The association of genomic lesions and PD-1/PD-L1 expression in resected triple-negative breast cancers

Elevated PD-L1 expression on tumor cells, a context associated with an adaptive immune response, has been linked to the total burden of copy number variants (CNVs) in aneuploid tumors, to microsatellite instability (MSI), and to specific genomic driver lesions, including loss of PTEN, MYC amplification, and activating mutations in driver oncogenes such as KRAS and PIK3CA. Triple-negative breast cancers (TNBCs) typically have high levels of CNVs and diverse driver lesions in their genomes. Thus, there is significant interest in exploiting genomic data to develop predictive immunotherapy biomarkers for patients with TNBC.

PD-L1 staining was detected on tumor cells in 29 out of 54 (54%) evaluable cases and was associated with increased overall survival (P = 0.0024). High levels of PD-1 and PD-L1 (IHC ≥4) were present in 11 out of 54 (20%) and 20 out of 54 (37%) cases with staining of PD-L1 primarily on tumor cells for 17 out of 20 (85%) cases. The latter included tumors with both high (>50) and low (<20) numbers of CNVs. Notably, homozygous deletion of PTEN (n = 6) or activating mutation in PIK3CA (n = 1) was not associated with increased expression of either immune checkpoint activator in TNBC. In contrast, two treatment-naïve cases with EGFR driver amplicons had high PD-L1 tumor staining. High mutational load and predicted neoepitopes were observed in MSI+ and high CNV burden TNBCs but were not associated with high PD-L1 expression on tumor cells. Our results challenge current models of genomic-based immunotherapy signatures yet suggest that discrete genomic lesions may complement existing biomarkers to advance immune checkpoint therapies for patients with TNBC.

Whole tissue samples from 55 resected TNBCs were screened by immunohistochemistry (IHC) for PD-1 and PD-L1 by using validated antibodies and established scoring methods for staining of tumor and non-tumor cells. In parallel, we interrogated biopsies from each resection with DNA content flow cytometry and sorted the nuclei of diploid, tetraploid, and aneuploid cell populations. CNVs were mapped with CNV oligonucleotide arrays by using purified (>95%) tumor populations. We generated whole exome data for 12 sorted tumor samples to increase the resolution within loci of interest and to incorporate somatic mutations into our genomic signatures.