A Population of Heterogeneous Breast Cancer Patient-Derived Xenografts Demonstrate Broad Activity of PARP Inhibitor in BRCA1/2 Wild-Type Tumors

Abstract

Background Breast cancer patients who do not respond to neoadjuvant therapy have a poor prognosis. There is a pressing need for novel targets and models for preclinical testing. Here we report characterization of breast cancer patient derived xenografts (PDXs) largely generated from residual tumors following neoadjuvant chemotherapy. Methods PDXs were derived from surgical samples of primary or locally recurrent tumors. Normal and tumor DNA sequencing, RNASeq and Reverse Phase Protein Arrays (RPPA) were performed. Phenotypic profiling was performed by determining efficacy of a panel of standard and investigational agents. Results Twenty-six PDXs were developed from 25 patients. Twenty-two were generated from residual disease following neoadjuvant chemotherapy, and 24 were from triple negative breast cancer (TNBC). These PDXs harbored a heterogeneous set of genomic alterations and represented all TNBC molecular subtypes. On RPPA, PDXs varied in extent of PI3K and MAPK activation. PDX also varied in their sensitivity to chemotherapeutic agents. PI3K, mTOR and MEK inhibitors repressed growth but did not cause tumor regression. PARP inhibitor talazoparib caused dramatic regression in 5 of 12 PDXs. Notably 4 of 5 talazoparib-sensitive models did not harbor germline BRCA1/2 mutations, but several had somatic alterations in homologous repair pathways, including ATM deletion and BRCA2 alterations. Conclusions PDXs capture the molecular and phenotypic heterogeneity of TNBC. Here we show that PARP inhibition can have activity beyond germline BRCA1/2 altered tumors, causing regression in a variety of molecular subtypes. These models represent an opportunity for the discovery of rational combinations with targeted therapies and predictive biomarkers.

A large collection of integrated genomically characterized patient‐derived xenografts highlighting the heterogeneity of triple‐negative breast cancer

“…We report the largest cohort of clinically annotated TNBC PDX, illustrating the genomic, transcriptomic and morphologic heterogeneity of TNBC. Several other authors have described genomic alterations in small cohorts of TNBC PDX, including description of morphological and genomic fidelity with the patient's tumor and possibility to identify efficient treatment and predictive biomarkers . The primary objective of transcriptomic classifications is to identify subtypes with biologic drivers in order to guide personalized treatment.…”

“…Several other authors have described genomic alterations in small cohorts of TNBC PDX, including description of morphological and genomic fidelity with the patient's tumor and possibility to identify efficient treatment and predictive biomarkers. 12,16,35 The primary objective of transcriptomic classifications is to identify subtypes with biologic drivers in order to…”

“…Trametinib was tested in eight PDX with a high range of MEK/ERK phosphorylation: the best response was observed in the PDX with the most highly activated MAPK pathway. 35 Interestingly, in a phase Ib trial in patients with solid tumors (n = 31) treated with gemcitabine and trametinib, the only complete response to therapy was observed in a patient with TNBC. 42 Selumetinib was tested in one model of breast cancer xenograft with regression of lung metastasis.…”

Applications of patient-derived tumor xenograft models and tumor organoids

“…Furthermore, cytogenetic analysis of tumor cells from PDXs has revealed significant preservation of the genomic and gene expression profiles between PDXs and parental patient tumors [10][11][12][13][14]. Notably, sensitivity to standard chemotherapeutics in PDXs closely correlates with clinical data in patients from which the PDXs are derived [12,13,[15][16][17][18]. All of these characteristics demonstrate that PDXs are more useful as predictive experimental models of therapeutic responses.…”

Clinically relevant inflammatory breast cancer patient-derived xenograft–derived ex vivo model for evaluation of tumor-specific therapies

“…Drugs ranking highest exhibited the strongest reduction in viability relative to the control. The statistical analysis for the in-vivo data described in the section “Value of the PDXEx model for predicting tumor response to drugs” is present in the paper by KURT et al [ 53 ].…”