bioRxivGenomicsPreprint
Tumor suppressor heterozygosity and homologous recombination deficiency mediate resistance to front-line therapy in breast cancer
Anton Mikhailovich SafonoviD, Antonio MarraiD, Chaitanya BandlamudiiD, Ben O’LearyiD, Bradley Stephen WubbenhorstiD, Emanuela FerraroiD, Enrico MoisoiD, Minna Lee, Julia Ah-Reum AniD, Mark T.A. DonoghueiD, Marie WilliD, Fresia G. ParejaiD, Emily A. NizialekiD, Natalia LukashchukiD, Eleni SofianopoulouiD, Yuan LiuiD, Xin HuangiD, Mehnaj Ahmed, Miika M. MehineiD, Dara S. RossiD, Diana L. MandelkeriD, Marc LadanyiiD, Nikolaus D. SchultziD, Michael F. BergeriD, Maurizio ScaltritiiD, , Pedram RazaviiD
Abstract
The co-occurrence of germline and somatic oncogenic alterations is frequently observed in breast cancer, but their combined biologic and clinical significance has not been evaluated. To assess the role of germline-somatic interactions on outcomes in routine practice, we developed an integrated clinicogenomic pipeline to analyze the genomes of over 4,500 patients with breast cancer. We find that germline (g)BRCA2-associated tumors are enriched for RB1 loss-of-function mutations and manifest poor outcomes on standard-of-care, front-line CDK4/6 inhibitor (CDK4/6i) combinations. Amongst these tumors, gBRCA2-related homologous recombination deficiency (HRD) as well as baseline RB1 LOH status promote acquisition of RB1 loss-of- function mutations under the selective pressure of CDK4/6i, causing therapy resistance. These findings suggest an alternative therapeutic strategy using sequential targeting of HRD in gBRCA- associated breast cancers through PARP inhibitors prior to CDK4/6i therapy to intercept deleterious RB1-loss trajectories and thus suppress the emergence of CDK4/6 inhibitor resistance. More broadly, our findings demonstrate how germline-somatic driven genomic configurations shape response to systemic therapy and can be exploited therapeutically as part of biomarker-directed clinical strategies.
- organism: human
- assay: whole-exome sequencing
- research focus: differential expression
- approach: statistical model
- Citations
- 18
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