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Prognostic Significance of Myeloid Immune Cells and Their Spatial Distribution in the Colorectal Cancer Microenvironment

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Prognostic Significance of Myeloid Immune Cells and Their Spatial Distribution in the Colorectal Cancer Microenvironment Open access Original research J Immunother Cancer: first published as 10.1136/jitc-2020-002297 on 30 April 2021. Downloaded from Prognostic significance of myeloid immune cells and their spatial distribution in the colorectal cancer microenvironment 1,2,3 2,3,4 2 3 Juha P Väyrynen , Koichiro Haruki, Sara A Väyrynen, Mai Chan Lau, Andressa Dias Costa,2 Jennifer Borowsky,5 Melissa Zhao,3 Tomotaka Ugai,3,6 Junko Kishikawa,3 Naohiko Akimoto,3 Rong Zhong,3 Shanshan Shi,3 Tzuu- Wang Chang,3 Kenji Fujiyoshi,3 Kota Arima,3 Tyler S Twombly,3 Annacarolina Da Silva,3 Mingyang Song,7,8,9 Kana Wu,6,7,10 Xuehong Zhang,10 Andrew T Chan,8,9,10,11 Reiko Nishihara,3,6,7,12 Charles S Fuchs,13,14,15 Jeffrey A Meyerhardt,2 Marios Giannakis,2,16,17 Shuji Ogino,3,6,16,18 3 Jonathan A Nowak To cite: Väyrynen JP, Haruki K, ABSTRACT prognostic significance in colorectal cancer, with mature Väyrynen SA, et al. Prognostic Background Myeloid cells represent an abundant CD14+HLA- DR+ and immature CD14+HLA- DR− monocytic significance of myeloid yet heterogeneous cell population in the colorectal phenotypes most notably showing opposite associations. immune cells and their spatial cancer microenvironment, and their roles remain poorly These results highlight the prognostic utility of multimarker distribution in the colorectal understood. evaluation of myeloid cell infiltrates and reveal a previously cancer microenvironment. Journal for ImmunoTherapy Methods We used multiplexed immunofluorescence unrecognized degree of spatial organization for myeloid + of Cancer 2021;9:e002297. combined with digital image analysis to identify CD14 cells in the immune microenvironment. doi:10.1136/jitc-2020-002297 monocytic and CD15+ granulocytic cells and to evaluate their maturity (HLA- DR and CD33), immunosuppressive potential (ARG1) and proximity to cytokeratin (KRT)- JPV, KH, SAV and MCL are joint BACKGROUND positive tumor cells in 913 colorectal carcinomas. Using first authors. Colorectal cancer is the second most common covariate data of 4465 incident colorectal cancers in 1 JAM, MG, SO and JAN are joint two prospective cohort studies, the inverse probability cause of cancer deaths in the world. A senior authors. weighting method was used with multivariable- adjusted substantial fraction of cells present in the Accepted 18 March 2021 Cox proportional hazards models to assess cancer- specific colorectal cancer microenvironment are mortality according to ordinal quartiles (Q1–Q4) of myeloid derived from myeloid progenitor cells in the http://jitc.bmj.com/ cell densities. Immune cell–tumor cell proximity was bone marrow.2 These cells are heterogenous, measured with the nearest neighbor method and the can exhibit functional and phenotypic plas- G- cross function, which determines the likelihood of any ticity and may exert protumorigenic and anti- tumor cell having at least one immune cell of the specified tumorigenic effects.2 3 Analyses incorporating type within a certain radius. this diversity may advance the understanding Results Higher intraepithelial (Ptrend=0.0002; HR for of colorectal cancer biology and facilitate the on October 1, 2021 by guest. Protected copyright. Q4 (vs Q1), 0.48, 95% CI 0.31 to 0.76) and stromal development of improved tumor-immune (Ptrend <0.0001; HR for Q4 (vs Q1), 0.42, 95% CI 0.29 to 0.63) densities of CD14+HLA- DR+ cells were associated biomarkers and cancer therapies. with lower colorectal cancer- specific mortality while, In the late 1990s and early 2000s, it was conversely, higher intraepithelial densities of CD14+HLA- established that cancer might cause aber- DR− cells were associated with higher colorectal cancer- rant, sustained myelopoiesis resulting in the © Author(s) (or their specific mortality P( trend=0.0003; HR for Q4 (vs Q1), accumulation of immature myeloid cells employer(s)) 2021. Re- use 4–6 permitted under CC BY-NC. No 1.78, 95% CI 1.25 to 2.55). Spatial analyses indicated in the circulation and peripheral tissues ; + commercial re- use. See rights that CD15 cells were located closer to tumor cells than such cells were subsequently termed myeloid- + + + and permissions. Published by CD14 cells, and CD14 HLA- DR cells were closer to derived suppressor cells (MDSCs) in recog- BMJ. + − tumor than CD14 HLA- DR cells (p<0.0001). The G- cross nition of their high potential to suppress proximity measurement, evaluating the difference in the For numbered affiliations see immune responses.7 Myeloid cells comprise end of article. likelihood of any tumor cell being colocated with at least + + + + − CD14 monocytic cells (such as monocytes one CD14 HLA- DR cell versus CD14 HLA- DR cell within + Correspondence to a 20 µm radius, was associated with lower colorectal and macrophages) and CD15 granulocytic Dr Jonathan A Nowak; cancer- specific mortality P( <0.0001; HR for Q4 (vs Q1), cells (such as neutrophils and eosinophils), janowak@ bwh. harvard. edu trend 0.37, 95% CI 0.24 to 0.57). and accordingly, the major human MDSC + Dr Shuji Ogino; Conclusions Myeloid cell populations occur in spatially subgroups include CD14 monocytic MDSCs + 6 sogino@ bwh. harvard. edu distinct distributions and exhibit divergent, subset- specific and CD15 polymorphonuclear MDSCs. Väyrynen JP, et al. J Immunother Cancer 2021;9:e002297. doi:10.1136/jitc-2020-002297 1 Open access Accurate identification of specific myeloid cell subsets D2S123, D5S346, D17S250, D18S55, D18S56, D18S67, J Immunother Cancer: first published as 10.1136/jitc-2020-002297 on 30 April 2021. Downloaded from requires a combination of multiple markers, which has and D18S487), as previously described.13 Methylation been possible with multiparameter flow cytometry.6 analyses for eight promoters specific for the CpG island Recent developments in multiplex immunofluorescence methylator phenotype (CIMP; CACNA1G, CDKN2A, have enabled simultaneous detection of multiple anti- CRABP1, IGF2, MLH1, NEUROG1, RUNX3, and SOCS1) gens in situ with single cell resolution.8 However, these were conducted using bisulfite- treated DNA and real- methods have not yet been used to analyze immune cells time PCR,13 and long interspersed nucleotide element-1 in the colorectal cancer microenvironment, where most (LINE-1) methylation level was assessed with pyrose- such analyses have been conducted using traditional quencing.14 Pyrosequencing was performed to evaluate immunohistochemistry.2 9 BRAF (codon 600), KRAS (codons 12, 13, 61 and 146) In this study, we used multiplex immunofluorescence and PIK3CA (exons 9 and 20) mutation status.15 Neoan- combined with digital image analysis and machine tigen load of 412 tumors was estimated using a neoan- learning to identify CD14+ monocytic and CD15+ granulo- tigen prediction pipeline for somatic mutations based cytic myeloid cells and to evaluate their maturity (HLA- DR on whole- exome sequencing and identifying peptides and CD33), suppressive potential (arginase 1 (ARG1)),10 binding to human leukocyte antigen (MHC) molecules and proximity to cytokeratin (KRT)- positive tumor cells with high affinity.16 One pathologist (SO) reviewed H&E- in 913 colorectal cancers in two US nationwide prospec- stained tissue sections to confirm the diagnoses and tive cohort studies. As our primary aim, using 4465 inci- evaluate tumor differentiation (well/moderate vs poor) dent colorectal cancer cases and the inverse probability and lymphocytic reaction patterns (tumor-infiltrating weighting (IPW) method to adjust for selection bias, we lymphocytes; intratumoral periglandular reaction; peri- analyzed the prognostic significance of different myeloid tumoral reaction; and Crohn’s- like lymphoid reaction).17 cell populations within tumor tissue. As our secondary Tissue microarrays (TMAs) containing 1–4 (median 2) aim, we characterized the spatial patterns of different 0.6 mm diameter cores from representative areas of each myeloid infiltrates and their prognostic significance, as tumor were constructed.18 Densities of granulocytic cells well as the relationships of myeloid infiltrates with tumor (neutrophils and eosinophils) from 900 tumors were eval- molecular features. uated from H&E- stained TMA sections using a computer- assisted method, as previously described.19 METHODS Multiplex immunofluorescence Study population We built a multiplex immunofluorescence assay, incor- The study was based on two prospective cohort studies, porating tyramide signal amplification for high antigen the Nurses’ Health Study (NHS; 121 701 women followed sensitivity,20 to evaluate myeloid cells in the colorectal since 1976) and the Health Professionals Follow- up Study cancer microenvironment. First, we screened potential (HPFS; 51 529 men followed since 1986), where 4465 inci- markers and antibody clones based on published litera- dent colorectal cancer cases had occurred and were docu- ture.6 21–27 Candidate antibody testing was then performed http://jitc.bmj.com/ mented until 2012. We included both colon and rectal on colorectal cancer tissue and lymphoid controls via carcinoma cases, based on the colorectal continuum chromogenic immunohistochemistry, and antibody model,11 and analyzed myeloid cell densities in 913 cases, clones with expression patterns corresponding to their based on the availability of adequate tissue specimens biologically expected distribution (at both the tissue level (table 1, online supplemental figure S1). All participants and subcellular level) were selected for further testing via gave informed consent for the study. immunofluorescence. Antibody clones with the highest on October
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