Tumor immune microenvironment and genomic evolution in a patient with metastatic triple negative breast cancer and a complete response to atezolizumab

Abstract

Background: Metastatic TNBC (mTNBC) has a poor prognosis and few treatment options. The anti-PD-L1 antibody atezolizumab demonstrated clinical activity in mTNBC patients with PD-L1-positive tumor-infiltrating immune cells. The current study describes the tumor immune microenvironment (TiME) and genomic evolution across sequential therapies in a patient with a 31-year history of TNBC and a complete response (CR) to atezolizumab monotherapy.

Materials and methods: In 1986, the patient had surgery and radiotherapy (XRT) for newly diagnosed TNBC, followed by surgery and adjuvant chemotherapy for two locoregional recurrences. She developed mTNBC in 2009 and was sequentially treated with capecitabine, gemcitabine-carboplatin-iniparib (GCI), XRT and an experimental vaccine. She experienced disease progression (PD) to all these therapies. In 2013, she had a PD-L1 positive tumor and enrolled in a phase 1 atezolizumab monotherapy study (PCD4989g; NCT01375842). She received atezolizumab for 1 year with initial pseudo-progression followed by a partial response. After 1 year without treatment she experienced PD, reinitiated atezolizumab and subsequently achieved CR. Tumor specimens were collected at numerous times between 2008 and 2015 and assessed by immunohistochemistry, RNA-seq and DNA-seq.

Results: TiME biomarkers, including CD8, ICs and PD-L1 on IC, increased after capecitabine and remained high after GCI, XRT and through pseudo-progression on atezolizumab. At PD post-atezolizumab exposure, TiME biomarkers decreased but PD-L1 status remained positive. Immune-related RNA signatures confirmed these findings. TNBC subtyping revealed evolution from luminal androgen receptor (LAR) to basal-like immune activated (BLIA). Genomic profiling showed truncal alterations in RB1 and TP53, while the presence of other genomic alterations varied over time. Tumor mutational burden peaked after XRT and declined after atezolizumab exposure.

Conclusions: This case report describes the evolution of TiME and TNBC molecular subtypes/genomics over time with sequential therapies in a TNBC patient with a CR to atezolizumab monotherapy. These data suggest the TiME is pliable and may be manipulated to maximize response to immunotherapy (NCT01375842, https://ichgcp.net/clinical-trials-registry/NCT01375842?term=NCT01375842&rank=1 ).

Keywords: Atezolizumab; PD-L1; Triple negative breast cancer (TNBC).

Conflict of interest statement

LM, YL, C-WC, SM, MF, CO, and PH are employees of Genentech, Incorporated. LAE receives research funding from Genentech, Incorporated and Hoffman-La Roche, Incorporated.

Figures

Fig. 1

Clinical course of disease and time-points of collected tumor biopsies. On the right: chronological schema of disease appearance and treatments, on years. On the left: time of sample collection (red dots) on days respect to initiation to atezolizumab first exposure. CMF: cyclophosphamide, methotrexate and fluorouracil; Biopsy Dx: diagnostic biopsy; LAD: lymphadenopathy

Fig. 2

Change in tumor burden and circulating biomarkers after atezolizumab exposures. Changes in sum of lesion diameter (SLD) was assessed over time in initial (a) and second (b) exposure to atezolizumab. Plasma tumor antigens CEA and CA27–29 (c), circulating T, B and NK lymphocytes (d) and the cytokines IL18, CXCL10 and granzyme A (GZMA)) (e) were assessed over time during the first exposure to atezolizumab. Upper limit of normal levels for CEA (3 ng/ml) and CA27–29 (38 U/ml) are indicated by the dotted lines (blue: CA27-29; red: CEA). Changes in lymphocyte populations were plotted as ratio to baseline to pre-treatment values

Fig. 3

Evolution of Tumor Microenvironment. Samples collected over time. Images at 100X (a) of tumor infiltrating immune cells (ICs), PDL1 in tumor cells and tumor infiltrating immune cells, CD8 T cells and CD163 macrophages were assessed by hematoxylin& eosin or immunostaining. b Quantification of the parameters in (A) are displayed as a percentage of tumor area and evaluated over time with respect to atezolizumab first exposure. c RNA-based signatures associated with T cells, regulatory T cells, CD8 effector T cells, NK cells, B cells, macrophages, immune checkpoints, cancer associated fibroblasts, cytolytic activity, antigen processing, angiogenesis, and proliferation were derived from RNA-Seq and plotted as PC1 scores and displayed over time. As reference, the aggregated value for the samples from the TNBC cohort in the PCD4989g study (PCD, all) is displayed as box plots representing median, 25th and 75th percentiles and the vertical bars represent range (maximum and minimum). d TNBC subtype classifiers were derived from RNA-Seq for each sample. Heatmap denotes relative RNA expression of genes involved in the subtype classifiers in the analyzed samples. BLIA and BLIS prob.: probability that the samples are BLIA or BLIS

Fig. 4

Characterization of Genomic Landscape Over Time. Samples collected pre- and post-atezolizumab exposure were tested with the FoundationOne® targeted NGS assay. Upper panel: genes with detected single nucleotide variants (SNV). Mutant allele frequencies (MAF) are shown for each specimen. Asterisk (*) indicates that the variant was present at a frequency below the validated reporting threshold. Light gray: predicted somatic mutations, dark gray: predicted germline mutations; Bold: predicted subclonal somatic mutations. Middle panel: genes with detected copy number alterations (CNAs). Numbers indicate the number of copies detected. Asterisk (*) indicates that low-level amplifications were detected below the validated reporting threshold of > 5 copies. No homozygous deletions were observed. Lower panel: tumor mutational burden (TMB) indicated as mutations per megabase