Signatures Of Dendritic Cells Research Articles

Profiling of Early Immune Responses to Vaccination Using THP-1-Derived Dendritic Cells.

The COVID-19 pandemic has made assessing vaccine efficacy more challenging. Besides neutralizing antibody assays, systems vaccinology studies use omics technology to reveal immune response mechanisms and identify gene signatures in human peripheral blood mononuclear cells (PBMCs). However, due to their low proportion in PBMCs, profiling the immune response signatures of dendritic cells (DCs) is difficult. Here, we develop a predictive model for evaluating early immune responses in dendritic cells. We establish a THP-1-derived dendritic cell (TDDC) model and stimulate their maturation in vitro with an optimal dose of attenuated yellow fever 17D (YF-17D). Transcriptomic analysis reveals that type I interferon (IFN-I)-induced immunity plays a key role in dendritic cells. IFN-I regulatory biomarkers (IRF7, SIGLEC1) and IFN-I-inducible biomarkers (IFI27, IFI44, IFIT1, IFIT3, ISG15, MX1, OAS2, OAS3) are identified and validated in vitro and in vivo. Furthermore, we apply this TDDC approach to various types of vaccines, providing novel insights into their early immune response signatures and their heterogeneity in vaccine recipients. Our findings suggest that a standardizable TDDC model is a promising predictive approach to assessing early immunity in DCs. Further research into vaccine efficacy assessment approaches on various types of immune cells could lead to a systemic regimen for vaccine development in the future.

Innate immune activation restricts priming and protective efficacy of the radiation-attenuated PfSPZ malaria vaccine.

A systems analysis was conducted to determine the potential molecular mechanisms underlying differential immunogenicity and protective efficacy results of a clinical trial of the radiation-attenuated whole sporozoite PfSPZ Vaccine in African infants. Innate immune activation and myeloid signatures at pre-vaccination baseline correlated with protection from Pf parasitemia in placebo controls. These same signatures were associated with susceptibility to parasitemia among infants who received the highest and most protective PfSPZ Vaccine dose. Machine learning identified spliceosome, proteosome, and resting dendritic cell signatures as pre-vaccination features predictive of protection after highest-dose PfSPZ vaccination, whereas baseline CSP-specific IgG predicted non-protection. Pre-vaccination innate inflammatory and myeloid signatures were associated with higher sporozoite-specific IgG Ab response but undetectable PfSPZ-specific CD8+ T-cell responses post-vaccination. Consistent with these human data, innate stimulation in vivo conferred protection against infection by sporozoite injection in malaria-naïve mice while diminishing the CD8+ T-cell response to radiation-attenuated sporozoites. These data suggest a dichotomous role of innate stimulation for malaria protection and induction of protective immunity of whole-sporozoite malaria vaccines. The uncoupling of vaccine-induced protective immunity achieved by Abs from more protective CD8+ T cell responses suggest that PfSPZ Vaccine efficacy in malaria-endemic settings may be constrained by opposing antigen presentation pathways.

Abstract 6633: Tracking cell-cell interactions using intercellular barcode transfer

Abstract Cell-cell interaction is one of the fundamental biological mechanisms by which cells communicate and is a key modality by which cancer cells interact with other cells in their microenvironment. Current methods, such as enzymatic labeling and proximity-based tagging, allow the experimental tracking of these interactions but are not compatible with sequencing-based readouts, which are essential for high-throughput analyses. We have developed a highly scalable intercellular barcode transfer technology that bridges this gap. Our novel “Relay” technology offers a scalable solution to monitor cell-cell interactions with unprecedented single-cell resolution, seamlessly integrating with existing high-throughput and sequencing platforms. Relay employs RNA barcodes to mark and track cell interaction events, providing definitive quantitative data on cell interaction partners. We used Relay to track interactions between cancer cells and T cells, capturing both potent antigen-specific engagements and subtler contacts involved in antigen sampling. Additionally, by integrating CRISPR libraries with Relay, we pioneered a novel approach for pooled CRISPR screens, focusing on intercellular interactions across different cell types. In this context, the cell harboring genetic perturbation may differ from the cell under analysis. To demonstrate this, we are conducting genome-wide perturbations in cancer cells and interrogating cancer cell factors that affect antigen sampling and trogocytosis by T cells and macrophages. Beyond its application in CRISPR screening, Relay can also be used with single-cell RNA sequencing to directly track and measure immune-cancer and immune-immune cell interactions at the single cell level. We applied single-cell Relay to a dendritic cell-T cell system to link dendritic cell signatures to T cell signatures based on direct cell contact and regulatory signaling. The design of Relay as a highly modular system extends its utility beyond cancer research, making it broadly applicable across various biological models and systems where cell-cell communication is a fundamental property in complex multicellular settings. This tool promises to accelerate the transition from theoretical understanding to practical exploration of cell-cell interactions, with profound implications for immunology, oncology, and beyond. Citation Format: Neil Q. Tay, Tiffany Juan, Joseph J. Muldoon, Justin Eyquem, Michael T. McManus. Tracking cell-cell interactions using intercellular barcode transfer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6633.

Real-Time Volatile Metabolomics Analysis of Dendritic Cells.

Dendritic cells (DCs) actively sample and present antigen to cells of the adaptive immune system and are thus vital for successful immune control and memory formation. Immune cell metabolism and function are tightly interlinked, and a better understanding of this interaction offers potential to develop immunomodulatory strategies. However, current approaches for assessing the immune cell metabolome are often limited by end-point measurements, may involve laborious sample preparation, and may lack unbiased, temporal resolution of the metabolome. In this study, we present a novel setup coupled to a secondary electrospray ionization-high resolution mass spectrometric (SESI-HRMS) platform allowing headspace analysis of immature and activated DCs in real-time with minimal sample preparation and intervention, with high technical reproducibility and potential for automation. Distinct metabolic signatures of DCs treated with different supernatants (SNs) of bacterial cultures were detected during real-time analyses over 6 h compared to their respective controls (SN only). Furthermore, the technique allowed for the detection of 13C-incorporation into volatile metabolites, opening the possibility for real-time tracing of metabolic pathways in DCs. Moreover, differences in the metabolic profile of naı̈ve and activated DCs were discovered, and pathway-enrichment analysis revealed three significantly altered pathways, including the TCA cycle, α-linolenic acid metabolism, and valine, leucine, and isoleucine degradation.

Vulnerability to immune therapy in BRAF- and MYB-altered pediatric gliomas.

2066 Background: The frequency and expression of predictive immune biomarkers in pediatric gliomas is relatively unknown. Here, we sought to define predictive signatures of immunotherapy responders by examining immune checkpoint expression, immune cell population signatures, and gene amplifications in a variety of pediatric gliomas. Methods: We profiled a cohort of pediatric, adolescent, and young adult glioma samples submitted to Caris Life Sciences (Phoenix, AZ) for analysis (N = 207). The cohort was further stratified by driver mutations: IDH mutant (N = 103), H3-3A mutant (N = 36), MYB-altered (N = 4), BRAF-altered (N = 39), and IDH wild type [IDH WT] (N = 25). De-identified next generation DNA sequencing (592-gene or whole exome) and RNA (whole transcriptome) sequencing were used to determine tumor-infiltrating immune cell signatures and immune checkpoint protein expression. Transcriptomic signatures predictive of response to immunotherapy (T cell inflamed score) and replication stress response defect (RSRD) score were calculated on transcripts per million (TPM) values. Immune cell fractions were estimated using RNA deconvolution (quanTIseq). Results: BRAF-altered tumors showed the highest IFN gamma signature (a clinically relevant inflammatory biomarker), a high pro-inflammatory M1 macrophage signature, and very high CD4+/CD8+ T cell signatures compared to other tumor groups. IDH mutant, but not WT gliomas, were relatively deficient in T cell infiltration but revealed an increase in dendritic cell signatures. IDH WT gliomas showed more T cell enrichment but higher immune suppressive checkpoint expression. H3-3A mutant tumors showed relatively low immune cell infiltration and immune checkpoint expression. Pro-inflammatory M1 macrophages were lower in the high-grade glioma microenvironment compared to low-grade. Immune suppressive M2 macrophages were elevated in the IDH WT microenvironment relative to other gliomas. There was no apparent difference in the frequency of PD-1+ T cells and tumor-expressed PD-L1 among the various molecularly defined pediatric glioma groups. Conclusions: In general, BRAF- and MYB-altered gliomas displayed high immune activation relative to other tumors. IDH WT tumors have an immune suppressive microenvironment with relatively high immune checkpoint expression. Based on predictive markers, BRAF- and MYB-driven gliomas show signatures suggesting the possibility of a greater response to immunotherapies than IDH WT/mutant gliomas or H3-3A gliomas.

Dendritic cell activation and screening for key molecular signatures required for the induction of allergic responses.

The chain of events that leads to the sensitization of the immune system to environmental antigens, resulting in the onset of allergic disease, has been studied in great detail over the past 30 years. However, during this time, the rate of allergic diseases has increased exponentially, indicating the need to concentrate our studies on host-environmental factors that contribute to the onset of disease. Monocyte-derived dendritic cells (DCs) play a key role in driving localized and systemic immune responses. In this study, we developed a platform for screening the molecular signature and phenotypic profile of DCs activated by allergenic stimuli, including TSLP, IL-25, IL-33, IL-1a, Vit-D3 (1α,25-Dihydroxyvitamin D3), PAR1-AP Peptide, Papain, and recombinant human DerP1 protein to induce a type II associated inflammatory signature. Following activation with allergenic stimuli, modulated DCs are subjected to deep phenotyping via flow cytometry for surface and intracellular markers to detect and/or validate immunomodulatory properties. RNA sequencing is further used to compare the gene expression profiles of DCs responding to either allergenic or microbial stimuli, including the TLR3 agonist dsRNA Poly I:C and TLR4 agonist LPS. In our study, we aimed to identify key molecular signatures of DCs involved in the development of asthma and allergy based on their comparative activation with this broad panel of allergens. We expect to determine central control modules of transcription factors in DCs associated with Th2 induction.

Genomic Profiling of Smoldering Multiple Myeloma Classifies Molecular Groups with Distinct Pathogenic Phenotypes and Clinical Outcomes

Genomic Profiling of Smoldering Multiple Myeloma Classifies Molecular Groups with Distinct Pathogenic Phenotypes and Clinical Outcomes

Neo-Fs Index: A Novel Immunohistochemical Biomarker Panel Predicts Survival and Response to Anti-Angiogenetic Agents in Clear Cell Renal Cell Carcinoma.

Simple SummaryAlthough anti-angiogenetic agents (AAA) are mainstay treatments for clear cell renal cell carcinoma (ccRCC), there are very few histology-based predictive biomarkers applicable in routine clinical practice. Considering that frameshifts contribute to antitumor immunity and ccRCC harbors the highest indel proportion across tumors, we hypothesized that protein markers frequently mutated via frameshift indels could predict prognosis and response to AAA. We evaluated the prognostic impact of the individual protein markers and found five proteins showing independent prognostic value. Utilizing the five proteins, we developed an integrated biomarker—Neo-fs index. High Neo-fs index predicted better prognosis and AAA response. High Neo-fs index, which harbored greater single nucleotide variant and indel mutation, was also associated with antitumor immune gene signature. Neo-fs index could be a practical biomarker to improve risk stratification and predict AAA response in ccRCC patients.Background: Frameshift indels have emerged as a predictor of immunotherapy response but were not evaluated yet to predict anti-angiogenetic agent (AAA) response or prognosis in clear cell renal cell carcinoma (ccRCC). Methods: Here, to develop biomarkers that predict survival and response to AAA, we evaluated the immunohistochemical expression of proteins whose genes frequently harbor frameshift indels in 638 ccRCC patients and correlated the individual and integrated markers with prognosis and AAA response. The mutational landscape was evaluated using targeted next-generation sequencing in 12 patients concerning protein markers. Immune gene signatures were retrieved from TCGA RNA seq data. Results: Five proteins (APC, NOTCH1, ARID1A, EYS, and filamin A) were independent adverse prognosticators and were incorporated into the Neo-fs index. Better overall, disease-specific and recurrence-free survival were observed with high Neo-fs index in univariate and multivariate survival analyses. Better AAA responses were observed with a high Neo-fs index, which reflected increased MHC class I, CD8+ T cell, cytolytic activity, and plasmacytoid dendritic cell signatures and decreased type II-IFN response signatures, as well as greater single-nucleotide variant (SNV) and indel counts. Conclusions: Neo-fs index, reflecting antitumor immune signature and more SNVs. and indels, is a powerful predictor of survival and AAA response in ccRCC.

Abstract P5-04-10: Immune and transcriptional signatures of dendritic cell (DC) vaccination combined with chemotherapy in locally advanced, triple-negative breast cancer (TNBC) patients

Abstract Women with triple-negative breast cancer (TNBC) have an increased pathologic complete response rate (pCR; residual disease after neoadjuvant chemotherapy) as compared to women with non-TNBC, and those with pCR have a 90% disease-free survival. However, women with TNBC who do not achieve a pCR have an increased risk of recurrence, decreased overall survival, and post-recurrence survival as compared to women with non-TNBC who do not achieve a pCR. A high priority for clinical research is therefore to increase the pCR rate in breast and axilla with preoperative therapy, as therapeutic options for patients who do not have a pCR are limited. Immunotherapy is an attractive strategy as human BCs can be immunogenic and enhancing the immune effector function may augment the cytotoxic effects of standard therapies. Immunity against tumor antigens can be boosted in cancer patients by vaccination with ex vivo-generated tumor antigen-loaded DCs. Here, we report the extended analysis of a clinical trial on 10 TNBC pts assessing the feasibility of combining cyclin B1/WT1/CEF (antigen)-loaded DC vaccination with preoperative chemotherapy in patients with locally advanced TNBC. Combination of preoperative chemotherapy and intratumoral and subcutaneous autologous DC vaccination led to 70% of combined rate of pCR and residual cancer burden 1 (RCB1). To assess expansion of antigen-specific T cell responses, IFN-g-ELISpot was carried out with PBMCs from baseline (BL) and several time points during vaccine treatment that were cultured with control peptides or with peptide libraries covering vaccine antigens. The expansion of antigen-specific immune responses could be detected at various time points post treatment. Transciptional profiling on blood (Nanostring) and tumors (RNAseq) revealed profound changes in immune transcription signatures. T cell and DC signatures in blood and T cell, inflammation, cytotoxic and cell cycle signatures in pre-chemotherapy breast cancer biopsies were linked with pathological responses in definitive surgery specimens. Taken together, differential gene and immunologic signatures of the pre-treatment breast cancer biopsies distinguish pts who have a pCR vs no pCR and can identify potential therapeutic targets for pts with TNBC. Citation Format: Te-Chia Wu, Joyce O’Shaughnessy, Lee K. Roberts, Jennifer L. Smith, Susan B. Burkeholder, Jennifer Finholt, Jessica Tarnowski, Tuoc Dao, Jeffrey Lamont, Sandra M. Zurawski, Phuong Nguyen, Yuanyuan Wang, Kyung In Kim, Derek Blankenship, Jacob Turner, Xuan Wang, Florentina Marches, Maren K. Levin, Michael Grant, Gerard Zurawski, Virginia Pascual, Jacques Banchereau, Karolina Palucka. Immune and transcriptional signatures of dendritic cell (DC) vaccination combined with chemotherapy in locally advanced, triple-negative breast cancer (TNBC) patients [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-04-10.

Association of Dendritic Cell Signatures With Autoimmune Inflammation Revealed by Single-Cell Profiling.

To identify single-cell transcriptional signatures of dendritic cells (DCs) that are associated with autoimmunity, and determine whether those DC signatures are correlated with the clinical heterogeneity of autoimmune disease. Blood-derived DCs were single-cell sorted from the peripheral blood of patients with rheumatoid arthritis, systemic lupus erythematosus, or type 1 diabetes as well as healthy individuals. DCs were analyzed using single-cell gene expression assays, performed immediately after isolation or after in vitro stimulation of the cells. In addition, protein expression was measured using fluorescence-activated cell sorting. CD1c+ conventional DCs and plasmacytoid DCs from healthy individuals exhibited diverse transcriptional signatures, while the DC transcriptional signatures in patients with autoimmune disease were altered. In particular, distinct DC clusters, characterized by up-regulation of TAP1, IRF7, and IFNAR1, were abundant in patients with systemic autoimmune disease, whereas DCs from patients with type 1 diabetes had decreased expression of the regulatory genes PTPN6, TGFB, and TYROBP. The frequency of CD1c+ conventional DCs that expressed a systemic autoimmune profile directly correlated with the extent of disease activity in patients with rheumatoid arthritis (Spearman's r = 0.60, P = 0.03). DC transcriptional signatures are altered in patients with autoimmune disease and are associated with the level of disease activity, suggesting that immune cell transcriptional profiling could improve our ability to detect and understand the heterogeneity of these diseases, and could guide treatment choices in patients with a complex autoimmune disease.

Microenvironmental immune cell signatures dictate clinical outcomes for PTCL-NOS

AbstractPeripheral T-cell lymphoma (PTCL), not otherwise specified (PTCL-NOS) is among the most common disease subtypes of PTCL, one that exhibits heterogeneous clinicopathological features. Although multiple disease-stratification models, including the cell-of-origin or gene-expression profiling methods, have been proposed for this condition, their clinical significance remains unclear. To establish a clinically meaningful stratification model, we analyzed gene-expression signatures of tumors and tumor-infiltrating immune cells using the nCounter system, which enables accurate quantification of low abundance and/or highly fragmented transcripts. To do so, we assessed transcripts of 120 genes related to cancer or immune cells using tumor samples from 68 newly diagnosed PTCL-NOS patients and validated findings by immunofluorescence in tumor sections. We show that gene-expression signatures representing tumor-infiltrating immune cells, but not those of cancerous T cells, dictate patient clinical outcomes. Cases exhibiting both B-cell and dendritic cell (DC) signatures (BD subgroup) showed favorable clinical outcomes, whereas those exhibiting neither B-cell nor DC signatures (non-BD subgroup) showed extremely poor prognosis. Notably, half of the non-BD cases exhibited a macrophage signature, and macrophage infiltration was evident in those cases, as revealed by immunofluorescence. Importantly, tumor-infiltrating macrophages expressed the immune-checkpoint molecules programmed death ligand 1/2 and indoleamine 2, 3-dioxygenase 1 at high levels, suggesting that checkpoint inhibitors could serve as therapeutic options for patients in this subgroup. Our study identifies clinically distinct subgroups of PTCL-NOS and suggests a novel therapeutic strategy for 1 subgroup associated with a poor prognosis. Our data also suggest functional interactions between cancerous T cells and tumor-infiltrating immune cells potentially relevant to PTCL-NOS pathogenesis.

A radiographic review of the subacromial architecture: a South African study

Peripheral T-cell lymphoma (PTCL), not otherwise specified (PTCL-NOS) is among the most common disease subtypes of PTCL, one that exhibits heterogeneous clinicopathological features. Although multiple disease-stratification models, including the cell-of-origin or gene-expression profiling methods, have been proposed for this condition, their clinical significance remains unclear. To establish a clinically meaningful stratification model, we analyzed gene-expression signatures of tumors and tumor-infiltrating immune cells using the nCounter system, which enables accurate quantification of low abundance and/or highly fragmented transcripts. To do so, we assessed transcripts of 120 genes related to cancer or immune cells using tumor samples from 68 newly diagnosed PTCL-NOS patients and validated findings by immunofluorescence in tumor sections. We show that gene-expression signatures representing tumor-infiltrating immune cells, but not those of cancerous T cells, dictate patient clinical outcomes. Cases exhibiting both B-cell and dendritic cell (DC) signatures (BD subgroup) showed favorable clinical outcomes, whereas those exhibiting neither B-cell nor DC signatures (non-BD subgroup) showed extremely poor prognosis. Notably, half of the non-BD cases exhibited a macrophage signature, and macrophage infiltration was evident in those cases, as revealed by immunofluorescence. Importantly, tumor-infiltrating macrophages expressed the immune-checkpoint molecules programmed death ligand 1/2 and indoleamine 2, 3-dioxygenase 1 at high levels, suggesting that checkpoint inhibitors could serve as therapeutic options for patients in this subgroup. Our study identifies clinically distinct subgroups of PTCL-NOS and suggests a novel therapeutic strategy for 1 subgroup associated with a poor prognosis. Our data also suggest functional interactions between cancerous T cells and tumor-infiltrating immune cells potentially relevant to PTCL-NOS pathogenesis.

Abstract CT175: Biomarker analyses from a phase I study of WNT974, a first-in-class Porcupine inhibitor, in patients (pts) with advanced solid tumors

Abstract Background: Dysregulated Wnt/β-catenin signaling has been linked to several cancers, including pancreatic cancer (PC) and colorectal cancer (CRC). WNT974 (formerly LGK974) - a first-in-class, selective, oral inhibitor of Porcupine (an O-acyltransferase required for Wnt activation and secretion) - has shown preclinical activity in tumor models with mutations upstream in the Wnt pathway. Furthermore, dysregulated Wnt signaling has been linked to T-cell exclusion in tumor tissue and resistance to immunotherapy, suggesting WNT974 may act synergistically with checkpoint inhibitors. Methods: This ongoing Phase I, open-label, dose-escalation and -expansion study (NCT01351103) is designed to determine the maximum tolerated dose and/or recommended dose for expansion, characterize the safety and tolerability, and assess preliminary antitumor activity, pharmacokinetic (PK), and pharmacodynamic properties of WNT974, alone or combined with PDR001 (spartalizumab, an anti-PD-1 antibody) in advanced/metastatic solid tumors. Here, we focus on preliminary biomarker analyses from the single-agent part of the study. The study initially enrolled pts with lobular breast cancer and melanoma and was later amended to enroll pts with triple negative breast cancer (TNBC), PC, and CRC, and those with tumors with genetic alterations upstream in the Wnt pathway. Pre and on-treatment skin and tumor tissue specimens were collected for RT-PCR analysis of AXIN2, a marker of Wnt pathway activity. NanoString gene expression was measured in a subset of pts using remnant RNA from the tumor samples, and chemokine and dendritic cell signatures were analyzed pre and on-treatment. Results: At the data cut-off date, March 2, 2017, 94 pts were enrolled. Median age was 58.5 years (range, 28-77), 43% were male, and the most common cancer types were PC (30%), melanoma (26%), and breast cancer (21%). Patients received single-agent WNT974 orally at doses of 5, 7.5, 10, 15, 20, 22.5, or 30 mg daily, 30 or 45 mg intermittently (4 days on, 3 days off), or 5 mg twice daily. Median duration of exposure was 4.9 weeks (range, 0.1-27.7). Safety, tolerability, and PK have previously been reported. AXIN2 expression in paired samples from skin and tumor showed evidence of Wnt pathway inhibition in all indications; this was not dose-dependent in the dose range studied. Immune signature analyses of a paired tumor sample subset (n=8) revealed an inverse association between change in AXIN2 expression and change in chemokine and activated dendritic cell signatures. Conclusions: Biomarker analyses show that WNT974 can potently inhibit Wnt pathway activity in skin and tumors. Immune signature data suggest that WNT974 treatment may promote T-cell recruitment into tumors, and support investigation of the combination of WNT974 with immunotherapy. The combination part of this study evaluating WNT974 combined with PDR001 (spartalizumab) is ongoing. Citation Format: Jordi Rodon, Guillem Argilés, Roisin M. Connolly, Ulka Vaishampayan, Maja de Jonge, Elena Garralda, Marios Giannakis, David C. Smith, Jason R. Dobson, Margaret McLaughlin, Abdelkader Seroutou, Yan Ji, Sinead Dolan, Jennifer Morawiak, Susan Moody, Filip Janku. Biomarker analyses from a phase I study of WNT974, a first-in-class Porcupine inhibitor, in patients (pts) with advanced solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr CT175.

Abstract PD6-08: Analysis of immune infiltrates (assessed via multiplex fluorescence immunohistochemistry) and immune gene expression signatures as predictors of response to the checkpoint inhibitor pembrolizumab in the neoadjuvant I-SPY 2 trial

Abstract Background: Pembrolizumab (Pembro), an anti-PD-1 immune checkpoint inhibitor, has been approved for the treatment of a variety of cancers including melanoma, non-small cell lung cancer, head and neck squamous cell carcinoma, and urothelial carcinoma. Pembro was recently evaluated in HER2- breast cancer patients in the neoadjuvant I-SPY 2 TRIAL and graduated in the triple negative (TN), HR+HER2-, and HER2- signatures. HER2- patients were randomized to receive Pembro+paclitaxel followed by doxorubicin/cyclophosphamide (P+T -> AC) vs. T -> AC. We and others have shown that TN breast cancers tend to have high numbers of immune infiltrates, including T cells and tumor associated macrophages (TAMs). We evaluated expression signatures representing 14 immune cell types (TILs, T cells, CD8 T cells, exhausted T cells, Th1, Tregs, cytotoxic cells, NK, NK CD56dim, dendritic cells, mast cells, B cells, macrophages, and neutrophils) as specific predictors of response to Pembro. Methods: Data from 248 patients (Pembro: 69; controls: 179) were available. Pre-treatment biopsies were assayed using Agilent gene expression arrays. Signature scores are calculated by averaging cell type specific genes. All I-SPY 2 qualifying biomarker analyses follow a pre-specified analysis plan. We used logistic modeling to assess biomarker performance. A biomarker is considered a specific predictor of Pembro response if it associates with response in the Pembro arm but not the control arm, and if the biomarker x treatment interaction is significant (likelihood ratio test, p<0.05). This analysis is also performed adjusting for HR status as covariates, and within receptor subsets. For successful biomarkers, we use Bayesian modeling to estimate the pCR rates of 'predicted sensitive' patients in each arm. Our statistics are descriptive rather than inferential and do not adjust for multiplicities of other biomarkers outside this study. Results: 10 out of the 14 cell-type signatures tested are associated with response in the Pembro arm. Higher expression levels of 9 of these cell-type signatures are associated with higher pCR rates (T cells, exhausted T cells, Th1, cytotoxic cells, NK, NK CD56dim, dendritic cells, B cells, and macrophages), whereas higher mast cell signature expression is associated with non-pCR. Interestingly, many of these same signatures also associate or trend towards association with response in the control arm; and in a model adjusting for HR status, only 3 of these signatures (Th1, B cells and dendritic cells) show significant interaction with treatment. Within the whole population and the TN subtype, the dendritic cell signature is the strongest predictor of specific response to Pembro (OR/1SD: 4.04 and 4.4, LR p < 0.001 overall and in TN). Although other immune signatures (T cells, exhausted T cells, NK, and macrophages) also associate with response in the Pembro arm in the TN subtype, only the dendritic cell and Th1 signatures have a significant interaction with treatment. In contrast, in the HR+HER2- subtype, only 3 signatures (Th1, B cells, and mast cells) associate with response to Pembro; but none of these signatures have significant interaction with treatment. Of note, in both the Pembro and control arms, HR+HER2- patients with higher average mast cell marker expression have lower pCR rates (OR/1SD: 0.33 and 0.51, LRp: 0.006 and 0.04 in Pembro and control arm). Conclusion: As expected, multiple immune cell expression signatures are predictive of response in the Pembro arm; but only dendritic cells and Th1 cells are specific to Pembro in both the population as a whole and the TN subtype. Interestingly, the presence of mast cells may impede response, especially in HR+HER2- patients. Correlation of these signatures with multiplex-IF immune markers is pending. Citation Format: Campbell M, Yau C, Borowsky A, Vandenberg S, Wolf D, Rimm D, Nanda R, Liu M, Brown-Swigart L, Hirst G, Asare S, van't Veer L, Yee D, DeMichele A, Berry D, Esserman L. Analysis of immune infiltrates (assessed via multiplex fluorescence immunohistochemistry) and immune gene expression signatures as predictors of response to the checkpoint inhibitor pembrolizumab in the neoadjuvant I-SPY 2 trial [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD6-08.