The programmed death protein 1 (PD-1) and its ligand (PD-L1) represent a well-characterized immune checkpoint in cancer, effectively targeted by monoclonal antibodies that are approved for routine clinical use. The regulation of PD-L1 expression is complex, varies between different tumor types and occurs at the genetic, transcriptional and post-transcriptional levels. Copy number alterations of PD-L1 locus have been reported with varying frequency in several tumor types. At the transcriptional level, a number of transcriptional factors seem to regulate PD-L1 expression including HIF-1, STAT3, NF-κΒ, and AP-1. Activation of common oncogenic pathways such as JAK/STAT, RAS/ERK, or PI3K/AKT/MTOR, as well as treatment with cytotoxic agents have also been shown to affect tumoral PD-L1 expression. Correlative studies of clinical trials with PD-1/PD-L1 inhibitors have so far shown markedly discordant results regarding the value of PD-L1 expression as a marker of response to treatment. As the indications for immune checkpoint inhibition broaden, understanding the regulation of PD-L1 in cancer will be of utmost importance for defining its role as predictive marker but also for optimizing strategies for cancer immunotherapy. Here, we review the current knowledge of PD-L1 regulation, and its use as biomarker and as therapeutic target in cancer.

Signal transducer and activator of transcription 3 (STAT3) is an oncogene and multifaceted transcription factor involved in multiple cellular functions. Its role in modifying anti-tumor immunity has been recently recognized. In this study, the biologic effects of STAT3 on immune checkpoint expression and anti-tumor responses were investigated in breast cancer (BC). A transcriptional signature of phosphorylated STAT3 was positively correlated with PD-L1 expression in two independent cohorts of early BC. Pharmacologic inhibition and gene silencing of STAT3 led to decreased Programmed Death Ligand 1 (PD-L1) expression levels in vitro, and resulted as well in reduction of tumor growth and decreased metastatic dissemination in a mammary carcinoma mouse model. The hampering of tumor progression was correlated to an anti-tumoral macrophage phenotype and accumulation of natural-killer cells, but also in reduced accrual of cytotoxic lymphocytes. In human BC, pro-tumoral macrophages correlated to PD-L1 expression, proliferation status and higher grade of malignancy, indicating a subset of patients with immunosuppressive properties. In conclusion, this study provides evidence for STAT3-mediated regulation of PD-L1 and modulation of immune microenvironment in BC.

Cancer immunotherapy has altered the management of human malignancies, improving outcomes in an expanding list of diseases. Breast cancer - presumably due to its perceived low immunogenicity - is a late addition to this list. Furthermore, most of the focus has been on the triple negative subtype because of its higher tumor mutational load and lymphocyte-enriched stroma, although emerging data show promise on the other breast cancer subtypes as well. To this point the clinical use of immunotherapy is limited to the inhibition of two immune checkpoints, Programmed Cell Death Protein 1 (PD-1) and Cytotoxic T-lymphocyte-associated Protein 4 (CTLA-4). Consistent with the complexity of the regulation of the tumor – host interactions and their lack of reliance on a single regulatory pathway, combinatory approaches have shown improved efficacy albeit at the cost of increased toxicity. Beyond those two checkpoints though, a large number of co-stimulatory or co-inhibitory molecules play major roles on tumor evasion from immunosurveillance. These molecules likely represent future targets of immunotherapy provided that the promise shown in early data is translated into improved patient survival in randomized trials. The biological role, prognostic and predictive implications regarding breast cancer and early clinical efforts on exploiting these immune-related therapeutic targets are herein reviewed.

Purpose: PREDIX HER2 is a randomized Phase II trial that compared neoadjuvant docetaxel, trastuzumab, and pertuzumab (THP) with trastuzumab emtansine (T-DM1) for HER2-positive breast cancer. Rates of pathologic complete response (pCR) did not differ between the two groups. Here, we present the survival outcomes from PREDIX HER2 and investigate metabolic response and tumor-infiltrating lymphocytes (TIL) as prognostic factors. Patients and Methods: In total, 202 patients with HER2-positive breast cancer were enrolled and 197 patients received six cycles of either THP or T-DM1. Secondary endpoints included event-free survival (EFS), recurrence-free survival (RFS), and overall survival (OS). Assessment with PET/CT was performed at baseline, after two and six treatment cycles. TILs were assessed manually at baseline biopsies, while image-based evaluation of TILs [digital TILs (DTIL)] was performed in digitized full-face sections. Results: After a median follow-up of 5.21 years, there was no difference between the two treatment groups in terms of EFS [HR = 1.26; 95% confidence interval (CI), 0.54–2.91], RFS (HR = 0.69; 95% CI, 0.24–1.93), or OS (HR = 0.52; 95% CI, 0.09–2.82). Higher SUVmax at cycle 2 (C2) predicted lower pCR (ORadj = 0.65; 95% CI, 0.48–0.87; P = 0.005) and worse EFS (HRadj = 1.27; 95% CI, 1.12–1.41; P < 0.001). Baseline TILs and DTILs provided additional prognostic information to clinical parameters and C2 SUVmax. Conclusions: Long-term outcomes following neoadjuvant T-DM1 were similar to neoadjuvant THP. SUVmax after two cycles of neoadjuvant therapy for HER2-positive breast cancer may be an independent predictor of both short- and long-term outcomes. Combined assessment with TILs may facilitate early selection of poor responders for alternative treatment strategies.

The tumor immune microenvironment (TIME) is an important player in breast cancer pathophysiology. Surrogates for antitumor immune response have been explored as predictive biomarkers to immunotherapy, though with several limitations. Immunohistochemistry for programmed death ligand 1 suffers from analytical problems, immune signatures are devoid of spatial information and histopathological evaluation of tumor infiltrating lymphocytes exhibits interobserver variability. Towards improved understanding of the complex interactions in TIME, several emerging multiplex in situ methods are being developed and gaining much attention for protein detection. They enable the simultaneous evaluation of multiple targets in situ, detection of cell densities/subpopulations as well as estimations of functional states of immune infiltrate. Furthermore, they can characterize spatial organization of TIME—by cell-to-cell interaction analyses and the evaluation of distribution within different regions of interest and tissue compartments—while digital imaging and image analysis software allow for reproducibility of the various assays. In this review, we aim to provide an overview of the different multiplex in situ methods used in cancer research with special focus on breast cancer TIME at the neoadjuvant, adjuvant and metastatic setting. Spatial heterogeneity of TIME and importance of longitudinal evaluation of TIME changes under the pressure of therapy and metastatic progression are also addressed.

Transcriptomic profiles have shown promise as predictors of response to neoadjuvant chemotherapy in breast cancer (BC). This study aimed to explore their predictive value in the advanced BC (ABC) setting. In a Phase 3 trial of first-line chemotherapy in ABC, a fine needle aspiration biopsy (FNAB) was obtained at baseline. Intrinsic molecular subtypes and gene modules related to immune response, proliferation, oestrogen receptor (ER) signalling and recurring genetic alterations were analysed for association with objective response to chemotherapy. Gene-set enrichment analysis (GSEA) of responders vs non-responders was performed independently. Lymphocytes were enumerated in FNAB smears and the absolute abundance of immune cell types was calculated using the Microenvironment Cell Populations counter method. Gene expression data were available for 109 patients. Objective response to chemotherapy was statistically significantly associated with an immune module score (odds ratio (OR)=1.62; 95% confidence interval (CI), 1.03–2.64; P=0.04). Subgroup analysis showed that this association was restricted to patients with ER-positive or luminal tumours (OR=3.54; 95%, 1.43–10.86; P=0.012 and P for interaction=0.04). Gene-set enrichment analysis confirmed that in these subgroups, immune-related gene sets were enriched in responders. Immune-related transcriptional signatures may predict response to chemotherapy in ER-positive and luminal ABC.