, HRD, and translocations. Second is a cost-effective method to investigate the homologous recombinant deficiency (HRD) status of solid tumor samples using the Agilent SureSelect Cancer CGP assay (targeting 679 genes). HRD status, a potential predictive biomarker for PARPi sensitivity, is demonstrated with two commercial informatics solutions.