Abstract 4123: Real-world data to identify the genomic association with response to CDK4/6i + Endocrine therapy in ER+ breast cancer patients

Abstract Background Real-world data (RWD) has been increasingly used for drug development. RWD coupled with genomic data provides an opportunity to identify the association between certain genomic alterations and response to current standard of care (SOC). Such analyses may help identify predictive biomarkers to select patients who will benefit most from SOC, and/or potential therapeutic nodes that can be pharmacologically targeted to overcome resistance to SOC. Methods We obtained Flatiron CGDB Breast Cancer (as of Q3 2020 release) data set. This data set includes clinical and genomic data from 6,918 breast cancer patients. Time to treatment discontinuation (TTD) was used as real world outcome. We performed two types of genomic-outcome association analysis: 1) Use Cox proportional hazards regression model to identify which baseline mutation (mutation occurred prior to the treatment) could predict the outcome; and 2) use Fisher exact test to identify which mutations are enriched in post-treatment tumors samples, compared to pre-treatment tumor samples. Result We found TP53 mutation is associated with shorter TTD for Palbociclib + Aromatase inhibitor (AI); Palbociclib + Fulvestrant; and endocrine monotherapy. It is consistent with the reports that TP53 mutation is poor prognostic factor (ref). Interestingly, ESR1 mutation is associated with shorter TTD for Palbociclib + AI and AI monotherapy; but not associated with TTD for Palbociclib + Fulvestrant or Fulvestrant monotherapy. On the other hand, MYC amplification is associated shorter TTD for Palbociclib + Fulvestrant or Fulvestrant monotherapy. We found that genes associated with Palbociclib + Endocrine are by and large same as those associated with endocrine monotherapy; suggesting the association is largely driven by endocrine treatment. Comparison of post-treatment vs. pre-treatment analysis found that ESR1 mutation is enriched in post treatment of AI; but not Fulvestrant. Conclusion We demonstrated that real-world clinicogenomic data could identify the biologically meaningful genomic biomarkers that are associated with real world response. This study warrants the further investigation of novel genomic biomarkers identified from the analysis. Citation Format: Kun Yu, Tenghui Chen, Manav Korpal, Ping Zhu, Zhaojie Zhang, Lihua Yu, Yonghong Xiao. Real-world data to identify the genomic association with response to CDK4/6i + Endocrine therapy in ER+ breast cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4123.