Integration of Comprehensive Genomic Analysis and Functional Screening of Affected Molecular Pathways to Inform Cancer Therapy

Objective To select optimal therapies based on the detection of actionable genomic alterations in tumor samples is a major challenge in precision medicine. Methods We describe an effective process (opened December 1, 2017) that combines comprehensive genomic and transcriptomic tumor profiling, custom algorithms and visualization software for data integration, and preclinical 3-dimensiona ex vivo models for drug screening to assess response to therapeutic agents targeting specific genomic alterations. The process was applied to a patient with widely metastatic, weakly hormone receptor positive, HER2 nonamplified, infiltrating lobular breast cancer refractory to standard therapy. Results Clinical testing of liver metastasis identified BRIP1, NF1, CDH1, RB1, and TP53 mutations pointing to potential therapies including PARP, MEK/RAF, and CDK inhibitors. The comprehensive genomic analysis identified 395 mutations and several structural rearrangements that resulted in loss of function of 36 genes. Meta-analysis revealed biallelic inactivation of TP53, CDH1, FOXA1, and NIN, whereas only one allele of NF1 and BRIP1 was mutated. A novel ERBB2 somatic mutation of undetermined significance (P702L), high expression of both mutated and wild-type ERBB2 transcripts, high expression of ERBB3, and a LITAF-BCAR4 fusion resulting in BCAR4 overexpression pointed toward ERBB-related therapies. Ex vivo analysis validated the ERBB-related therapies and invalidated therapies targeting mutations in BRIP1 and NF1. Systemic patient therapy with afatinib, a HER1/HER2/HER4 small molecule inhibitor, resulted in a near complete radiographic response by 3 months. Conclusion Unlike clinical testing, the combination of tumor profiling, data integration, and functional validation accurately assessed driver alterations and predicted effective treatment.