Immunologic Factors Associated with Differential Response to Neoadjuvant Chemoimmunotherapy in Triple-Negative Breast Cancer

Abstract

Background: KEYNOTE-522 resulted in FDA approval of the immune checkpoint inhibitor pembrolizumab in combination with neoadjuvant chemotherapy for patients with early-stage, high-risk, triple-negative breast cancer (TNBC). Unfortunately, pembrolizumab is associated with several immune-related adverse events (irAEs). We aimed to identify potential tumor microenvironment (TME) biomarkers which could predict patients who may attain pathological complete response (pCR) with chemotherapy alone and be spared the use of anti-PD-1 immunotherapy. Methods: Comprehensive immune profiling, including RNA-seq gene expression assessment of 395 immune genes, was performed on matched FFPE tumor samples from 22 stage I-III TNBC patients (14 patients treated with neoadjuvant chemotherapy alone (NAC) and 8 treated with neoadjuvant chemotherapy combined with pembrolizumab (NAC+I)). Results: Differential gene expression analysis revealed that in the NAC group, IL12B and IL13 were both significantly associated with pCR. In the NAC+I group, LCK and TP63 were significantly associated with pCR. Patients in both treatment groups exhibiting pCR tended to have greater tumor inflammation than non-pCR patients. In the NAC+I group, patients with pCR tended to have greater cell proliferation and higher PD-L1 expression, while in the NAC group, patients with pCR tended to have lower cancer testis antigen expression. Additionally, the NAC+I group trended toward a lower relative dose intensity averaged across all chemotherapy drugs, suggesting that more dose reductions or treatment delays occurred in the NAC+I group than the NAC group. Conclusions: A comprehensive understanding of immunologic factors could potentially predict pCR to chemotherapy alone, enabling the avoidance of the unnecessary treatment of these patients with checkpoint inhibitors.

Keywords: breast cancer; chemotherapy; combination therapy; gene expression profiling; immune checkpoint inhibitors; immune profiling; immunotherapy; neoadjuvant; triple-negative; tumor microenvironment.

Figure 1

Distributions of cell proliferation (A), tumor inflammation (B), cancer testis antigen burden (C), and PD-L1 expression measured by RNA-seq (D) for groups treated with neoadjuvant chemotherapy alone (NAC) and neoadjuvant chemotherapy combined with immunotherapy (NAC+I). Individual biomarker values for pCR and non-pCR patients are denoted by overlaid colored points.

Figure 2

Volcano plots showing gene expression differences between pCR and non-pCR groups in the (A) neoadjuvant chemotherapy alone (NAC) and (B) neoadjuvant chemotherapy combined with immunotherapy (NAC+I) treatment groups. Significantly differentially expressed genes with a fold change greater than 2 are shown in red. Those associated with pCR are to the right of the central vertical line and those associated with non-pCR are to the left of the central vertical line.

Figure 3

Chemotherapy dose and pCR in both treatment groups. Violin plots of relative dose intensity (RDI) in the pathological complete response (pCR) and non-pCR groups in each treatment group, neoadjuvant chemotherapy alone (NAC) and neoadjuvant chemotherapy in combination with pembrolizumab immunotherapy (NAC+I), for four chemotherapy drugs: doxorubicin (A), cyclophosphamide (B), paclitaxel (C), carboplatin (D), and the average of all drugs used to treat each patient (E). Also shown are violin plots of the distributions of the number of doses of pembrolizumab administered to patients in the pCR and non-pCR groups within the NAC+I treatment group (F).