Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer

Abstract

Background: Breast cancer patients with residual disease after neoadjuvant chemotherapy (NAC) have increased recurrence risk. Molecular characterization, knowledge of NAC response, and simultaneous generation of patient-derived xenografts (PDXs) may accelerate drug development. However, the feasibility of this approach is unknown.

Methods: We conducted a prospective study of 140 breast cancer patients treated with NAC and performed tumor and germline sequencing and generated patient-derived xenografts (PDXs) using core needle biopsies. Chemotherapy response was assessed at surgery.

Results: Recurrent "targetable" alterations were not enriched in patients without pathologic complete response (pCR); however, upregulation of steroid receptor signaling and lower pCR rates (16.7%, 1/6) were observed in triple-negative breast cancer (TNBC) patients with luminal androgen receptor (LAR) vs basal subtypes (60.0%, 21/35). Within TNBC, TP53 mutation frequency (75.6%, 31/41) did not differ comparing basal (74.3%, 26/35) and LAR (83.3%, 5/6); however, TP53 stop-gain mutations were more common in basal (22.9%, 8/35) vs LAR (0.0%, 0/6), which was confirmed in The Cancer Genome Atlas and British Columbia data sets. In luminal B tumors, Ki-67 responses were observed in tumors that harbored mutations conferring endocrine resistance ( p53, AKT, and IKBKE ). PDX take rate (27.4%, 31/113) varied according to tumor subtype, and in a patient with progression on NAC, sequencing data informed drug selection (olaparib) with in vivo antitumor activity observed in the primary and resistant (postchemotherapy) PDXs.

Conclusions: In this study, we demonstrate the feasibility of tumor sequencing and PDX generation in the NAC setting. "Targetable" alterations were not enriched in chemotherapy-resistant tumors; however, prioritization of drug testing based on sequence data may accelerate drug development.

Figure 1.

Somatically mutated genes in patients with triple-negative breast cancer (TNBC) clinical molecular subtype. The mutation profile of the 30 most frequently mutated genes (P < .006) for triple-negative subtype, as determined by the MutSigCV method. After adjustment for multiple testing (q < .05), three genes (TP53, PTEN, and OTOP1) remained statistically significant. The upper left panel shows the distribution of the mutation type across all patients; the upper right panel shows the distribution of mutations by chemotherapy response for each patient. The lower left panel shows the number and type of mutations seen per gene for the 30 mutated genes. We order the genes in the figures by the number of patients with mutations. For genes with equal numbers of patients with somatic SNV/indel alterations, the presentation order is based on estimated cancer gene statistical significance. The lower right panel gives the mutation, the copy number gain and loss, and modulation of expression (described in the “Methods” section) by patient and by gene. CNV = copy number variants; INDEL = insertion and deletion; pCR = pathologic complete response; SNV = single-nucleotide variant.

Figure 2.

Circos plots of mutations in clinical molecular breast cancer subtypes. This plot depicts the human chromosomes arranged in a circular pattern, with individual chromosomes represented as sections. From outside to inner side: The outermost track represents the copy number alteration (CNA), amplification in red, and deletion in green); the second track presents somatic single-nucleotide variants (SNVs) identified in whole-exome sequencing data (blue); the third track is RNA nonsynonymous tumor-specific expressed SNV(eSNVs; orange). The radius height in the outer three tracks represents the CNA ratio across the samples of this subtype. The innermost arches (purple) are the fusions; the two ends of an arch indicate the location of the two fused genes, and the thickness of the arch is proportional to the frequency of the fusion.

Figure 3.

Tumor growth in patient-derived xenografts (PDXs) generated from patient specimens. A) PDXs were generated from a pre–neoadjuvant chemotherapy (NAC) specimen treated with olaparib or placebo and B) PDXs generated from residual tumor after NAC treated with either olaparib or placebo. Error bars represent the standard deviation. NAC = neoadjuvant chemotherapy; PDX = patient-derived xenograft.