- Email: [email protected]
Merkel cell carcinomas infiltrated with CD33+ myeloid cells and CD8+ T cells are associated with improved outcome
Accepted Manuscript + + Merkel cell carcinomas infiltrated with CD33 myeloid cells and CD8 T cells are associated with improved outcome Thibault Kervarrec, MD MSc, Pauline Gaboriaud, Patricia Berthon, PhD, Julia Zaragoza, MD, David Schrama, PhD, Roland Houben, PhD, Yannick Le Corre, MD, Eva Hainaut-Wierzbicka, MD, Francois Aubin, MD PhD, Guido Bens, MD PhD, Jorge Domenech, PhD, Serge Guyétant, MD PhD, Antoine Touzé, PhD, Mahtab Samimi, MD PhD PII:
S0190-9622(17)32867-0
DOI:
10.1016/j.jaad.2017.12.029
Reference:
YMJD 12194
To appear in:
Journal of the American Academy of Dermatology
Received Date: 13 September 2017 Revised Date:
6 December 2017
Accepted Date: 7 December 2017
Please cite this article as: Kervarrec T, Gaboriaud P, Berthon P, Zaragoza J, Schrama D, Houben R, Le Corre Y, Hainaut-Wierzbicka E, Aubin F, Bens G, Domenech J, Guyétant S, Touzé A, Samimi M, Merkel + + cell carcinomas infiltrated with CD33 myeloid cells and CD8 T cells are associated with improved outcome, Journal of the American Academy of Dermatology (2018), doi: 10.1016/j.jaad.2017.12.029. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
Article type: Original article
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Institutional review board: The local Ethics Committee of Tours (France) approved the
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study (N° ID RCB2009-A01056-51)
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Thibault Kervarrec MD MSc1,2,3, Pauline Gaboriaud2, Patricia Berthon PhD2, Julia Zaragoza MD4, David Schrama PhD3, Roland Houben PhD3, Yannick Le Corre MD5, Eva Hainaut-Wierzbicka MD6,, Francois Aubin MD PhD7, Guido Bens MD PhD8 , Jorge Domenech PhD9, Serge Guyétant MD PhD1,2, Antoine Touzé PhD2 and Mahtab Samimi MD PhD2,3
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(1) Université Francois Rabelais, CHU de Tours, Departement of Pathology, avenue de la République, 37170 Chambray-les-tours, France (2) Université Francois Rabelais, “Biologie des infections à polyomavirus” team, UMR INRA ISP 1282, 31 avenue Monge, 37200 Tours, France (3) Department of Dermatology, Venereology and Allergology, University Hospital Würzburg, Josef-Schneider-Straße 2, 97080 Würzburg, Germany (4) Université Francois Rabelais, CHU de Tours, Departement of Dermatology, avenue de la République, 37170 Chambray-les-tours, France (5) LUNAM Université, CHU Angers, Departement of Dermatology, 4 rue Larrey, 49933 Angers, France (6) Université de Poitiers, CHU de Poitiers, Departement of Dermatology, 2 rue de la Milétrie, 86021 Poitiers, France (7) Université de Franche Comté, CHU Besançon, Departement of Dermatology, EA3181, IFR133, 2 boulevard Fleming, 25030 Besançon, France (8) CHR d’Orléans, Departement of Dermatology, 14 avenue de l’hopital, 45100 Orléans, France (9) Université Francois Rabelais, CHU de Tours, Departement of Hematology, boulevard Tonnelé, 37200, Tours France
Corresponding authors: Dr Mahtab Samimi Dermatology Department, Hospital of Tours, avenue de la République, 37170, Chambray-lestours, France Email: [email protected] Fax: +33 247478247/Tel :+33 247474625
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Grant numbers and sources of support: Grant to project POCAME, Cancéropole Grand Ouest-Région Centre Val de Loire (France)
Conflict of Interest: The authors have no conflict of interest to declare. Statement on prior presentation: none Reprint request: none Manuscript Word count (Excluding capsule summary, abstract, references, figures, and tables): 2552 Abstract word count: 200 Capsule summary word count: 50 References: 34 Figures: 4 Supplementary Figures: 0 Tables: 3 Supplementary Tables: 3 Attachments: Supplemental Methods : 4, STROBE statement and RECORD Checklist Key words : myeloid cells, macrophages, Merkel cell carcinoma, immune infiltrate, CD33, PD-L1
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Title: Merkel cell carcinomas infiltrated with CD33+ myeloid cells and CD8+ T cells are associated with improved outcome
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ACCEPTED MANUSCRIPT Abstract: Background: Merkel cell carcinoma (MCC) is a rare tumor of the skin with an aggressive
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behavior. Immunity is the main regulator of MCC development, and many interactions
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between lymphocytes and tumor cells have been proven. However, the impact of tumor-
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infiltrating myeloid cells (TIMs) needs better characterization.
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Objective: To characterize TIMs in MCC and their association with other immune effectors
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and patient outcome.
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Methods: MCC cases were reviewed from a historical/prospective cohort. In all, 103 triplicate
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tumor samples were included in a tissue microarray. Macrophages, neutrophils and myeloid-
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derived suppressor cells were characterized by the following markers: CD68, CD33, CD163,
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CD15, and CD33+/HLA-DR-. The association between these populations and PD-L1
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expression, CD8 infiltrates and vascular density was assessed. Impact on survival was
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analyzed by log-rank tests and a Cox multivariate model.
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Results: The median density of macrophages was 216/mm2. CD68+ and CD33+ macrophage
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densities were associated with CD8 infiltrates and PD-L1 expression. In addition, MCC
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harboring infiltration of CD8 T cells and brisk CD33 myeloid-cell infiltrates was significantly
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and independently associated with improved outcome (MCC recurrence and death).
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Limitations: Sampling bias and retrospective design.
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Conclusion: Infiltration of CD33 myeloid cells and CD8 lymphocytes defines a subset of
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MCC associated with improved outcome.
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Capsule summary:
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I) What is already known on this topic:
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Brisk infiltration of CD8 lymphocytes represents an efficient immune response in patients
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with Merkel cell carcinoma.
76 2)What this study adds to our knowledge:
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In this study, tumors with brisk infiltration of both CD33 myeloid cells and CD8 lymphocytes
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were associated with an improved outcome.
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3)How this knowledge impacts patient care:
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Patients with tumors lacking brisk CD33 infiltration may be considered to be at higher risk.
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ACCEPTED MANUSCRIPT Introduction
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Merkel cell carcinoma (MCC) is a rare and aggressive tumor of the skin and the main risk
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factors are age, UV exposure and immunosuppression. The diagnosis of MCC relies on the
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association of histological features of small cell neuroendocrine carcinoma and
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immunohistochemical expression of cytokeratin 20 and/or neuroendocrine markers1. In 2008,
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Feng et al. discovered Merkel cell polyomavirus (MCPyV) integration in a large proportion of
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MCC tumors2 and MCPyV is currently considered as the main etiologic agent of MCC.
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Increasing evidence supports the crucial role of cellular immune responses in controlling
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MCC progression. Brisk intra-tumoral CD8 lymphoid infiltrates have been related to
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improved outcome in MCC cohorts3–5, which suggests effective anti-tumoral–specific
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cytotoxic responses in at least some MCC cases. However, most MCC cases display immune
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evasion from anti-tumoral effectors by excluding lymphocytes at the periphery of the tumor
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(“stalling phenomenon”) and/or by inhibition of the cytotoxic responses4–7.
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Tumor-infiltrating myeloid cells (TIMs) have been suggested to be involved in such immune
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regulation in MCC8,9. Indeed TIMs can affect tumor development by modulating immune
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responses
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enhancing vascular density10–12. Recruited immune-efficient M1-
polarized macrophages are progressively replaced during tumor development by tumor-
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associated macrophages closely related to the M2 tolerogenic subset. Tumor-secreted factors
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can block the differentiation process of myeloid progenitors, thereby leading to constitution of
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an immunosuppressive myeloid subset, myeloid-derived suppressor cells (MDSCs)13.
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In MCC, TIMs, previously characterized by immunohistochemistry5,14 assessing CD68+ and
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CD163+ macrophages, were found to be major components of the tumoral microenvironment
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and were evidenced as the main source of PD-L1 (programmed death ligand 1), a component
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of the tolerogenic PD-1/PD-L1 pathway currently targeted by avelumab immunotherapy15.
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ACCEPTED MANUSCRIPT One recent study8 of 12 MCC samples revealed that MCC tumors were also infiltrated by
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CD33-expressing cells, suspected to be tumor-infiltrating MDSCs.
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In this study, we investigated TIMs in a cohort of MCC patients by using the pan-macrophage
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marker CD68, the M2 macrophage marker CD163 as well as CD33 as an early differentiation
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myeloid marker. CD15 was used as immunochemical neutrophil marker and an innovative
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combination of immunostaining was developed to identify tumor-infiltrating MDSCs. TIM
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subsets were investigated by tumoral characteristics, composition of the intra-tumoral
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microenvironment (CD8 infiltration, PD-L1 expression, tumoral vascular density, MCPyV
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detection) and patient outcome (MCC recurrence and overall survival).
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Study period, data and settings
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MCC cases were recruited from an ongoing historical/prospective cohort of MCC patients
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with a diagnosis of MCC established between 1998 and 2015 from 5 French hospital centers
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(Local Ethic Committee, Tours, France, no. ID RCB2009-A01056-51). Cohort inclusion
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criteria were previously reported16. Only cases with sufficient available formalin-fixed and
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paraffin-embedded (FFPE) samples were included.
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Clinical and follow-up data
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Age, sex, American Joint Committee on Cancer (AJCC) 2010 stage at time of surgery17,
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location of samples (primary tumors or metastases), immunosuppression (HIV infection,
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organ transplant recipients, hematological malignancies)18 and follow-up data were collected
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from patient files.
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131 Tissue microarray establishment
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Inflammatory immune cells are localized in peri-tumoral or intra-tumoral areas of the tumor
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microenvironment (TME), but prognosis is related mostly to the intra-tumoral components3,4.
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Therefore, we focused the study on intra-tumoral areas. Briefly, these areas were selected on
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hematoxylin/phloxin/safran-stained (HPS) sections by using the following criteria: central
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intra-tumoral area, lack of necrosis or fibrous septa and representative immune infiltrates after
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overall slide evaluation on HPS. The selected areas were extracted as a 1-mm tissue core and
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mounted in triplicate by using a semi-motorized tissue arrayer (MTA booster OI v2.00,
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Alphelys).
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Immunohistochemistry
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Immunohistochemistry involved use of the BenchMark XT Platform as instructed. Targeted
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population markers, antibodies and dilutions are summarized in Supplemental Method 1.
144 Assessment of tumor-infiltrating immune cells
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Myeloid cells were counted on 5 high-power fields of the “intra-tumor area” defined as the
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tumor area with few fibrous septa and no necrosis. Only immune cells with obvious nuclei
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and adequate morphology (macrophages or neutrophils) in contact with tumor cells and not
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within vessels were considered in the analysis4. The representativeness of our count was
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validated on a first set of overall slides as shown in Supplemental Method 2. Secondly cells
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were counted by 2 pathologists on TMA slides (SG, TK). When cell counts differed by more
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than 10%, a third count was performed by the 2 pathologists together. Mean cell count was
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used for further analysis. Density of CD8 lymphocytes was graded as described4. Cases with
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less than 5 representative high-power foci were excluded as not interpretable.
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Assessment of MDSCs by double-staining immunochemistry
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MDSCs were previously investigated by flow cytometry by the current phenotype
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CD33+/CD11b+/HLA-DR-/low13. Because both CD33 and CD11b are myeloid lineage markers,
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with CD33 the earlier one19, we focused on CD33/HLA-DR double staining. To detect cells
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expressing CD33 without HLA-DR, we used a strong dark chromogenic component for HLA-
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DR staining. This component, the NBT/BCIP, masks the others in co-localization cases and
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allowed for excluding all cells expressing HLA-DR. Procedures and controls are described in
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Supplemental Method 3.
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To investigate MDSC location, cases with the highest CD33+/HLA-DR- cell count were
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reviewed on overall slide staining, and cells were counted on 3 fields of the intra-tumor area,
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area of necrosis, and fibrous septa.
167 Assessment of vascular density
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After CD34 immunostaining, slides were scanned by using a Nanozoomer (Hamamatsu).
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Digitalized slides were analyzed by using ImageJ software20 as described in Supplemental
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Method 4.
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172 Assessment of MCPyV status
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MCPyV status of the tumors was assessed by the expression of the large T antigen by using
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CM2B4 antibody and the Allred score, as described21,22. Briefly, a semi-quantitative score
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was used to assess intensity and proportion of large T-antigen–expressing cells; tumors with
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scores > 2 were considered MCPyV-positive22.
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Statistical Analyses
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Continuous data were described with median and quartiles (Q1-Q3). Categorical data were
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described with number and percentage of interpretable cases. Associations were assessed by
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two-tailed Fisher exact test for categorical data and non parametric Mann-Whitney test for
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continuous data. Recurrence-free survival and overall survival related to patient
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characteristics were analyzed by log-rank test and represented by Kaplan-Meier curves.
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Univariate and multivariate Cox proportional-hazards regression was used to identify factors
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associated with MCC recurrence and death, estimating hazard ratios (HRs) and 95%
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confidence intervals (CIs). Overall deaths were considered events and living patients were
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censored on the date of last follow up. Covariates were identified as potential prognostic
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confounders with p ≤ 0.20 on Cox univariate regression analysis and then included in the
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multivariate Cox analysis. Statistical analysis involved use of XL-Stat-Life (Addinsoft,
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Paris, France). P < 0.05 was considered statistically significant, except with multiple testing
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when only p <0.01 was considered significant.
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Results
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Density of TIM populations in MCC tumors
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Among the 242 MCC patients included in the cohort, 103 cases with sufficient available
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FFPE samples were included (Figure 1: Flow chart). The number of interpretable cases
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according to each myeloid marker is available in Table 1. The median number of CD68-,
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CD163- and CD33-expressing myeloid cells was 216 cells/mm2 (Q1:131-Q3:323), 120
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cells/mm2 (Q1:76-Q3:191) and 83 cells/mm2 (Q1:31-Q3:213), respectively. Overall, 66/95
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interpretable samples (69%) showed tumor-infiltrating CD15-expressing neutrophils (median
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density: 2.5 cells/mm2 (Q1:0-Q3:4)). Only 5/84 interpretable MCC samples (7%) showed
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CD33+/HL-DR- cells, with a median of 5 cells/mm2 in positive cases (Q1:3-Q3:5). On overall
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slide examination of these latter cases, MDSCs were only rarely located in intra-tumor areas
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without necrosis (median: 2.8 cells/mm2 (Q1:0-Q3:5)) versus with necrosis (median: 66
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cells/mm2, (Q1:39-Q3:81), p<0.01) or in fibrous septa surrounding the tumor (median: 57
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cells/mm2 (Q1:11-Q3:112)), p<0.01) as shown in Figure 2.
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Association of TIMs with baseline clinical characteristics
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Median age of patients was 77 years (Q1:69, Q3:84), 42% of the population (N=42/100) were
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male and 14% (N=10/72) were immunosuppressed. Regarding AJCC staging on diagnosis,
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patients were classified as having stage 1 (N=21 (25%)), stage 2 (N=22 (26%)), stage 3
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(N=39 (45%)) and stage 4 disease (N=3 (4%)), respectively.
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Patient baseline clinical characteristics by density of TIMs (macrophages, neutrophils,
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MDSCs) are provided in Supplemental Table S1. Briefly, TIM infiltrates were dichotomized
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as “brisk” and “non-brisk” by median count excepted for MDSCs which were dichotomized
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as “MDSC-positive” (n=5) and “MDSC-negative”tumors) (n=79). TIMs were not associated
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with clinical baseline characteristics or MCPyV status, excepted for neutrophil infiltrates
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which were more frequent in advanced tumor stages (Table S1).
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TIMs are closely associated with other components of the TME
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The association
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microenvironment is reported in Table 1 and illustrated in Figure 3.
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MCC tumors with CD8 infiltrates (score 1-5, n=62, 63% of cases) harbored brisker TIM
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infiltrates than CD8-negative tumors (score 0, n=36, 37% of cases) (p<0.001 for CD68,
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CD163 and CD33 myeloid cells) (Table 1). MCC cases with the highest CD8 infiltrates
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(scores 2-5, n=11, 11%) were significantly associated with brisk CD68, CD163 and CD33
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myeloid-cell infiltration (Fisher’s exact test, p=0.0002, 0.02 and 0.001, respectively).
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Most MCC tumors (61 cases, 78%) showed PD-L1-positive myeloid cells within their
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microenvironment (Figure 3). Cases were dichotomized as “brisk” and “non-brisk” according
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to the median count of PD-L1-positive myeloid cells. MCC tumors with brisk CD68 and
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CD33 infiltrates frequently showed brisk PD-L1-positive cells in their microenvironment
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(Fisher’s exact test, p=9.10-3and p=3.10-3 respectively) (Table 1).
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The vascular area occupied 1.5% of the tumor surface (Q1:0.9-Q3:1.9%), with no significant
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association with TIM infiltrates (Table 1).
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Association between tumor immune infiltrates and patient’s outcome
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Factors associated with survival on univariate analysis are reported in Table 2. On univariate
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analysis, only female sex, as previously reported23–26,and CD33 TIM density were associated
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with decreased risk of recurrence (HR 0.39, 95% CI 0.19-0.83, p=0.014 and HR 0.35, 95% CI
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0.15-0.83, p=0.016 respectively) and death (HR 0.40, 95% CI 0.19-0.82, p=0.012 and HR 0.44,
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95%CI 0.20-0.99, p=0.047 respectively) (Table 2). Covariates identified as potential prognostic
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ACCEPTED MANUSCRIPT confounders (p ≤ 0.20) on Cox univariate regression analysis were included in the multivariate
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Cox analysis. In this model (Supplemental Table 2), only AJCC stage was associated
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independently with death (HR 3.90, 95%CI 1.20-12.70, p=0.024). Interestingly, among myeloid
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infiltrates, brisk CD33 infiltrates showed a trend towards association with decreased risk of
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recurrence (HR 0.35, 95% CI 0.11-1.00, p=0.051) and death (HR 0.40, 95%CI 0.14-1.25,
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p=0.083).
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Merkel cell carcinoma infiltrated with CD33+ myeloid cells and CD8+ T cells are associated with improved outcome
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MCC outcome5-7. Although we did not evidence such association in our study (Figure 4), we
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observed a strong correlation between infiltrating CD8 infiltrates and CD33 myeloid cells
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(Table 1) as well as an impact of CD33 myeloid cells on outcome (Figure 4). We therefore
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hypothesized that concomitant intra-tumoral infiltration by these two cell populations would
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impact outcome. 35 MCC cases (43% of interpretable cases) harbored both brisk CD33
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infiltrates (> median) together with CD8 T-cell infiltrates (scores 1-5). Characteristics of this
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population are reported in Supplemental Table 3. These cases had a mean time to death of
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97.5±16.4 months (vs 32.3±3.7 months for other patients, p=0.049, log-rank test) and mean time
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to recurrence of 120.3±15.0 months (vs 30.3±4.6 months for other patients, p=0.007, log-rank
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test) (Figure 4). This subset was therefore assessed in a Cox multivariate model including
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previous covariates identified in the univariate analysis (age, sex, AJCC stage,
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immunosuppression and MCPyV status). In this model, such subset of MCC cases were
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associated with both decreased risk of recurrence (HR 0.22, 0.008-0.61, p=0.004) and decreased
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risk of death (HR 0.28, 0.1-0.83, p=0.022). (Table 3).
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We investigated intra-tumoral infiltrating myeloid cells in 103 MCC tumors, together with
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CD8 infiltrates, vascular density and PD-L1 expression in the microenvironment. All MCC
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tumors were infiltrated with macrophages. Brisk CD8 infiltration and PD-L1 expression were
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associated with intra-tumoral CD68 myeloid infiltrates, as well as CD33 myeloid infiltrates.
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These recently described inta-tumoral CD33+ cells were not found to be myeloid-derived
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suppressor cells, but are likely to yield clinical relevance. Indeed, the subset of MCC cases
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with both CD8 T-cell infiltration and brisk CD33 infiltrates showed improved outcome.
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Previous reports have described the presence of CD68+ macrophages in most MCC cases, in
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the same proportion or even exceeding that of lymphoid cells27,28–30. CD68+ macrophages
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were found located at the periphery of the tumor and in intra-tumoral areas29,30 and we
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focused on intra-tumoral spots, considered areas of privileged immune responses4. In this
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setting, myeloid infiltrating cells consisted of CD68+ and CD163+ cells as previously
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described27,28–30 but also a high number of CD33+ myeloid cells. Such CD33+ myeloid cells
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were recently reported in the MCC microenvironment in an immunochemical study of 14
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tumor samples8. CD33 is a trans-membranous protein that belongs to the sialic acid receptor
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family (Sialic acid-binding immunoglobulin-type lectins (SIGLEC)). This protein is used as
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an early myeloid differentiation marker,19 expressed at various levels by both neutrophil and
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monocyte precursors, with further downregulation during cell maturation in peripheral
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tissues31,32. CD33 has also been suggested as an MDSC marker33 thus leading to the
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hypothesis that CD33+ cells infiltrating MCC tumors were actually MDSCs8. Indeed, a
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putative role for MDSCs was previously suggested as acting to exclude lymphocytes from
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MCC intra-tumoral areas (“stalling phenomenon”) 6. Therefore, along such lines, we expected
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to observe a negative relation between myeloid infiltrates, especially CD33 myeloid cells, and
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CD8 T-lymphocyte infiltrates in the intra-tumoral MCC microenvironment. By contrast, we
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infiltrates.
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To characterize this CD33 subset further, we developed an innovative immunochemistry
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staining protocol to visualize MDSCs. Previously, MDSC identification in FFPE tissues was
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proposed with only CD3334 or the association of several slide stainings33. Here, we used an
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immunohistochemical approach based on a double enzymatic staining in a unique cut-FFPE
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sample with no co-localization required. This procedure allowed us to identify putative
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MDSCs harboring a CD33+/HLA-DR- phenotype in only 5 MCC cases. Variations in MDSC
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nature between peripheral and intra-tumoral areas have been demonstrated11. Indeed, overall
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staining of our 5 MCC cases revealed fibrous septa distant from the tumor areas as privileged
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sites of CD33+/HLA-DR- cells. Regarding intra-tumoral areas, MDSC were identified in
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necrosis and their characteristic large-cell monocytoid morphology allowed us to rule out
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artefactual staining due to necrosis (Figure 2). In contrast, most of the tumor-infiltrating
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CD33+ cells in the non-necrotic intra-tumoral areas actually expressed HLA-DR, and thus
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were not likely to be MDSCs. In line with this, these tumor-infiltrating CD33+ cells are not
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likely to exert immunosuppressive effects as they were found to be associated with a subset of
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MCC cases with improved outcome.
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Previous studies failed to reveal an impact of myeloid populations on MCC outcome5,27,14.
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Here, we reveal the prognostic relevance of the concomitant intra-tumoral infiltration by brisk
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CD33+ myeloid cells and CD8+ tumor-infiltrating lymphocytes. Taken together, their close
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correlation with CD8 infiltrates; their expression of HLA-DR, part of the class II major
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histocompatibility complex; and their positive impact on outcome led us to hypothesize that
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such CD33-expressing tumor-infiltrating macrophages contribute to an efficient anti-tumoral
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immune response.
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ACCEPTED MANUSCRIPT The subset of MCC cases with brisk CD33 TIMs and CD8 T-lymphocyte infiltrates identified
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in our study did not display other specific clinical features, were not associated with MCPyV
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status but harbored frequent PD-L1 expression in the microenvironment. CD33+/HLA-DR+
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infiltrating myeloid cells therefore appears as a potential component of the PD-L1–expressing
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immune infiltrates. This observation led us to distinguish two classes of tumors: 1) CD33 high
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/CD8
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PD1/PD-L1 blockage therapy and 2) other tumors with low immune infiltrates and few
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therapeutic targets.
infiltrating tumors associated with improved outcome that could be targeted by
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325 Acknowledgments:
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The authors express their sincerest thanks to the patients who gave their approval for use of
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their data in the study. We also thank Pr G Fromont (Tours, France) and Roseline Guibon
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(Tours, France) for their help and contributions.
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Abbreviations:
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AJCC: American Joint Committee on Cancer.
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CD: Cluster of differentiation.
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CI: Confidence interval.
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HPS: Hematein, phloxin, safran.
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MCC: Merkel cell carcinoma.
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MCPyV: Merkel celll Polyomavirus.
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MDSC: Myeloid derived supressor cells.
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PD-L1: Programmed death-ligand 1.
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TIM: Tumor infiltrating myeloid cells.
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TMA: Tissue micro array.
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ACCEPTED MANUSCRIPT Legends
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Figure 1: Flow Chart
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Figure 2: Illustration of myeloid-derived suppressor cell (MDSC) immunostaining in Merkel
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cell carcinoma. a) details of CD33+, HLA-DR- (green) cells, b) presence of CD33+/ HLA-DR-
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(green) cells in areas of necrosis, c: HLA-DR–expressing tumor-infiltrating myeloid cells
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(TIMs) in the intratumoral area, d) admixture of CD33+/HLA-DR- and HLA-DR–expressing
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cells in fibrous septa surrounding the tumor.
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Figure 3: Representative illustrations of immunostaining in both high-infiltrated (a,c,e,g) and
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non-infiltrated (b,d,f,h) Merkel cell carcinoma tumors: CD68 macrophages (a,b), CD33
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macrophages (c,d), PD-L1–expressing TIMs (e,f) and CD8 infiltrates (g,h).
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Figure 4: Kaplan-Meier survival curves for the Merkel cell carcinoma population by level of
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CD8, CD33 and CD33/CD8 infiltrates. A: recurrence-free survival, B: overall survival.
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Table 1: Merkel cell carcinoma microenvironment by tumor-infiltrating myeloid cell density.
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Table 2. Univariate analysis of factors associated with Merkel cell carcinoma recurrence and
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death
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Table 3 Multivariate Cox proportional-hazard analysis of factors associated with Merkel cell
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carcinoma recurrence and death
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Supplementary Method 1: Antibodies used and dilution.
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Supplemental Method 2: Assessment of the reproducibility of the immune cells count in a
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validation cohort of overall slide stained cases.
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controls.
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Supplemental Method 4: Measurement of vascular density.
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Supplemental Table 1. Baseline clinical characteristics of patients with Merkel cell
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carcinoma by tumor-infiltrating myeloid cell density.
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Supplemental Table 2: Multivariate Cox proportional-hazard analysis of factors associated
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with Merkel cell carcinoma recurrence and death.
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Supplemental Table 3: Characteristics of Merkel cell carcinoma subset with CD33 brisk /
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CD8 positive infiltrates.
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References: 1. Kuwamoto, S. Recent advances in the biology of Merkel cell carcinoma. Hum. Pathol. 42, 1063–1077 (2011). 2. Feng, H., Shuda, M., Chang, Y. & Moore, P. S. Clonal integration of a polyomavirus in human Merkel cell carcinoma. Science 319, 1096–1100 (2008). 3. Paulson, K. G. et al. Transcriptome-wide studies of merkel cell carcinoma and validation of intratumoral CD8+ lymphocyte invasion as an independent predictor of survival. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 29, 1539–1546 (2011). 4. Paulson, K. G. et al. CD8+ lymphocyte intratumoral infiltration as a stage-independent predictor of Merkel cell carcinoma survival: a population-based study. Am. J. Clin. Pathol. 142, 452–458 (2014). 5. Sihto, H. et al. Tumor infiltrating immune cells and outcome of Merkel cell carcinoma: a population-based study. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 18, 2872–2881 (2012). 6. Afanasiev, O. K. et al. Vascular E-selectin expression correlates with CD8 lymphocyte infiltration and improved outcome in Merkel cell carcinoma. J. Invest. Dermatol. 133, 2065–2073 (2013). 7. Dowlatshahi, M. et al. Tumor-specific T cells in human Merkel cell carcinomas: a possible role for Tregs and T-cell exhaustion in reducing T-cell responses. J. Invest. Dermatol. 133, 1879–1889 (2013). 8. Mitteldorf, C., Berisha, A., Tronnier, M., Pfaltz, M. C. & Kempf, W. PD-1 and PD-L1 in neoplastic cells and the tumor microenvironment of Merkel cell carcinoma. J. Cutan. Pathol. (2017). doi:10.1111/cup.12973 9. Vandeven, N. & Nghiem, P. Rationale for immune-based therapies in Merkel polyomavirus-positive and -negative Merkel cell carcinomas. Immunotherapy 8, 907–921 (2016). 10. Elliott, L. A., Doherty, G. A., Sheahan, K. & Ryan, E. J. Human Tumor-Infiltrating Myeloid Cells: Phenotypic and Functional Diversity. Front. Immunol. 8, 86 (2017). 11. Kumar, V., Patel, S., Tcyganov, E. & Gabrilovich, D. I. The Nature of MyeloidDerived Suppressor Cells in the Tumor Microenvironment. Trends Immunol. 37, 208–220 (2016). 12. Granot, Z. & Jablonska, J. Distinct Functions of Neutrophil in Cancer and Its Regulation. Mediators Inflamm. 2015, 701067 (2015). 13. Talmadge, J. E. & Gabrilovich, D. I. History of myeloid-derived suppressor cells. Nat. Rev. Cancer 13, 739–752 (2013). 14. O’Reilly, D., Quinn, C. M., El-Shanawany, T., Gordon, S. & Greaves, D. R. Multiple Ets factors and interferon regulatory factor-4 modulate CD68 expression in a cell typespecific manner. J. Biol. Chem. 278, 21909–21919 (2003). 15. Kaufman, H. L. et al. Avelumab in patients with chemotherapy-refractory metastatic Merkel cell carcinoma: a multicentre, single-group, open-label, phase 2 trial. Lancet Oncol. 17, 1374–1385 (2016). 16. Gardair, C. et al. Somatostatin Receptors 2A and 5 Are Expressed in Merkel Cell Carcinoma with No Association with Disease Severity. Neuroendocrinology 101, 223–235 (2015). 17. Harms, K. L. et al. Analysis of Prognostic Factors from 9387 Merkel Cell Carcinoma Cases Forms the Basis for the New 8th Edition AJCC Staging System. Ann. Surg. Oncol. 23, 3564–3571 (2016). 18. Asgari, M. M. et al. Effect of host, tumor, diagnostic, and treatment variables on outcomes in a large cohort with Merkel cell carcinoma. JAMA Dermatol. 150, 716–723 (2014).
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19. Ferlazzo, G., Spaggiari, G. M., Semino, C., Melioli, G. & Moretta, L. Engagement of CD33 surface molecules prevents the generation of dendritic cells from both monocytes and CD34+ myeloid precursors. Eur. J. Immunol. 30, 827–833 (2000). 20. Ozerdem, U., Wojcik, E. M., Barkan, G. A., Duan, X. & Erşahin, Ç. A practical application of quantitative vascular image analysis in breast pathology. Pathol. Res. Pract. 209, 455–458 (2013). 21. Houben, R. et al. An intact retinoblastoma protein-binding site in Merkel cell polyomavirus large T antigen is required for promoting growth of Merkel cell carcinoma cells. Int. J. Cancer 130, 847–856 (2012). 22. Moshiri, A. S. et al. Polyomavirus-Negative Merkel Cell Carcinoma: A More Aggressive Subtype Based on Analysis of 282 Cases Using Multimodal Tumor Virus Detection. J. Invest. Dermatol. (2016). doi:10.1016/j.jid.2016.10.028 23. Iyer, J. G. et al. Relationships among primary tumor size, number of involved nodes, and survival for 8044 cases of Merkel cell carcinoma. J. Am. Acad. Dermatol. 70, 637–643 (2014). 24. Harrington, C. & Kwan, W. Outcomes of Merkel cell carcinoma treated with radiotherapy without radical surgical excision. Ann. Surg. Oncol. 21, 3401–3405 (2014). 25. Bhatia, S. et al. Adjuvant Radiation Therapy and Chemotherapy in Merkel Cell Carcinoma: Survival Analyses of 6908 Cases From the National Cancer Data Base. J. Natl. Cancer Inst. 108, (2016). 26. Albores-Saavedra, J. et al. Merkel cell carcinoma demographics, morphology, and survival based on 3870 cases: a population based study. J. Cutan. Pathol. 37, 20–27 (2010). 27. Lipson, E. J. et al. PD-L1 expression in the Merkel cell carcinoma microenvironment: association with inflammation, Merkel cell polyomavirus and overall survival. Cancer Immunol. Res. 1, 54–63 (2013). 28. Werchau, S., Toberer, F., Enk, A., Dammann, R. & Helmbold, P. Merkel cell carcinoma induces lymphatic microvessel formation. J. Am. Acad. Dermatol. 67, 215–225 (2012). 29. Walsh, N. M. et al. A morphological and immunophenotypic map of the immune response in Merkel cell carcinoma. Hum. Pathol. 52, 190–196 (2016). 30. Wheat, R. et al. Inflammatory cell distribution in primary merkel cell carcinoma. Cancers 6, 1047–1064 (2014). 31. Forsyth, R. G. et al. CD33+ CD14- phenotype is characteristic of multinuclear osteoclast-like cells in giant cell tumor of bone. J. Bone Miner. Res. Off. J. Am. Soc. Bone Miner. Res. 24, 70–77 (2009). 32. Lock, K., Zhang, J., Lu, J., Lee, S. H. & Crocker, P. R. Expression of CD33-related siglecs on human mononuclear phagocytes, monocyte-derived dendritic cells and plasmacytoid dendritic cells. Immunobiology 209, 199–207 (2004). 33. Liu, W.-R. et al. PKM2 promotes metastasis by recruiting myeloid-derived suppressor cells and indicates poor prognosis for hepatocellular carcinoma. Oncotarget 6, 846–861 (2015). 34. Cui, T. X. et al. Myeloid-derived suppressor cells enhance stemness of cancer cells by inducing microRNA101 and suppressing the corepressor CtBP2. Immunity 39, 611–621 (2013).
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Table 1. Merkel cell carcinoma microenvironment by tumor-infiltrating myeloid cell density. CD68 macrophages (216 cells/mm2)a Non-brisk density (n=47)
Brisk density (n=46)
p
Non-brisk density (n=45)
Brisk density (n=44)
p
Non-brisk density (n=41)
Brisk density (n=41)
2x10-4
1x10-4
CD8 infiltration
Myeloid cells (median count, /mm2) CD33 macrophages (83 cells/mm2)c
CD163 macrophages (120 cells/mm2)b
p
CD15 neutrophils (2.5 cells/mm2)d Non-brisk density (n=47)
Brisk density (n=48)
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MCC microenvironment
3x10-5
MDSC (5 positive cases)e p
Negative (n=79)
Positive (n=5)
0.40
0.06
24 (51%)
11 (24%)
26 (58%)
8 (18%)
21 (51%)
6 (15%)
20 (44%)
15 (31%)
27 (35%)
0
Low (score 1)
25 (61%)
21 (47%)
26 (54%)
41 (53%)
3 (60%)
10 (24%)
4 (9%)
7 (15%)
9 (12%)
2 (40%)
2
0
2
0
23 (49%)
24 (52%)
17 (38%)
27 (62%)
20 (49%)
0
11 (24%)
2 (4%)
9 (20%)
0
Unknown status
0
0
0
0
9x10-3
Brisk
12 (32%)
23 (64%)
16 (44%)
21 (54%)
Non brisk
26 (68%)
13 (36%)
20 (56%)
18 (36%)
9
10
9
5
Unknown status
0.06
Vascularization 28 (62%)
21 (47%)
22 (55%)
27 (59%)
17 (38%)
24 (53%)
20 (45%)
1
1
0
2
0.90
3x10-3
3x10-3
0.80
10 (31%)
24 (69%)
11 (31%)
26 (65%)
32 (51%)
3 (60%)
23 (69%)
11 (31%)
25 (69%)
14 (35%)
31 (49%)
2 (40%)
8
6
11
8
16
0
0.26
0.80
0.90
18 (45%)
24 (60%)
23 (52%)
24 (52%)
40 (53%)
3 (60%)
22 (55%)
16 (40%)
21 (48%)
22 (48%)
36 (47%)
2 (40%)
3
1
3
0
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19 (41%)
Low
1
1
0.90
0.22
0.27
0.33
Positive
28 (61%)
26 (62%)
27 (61%)
25 (61%)
23 (59%)
28 (74%)
25 (57%)
31 (69%)
49 (67%)
2 (40%)
Negative
18 (39%)
16 (38%)
17 (39%)
16 (39%)
16 (41%)
10 (26%)
19 (43%)
14 (31%)
24 (33%)
3 (60%)
1
4
1
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0
0.70
High
Unknown status
0 0.49
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PD-L1 expression
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Absent (score 0)
Moderate to robust (score 2-5)
2
3
3
3
6
Unknown status
a)
b)
c)
0 d)
Data are expressed as number and percentages (n, %). of interpretable cases 93 interpretable cases; 89 interpretable cases; 82 interpretable cases; 95 cases; e) 84 interpretable cases. MCC tumors were dichotomized as having “brisk” and “non brisk” infiltrates according to the median count of intra-tumoral CD68, CD163-, CD33-expressing macrophages and neutrophil counts, as “MDSC-positive” or “MDSC-negative” tumors and as “high” or “low vascularization according to the median percentage of vascularized area. Association between TIM infiltrates and MCC microenvironement components were assessed with Fisher’s exact test. MDSCs, myeloid-derived suppressor cells
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472 473 474 475 476 477
3
p
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Table 2. Univariate analysis of factors associated with Merkel cell carcinoma recurrence and death
p 0.448 0.014 0.458
0.68 (0.24-1.97) Immunosuppression (yes vs no) MCPyV status (positive vs negative) 0.58 (0.26-1.28)
0.481 0.175
1.72 (0.82-3.63) CD8 infiltrates (score 0 vs 1-5) CD68 infiltrates (brisk vs non-brisk) 0.78 (0.36 -1.68) 0.63 (0.28-1.41) CD163 infiltrates (brisk vs non-
0.152 0.530 0.260
Age (≥77 vs <77 years) Sex (female versus male) AJCC stages (3-4 vs 1-2)
0.016 0.790
p 0.073 0.012 0.264
1.81 (0.80-4.12) 0.56 (0.27-1.19)
0.157 0.130
1.27 (0.60-2.68) 1.22 (0.59-2.52) 0.91 (0.43-1.93)
0.601 0.590 0.820
0.44 (0.20-0.99) 1.06 (0.51-2.20)
0.047 0.850
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CD33 infiltrates (brisk vs non-brisk) 0.35 (0.15-0.83) CD15 infiltrates (brisk vs non-brisk) 0.90 (0.41-1.96)
Death HR (95% CI) 1.94 (0.94- 4.00) 0.40 (0.19-0.82) 1.51 (0.73-3.13)
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Recurrence HR (95% CI) 1.33 (0.64-2.75) 0.39 (0.19-0.83) 1.34 (0.62-2.92)
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HR, hazard ratio; CI, confidence interval; MCC, Merkel cell carcinoma; AJCC, American Joint Committee on Cancer; MCPyV, Merkel cell
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polyomavirus
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“Brisk” and “non-brisk” defined by median count of intra-tumoral CD68-, CD163-, and CD33-expressing macrophages and CD15-expressing
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neutrophils, respectively. Covariates identified as potential prognostic confounders with p ≤ 0.20 on Cox univariate regression analysis were included in
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the multivariate Cox analysis.
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Table 3. Multivariate Cox proportional-hazard analysis of factors associated with Merkel cell carcinoma recurrence and death.
adjusted HR (95% CI) 2.70 (0.98-7.43)
0.055
Sex (female versus male) AJCC stages (3-4 versus 1-2) Immunosuppression (yes vs no)
0.36 (0.15-0.9)) 2.08 (0.81-5.34) 0.65 (0.21-2.01)
0.42 (0.17-1.03) 3.80 (1.32-10.90) 2.50 (0.99-6.36)
0.058 0.013 0.053
MCPyV status (positive vs negative)
0.94 (0.37-2.42)
0.902
0.91 (0.35-2.33)
0.842
Brisk CD33 and positive CD8 infiltrates (yes vs no)
0.22 (0.008-0.61)
0.004
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Age (≥77 vs <77 years)
Recurrence adjusted HR (95% p CI) 1.37 (0.52-3.62) 0.525
0.028 0.130 0.458
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Covariate
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0.28 (0.1-0.83)
Death p
0.022
HR, hazard ratio; CI, confidence interval; MCC, Merkel cell carcinoma; MCPyV, Merkel cell polyomavirus “Brisk” and “non-brisk” by median count of intra-tumoral CD68-, CD163-, and CD33-expressing macrophages and CD15-expressing
491
neutrophils, respectively. Brisk CD33 and positive CD8 infiltrates was defined by a brisk CD33 infiltrates (> median) together with positive
492
CD8 T-cell infiltrates (scores 1-5).
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ACCEPTED MANUSCRIPT Capsule summary: I) What is already known on this topic: Brisk infiltration of CD8 lymphocytes represents an efficient immune response in patients
2)What this study adds to our knowledge:
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with Merkel cell carcinoma.
In this study, tumors with brisk infiltration of both CD33 myeloid cells and CD8 lymphocytes were associated with an improved outcome.
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3)How this knowledge impacts patient care:
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Patients with tumors lacking brisk CD33 infiltration may be considered to be at higher risk.
ACCEPTED MANUSCRIPT Supplementary Method 1: Antibodies used and dilution.
HLA-DR CD15 CD8 CD34 PD-L1 MCPyV-LT
TAL.1B5/Dako MMA/Roche M7103/Dako QBEnd10/Dako E1L3N/Cell signaling CM2B4/Santa Cruz
dilution
Targeted population
1/400 Pan monocyte-macrophages 1/200 Tumor-associated macrophages Ready to use Early differentiation myeloid population 1/400 Macrophages/dendritic cells Ready to use Neutrophils 1/50 CD8 lymphocytes 1/50 Endothelial cells 1/200 Not appropriate 1/200 Tumor cells
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CD68 CD163 CD33
Antibody (Clone/manufacturer) PGM1/Dako 10D6/Novocastra SP166/Ventana
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ACCEPTED MANUSCRIPT Supplemental Method 2: Assessment of the reproducibility of the immune cells count in a validation cohort of overall slide stained cases.
In order to assess the representativeness of our TMA approach, studies of the CD68, CD163,
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CD33 and CD15 markers were performed on overall slide for 20 cases. Evaluation was performed in intra tumoral area as described in the Method section. For each case, counts of cells were performed on 2 distinctive areas corresponding to 5 high power fields each. The
available in the following table :
P value 7.10-7 2.10-10 4.10-6 0.03
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obtained counts were comparted for each cases using a pearson correlation and results are
ACCEPTED MANUSCRIPT Supplemental Method 3: Protocol of CD33/HLA-DR immunostaining and associated controls.
The procedure was performed as follows: 4-µm sections of paraffin-embedded MCC tissues
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were dried at 37°C overnight and deparaffinized by a graded alcohol series according to standard protocols. Subsequent heat-induced antigen retrieval was performed in EDTA buffer pH 8.4 for 20 min at 121°C. Slides were stained with antibodies for CD33 (SP166, Ventana,
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ready-to-use solution) and HLA-DR (TAL.1B5, Dako, 1:400 dilution). Antigen-bound primary antibodies were visualized by appropriate horseradish-peroxidase-coupled anti-rabbit
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antibody with the secondary anti-rabbit antibody) and secondary antibodies alone. In addition, to test our procedure on immature myeloid cells, bone marrow blood precursors
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were used as biologic positive controls and investigated by immunochemistry. Bone marrow mobilization of hematopoietic precursors is currently used during the monitoring of patients with a history of acute leukemia and bone-marrow transplant. These patients receive G-CSF inducing activation, degranulation of neutrophils in bone marrow and finally release of bone marrow precursors in blood circulation. At this time, cytoapheresis is performed to isolate nucleate cells, which are analyzed to check the quality of the transplant. With the consent of the patients and local committee agreement (OPTICYTE protocol), two anonymized samples were included in our study. After centrifugation, cells were formalin-fixed and paraffin-
ACCEPTED MANUSCRIPT embedded (FFPE). Immunochemical staining was performed as described below. Microscopy reveals green staining of numerous bone-marrow precursors associated with few mature blood-circulating monocytes showing HLA-DR expression, thereby validating our strategy.
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Microphotograph (x 200): CD33/HLA-DR immunostaining on FFPE cytoapheresis sample after bone-marrow precursor mobilization. Myeloid precursors are stained green (green
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arrow) and circulating monocytes are stained black (black arrow).
ACCEPTED MANUSCRIPT Supplemental Method 4: Measurement of vascular density.
Analyses involved use of ImageJ. Tumor areas were first delineated using the “CROP” function. “Adjust color” was then used to exclude the blue counterstaining color. Size of the
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picture was then restricted to 8 bits and the staining was underlined by using the following functions: “binary”, and “dilate”. Area measurement was performed by the “Analyse particle” function with the following parameters: size: 30-infinity; sphericity: 0-0.9. Finally,
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morphology of the delineated areas was assessed by a pathologist who used the “overlying
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Representative illustrations of the vascular measurement: a) CD34 immunostaining, b)
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Supplemental Table 1. Baseline clinical characteristics of patients with Merkel cell carcinoma by tumor-infiltrating myeloid cell density.
0.26 20 (52%) 18 (48%) 9
16 (39%) 25 (61%) 5
24 (53%) 21 (47%) 2
28 (62%) 17 (38%) 1
7 (23%) 24 (77%) 16
3 (9%) 30 (91%) 13
9 (24%) 13 (34%) 15 (39%) 1 (3%) 9
11 (28%) 7 (18%) 19 (49%) 2 (5%) 7
29 (70%) 14 1 2 12 12 (30%) 6
27 (64%) 9 0 4 14 15 (36%) 4
p
CD33 macrophages (83 cells/mm2)c Non-brisk Brisk density (n=41) density (n=41)
0.17 22 (54%) 19 (46%) 4
13 (37%) 22 (63%) 9
24 (55%) 20 (45%) 1
27 (64%) 15 (36%) 2
4 (11%) 31 (89%) 10
5 (19%) 21 (81%) 18
8 (20%) 16 (39%) 16 (39%) 1 (2%) 4
12 (38%) 4 (13%) 15 (46%) 1 (3%) 12
0.18
17 (46%) 20 (54%) 4
24 (60%) 16 (40%) 1
21 (54%) 18 (46%) 2
7 (24%) 22 (76%) 12
2 (7%) 27 (93%) 12
9 (26%) 10 (29%) 13 (39%) 2 (6%) 7
10 (29%) 6 (18%) 17 (50%) 1 (3%) 7
27 (73%) 13 1 2 11 10 (27%) 4
23 (60%) 9 1 3 10 15 (40%) 3
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27 (71%) 8 1 4 14 11 (29%) 6
21 (51%) 20 (49%) 7
31 (67%) 15 (33%) 1
22 (48%) 24 (52%) 2
4 (13%) 27 (87%) 16
6 (18%) 28 (82%) 14
16 (43%) 8 (22%) 13 (35%) 0 10
4 (10%) 14 (34%) 20 (48%) 3 (8%) 7
31 (74%) 10 2 3 16 11 (26%) 5
26 (60%) 14 0 3 9 17 (40%) 5
0.65
1 (25%) 3 (75%)1 1
44 (58%) 32 (42%) 3
3 (60%) 2 (40%) 0
9 (17%) 45 (83%) 25
0 4 (100%) 1
18 (28%) 15 (23%) 28 (44%) 3 (5%) 15
1 (25%) 2 (50%) 1 (25%) 0 1
48 (67%) 21 2 5 20 23 (33%) 8
3 (80%) 2 0 0 1 1 (20%) 1
0.90
0.73
0.90
0.70
0.002
0.80
p
0.60 30 (45%) 37 (55% 12
0.09
0.60
0.60
27 (66%) 15 0 1 11 14 (34%) 4
p
MDSC (5 positive cases)e Neg Pos (n=79) (n=5)
0.40 16 (39%) 23 (61%) 8
0.14
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0.5
CD15 neutrophils (2.5 cells/mm2)d Non-brisk Brisk density (n=47) density (n=48)
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CD163 macrophages (120 cells/mm2)b Non-brisk Brisk density (n=45) density (n=44)
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CD68 macrophages (216 cells/mm2)a Non-brisk density Brisk density (n=47) (n=46)
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Age (years) (median,77.3) Age ≤ median Age > median Unknown status Sex Female Male Unknown status Immunosuppression Yes No Unknown status AJCC stage I II III IV Unknown status Location of the sample Primary tumors: Head Trunk Upper limb Lower limb Metastasis: Unknown status:
Myeloid cells (median count/mm2)
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Clinical characteristics
0.47
0.90
Data are expressed as number and percentages (n,%) of interpretable cases. a)93 interpretable cases; b)89 interpretable cases; c)82 interpretable cases; d)95 interpretable cases; e)84 interpretable cases. MCC tumors were dichotomized as having “brisk” and “non brisk” infiltrates according to the median count of intra-tumoral CD68-, CD163-, CD33-expressing macrophages and neutrophil counts, and as “MDSC-positive” or “MDSC-negative” tumors. Association between TIM infiltrates and clinical characteristics were assessed with Fisher’s exact test. AJCC, American Joint Committee on Cancer; MDSC, myeloid-derived suppressor cells.
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Multivariate analysis specific survival Covariate
p
overall survival adjusted HR (95% CI)
p
0.529
2.42 (0.85-6.85)
0.09
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MCC recurrence adjusted HR (95% CI)
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Supplemental Table 2: Multivariate Cox proportional-hazard analysis of factors associated with Merkel cell carcinoma recurrence and death..
1.39 (0.50-3.89)
Male vs female AJCC score 3/4 vs 1/2 Immunosuppression (yes vs no)
2.42 (0.93-6.29) 2.75 (0.94-8.08) 0.84 (0.27-2.60)
0.070 0.065 0.775
2.12 (0.81-5.52) 3.90 (1.20-12.70) 2.40 (0.86-6.66)
0.126 0.024 0.096
MCPyV status (positive vs negative)
0.75 (0.247-2.10)
0.582
0.88 (0.30-2.55)
0.808
CD8 infiltrate (score 0 vs 1-5) CD33 infiltrate (non-brisk vs brisk)
1.65 (0.63-4.38) 0.35 (0.11-1)
0.315 0.051
1.30 (0.48-3.53) 0.40 (0.14-1.25)
0.601 0.083
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HR, hazard ratio; CI, confidence interval; MCC, Merkel cell carcinoma; MCPyV, Merkel cell polyomavirus “Brisk” and “non-brisk” by median count of intra-tumoral CD68-, CD163-, and CD33-expressing macrophages and CD15-expressing neutrophils, respectively
ACCEPTED MANUSCRIPT Supplemental Table 3: Characteristics of Merkel cell carcinoma subset with CD33 brisk / CD8 positive infiltrates. Characteristics
CD33 brisk / CD8-positive infiltrates No (n=47)
Yes (n=35)
P value
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0.8 Age (median 77.3 years) 19 (48%) 13 (58%) Age ≤ median Age > median 21 (52%) 18 (42%) Unknown status 7 4 0.8 Sex Female 25 (56%) 20 (59%) Male 20 (44%) 14 (41%) Unknown status 2 1 0.17 Immunosuppression Yes 7 (22%) 2 (8%) No 25 (78%) 24 (92%) Unknown status 15 9 0.9 AJCC stage I 10 (25%) 9 (32%) II 10 (25%) 6 (21%) III 18 (45%) 12 (43%) IV 2 (5%) 1 (4%) Unknown status 7 7 0.8 Location of the sample Primary tumors: 28 (65%) 22 (69%) - Head 14 8 - Trunk 1 1 - Upper limb 2 3 - Lower limb 11 10 Metastasis: 15 (35%) 10 (31%) Unknown status: 4 3 PD-L1 expression 6x10-3 Brisk 13 (34%) 21 (70%) Non brisk 25 (66%) 9 (30%) Unknown status 9 5 0.9 Vascularization High 24 (52%) 17 (50%) Low 22 (48%) 17 (50%) Unknown status 1 1 0.2 Viral status Positive 27 (60%) 24 (75%) Negative 18 (40%) 8 (25%) Unknown status 2 3 Data are n (%). AJCC, American Joint Committee on Cancer “Brisk” and “non-brisk” defined by median count of intra-tumoral CD33-expressing macrophages. High and low vascularized cases defined by the median density of vascular area (1.5%)
S0190-9622(17)32867-0
DOI:
10.1016/j.jaad.2017.12.029
Reference:
YMJD 12194
To appear in:
Journal of the American Academy of Dermatology
Received Date: 13 September 2017 Revised Date:
6 December 2017
Accepted Date: 7 December 2017
Please cite this article as: Kervarrec T, Gaboriaud P, Berthon P, Zaragoza J, Schrama D, Houben R, Le Corre Y, Hainaut-Wierzbicka E, Aubin F, Bens G, Domenech J, Guyétant S, Touzé A, Samimi M, Merkel + + cell carcinomas infiltrated with CD33 myeloid cells and CD8 T cells are associated with improved outcome, Journal of the American Academy of Dermatology (2018), doi: 10.1016/j.jaad.2017.12.029. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
Article type: Original article
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Institutional review board: The local Ethics Committee of Tours (France) approved the
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study (N° ID RCB2009-A01056-51)
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Thibault Kervarrec MD MSc1,2,3, Pauline Gaboriaud2, Patricia Berthon PhD2, Julia Zaragoza MD4, David Schrama PhD3, Roland Houben PhD3, Yannick Le Corre MD5, Eva Hainaut-Wierzbicka MD6,, Francois Aubin MD PhD7, Guido Bens MD PhD8 , Jorge Domenech PhD9, Serge Guyétant MD PhD1,2, Antoine Touzé PhD2 and Mahtab Samimi MD PhD2,3
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(1) Université Francois Rabelais, CHU de Tours, Departement of Pathology, avenue de la République, 37170 Chambray-les-tours, France (2) Université Francois Rabelais, “Biologie des infections à polyomavirus” team, UMR INRA ISP 1282, 31 avenue Monge, 37200 Tours, France (3) Department of Dermatology, Venereology and Allergology, University Hospital Würzburg, Josef-Schneider-Straße 2, 97080 Würzburg, Germany (4) Université Francois Rabelais, CHU de Tours, Departement of Dermatology, avenue de la République, 37170 Chambray-les-tours, France (5) LUNAM Université, CHU Angers, Departement of Dermatology, 4 rue Larrey, 49933 Angers, France (6) Université de Poitiers, CHU de Poitiers, Departement of Dermatology, 2 rue de la Milétrie, 86021 Poitiers, France (7) Université de Franche Comté, CHU Besançon, Departement of Dermatology, EA3181, IFR133, 2 boulevard Fleming, 25030 Besançon, France (8) CHR d’Orléans, Departement of Dermatology, 14 avenue de l’hopital, 45100 Orléans, France (9) Université Francois Rabelais, CHU de Tours, Departement of Hematology, boulevard Tonnelé, 37200, Tours France
Corresponding authors: Dr Mahtab Samimi Dermatology Department, Hospital of Tours, avenue de la République, 37170, Chambray-lestours, France Email: [email protected] Fax: +33 247478247/Tel :+33 247474625
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Grant numbers and sources of support: Grant to project POCAME, Cancéropole Grand Ouest-Région Centre Val de Loire (France)
Conflict of Interest: The authors have no conflict of interest to declare. Statement on prior presentation: none Reprint request: none Manuscript Word count (Excluding capsule summary, abstract, references, figures, and tables): 2552 Abstract word count: 200 Capsule summary word count: 50 References: 34 Figures: 4 Supplementary Figures: 0 Tables: 3 Supplementary Tables: 3 Attachments: Supplemental Methods : 4, STROBE statement and RECORD Checklist Key words : myeloid cells, macrophages, Merkel cell carcinoma, immune infiltrate, CD33, PD-L1
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Title: Merkel cell carcinomas infiltrated with CD33+ myeloid cells and CD8+ T cells are associated with improved outcome
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ACCEPTED MANUSCRIPT Abstract: Background: Merkel cell carcinoma (MCC) is a rare tumor of the skin with an aggressive
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behavior. Immunity is the main regulator of MCC development, and many interactions
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between lymphocytes and tumor cells have been proven. However, the impact of tumor-
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infiltrating myeloid cells (TIMs) needs better characterization.
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Objective: To characterize TIMs in MCC and their association with other immune effectors
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and patient outcome.
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Methods: MCC cases were reviewed from a historical/prospective cohort. In all, 103 triplicate
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tumor samples were included in a tissue microarray. Macrophages, neutrophils and myeloid-
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derived suppressor cells were characterized by the following markers: CD68, CD33, CD163,
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CD15, and CD33+/HLA-DR-. The association between these populations and PD-L1
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expression, CD8 infiltrates and vascular density was assessed. Impact on survival was
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analyzed by log-rank tests and a Cox multivariate model.
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Results: The median density of macrophages was 216/mm2. CD68+ and CD33+ macrophage
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densities were associated with CD8 infiltrates and PD-L1 expression. In addition, MCC
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harboring infiltration of CD8 T cells and brisk CD33 myeloid-cell infiltrates was significantly
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and independently associated with improved outcome (MCC recurrence and death).
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Limitations: Sampling bias and retrospective design.
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Conclusion: Infiltration of CD33 myeloid cells and CD8 lymphocytes defines a subset of
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MCC associated with improved outcome.
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Capsule summary:
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I) What is already known on this topic:
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Brisk infiltration of CD8 lymphocytes represents an efficient immune response in patients
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with Merkel cell carcinoma.
76 2)What this study adds to our knowledge:
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In this study, tumors with brisk infiltration of both CD33 myeloid cells and CD8 lymphocytes
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were associated with an improved outcome.
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3)How this knowledge impacts patient care:
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Patients with tumors lacking brisk CD33 infiltration may be considered to be at higher risk.
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ACCEPTED MANUSCRIPT Introduction
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Merkel cell carcinoma (MCC) is a rare and aggressive tumor of the skin and the main risk
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factors are age, UV exposure and immunosuppression. The diagnosis of MCC relies on the
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association of histological features of small cell neuroendocrine carcinoma and
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immunohistochemical expression of cytokeratin 20 and/or neuroendocrine markers1. In 2008,
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Feng et al. discovered Merkel cell polyomavirus (MCPyV) integration in a large proportion of
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MCC tumors2 and MCPyV is currently considered as the main etiologic agent of MCC.
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Increasing evidence supports the crucial role of cellular immune responses in controlling
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MCC progression. Brisk intra-tumoral CD8 lymphoid infiltrates have been related to
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improved outcome in MCC cohorts3–5, which suggests effective anti-tumoral–specific
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cytotoxic responses in at least some MCC cases. However, most MCC cases display immune
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evasion from anti-tumoral effectors by excluding lymphocytes at the periphery of the tumor
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(“stalling phenomenon”) and/or by inhibition of the cytotoxic responses4–7.
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Tumor-infiltrating myeloid cells (TIMs) have been suggested to be involved in such immune
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regulation in MCC8,9. Indeed TIMs can affect tumor development by modulating immune
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responses
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and
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enhancing vascular density10–12. Recruited immune-efficient M1-
polarized macrophages are progressively replaced during tumor development by tumor-
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associated macrophages closely related to the M2 tolerogenic subset. Tumor-secreted factors
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can block the differentiation process of myeloid progenitors, thereby leading to constitution of
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an immunosuppressive myeloid subset, myeloid-derived suppressor cells (MDSCs)13.
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In MCC, TIMs, previously characterized by immunohistochemistry5,14 assessing CD68+ and
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CD163+ macrophages, were found to be major components of the tumoral microenvironment
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and were evidenced as the main source of PD-L1 (programmed death ligand 1), a component
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of the tolerogenic PD-1/PD-L1 pathway currently targeted by avelumab immunotherapy15.
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ACCEPTED MANUSCRIPT One recent study8 of 12 MCC samples revealed that MCC tumors were also infiltrated by
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CD33-expressing cells, suspected to be tumor-infiltrating MDSCs.
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In this study, we investigated TIMs in a cohort of MCC patients by using the pan-macrophage
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marker CD68, the M2 macrophage marker CD163 as well as CD33 as an early differentiation
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myeloid marker. CD15 was used as immunochemical neutrophil marker and an innovative
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combination of immunostaining was developed to identify tumor-infiltrating MDSCs. TIM
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subsets were investigated by tumoral characteristics, composition of the intra-tumoral
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microenvironment (CD8 infiltration, PD-L1 expression, tumoral vascular density, MCPyV
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detection) and patient outcome (MCC recurrence and overall survival).
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Study period, data and settings
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MCC cases were recruited from an ongoing historical/prospective cohort of MCC patients
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with a diagnosis of MCC established between 1998 and 2015 from 5 French hospital centers
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(Local Ethic Committee, Tours, France, no. ID RCB2009-A01056-51). Cohort inclusion
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criteria were previously reported16. Only cases with sufficient available formalin-fixed and
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paraffin-embedded (FFPE) samples were included.
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Clinical and follow-up data
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Age, sex, American Joint Committee on Cancer (AJCC) 2010 stage at time of surgery17,
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location of samples (primary tumors or metastases), immunosuppression (HIV infection,
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organ transplant recipients, hematological malignancies)18 and follow-up data were collected
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from patient files.
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131 Tissue microarray establishment
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Inflammatory immune cells are localized in peri-tumoral or intra-tumoral areas of the tumor
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microenvironment (TME), but prognosis is related mostly to the intra-tumoral components3,4.
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Therefore, we focused the study on intra-tumoral areas. Briefly, these areas were selected on
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hematoxylin/phloxin/safran-stained (HPS) sections by using the following criteria: central
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intra-tumoral area, lack of necrosis or fibrous septa and representative immune infiltrates after
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overall slide evaluation on HPS. The selected areas were extracted as a 1-mm tissue core and
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mounted in triplicate by using a semi-motorized tissue arrayer (MTA booster OI v2.00,
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Alphelys).
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Immunohistochemistry
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Immunohistochemistry involved use of the BenchMark XT Platform as instructed. Targeted
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population markers, antibodies and dilutions are summarized in Supplemental Method 1.
144 Assessment of tumor-infiltrating immune cells
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Myeloid cells were counted on 5 high-power fields of the “intra-tumor area” defined as the
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tumor area with few fibrous septa and no necrosis. Only immune cells with obvious nuclei
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and adequate morphology (macrophages or neutrophils) in contact with tumor cells and not
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within vessels were considered in the analysis4. The representativeness of our count was
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validated on a first set of overall slides as shown in Supplemental Method 2. Secondly cells
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were counted by 2 pathologists on TMA slides (SG, TK). When cell counts differed by more
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than 10%, a third count was performed by the 2 pathologists together. Mean cell count was
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used for further analysis. Density of CD8 lymphocytes was graded as described4. Cases with
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less than 5 representative high-power foci were excluded as not interpretable.
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Assessment of MDSCs by double-staining immunochemistry
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MDSCs were previously investigated by flow cytometry by the current phenotype
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CD33+/CD11b+/HLA-DR-/low13. Because both CD33 and CD11b are myeloid lineage markers,
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with CD33 the earlier one19, we focused on CD33/HLA-DR double staining. To detect cells
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expressing CD33 without HLA-DR, we used a strong dark chromogenic component for HLA-
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DR staining. This component, the NBT/BCIP, masks the others in co-localization cases and
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allowed for excluding all cells expressing HLA-DR. Procedures and controls are described in
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Supplemental Method 3.
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To investigate MDSC location, cases with the highest CD33+/HLA-DR- cell count were
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reviewed on overall slide staining, and cells were counted on 3 fields of the intra-tumor area,
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area of necrosis, and fibrous septa.
167 Assessment of vascular density
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After CD34 immunostaining, slides were scanned by using a Nanozoomer (Hamamatsu).
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Digitalized slides were analyzed by using ImageJ software20 as described in Supplemental
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Method 4.
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172 Assessment of MCPyV status
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MCPyV status of the tumors was assessed by the expression of the large T antigen by using
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CM2B4 antibody and the Allred score, as described21,22. Briefly, a semi-quantitative score
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was used to assess intensity and proportion of large T-antigen–expressing cells; tumors with
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scores > 2 were considered MCPyV-positive22.
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Statistical Analyses
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Continuous data were described with median and quartiles (Q1-Q3). Categorical data were
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described with number and percentage of interpretable cases. Associations were assessed by
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two-tailed Fisher exact test for categorical data and non parametric Mann-Whitney test for
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continuous data. Recurrence-free survival and overall survival related to patient
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characteristics were analyzed by log-rank test and represented by Kaplan-Meier curves.
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Univariate and multivariate Cox proportional-hazards regression was used to identify factors
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associated with MCC recurrence and death, estimating hazard ratios (HRs) and 95%
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confidence intervals (CIs). Overall deaths were considered events and living patients were
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censored on the date of last follow up. Covariates were identified as potential prognostic
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confounders with p ≤ 0.20 on Cox univariate regression analysis and then included in the
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multivariate Cox analysis. Statistical analysis involved use of XL-Stat-Life (Addinsoft,
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Paris, France). P < 0.05 was considered statistically significant, except with multiple testing
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when only p <0.01 was considered significant.
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Results
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Density of TIM populations in MCC tumors
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Among the 242 MCC patients included in the cohort, 103 cases with sufficient available
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FFPE samples were included (Figure 1: Flow chart). The number of interpretable cases
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according to each myeloid marker is available in Table 1. The median number of CD68-,
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CD163- and CD33-expressing myeloid cells was 216 cells/mm2 (Q1:131-Q3:323), 120
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cells/mm2 (Q1:76-Q3:191) and 83 cells/mm2 (Q1:31-Q3:213), respectively. Overall, 66/95
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interpretable samples (69%) showed tumor-infiltrating CD15-expressing neutrophils (median
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density: 2.5 cells/mm2 (Q1:0-Q3:4)). Only 5/84 interpretable MCC samples (7%) showed
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CD33+/HL-DR- cells, with a median of 5 cells/mm2 in positive cases (Q1:3-Q3:5). On overall
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slide examination of these latter cases, MDSCs were only rarely located in intra-tumor areas
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without necrosis (median: 2.8 cells/mm2 (Q1:0-Q3:5)) versus with necrosis (median: 66
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cells/mm2, (Q1:39-Q3:81), p<0.01) or in fibrous septa surrounding the tumor (median: 57
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cells/mm2 (Q1:11-Q3:112)), p<0.01) as shown in Figure 2.
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Association of TIMs with baseline clinical characteristics
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Median age of patients was 77 years (Q1:69, Q3:84), 42% of the population (N=42/100) were
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male and 14% (N=10/72) were immunosuppressed. Regarding AJCC staging on diagnosis,
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patients were classified as having stage 1 (N=21 (25%)), stage 2 (N=22 (26%)), stage 3
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(N=39 (45%)) and stage 4 disease (N=3 (4%)), respectively.
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Patient baseline clinical characteristics by density of TIMs (macrophages, neutrophils,
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MDSCs) are provided in Supplemental Table S1. Briefly, TIM infiltrates were dichotomized
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as “brisk” and “non-brisk” by median count excepted for MDSCs which were dichotomized
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as “MDSC-positive” (n=5) and “MDSC-negative”tumors) (n=79). TIMs were not associated
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with clinical baseline characteristics or MCPyV status, excepted for neutrophil infiltrates
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which were more frequent in advanced tumor stages (Table S1).
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TIMs are closely associated with other components of the TME
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The association
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microenvironment is reported in Table 1 and illustrated in Figure 3.
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MCC tumors with CD8 infiltrates (score 1-5, n=62, 63% of cases) harbored brisker TIM
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infiltrates than CD8-negative tumors (score 0, n=36, 37% of cases) (p<0.001 for CD68,
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CD163 and CD33 myeloid cells) (Table 1). MCC cases with the highest CD8 infiltrates
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(scores 2-5, n=11, 11%) were significantly associated with brisk CD68, CD163 and CD33
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myeloid-cell infiltration (Fisher’s exact test, p=0.0002, 0.02 and 0.001, respectively).
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Most MCC tumors (61 cases, 78%) showed PD-L1-positive myeloid cells within their
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microenvironment (Figure 3). Cases were dichotomized as “brisk” and “non-brisk” according
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to the median count of PD-L1-positive myeloid cells. MCC tumors with brisk CD68 and
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CD33 infiltrates frequently showed brisk PD-L1-positive cells in their microenvironment
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(Fisher’s exact test, p=9.10-3and p=3.10-3 respectively) (Table 1).
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The vascular area occupied 1.5% of the tumor surface (Q1:0.9-Q3:1.9%), with no significant
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association with TIM infiltrates (Table 1).
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between
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Association between tumor immune infiltrates and patient’s outcome
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Factors associated with survival on univariate analysis are reported in Table 2. On univariate
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analysis, only female sex, as previously reported23–26,and CD33 TIM density were associated
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with decreased risk of recurrence (HR 0.39, 95% CI 0.19-0.83, p=0.014 and HR 0.35, 95% CI
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0.15-0.83, p=0.016 respectively) and death (HR 0.40, 95% CI 0.19-0.82, p=0.012 and HR 0.44,
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95%CI 0.20-0.99, p=0.047 respectively) (Table 2). Covariates identified as potential prognostic
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Cox analysis. In this model (Supplemental Table 2), only AJCC stage was associated
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independently with death (HR 3.90, 95%CI 1.20-12.70, p=0.024). Interestingly, among myeloid
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infiltrates, brisk CD33 infiltrates showed a trend towards association with decreased risk of
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recurrence (HR 0.35, 95% CI 0.11-1.00, p=0.051) and death (HR 0.40, 95%CI 0.14-1.25,
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Merkel cell carcinoma infiltrated with CD33+ myeloid cells and CD8+ T cells are associated with improved outcome
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MCC outcome5-7. Although we did not evidence such association in our study (Figure 4), we
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observed a strong correlation between infiltrating CD8 infiltrates and CD33 myeloid cells
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(Table 1) as well as an impact of CD33 myeloid cells on outcome (Figure 4). We therefore
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hypothesized that concomitant intra-tumoral infiltration by these two cell populations would
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impact outcome. 35 MCC cases (43% of interpretable cases) harbored both brisk CD33
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infiltrates (> median) together with CD8 T-cell infiltrates (scores 1-5). Characteristics of this
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population are reported in Supplemental Table 3. These cases had a mean time to death of
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97.5±16.4 months (vs 32.3±3.7 months for other patients, p=0.049, log-rank test) and mean time
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to recurrence of 120.3±15.0 months (vs 30.3±4.6 months for other patients, p=0.007, log-rank
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test) (Figure 4). This subset was therefore assessed in a Cox multivariate model including
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previous covariates identified in the univariate analysis (age, sex, AJCC stage,
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immunosuppression and MCPyV status). In this model, such subset of MCC cases were
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associated with both decreased risk of recurrence (HR 0.22, 0.008-0.61, p=0.004) and decreased
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risk of death (HR 0.28, 0.1-0.83, p=0.022). (Table 3).
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We investigated intra-tumoral infiltrating myeloid cells in 103 MCC tumors, together with
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CD8 infiltrates, vascular density and PD-L1 expression in the microenvironment. All MCC
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tumors were infiltrated with macrophages. Brisk CD8 infiltration and PD-L1 expression were
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associated with intra-tumoral CD68 myeloid infiltrates, as well as CD33 myeloid infiltrates.
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These recently described inta-tumoral CD33+ cells were not found to be myeloid-derived
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suppressor cells, but are likely to yield clinical relevance. Indeed, the subset of MCC cases
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with both CD8 T-cell infiltration and brisk CD33 infiltrates showed improved outcome.
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Previous reports have described the presence of CD68+ macrophages in most MCC cases, in
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the same proportion or even exceeding that of lymphoid cells27,28–30. CD68+ macrophages
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were found located at the periphery of the tumor and in intra-tumoral areas29,30 and we
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focused on intra-tumoral spots, considered areas of privileged immune responses4. In this
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setting, myeloid infiltrating cells consisted of CD68+ and CD163+ cells as previously
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described27,28–30 but also a high number of CD33+ myeloid cells. Such CD33+ myeloid cells
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were recently reported in the MCC microenvironment in an immunochemical study of 14
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tumor samples8. CD33 is a trans-membranous protein that belongs to the sialic acid receptor
284
family (Sialic acid-binding immunoglobulin-type lectins (SIGLEC)). This protein is used as
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an early myeloid differentiation marker,19 expressed at various levels by both neutrophil and
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monocyte precursors, with further downregulation during cell maturation in peripheral
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tissues31,32. CD33 has also been suggested as an MDSC marker33 thus leading to the
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hypothesis that CD33+ cells infiltrating MCC tumors were actually MDSCs8. Indeed, a
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putative role for MDSCs was previously suggested as acting to exclude lymphocytes from
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MCC intra-tumoral areas (“stalling phenomenon”) 6. Therefore, along such lines, we expected
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to observe a negative relation between myeloid infiltrates, especially CD33 myeloid cells, and
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CD8 T-lymphocyte infiltrates in the intra-tumoral MCC microenvironment. By contrast, we
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infiltrates.
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To characterize this CD33 subset further, we developed an innovative immunochemistry
296
staining protocol to visualize MDSCs. Previously, MDSC identification in FFPE tissues was
297
proposed with only CD3334 or the association of several slide stainings33. Here, we used an
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immunohistochemical approach based on a double enzymatic staining in a unique cut-FFPE
299
sample with no co-localization required. This procedure allowed us to identify putative
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MDSCs harboring a CD33+/HLA-DR- phenotype in only 5 MCC cases. Variations in MDSC
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nature between peripheral and intra-tumoral areas have been demonstrated11. Indeed, overall
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staining of our 5 MCC cases revealed fibrous septa distant from the tumor areas as privileged
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sites of CD33+/HLA-DR- cells. Regarding intra-tumoral areas, MDSC were identified in
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necrosis and their characteristic large-cell monocytoid morphology allowed us to rule out
305
artefactual staining due to necrosis (Figure 2). In contrast, most of the tumor-infiltrating
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CD33+ cells in the non-necrotic intra-tumoral areas actually expressed HLA-DR, and thus
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were not likely to be MDSCs. In line with this, these tumor-infiltrating CD33+ cells are not
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likely to exert immunosuppressive effects as they were found to be associated with a subset of
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MCC cases with improved outcome.
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Previous studies failed to reveal an impact of myeloid populations on MCC outcome5,27,14.
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Here, we reveal the prognostic relevance of the concomitant intra-tumoral infiltration by brisk
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CD33+ myeloid cells and CD8+ tumor-infiltrating lymphocytes. Taken together, their close
313
correlation with CD8 infiltrates; their expression of HLA-DR, part of the class II major
314
histocompatibility complex; and their positive impact on outcome led us to hypothesize that
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such CD33-expressing tumor-infiltrating macrophages contribute to an efficient anti-tumoral
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immune response.
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in our study did not display other specific clinical features, were not associated with MCPyV
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status but harbored frequent PD-L1 expression in the microenvironment. CD33+/HLA-DR+
320
infiltrating myeloid cells therefore appears as a potential component of the PD-L1–expressing
321
immune infiltrates. This observation led us to distinguish two classes of tumors: 1) CD33 high
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/CD8
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PD1/PD-L1 blockage therapy and 2) other tumors with low immune infiltrates and few
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therapeutic targets.
infiltrating tumors associated with improved outcome that could be targeted by
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325 Acknowledgments:
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The authors express their sincerest thanks to the patients who gave their approval for use of
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their data in the study. We also thank Pr G Fromont (Tours, France) and Roseline Guibon
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(Tours, France) for their help and contributions.
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Abbreviations:
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AJCC: American Joint Committee on Cancer.
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CD: Cluster of differentiation.
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CI: Confidence interval.
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HPS: Hematein, phloxin, safran.
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MCC: Merkel cell carcinoma.
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MCPyV: Merkel celll Polyomavirus.
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MDSC: Myeloid derived supressor cells.
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PD-L1: Programmed death-ligand 1.
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TIM: Tumor infiltrating myeloid cells.
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TMA: Tissue micro array.
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Figure 1: Flow Chart
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Figure 2: Illustration of myeloid-derived suppressor cell (MDSC) immunostaining in Merkel
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cell carcinoma. a) details of CD33+, HLA-DR- (green) cells, b) presence of CD33+/ HLA-DR-
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(green) cells in areas of necrosis, c: HLA-DR–expressing tumor-infiltrating myeloid cells
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(TIMs) in the intratumoral area, d) admixture of CD33+/HLA-DR- and HLA-DR–expressing
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cells in fibrous septa surrounding the tumor.
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Figure 3: Representative illustrations of immunostaining in both high-infiltrated (a,c,e,g) and
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non-infiltrated (b,d,f,h) Merkel cell carcinoma tumors: CD68 macrophages (a,b), CD33
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macrophages (c,d), PD-L1–expressing TIMs (e,f) and CD8 infiltrates (g,h).
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Figure 4: Kaplan-Meier survival curves for the Merkel cell carcinoma population by level of
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CD8, CD33 and CD33/CD8 infiltrates. A: recurrence-free survival, B: overall survival.
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Table 1: Merkel cell carcinoma microenvironment by tumor-infiltrating myeloid cell density.
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Table 2. Univariate analysis of factors associated with Merkel cell carcinoma recurrence and
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death
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Table 3 Multivariate Cox proportional-hazard analysis of factors associated with Merkel cell
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carcinoma recurrence and death
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Supplementary Method 1: Antibodies used and dilution.
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Supplemental Method 2: Assessment of the reproducibility of the immune cells count in a
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validation cohort of overall slide stained cases.
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controls.
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Supplemental Method 4: Measurement of vascular density.
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Supplemental Table 1. Baseline clinical characteristics of patients with Merkel cell
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carcinoma by tumor-infiltrating myeloid cell density.
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Supplemental Table 2: Multivariate Cox proportional-hazard analysis of factors associated
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with Merkel cell carcinoma recurrence and death.
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Supplemental Table 3: Characteristics of Merkel cell carcinoma subset with CD33 brisk /
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CD8 positive infiltrates.
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References: 1. Kuwamoto, S. Recent advances in the biology of Merkel cell carcinoma. Hum. Pathol. 42, 1063–1077 (2011). 2. Feng, H., Shuda, M., Chang, Y. & Moore, P. S. Clonal integration of a polyomavirus in human Merkel cell carcinoma. Science 319, 1096–1100 (2008). 3. Paulson, K. G. et al. Transcriptome-wide studies of merkel cell carcinoma and validation of intratumoral CD8+ lymphocyte invasion as an independent predictor of survival. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 29, 1539–1546 (2011). 4. Paulson, K. G. et al. CD8+ lymphocyte intratumoral infiltration as a stage-independent predictor of Merkel cell carcinoma survival: a population-based study. Am. J. Clin. Pathol. 142, 452–458 (2014). 5. Sihto, H. et al. Tumor infiltrating immune cells and outcome of Merkel cell carcinoma: a population-based study. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 18, 2872–2881 (2012). 6. Afanasiev, O. K. et al. Vascular E-selectin expression correlates with CD8 lymphocyte infiltration and improved outcome in Merkel cell carcinoma. J. Invest. Dermatol. 133, 2065–2073 (2013). 7. Dowlatshahi, M. et al. Tumor-specific T cells in human Merkel cell carcinomas: a possible role for Tregs and T-cell exhaustion in reducing T-cell responses. J. Invest. Dermatol. 133, 1879–1889 (2013). 8. Mitteldorf, C., Berisha, A., Tronnier, M., Pfaltz, M. C. & Kempf, W. PD-1 and PD-L1 in neoplastic cells and the tumor microenvironment of Merkel cell carcinoma. J. Cutan. Pathol. (2017). doi:10.1111/cup.12973 9. Vandeven, N. & Nghiem, P. Rationale for immune-based therapies in Merkel polyomavirus-positive and -negative Merkel cell carcinomas. Immunotherapy 8, 907–921 (2016). 10. Elliott, L. A., Doherty, G. A., Sheahan, K. & Ryan, E. J. Human Tumor-Infiltrating Myeloid Cells: Phenotypic and Functional Diversity. Front. Immunol. 8, 86 (2017). 11. Kumar, V., Patel, S., Tcyganov, E. & Gabrilovich, D. I. The Nature of MyeloidDerived Suppressor Cells in the Tumor Microenvironment. Trends Immunol. 37, 208–220 (2016). 12. Granot, Z. & Jablonska, J. Distinct Functions of Neutrophil in Cancer and Its Regulation. Mediators Inflamm. 2015, 701067 (2015). 13. Talmadge, J. E. & Gabrilovich, D. I. History of myeloid-derived suppressor cells. Nat. Rev. Cancer 13, 739–752 (2013). 14. O’Reilly, D., Quinn, C. M., El-Shanawany, T., Gordon, S. & Greaves, D. R. Multiple Ets factors and interferon regulatory factor-4 modulate CD68 expression in a cell typespecific manner. J. Biol. Chem. 278, 21909–21919 (2003). 15. Kaufman, H. L. et al. Avelumab in patients with chemotherapy-refractory metastatic Merkel cell carcinoma: a multicentre, single-group, open-label, phase 2 trial. Lancet Oncol. 17, 1374–1385 (2016). 16. Gardair, C. et al. Somatostatin Receptors 2A and 5 Are Expressed in Merkel Cell Carcinoma with No Association with Disease Severity. Neuroendocrinology 101, 223–235 (2015). 17. Harms, K. L. et al. Analysis of Prognostic Factors from 9387 Merkel Cell Carcinoma Cases Forms the Basis for the New 8th Edition AJCC Staging System. Ann. Surg. Oncol. 23, 3564–3571 (2016). 18. Asgari, M. M. et al. Effect of host, tumor, diagnostic, and treatment variables on outcomes in a large cohort with Merkel cell carcinoma. JAMA Dermatol. 150, 716–723 (2014).
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19. Ferlazzo, G., Spaggiari, G. M., Semino, C., Melioli, G. & Moretta, L. Engagement of CD33 surface molecules prevents the generation of dendritic cells from both monocytes and CD34+ myeloid precursors. Eur. J. Immunol. 30, 827–833 (2000). 20. Ozerdem, U., Wojcik, E. M., Barkan, G. A., Duan, X. & Erşahin, Ç. A practical application of quantitative vascular image analysis in breast pathology. Pathol. Res. Pract. 209, 455–458 (2013). 21. Houben, R. et al. An intact retinoblastoma protein-binding site in Merkel cell polyomavirus large T antigen is required for promoting growth of Merkel cell carcinoma cells. Int. J. Cancer 130, 847–856 (2012). 22. Moshiri, A. S. et al. Polyomavirus-Negative Merkel Cell Carcinoma: A More Aggressive Subtype Based on Analysis of 282 Cases Using Multimodal Tumor Virus Detection. J. Invest. Dermatol. (2016). doi:10.1016/j.jid.2016.10.028 23. Iyer, J. G. et al. Relationships among primary tumor size, number of involved nodes, and survival for 8044 cases of Merkel cell carcinoma. J. Am. Acad. Dermatol. 70, 637–643 (2014). 24. Harrington, C. & Kwan, W. Outcomes of Merkel cell carcinoma treated with radiotherapy without radical surgical excision. Ann. Surg. Oncol. 21, 3401–3405 (2014). 25. Bhatia, S. et al. Adjuvant Radiation Therapy and Chemotherapy in Merkel Cell Carcinoma: Survival Analyses of 6908 Cases From the National Cancer Data Base. J. Natl. Cancer Inst. 108, (2016). 26. Albores-Saavedra, J. et al. Merkel cell carcinoma demographics, morphology, and survival based on 3870 cases: a population based study. J. Cutan. Pathol. 37, 20–27 (2010). 27. Lipson, E. J. et al. PD-L1 expression in the Merkel cell carcinoma microenvironment: association with inflammation, Merkel cell polyomavirus and overall survival. Cancer Immunol. Res. 1, 54–63 (2013). 28. Werchau, S., Toberer, F., Enk, A., Dammann, R. & Helmbold, P. Merkel cell carcinoma induces lymphatic microvessel formation. J. Am. Acad. Dermatol. 67, 215–225 (2012). 29. Walsh, N. M. et al. A morphological and immunophenotypic map of the immune response in Merkel cell carcinoma. Hum. Pathol. 52, 190–196 (2016). 30. Wheat, R. et al. Inflammatory cell distribution in primary merkel cell carcinoma. Cancers 6, 1047–1064 (2014). 31. Forsyth, R. G. et al. CD33+ CD14- phenotype is characteristic of multinuclear osteoclast-like cells in giant cell tumor of bone. J. Bone Miner. Res. Off. J. Am. Soc. Bone Miner. Res. 24, 70–77 (2009). 32. Lock, K., Zhang, J., Lu, J., Lee, S. H. & Crocker, P. R. Expression of CD33-related siglecs on human mononuclear phagocytes, monocyte-derived dendritic cells and plasmacytoid dendritic cells. Immunobiology 209, 199–207 (2004). 33. Liu, W.-R. et al. PKM2 promotes metastasis by recruiting myeloid-derived suppressor cells and indicates poor prognosis for hepatocellular carcinoma. Oncotarget 6, 846–861 (2015). 34. Cui, T. X. et al. Myeloid-derived suppressor cells enhance stemness of cancer cells by inducing microRNA101 and suppressing the corepressor CtBP2. Immunity 39, 611–621 (2013).
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Table 1. Merkel cell carcinoma microenvironment by tumor-infiltrating myeloid cell density. CD68 macrophages (216 cells/mm2)a Non-brisk density (n=47)
Brisk density (n=46)
p
Non-brisk density (n=45)
Brisk density (n=44)
p
Non-brisk density (n=41)
Brisk density (n=41)
2x10-4
1x10-4
CD8 infiltration
Myeloid cells (median count, /mm2) CD33 macrophages (83 cells/mm2)c
CD163 macrophages (120 cells/mm2)b
p
CD15 neutrophils (2.5 cells/mm2)d Non-brisk density (n=47)
Brisk density (n=48)
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MCC microenvironment
3x10-5
MDSC (5 positive cases)e p
Negative (n=79)
Positive (n=5)
0.40
0.06
24 (51%)
11 (24%)
26 (58%)
8 (18%)
21 (51%)
6 (15%)
20 (44%)
15 (31%)
27 (35%)
0
Low (score 1)
25 (61%)
21 (47%)
26 (54%)
41 (53%)
3 (60%)
10 (24%)
4 (9%)
7 (15%)
9 (12%)
2 (40%)
2
0
2
0
23 (49%)
24 (52%)
17 (38%)
27 (62%)
20 (49%)
0
11 (24%)
2 (4%)
9 (20%)
0
Unknown status
0
0
0
0
9x10-3
Brisk
12 (32%)
23 (64%)
16 (44%)
21 (54%)
Non brisk
26 (68%)
13 (36%)
20 (56%)
18 (36%)
9
10
9
5
Unknown status
0.06
Vascularization 28 (62%)
21 (47%)
22 (55%)
27 (59%)
17 (38%)
24 (53%)
20 (45%)
1
1
0
2
0.90
3x10-3
3x10-3
0.80
10 (31%)
24 (69%)
11 (31%)
26 (65%)
32 (51%)
3 (60%)
23 (69%)
11 (31%)
25 (69%)
14 (35%)
31 (49%)
2 (40%)
8
6
11
8
16
0
0.26
0.80
0.90
18 (45%)
24 (60%)
23 (52%)
24 (52%)
40 (53%)
3 (60%)
22 (55%)
16 (40%)
21 (48%)
22 (48%)
36 (47%)
2 (40%)
3
1
3
0
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19 (41%)
Low
1
1
0.90
0.22
0.27
0.33
Positive
28 (61%)
26 (62%)
27 (61%)
25 (61%)
23 (59%)
28 (74%)
25 (57%)
31 (69%)
49 (67%)
2 (40%)
Negative
18 (39%)
16 (38%)
17 (39%)
16 (39%)
16 (41%)
10 (26%)
19 (43%)
14 (31%)
24 (33%)
3 (60%)
1
4
1
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0
0.70
High
Unknown status
0 0.49
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Absent (score 0)
Moderate to robust (score 2-5)
2
3
3
3
6
Unknown status
a)
b)
c)
0 d)
Data are expressed as number and percentages (n, %). of interpretable cases 93 interpretable cases; 89 interpretable cases; 82 interpretable cases; 95 cases; e) 84 interpretable cases. MCC tumors were dichotomized as having “brisk” and “non brisk” infiltrates according to the median count of intra-tumoral CD68, CD163-, CD33-expressing macrophages and neutrophil counts, as “MDSC-positive” or “MDSC-negative” tumors and as “high” or “low vascularization according to the median percentage of vascularized area. Association between TIM infiltrates and MCC microenvironement components were assessed with Fisher’s exact test. MDSCs, myeloid-derived suppressor cells
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3
p
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Table 2. Univariate analysis of factors associated with Merkel cell carcinoma recurrence and death
p 0.448 0.014 0.458
0.68 (0.24-1.97) Immunosuppression (yes vs no) MCPyV status (positive vs negative) 0.58 (0.26-1.28)
0.481 0.175
1.72 (0.82-3.63) CD8 infiltrates (score 0 vs 1-5) CD68 infiltrates (brisk vs non-brisk) 0.78 (0.36 -1.68) 0.63 (0.28-1.41) CD163 infiltrates (brisk vs non-
0.152 0.530 0.260
Age (≥77 vs <77 years) Sex (female versus male) AJCC stages (3-4 vs 1-2)
0.016 0.790
p 0.073 0.012 0.264
1.81 (0.80-4.12) 0.56 (0.27-1.19)
0.157 0.130
1.27 (0.60-2.68) 1.22 (0.59-2.52) 0.91 (0.43-1.93)
0.601 0.590 0.820
0.44 (0.20-0.99) 1.06 (0.51-2.20)
0.047 0.850
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CD33 infiltrates (brisk vs non-brisk) 0.35 (0.15-0.83) CD15 infiltrates (brisk vs non-brisk) 0.90 (0.41-1.96)
Death HR (95% CI) 1.94 (0.94- 4.00) 0.40 (0.19-0.82) 1.51 (0.73-3.13)
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Recurrence HR (95% CI) 1.33 (0.64-2.75) 0.39 (0.19-0.83) 1.34 (0.62-2.92)
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HR, hazard ratio; CI, confidence interval; MCC, Merkel cell carcinoma; AJCC, American Joint Committee on Cancer; MCPyV, Merkel cell
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polyomavirus
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“Brisk” and “non-brisk” defined by median count of intra-tumoral CD68-, CD163-, and CD33-expressing macrophages and CD15-expressing
484
neutrophils, respectively. Covariates identified as potential prognostic confounders with p ≤ 0.20 on Cox univariate regression analysis were included in
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the multivariate Cox analysis.
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Table 3. Multivariate Cox proportional-hazard analysis of factors associated with Merkel cell carcinoma recurrence and death.
adjusted HR (95% CI) 2.70 (0.98-7.43)
0.055
Sex (female versus male) AJCC stages (3-4 versus 1-2) Immunosuppression (yes vs no)
0.36 (0.15-0.9)) 2.08 (0.81-5.34) 0.65 (0.21-2.01)
0.42 (0.17-1.03) 3.80 (1.32-10.90) 2.50 (0.99-6.36)
0.058 0.013 0.053
MCPyV status (positive vs negative)
0.94 (0.37-2.42)
0.902
0.91 (0.35-2.33)
0.842
Brisk CD33 and positive CD8 infiltrates (yes vs no)
0.22 (0.008-0.61)
0.004
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Age (≥77 vs <77 years)
Recurrence adjusted HR (95% p CI) 1.37 (0.52-3.62) 0.525
0.028 0.130 0.458
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Covariate
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0.28 (0.1-0.83)
Death p
0.022
HR, hazard ratio; CI, confidence interval; MCC, Merkel cell carcinoma; MCPyV, Merkel cell polyomavirus “Brisk” and “non-brisk” by median count of intra-tumoral CD68-, CD163-, and CD33-expressing macrophages and CD15-expressing
491
neutrophils, respectively. Brisk CD33 and positive CD8 infiltrates was defined by a brisk CD33 infiltrates (> median) together with positive
492
CD8 T-cell infiltrates (scores 1-5).
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ACCEPTED MANUSCRIPT Capsule summary: I) What is already known on this topic: Brisk infiltration of CD8 lymphocytes represents an efficient immune response in patients
2)What this study adds to our knowledge:
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with Merkel cell carcinoma.
In this study, tumors with brisk infiltration of both CD33 myeloid cells and CD8 lymphocytes were associated with an improved outcome.
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3)How this knowledge impacts patient care:
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Patients with tumors lacking brisk CD33 infiltration may be considered to be at higher risk.
ACCEPTED MANUSCRIPT Supplementary Method 1: Antibodies used and dilution.
HLA-DR CD15 CD8 CD34 PD-L1 MCPyV-LT
TAL.1B5/Dako MMA/Roche M7103/Dako QBEnd10/Dako E1L3N/Cell signaling CM2B4/Santa Cruz
dilution
Targeted population
1/400 Pan monocyte-macrophages 1/200 Tumor-associated macrophages Ready to use Early differentiation myeloid population 1/400 Macrophages/dendritic cells Ready to use Neutrophils 1/50 CD8 lymphocytes 1/50 Endothelial cells 1/200 Not appropriate 1/200 Tumor cells
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CD68 CD163 CD33
Antibody (Clone/manufacturer) PGM1/Dako 10D6/Novocastra SP166/Ventana
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ACCEPTED MANUSCRIPT Supplemental Method 2: Assessment of the reproducibility of the immune cells count in a validation cohort of overall slide stained cases.
In order to assess the representativeness of our TMA approach, studies of the CD68, CD163,
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CD33 and CD15 markers were performed on overall slide for 20 cases. Evaluation was performed in intra tumoral area as described in the Method section. For each case, counts of cells were performed on 2 distinctive areas corresponding to 5 high power fields each. The
available in the following table :
P value 7.10-7 2.10-10 4.10-6 0.03
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obtained counts were comparted for each cases using a pearson correlation and results are
ACCEPTED MANUSCRIPT Supplemental Method 3: Protocol of CD33/HLA-DR immunostaining and associated controls.
The procedure was performed as follows: 4-µm sections of paraffin-embedded MCC tissues
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were dried at 37°C overnight and deparaffinized by a graded alcohol series according to standard protocols. Subsequent heat-induced antigen retrieval was performed in EDTA buffer pH 8.4 for 20 min at 121°C. Slides were stained with antibodies for CD33 (SP166, Ventana,
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ready-to-use solution) and HLA-DR (TAL.1B5, Dako, 1:400 dilution). Antigen-bound primary antibodies were visualized by appropriate horseradish-peroxidase-coupled anti-rabbit
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antibody with the secondary anti-rabbit antibody) and secondary antibodies alone. In addition, to test our procedure on immature myeloid cells, bone marrow blood precursors
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were used as biologic positive controls and investigated by immunochemistry. Bone marrow mobilization of hematopoietic precursors is currently used during the monitoring of patients with a history of acute leukemia and bone-marrow transplant. These patients receive G-CSF inducing activation, degranulation of neutrophils in bone marrow and finally release of bone marrow precursors in blood circulation. At this time, cytoapheresis is performed to isolate nucleate cells, which are analyzed to check the quality of the transplant. With the consent of the patients and local committee agreement (OPTICYTE protocol), two anonymized samples were included in our study. After centrifugation, cells were formalin-fixed and paraffin-
ACCEPTED MANUSCRIPT embedded (FFPE). Immunochemical staining was performed as described below. Microscopy reveals green staining of numerous bone-marrow precursors associated with few mature blood-circulating monocytes showing HLA-DR expression, thereby validating our strategy.
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Microphotograph (x 200): CD33/HLA-DR immunostaining on FFPE cytoapheresis sample after bone-marrow precursor mobilization. Myeloid precursors are stained green (green
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arrow) and circulating monocytes are stained black (black arrow).
ACCEPTED MANUSCRIPT Supplemental Method 4: Measurement of vascular density.
Analyses involved use of ImageJ. Tumor areas were first delineated using the “CROP” function. “Adjust color” was then used to exclude the blue counterstaining color. Size of the
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picture was then restricted to 8 bits and the staining was underlined by using the following functions: “binary”, and “dilate”. Area measurement was performed by the “Analyse particle” function with the following parameters: size: 30-infinity; sphericity: 0-0.9. Finally,
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Representative illustrations of the vascular measurement: a) CD34 immunostaining, b)
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Supplemental Table 1. Baseline clinical characteristics of patients with Merkel cell carcinoma by tumor-infiltrating myeloid cell density.
0.26 20 (52%) 18 (48%) 9
16 (39%) 25 (61%) 5
24 (53%) 21 (47%) 2
28 (62%) 17 (38%) 1
7 (23%) 24 (77%) 16
3 (9%) 30 (91%) 13
9 (24%) 13 (34%) 15 (39%) 1 (3%) 9
11 (28%) 7 (18%) 19 (49%) 2 (5%) 7
29 (70%) 14 1 2 12 12 (30%) 6
27 (64%) 9 0 4 14 15 (36%) 4
p
CD33 macrophages (83 cells/mm2)c Non-brisk Brisk density (n=41) density (n=41)
0.17 22 (54%) 19 (46%) 4
13 (37%) 22 (63%) 9
24 (55%) 20 (45%) 1
27 (64%) 15 (36%) 2
4 (11%) 31 (89%) 10
5 (19%) 21 (81%) 18
8 (20%) 16 (39%) 16 (39%) 1 (2%) 4
12 (38%) 4 (13%) 15 (46%) 1 (3%) 12
0.18
17 (46%) 20 (54%) 4
24 (60%) 16 (40%) 1
21 (54%) 18 (46%) 2
7 (24%) 22 (76%) 12
2 (7%) 27 (93%) 12
9 (26%) 10 (29%) 13 (39%) 2 (6%) 7
10 (29%) 6 (18%) 17 (50%) 1 (3%) 7
27 (73%) 13 1 2 11 10 (27%) 4
23 (60%) 9 1 3 10 15 (40%) 3
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27 (71%) 8 1 4 14 11 (29%) 6
21 (51%) 20 (49%) 7
31 (67%) 15 (33%) 1
22 (48%) 24 (52%) 2
4 (13%) 27 (87%) 16
6 (18%) 28 (82%) 14
16 (43%) 8 (22%) 13 (35%) 0 10
4 (10%) 14 (34%) 20 (48%) 3 (8%) 7
31 (74%) 10 2 3 16 11 (26%) 5
26 (60%) 14 0 3 9 17 (40%) 5
0.65
1 (25%) 3 (75%)1 1
44 (58%) 32 (42%) 3
3 (60%) 2 (40%) 0
9 (17%) 45 (83%) 25
0 4 (100%) 1
18 (28%) 15 (23%) 28 (44%) 3 (5%) 15
1 (25%) 2 (50%) 1 (25%) 0 1
48 (67%) 21 2 5 20 23 (33%) 8
3 (80%) 2 0 0 1 1 (20%) 1
0.90
0.73
0.90
0.70
0.002
0.80
p
0.60 30 (45%) 37 (55% 12
0.09
0.60
0.60
27 (66%) 15 0 1 11 14 (34%) 4
p
MDSC (5 positive cases)e Neg Pos (n=79) (n=5)
0.40 16 (39%) 23 (61%) 8
0.14
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0.5
CD15 neutrophils (2.5 cells/mm2)d Non-brisk Brisk density (n=47) density (n=48)
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CD163 macrophages (120 cells/mm2)b Non-brisk Brisk density (n=45) density (n=44)
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CD68 macrophages (216 cells/mm2)a Non-brisk density Brisk density (n=47) (n=46)
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Age (years) (median,77.3) Age ≤ median Age > median Unknown status Sex Female Male Unknown status Immunosuppression Yes No Unknown status AJCC stage I II III IV Unknown status Location of the sample Primary tumors: Head Trunk Upper limb Lower limb Metastasis: Unknown status:
Myeloid cells (median count/mm2)
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Clinical characteristics
0.47
0.90
Data are expressed as number and percentages (n,%) of interpretable cases. a)93 interpretable cases; b)89 interpretable cases; c)82 interpretable cases; d)95 interpretable cases; e)84 interpretable cases. MCC tumors were dichotomized as having “brisk” and “non brisk” infiltrates according to the median count of intra-tumoral CD68-, CD163-, CD33-expressing macrophages and neutrophil counts, and as “MDSC-positive” or “MDSC-negative” tumors. Association between TIM infiltrates and clinical characteristics were assessed with Fisher’s exact test. AJCC, American Joint Committee on Cancer; MDSC, myeloid-derived suppressor cells.
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Multivariate analysis specific survival Covariate
p
overall survival adjusted HR (95% CI)
p
0.529
2.42 (0.85-6.85)
0.09
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MCC recurrence adjusted HR (95% CI)
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Supplemental Table 2: Multivariate Cox proportional-hazard analysis of factors associated with Merkel cell carcinoma recurrence and death..
1.39 (0.50-3.89)
Male vs female AJCC score 3/4 vs 1/2 Immunosuppression (yes vs no)
2.42 (0.93-6.29) 2.75 (0.94-8.08) 0.84 (0.27-2.60)
0.070 0.065 0.775
2.12 (0.81-5.52) 3.90 (1.20-12.70) 2.40 (0.86-6.66)
0.126 0.024 0.096
MCPyV status (positive vs negative)
0.75 (0.247-2.10)
0.582
0.88 (0.30-2.55)
0.808
CD8 infiltrate (score 0 vs 1-5) CD33 infiltrate (non-brisk vs brisk)
1.65 (0.63-4.38) 0.35 (0.11-1)
0.315 0.051
1.30 (0.48-3.53) 0.40 (0.14-1.25)
0.601 0.083
TE D
M AN U
Age (≥77 vs <77 years)
AC C
EP
HR, hazard ratio; CI, confidence interval; MCC, Merkel cell carcinoma; MCPyV, Merkel cell polyomavirus “Brisk” and “non-brisk” by median count of intra-tumoral CD68-, CD163-, and CD33-expressing macrophages and CD15-expressing neutrophils, respectively
ACCEPTED MANUSCRIPT Supplemental Table 3: Characteristics of Merkel cell carcinoma subset with CD33 brisk / CD8 positive infiltrates. Characteristics
CD33 brisk / CD8-positive infiltrates No (n=47)
Yes (n=35)
P value
AC C
EP
TE D
M AN U
SC
RI PT
0.8 Age (median 77.3 years) 19 (48%) 13 (58%) Age ≤ median Age > median 21 (52%) 18 (42%) Unknown status 7 4 0.8 Sex Female 25 (56%) 20 (59%) Male 20 (44%) 14 (41%) Unknown status 2 1 0.17 Immunosuppression Yes 7 (22%) 2 (8%) No 25 (78%) 24 (92%) Unknown status 15 9 0.9 AJCC stage I 10 (25%) 9 (32%) II 10 (25%) 6 (21%) III 18 (45%) 12 (43%) IV 2 (5%) 1 (4%) Unknown status 7 7 0.8 Location of the sample Primary tumors: 28 (65%) 22 (69%) - Head 14 8 - Trunk 1 1 - Upper limb 2 3 - Lower limb 11 10 Metastasis: 15 (35%) 10 (31%) Unknown status: 4 3 PD-L1 expression 6x10-3 Brisk 13 (34%) 21 (70%) Non brisk 25 (66%) 9 (30%) Unknown status 9 5 0.9 Vascularization High 24 (52%) 17 (50%) Low 22 (48%) 17 (50%) Unknown status 1 1 0.2 Viral status Positive 27 (60%) 24 (75%) Negative 18 (40%) 8 (25%) Unknown status 2 3 Data are n (%). AJCC, American Joint Committee on Cancer “Brisk” and “non-brisk” defined by median count of intra-tumoral CD33-expressing macrophages. High and low vascularized cases defined by the median density of vascular area (1.5%)