Annals of Oncology 29: 2232–2239, 2018 doi:10.1093/annonc/mdy399 Published online 10 September 2018
ORIGINAL ARTICLE
B. Szekely1,2, V. Bossuyt3, X. Li1, V. B. Wali1, G. A. Patwardhan1, C. Frederick1, A. Silber1, T. Park4, M. Harigopal3, V. Pelekanou3, M. Zhang3, Q. Yan1, D. L. Rimm3, G. Bianchini5, C. Hatzis1 & L. Pusztai1* 1 Breast Medical Oncology, Yale Cancer Center, Yale University, New Haven, USA; 2Department of Oncological Internal Medicine and Clinical Pharmacology “B”, National Institute of Oncology, Budapest, Hungary; Departments of 3Pathology; 4Surgery, Yale School of Medicine, New Haven, USA; 5Department of Breast Medical Oncology, Hospital San Raphael, Milan, Italy
*Correspondence to: Prof. Lajos Pusztai, Breast Medical Oncology, Yale Cancer Center, Yale School of Medicine, 333 Cedar St, PO Box 208032, New Haven, CT 06520, USA. Tel: þ1-203-737-6858; E-mail:
[email protected] Note: Results were presented at the 2017 San Antonio Breast Cancer Symposium, San Antonio TX, USA.
Background: Little is known about how the immune microenvironment of breast cancer evolves during disease progression. Patients and methods: We compared tumor infiltrating lymphocyte (TIL) count, programmed death-ligand 1 (PD-L1) protein expression by immunohistochemistry and mRNA levels of 730 immune-related genes using Nanostring technology in primary and metastatic cancer samples. Results: TIL counts and PD-L1 positivity were significantly lower in metastases. Immune cell metagenes corresponding to CD8, T-helper, T-reg, Cytotoxic T, Dendritic and Mastoid cells, and expression of 13 of 29 immuno-oncology therapeutic targets in clinical development including PD1, PD-L1, and CTLA4 were significantly lower in metastases. There was also coordinated down regulation of chemoattractant ligand/receptor pairs (CCL19/CCR7, CXCL9/CXCR3, IL15/IL15R), interferon regulated genes (STAT1, IRF-1,-4,-7, IFI-27,-35), granzyme/granulysin, MHC class I and immune proteasome (PSMB-8,-9,-10) expression in metastases. Immunotherapy response predictive signatures were also lower. The expression of macrophage markers (CD163, CCL2/CCR2, CSF1/CSFR1, CXCR4/CXCL12), protumorigenic toll-like receptor pathway genes (CD14/TLR-1,-2,-4,-5,-6/MyD88), HLA-E, ecto-nuclease CD73/NT5E and inhibitory complement receptors (CD-59,-55,-46) remained high in metastases and represent potential therapeutic targets. Conclusions: Metastatic breast cancers are immunologically more inert than the corresponding primary tumors but some immune-oncology targets and macrophage and angiogenesis signatures show preserved expression and suggest therapeutic combinations for clinical testing. Key words: breast cancer, metastasis, immune surveillance, immune therapy, immune escape
Introduction Cancers evolve through continuous interaction with immune cells in the tumor microenvironment [1]. Greater tumor infiltrating lymphocyte (TIL) count and increased immune-related gene expression are associated with better survival in early stage triplenegative (TNBC), human epidermal growth factor receptor-2 (HER-2) positive and high-risk estrogen receptor (ER) positive breast cancers, even in the absence of any systemic adjuvant therapy [2, 3]. These immune parameters are also associated with greater chemotherapy sensitivity all subtypes which is evident from the high pathologic complete response rates (pCR, i.e.
complete eradication of cancer from the breast and lymph nodes) to preoperative chemotherapy in immune-rich stages I–III breast cancers [4–8]. What genomic features drive high or low immune infiltration in breast cancer remains unclear. A recent study examined associations between tumor clonal heterogeneity, total mutation load, neoantigen load, copy number variations (CNVs), gene- or pathway-level somatic mutations, or germline polymorphisms (SNP) and immune metagene expression in breast cancer subtypes [9]. Surprisingly, in TNBC and HER2positive cancers, high immune gene expression was associated with lower clonal heterogeneity and lower overall mutation,
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Immunological differences between primary and metastatic breast cancer
Original article
Annals of Oncology
Methods Patients and samples Paired formalin fixed paraffin embedded tissue blocks of primary tumor and metastasis were obtained from the Yale Pathology Tissue Services. Samples included both ER positive and ER negative cases. This study was approved by the Yale Cancer Center Human Investigations Committee. Supplementary Table S1, available at Annals of Oncology online presents the clinical pathological details of each sample included in the current analysis. All supplementary tables, available at Annals of Oncology online were deposited in FigShare and are publicly available at https://doi.org/ 10.6084/m9.figshare.6977753.v1.
TIL assessment and programmed death-ligand 1 immunohistochemistry Two independent patient cohorts were used to assess TIL counts and programmed death-ligand 1 (PD-L1) protein expression. Cohort 1 included 45 patients with full sections of paired metastatic and primary tumors. Cohort 2 included tissue microarrays (TMAs) from 55 other patients including 42 paired primary and metastatic lesions. The median time between obtaining the primary tumor tissue and the matching metastatic biopsy was 3.4 years and patients received a median of 1 prior lines of therapy for metastatic breast cancer before the biopsy. Stromal TIL was assessed on hematoxylin eosin stained tissues and was defined as the percentage of tumor stroma area that was occupied by mononuclear inflammatory cells following the scoring guidelines of the ImmunoOncology Biomarker Working Group [11]. PD-L1 immunohistochemistry was carried out using the E1L3N XP rabbit monoclonal antibody (Cell Signaling Technology) as previously reported [12]. PD-L1 positivity was defined as 1% of either tumor or stromal cells staining positive. This is the same threshold as used in metastatic breast cancer trials for patient selection for anti-PD-1 therapy with pembrolizumab [12–14].
mRNA expression analysis For immune gene expression analysis, a total of 31 primary and 17 metastatic formalin fixed paraffin embedded (FFPE) samples from Cohort 1 were used, corresponding to 36 patients (10 ER negative and 26 ER positive) including paired primary and metastatic tissues from 10 patients (one patient had tissues from two different metastases and another had two different biopsies from one primary tumor). Fifty-six percent of primary tumor tissues and 38% of metastatic tissues were surgical resection specimens, the rest were core needle biopsies. Tumor cellularity was estimated by a pathologist from adjacent sections used for TIL and PD-L1 assessment and ranged between 15% and 60% without significant differences between the primary and metastatic cohorts. RNA was extracted from three 10-lm FFPE curls of whole sections using the High Pure RNA Paraffin Kit (Roche Applied Science). The expression of 730 immune-related genes and 40 housekeeping genes were assessed using
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the Nanostring PanCancer Immune Profiling assay (Nanostring Technologies, Inc.). The Nanostring nSolver 2.6 software was used to normalize expression values using housekeeping genes following the manufacturer’s recommendations [15]. Normalized gene expression data are deposited in the Gene Expression Omnibus database (GSE102818). Genes were grouped into 14 immune cell type metagenes (total T, Th1, Treg, Total CD8, exhausted CD8, Cytotoxic T, B, NK, NKCD56, Mastoid cell, CD45, Dendritic cell, macrophage, and neutrophil) and 22 immune functions (supplementary Table S2, available at Annals of Oncology online). The metagene scores were calculated as the geometric mean expression of the member genes [15]. We also examined 27 previously published prognostic [10–16] and immuno therapy response predictive [17–20] metagenes (supplementary Table S3, available at Annals of Oncology online). We calculated these metagene scores following the methods described in the respective publications.
Statistical analysis The differences in TIL counts and PD-L1 protein expression levels between primary and metastatic samples were compared using the Wilcoxon signed-rank test. The differences in mRNA expression levels were assessed using the t-test. The false-discovery rate (FDR) was controlled to 5% using P-values adjusted by the Benjamini–Hochberg method. Unsupervised hierarchical clustering of the log2-transformed normalized expression values of the 730 immune genes was carried out using 1 – Euclidean distance as the similarity metric. Clustering results were displayed as heat maps using log2-transformed, normalized expression values scaled to have mean zero and standard deviation of one. Immune metagene scores were compared between primary and metastatic samples using the Wilcoxon rank-sum test without adjustment for multiple comparisons due to large overlap in signature gene membership. Due to the overall small sample size, separate analysis of ER-positive and -negative cases was not possible.
Results TILs and PD-L1 expression Paired TIL counts were available for 37 and 39 cases in Cohort 1 (Whole Section) and Cohort 2 (TMA), respectively. TIL counts significantly decreased in metastases compared with primary tumor in both cohorts (Figure 1A). Paired PD-L1 staining results were available for 35 and 41 cases in Cohorts 1 and 2, respectively. PD-L1 staining was primarily localized to stromal immune cells rather than tumor cells. The median stromal PD-L1 positivity in metastases and primary tumor was 14% and 52% (P ¼ 0.0004) in Cohort 1, and 7% and 22% (P ¼ 0.03) in Cohort 2 (Figure 1B and C). The overall lower PD-L1 expression in either the primary or metastatic site in the TMA cohort compared with full sections suggests that TMAs underestimate the true PD-L1 positivity. We previously studied the impact of sampling error on immune markers and examined TIL subpopulation counts between biopsies from different regions of the same primary breast cancer. We found that the average counts across multiple fields of view from a single biopsy were representative of the entire cancer, but we also noted large differences between fields of view in the same section which may explain the lesser accuracy of results derived from TMAs [21]. PD-L1 IHC negative cancers in Cohort 1, where mRNA data were also available, showed significantly lower PDL1 mRNA expression (P ¼ 0.007; supplementary Figure S1, available at Annals of Oncology online). Metastatic lesions also had
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neoantigen and CNV loads [9]. Lymphocyte-rich, good prognosis TNBC has significantly fewer genomic aberrations and lower neoantigen counts than lymphocyte-poor TNBC [10]. These results suggest that antitumor immune surveillance in immunerich primary breast cancers may continuously eliminate cancer cells leading to lower clonal heterogeneity and ‘simpler’ genomes in the surviving cancer. Consequently, metastatic lesions, which by definition have escaped immune surveillance at the primary tumor site, may have lower ‘immunogenicity’ than the corresponding primary tumor. The goal of this study was to characterize the immune microenvironment of metastatic lesions compared with that of the corresponding primary breast tumors.
Original article
Annals of Oncology
lower median PD-L1 mRNA expression compared with primary tumors (38 versus 67, FDR-adjusted P value ¼ 0.033) (Table 1).
Immune gene expression RNA was extracted from 31 primary and 17 metastatic samples corresponding to 36 patients (10 ER negative and 26 ER positive, including 11 paired samples) in Cohort 1. Supplementary Figure S2, available at Annals of Oncology online shows a heat map of the normalized expression of all 730 immune genes in all samples. One hundred and twenty-nine genes (18%) showed significantly lower expression (FDR-adjusted P < 0.05) in metastases (supplementary Table S4, available at Annals of Oncology online). Only one gene, glucose-6-phosphate isomerase, a cytoplasmic glycolytic enzyme and secreted tumor motility and angiogenic factor [22], showed increased expression compared with primary tumors. Immune cell metagenes corresponding to activated T cells, CD8 cells, T-helper cells, Regulatory T cells, Cytotoxic cells, Dendritic and Mastoid cells were significantly lower in metastases compared with primary tumors (supplementary Figure S3, available at Annals of Oncology online). We also observed coordinated downregulation of several chemotactic ligand–receptor pairs including CCL5/CCR5, CCL17/CCR4, CCL19/CCR7, CXCL9/ CXCR3, and IL15/IL15R which mediate migration of dendritic cells, B cells, activated T cells, monocytes, and NK cells into peripheral tissues. TILs in metastases also showed significantly lower expression of CD27 and its ligand CD70 as well as CD29 and CD40L that are required for T-cell activation. Expression of activated T-cell transcription factors NFAT-1,-2 as well granzyme, granulysin, IFNc, and interferon regulated genes (STAT1, IRF-1,-4,-7, IFI-27,-35, MX1) were also low consistent with an inactive state of T lymphocytes in metastases. MHC class I (HLA-
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A,-B, and -C) and class II (HLA-DRB3,-DOB, CD74) expression as well as the immune proteasome components TAP1/TAPBP, and PSMB-8,-9,-10 were all significantly lower in metastases indicating impairment in antigen presentation. Overall, among the 22 immune functions represented on the Nanostring panel, T cell, B cell, and NK cell functions, cytotoxicity, chemokine/TNF superfamily expression, immune regulation, and pathogen defense were all significantly lower in metastasis despite normalization for overall lower TIL metagene (supplementary Figure S4, available at Annals of Oncology online). Of 29 selected immunooncology (IO) therapeutic targets in clinical development, 13 showed significantly lower expression in metastases including PD1, PD-L1, and CTLA4 (Table 1). The expression of several previously published [15, 16] prognostic immune gene signatures and pembrolizumab response predictor signatures [17, 18] were also lower in metastasis (Figure 2 and supplementary Figure S5, available at Annals of Oncology online). Collectively, these findings indicate not only an immune depleted but also an immune inert state in metastases (Figure 3). Components of the immune system that are preserved in metastatic lesions, particularly immunosuppressive mechanisms, are of interest because they suggest potential therapeutic strategies. Several macrophage markers (CD68 and CD163) remained high in metastases along with cytokine ligand/receptor pairs that drive M2 differentiation and mediate protumorigenic effects including CCL2/CCR2, CSF1/CSFR1, and CXCR4/CXCL12. The expression of the tumor promoting toll-like receptor axis CD14, TLR-1,-2,-4,-5,-6, and MyD88 [23] were high in metastases. In contrast, expression of TLR-7,-8,-9, which are implicated in antitumor immunity, were low. We also observed high expression of HLA-E, an important ‘self-signal’ that suppresses autoimmunity [24], and CD73/NT5E and ecto-nucleotidase that
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Figure 1. Tumor infiltrating lymphocyte (TIL) and PD-L1 protein expression in paired primary and metastatic cancers assessed on full sections (FSs) and tissue microarrays (TMAs). (A) Percent TIL counts in full sections and TMAs. (B) PD-L1 positivity rates, defined as 1% of stromal or tumor cells showing immunohistochemistry staining. (C) Change in PD-L1 status between the primary and metastatic cohorts.
Original article
Annals of Oncology
Table 1. mRNA expression of IO targets currently in clinical development in primary and metastatic breast cancers Gene names
Median in primary
Fold change of median
FDR-adjusted P-value
1780 1325 30 39 17 26 41 38 29 21 11 12 11
0.67 0.83 0.202 0.294 0.133 0.258 0.53 0.564 0.435 0.439 0.311 0.396 0.44
0.047 0.019 0.003 0.007 0.003 0.003 0.003 0.033 0.053 0.005 0.003 0.008 0.004
6837 1552 851 697 459 367 234 115 169 137 128 43 42 63 56 30
0.793 0.458 0.617 0.746 0.914 0.985 0.858 0.615 0.914 0.854 0.825 0.323 0.479 0.825 0.774 0.779
0.399 0.321 0.377 0.803 0.961 0.786 0.774 0.928 0.991 0.904 0.539 0.226 0.336 0.326 0.165 0.75
Median expression, fold change relative to primary tumor, and FDR-adjusted P-values are shown. FDR, false-discovery rate; IO, immuno-oncology.
generates immunosupressive adenosine [25]. Other potential IO targets preserved in metastatic lesions included the chemokine ligand–receptor pairs CCL-3,-4,-14/CCR1, CX3CL1/CX3CR1, and IL6/IL6R, the chemokine ligands CCL14, CCL23, CXCL16, IL32, IL16, IL18, IL8, signaling molecules STAT-3,-6, JAK2, and regulatory molecules TIM3 and LAG3. Complement mediates important immune effector functions, we observed high levels of inhibitory complement receptor expression including CD59, CD46, and CD55 which prevent formation of complement membrane attack complexes and accelerate complement decay suggesting impaired complement-mediated immune effects in metastatic lesions. Figure 4 summarizes the multiple immune escape mechanisms that we observed in metastatic tissues.
Discussion We detected large-scale differences in the immune microenvironment of primary and metastatic lesions. TIL counts and PD-L1
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protein expression were substantially lower in metastases compared with primary tumors. Similar observations were reported earlier by several smaller studies [26–28]. Our immune gene expression profiling results showed that most immune cell types and immune functions were depleted in metastases. This was also observed in nonmatched cohorts of primary and metastatic cancers in publicly available gene expression data sets [29]. Due to the small sample size, we could not compare immune marker differences across different metastatic organ sites. However, emerging data suggest that lymph node metastases have significantly higher PD-L1 expression than visceral metastasis [30]. The decreased expression of MHC class I and immune proteasome genes coupled with increased expression of HLA-E and reduced dendritic cell presence suggest lesser immunogenicity of metastatic breast cancer cells. However, the acquisition of PD1, PD-L1, and CTLA-4 expression in cancer cells does not appear to be a major mechanism of immune escape in metastatic breast cancer since the expression of these molecules is low [31]. Coordinated downregulation of a broad range of chemotactic and immune activating cytokines and their receptors further contribute to the immune-cell-depleted
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IO targets decreased in metastatic lesions CD276 (B7H3) 2640 JAK1 1596 CD27 146 SLAMF7 132 CTLA4 130 TIGIT 100 KLRC1 78 CD274 (PD-L1) 67 TNFRSF4 (OX40) 66 ICOS 48 TNFRSF9 (CD137) 37 CCR4 30 PDCD1 (PD1) 24 IO targets preserved in metastatic lesions STAT3 8612 CXCR4 3384 CXCL12 1378 JAK2 933 TLR1 502 NT5E (CD73) 373 TLR2 273 TNFRSF18 (GITR) 189 CSF1 185 HAVCR2 (TIM3) 161 IL8 154 IDO1 134 CCR2 88 TLR7 76 LAG3 73 TLR8 39
Median in metastasis
Original article
Annals of Oncology
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Figure 2. Heat map of the expression of selected immune genes that represent tolerance mechanisms in metastatic breast cancers. Log2 transformed mRNA expression levels of immune genes are shown as a heat map for 17 metastatic lesions annotated with estrogen receptor status, organ site, TIL counts, and race. Genes were selected to represent various immune functions and correspond to the schema in Figure 4.
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Annals of Oncology
Original article
Figure 4. Schema of immune escape mechanisms observed in metastatic breast cancer. Genes are grouped by immune functions, red indicates genes with significantly reduced expression and blue indicates genes with preserved expression in metastasis in metastases compared with primary tumors (data are from supplementary Table S3, available at Annals of Oncology online).
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Figure 3. Expression of prognostic and immune checkpoint therapy response predictive signatures in paired primary and metastatic breast cancers. (A) Paired metagene expression levels are shown for 18 immune signatures that have previously been shown to have prognostic or immune therapy response predictive values. (B) Magnified scale of 12 signatures in the lower end of the expression spectrum. Yellow lines indicate significant change between primary and metastatic lesions.
Original article
Funding Breast Cancer Research Foundation (to LP, CH, and DLR), Susan Komen Foundation for the Cure (to LP, grant number SAC160076), Department of Defense Breast Cancer Research Program Awards W81XWH-15-1-0117 (to QY), and Rosztoczy Foundation (to BS).
Disclosure VP is currently an employee of Sanofi Aventis. LP received consultations fees from Merck, Genenetech, Seattle Genetiucs, AstraZeneca, Eisai and Novartis. All remaining authors have declared no conflicts of interest.
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microenvironment in metastasis. In addition to generally lower immune cell infiltration, we observed upregulation of inhibitory complement receptors, increased production of immunosuppressive small molecules (i.e. adenosine) and M2 macrophage markers in metastases indicating an immunosuppressed microenvironment which was also apparent from decreased IFNc signaling and low expression of cytotoxic T cell markers. Our results also identified potential therapeutic strategies to increase the efficacy of IO therapy in metastatic breast cancer. We detected high expression of CSFR1, CXCR4, CXCL12, TIM3, NT5E, STAT3, and IL8. We suggest that targeting these molecules may lead to synergy with PD1/PD-L1 blockade in metastatic breast cancer. Other highly expressed immune suppressive and protumorigenic molecules in the metastatic tissue microenvironment were CD59, CD46, CCL2, CD14, and CXCL16 that represent novel targets for IO drug development. In summary, our data suggest that metastatic breast cancer cells evade immune surveillance through multiple mechanisms including downregulation of a broad range of chemotactic and immune activating cytokines, decreased antigen presentation leading to an immune-cell-depleted microenvironment and upregulation of immunosuppressive and immune evasion mechanisms that result in immune inert environment. These results predict that immune therapy may be more successful in early stage breast cancers rather than in metastatic disease. Importantly, we also identified several IO targets that are present in metastatic breast cancers and can provide the foundation for rational immunotherapy combination strategies.
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Original article