Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer

Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning (ML) to analyze a single-cell, spatial, and highly multiplexed proteomic data set from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcomes. We designed a multiplex immunohistochemistry antibody panel to compare T-cell functionality and spatial localization in resected tumors from treatment-naïve patients with localized pancreatic ductal adenocarcinoma (PDAC) with resected tumors from a second cohort of patients treated with neoadjuvant agonistic CD40 (anti-CD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both cohorts were assayed, and over 1,000 tumor microenvironment (TME) features were quantified. We then trained ML models to accurately predict anti-CD40 treatment status and disease-free survival (DFS) following anti-CD40 therapy based on TME features. Through downstream interpretation of the ML models' predictions, we found anti-CD40 therapy reduced canonical aspects of T-cell exhaustion within the TME, as compared with treatment-naïve TMEs. Using automated clustering approaches, we found improved DFS following anti-CD40 therapy correlated with an increased presence of CD44+CD4+ Th1 cells located specifically within cellular neighborhoods characterized by increased T-cell proliferation, antigen experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of ML in molecular cancer immunology applications, highlight the impact of anti-CD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for anti-CD40-treated patients with PDAC.

Digitize your Biology! Modeling multicellular systems through interpretable cell behavior

Cells are fundamental units of life, constantly interacting and evolving as dynamical systems. While recent spatial multi-omics can quantitate individual cells' characteristics and regulatory programs, forecasting their evolution ultimately requires mathematical modeling. We develop a conceptual framework-a cell behavior hypothesis grammar-that uses natural language statements (cell rules) to create mathematical models. This allows us to systematically integrate biological knowledge and multi-omics data to make them computable. We can then perform virtual "thought experiments" that challenge and extend our understanding of multicellular systems, and ultimately generate new testable hypotheses. In this paper, we motivate and describe the grammar, provide a reference implementation, and demonstrate its potential through a series of examples in tumor biology and immunotherapy. Altogether, this approach provides a bridge between biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale, allowing the community to extrapolate from single-cell characterization to emergent multicellular behavior.

Dual-modality imaging of immunofluorescence and imaging mass cytometry for whole-slide imaging and accurate segmentation

Imaging mass cytometry (IMC) is a powerful technique capable of detecting over 30 markers on a single slide. It has been increasingly used for single-cell-based spatial phenotyping in a wide range of samples. However, it only acquires a rectangle field of view (FOV) with a relatively small size and low image resolution, which hinders downstream analysis. Here, we reported a highly practical dual-modality imaging method that combines high-resolution immunofluorescence (IF) and high-dimensional IMC on the same tissue slide. Our computational pipeline uses the whole-slide image (WSI) of IF as a spatial reference and integrates small-FOV IMC into a WSI of IMC. The high-resolution IF images enable accurate single-cell segmentation to extract robust high-dimensional IMC features for downstream analysis. We applied this method in esophageal adenocarcinoma of different stages, identified the single-cell pathology landscape via reconstruction of WSI IMC images, and demonstrated the advantage of the dual-modality imaging strategy.

Machine learning links T cell function and spatial localization to neoadjuvant immunotherapy and clinical outcome in pancreatic cancer

Tumor molecular datasets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning to analyze a single-cell, spatial, and highly multiplexed proteomic dataset from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcome. A novel multiplex immunohistochemistry antibody panel was used to audit T cell functionality and spatial localization in resected tumors from treatment-naive patients with localized pancreatic ductal adenocarcinoma (PDAC) compared to a second cohort of patients treated with neoadjuvant agonistic CD40 (αCD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both treatment cohorts were assayed, and more than 1,000 tumor microenvironment (TME) features were quantified. We then trained machine learning models to accurately predict αCD40 treatment status and disease-free survival (DFS) following αCD40 therapy based upon TME features. Through downstream interpretation of the machine learning models' predictions, we found αCD40 therapy to reduce canonical aspects of T cell exhaustion within the TME, as compared to treatment-naive TMEs. Using automated clustering approaches, we found improved DFS following αCD40 therapy to correlate with the increased presence of CD44+ CD4+ Th1 cells located specifically within cellular spatial neighborhoods characterized by increased T cell proliferation, antigen-experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of machine learning in molecular cancer immunology applications, highlight the impact of αCD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for αCD40-treated patients with PDAC.

MYC Deregulation and PTEN Loss Model Tumor and Stromal Heterogeneity of Aggressive Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new therapies, however, few mouse models represent the complexity of TNBC. Here, we develop a female TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl model develops heterogeneous triple-negative mammary tumors that display histological and molecular features commonly found in human TNBC. Our research involves deep molecular and spatial analyses on Myc;Ptenfl tumors including bulk and single-cell RNA-sequencing, and multiplex tissue-imaging. Through comparison with human TNBC, we demonstrate that this genetic mouse model develops mammary tumors with differential survival and therapeutic responses that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC, providing a pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response.

Alignment, segmentation and neighborhood analysis in cyclic immunohistochemistry data using CASSATT

Cyclic immunohistochemistry (cycIHC) uses sequential rounds of colorimetric immunostaining and imaging for quantitative mapping of location and number of cells of interest. Additionally, cycIHC benefits from the speed and simplicity of brightfield microscopy, making the collection of entire tissue sections and slides possible at a trivial cost compared to other high dimensional imaging modalities. However, large cycIHC datasets currently require an expert data scientist to concatenate separate open-source tools for each step of image pre-processing, registration, and segmentation, or the use of proprietary software. Here, we present a unified and user-friendly pipeline for processing, aligning, and analyzing cycIHC data - Cyclic Analysis of Single-Cell Subsets and Tissue Territories (CASSATT). CASSATT registers scanned slide images across all rounds of staining, segments individual nuclei, and measures marker expression on each detected cell. Beyond straightforward single cell data analysis outputs, CASSATT explores the spatial relationships between cell populations. By calculating the log odds of interaction frequencies between cell populations within tissues and tissue regions, this pipeline helps users identify populations of cells that interact-or do not interact-at frequencies that are greater than those occurring by chance. It also identifies specific neighborhoods of cells based on the assortment of neighboring cell types that surround each cell in the sample. The presence and location of these neighborhoods can be compared across slides or within distinct regions within a tissue. CASSATT is a fully open source workflow tool developed to process cycIHC data and will allow greater utilization of this powerful staining technique.

An open protocol for modeling T Cell Clonotype repertoires using TCRβ CDR3 sequences

T cell receptor repertoires can be profiled using next generation sequencing (NGS) to measure and monitor adaptive dynamical changes in response to disease and other perturbations. Genomic DNA-based bulk sequencing is cost-effective but necessitates multiplex target amplification using multiple primer pairs with highly variable amplification efficiencies. Here, we utilize an equimolar primer mixture and propose a single statistical normalization step that efficiently corrects for amplification bias post sequencing. Using samples analyzed by both our open protocol and a commercial solution, we show high concordance between bulk clonality metrics. This approach is an inexpensive and open-source alternative to commercial solutions.

Challenges and opportunities for modeling aging and cancer

Age is among the main risk factors for cancer, and any cancer study in adults is faced with an aging tissue and organism. Yet, pre-clinical studies are carried out using young mice and are not able to address the impact of aging and associated comorbidities on disease biology and treatment outcomes. Here, we discuss the limitations of current mouse cancer models and suggest strategies for developing novel models to address these major gaps in knowledge and experimental approaches.

Abstract 3473: High throughput screening of combination therapies to improve response to checkpoint inhibitors in solid tumors using a myelomonocytic and T cell co-culture assay

Background: Immune checkpoint inhibitors (ICI) targeting the PD-1/PD-L1 pathway are part of the new “standard of care” treatment for a number of advanced cancers. However, for many types of cancer, targeting either PD-1 or PD-L1 is associated with clinical benefit in a minority of patients. Combination strategies are needed to improve clinical benefit rates in ‘immune responsive’ cancers, and to expand treatment options for non-responsive cancers. Preclinical models have revealed that tumor-associated macrophages (TAMs) possess T cell-suppressive activities associated with resistance to PD-1/PD-L1 targeted therapies. To reveal therapeutic targets to relieve this suppression, we developed a robust cell-based high-throughput screening (HTS) assay to identify small molecules that can relieve myelomonocytic cell-dependent T cell-suppression, and that enhance T cell activities when combined with PD-1/PD-L1 ICI.

Methods: Bone marrow-derived myelomonocytic cells and splenic T cells were used to develop the HTS assay. After exposure to libraries of small molecules, co-cultures were evaluated for enhanced T cell activity, followed by in vivo investigations of emerging small molecules in syngeneic murine models of breast cancer to reveal anti-tumor activity.

Results: Over 1,400 FDA-approved drugs, used for both cancer or non-cancer indications, were screened in the HTS assay, 66 of which demonstrated activity in the HTS assay. Approximately 50% of these were known anti-inflammatory agents, with the highest density reflecting various COX-2 inhibitors (COX-2i). In vivo, combination therapy of the COX-2i with PD-1/PD-L1 ICI resulted in a significant reduction in tumor growth kinetics in both 4T1 and EMT6 breast cancer models, both of which are resistant to PD-1/PD-L1 inhibitors as monotherapy. In the 4T1 model, slowed tumor kinetics was associated with ICI increased T cell activation as compared to controls or monotherapy anti-PD-1/PD-L1 therapy.

Conclusions: A myelomonocytic cell-dependent T cell-suppression assay can be used to develop a HTS platform for discovering combination therapies showing antitumor responses in preclinical models. COX-2 inhibitors can be repurposed to enhance therapeutic benefits of PD-1/PD-L1 targeting agents in breast cancer patients.

Keywords: Myelomonocytic cells, T-cell, immunotherapy, PD-1, PD-L1, breast cancer

Citation Format: Sushil Kumar, Dhanir Tailor, Arpit Dheeraj, Wenqi Li, Jee Min Lee, Kirsten Stefan, Dylan Nelson, Shivaani Kummar, Lisa M. Coussens, Sanjay V. Malhotra. High throughput screening of combination therapies to improve response to checkpoint inhibitors in solid tumors using a myelomonocytic and T cell co-culture assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3473.

Abstract 4916: Spatial analysis of local drug induced changes in tumor microenvironment predicts effective treatment combinations in breast cancer

Anticancer therapeutics primarily designed to target tumor intrinsic mechanisms may also affect components of tumor microenvironment (TME) - immune cells and non-immune stroma. Recent literature reenforces the concept that complex interactions between drugs, neoplastic cells and cells of TME determine the efficacy of anticancer therapies. Systems understanding of these interactions can serve to predict effective treatment combinations simultaneously attacking tumor cell vulnerabilities, enhancing immune surveillance, and mitigating stromal mediators of resistance. The key challenge is to find such TME-modulating combinations in a fast and more informative way. We have developed an integrated analytical platform termed Multiplex Implantable Microdevice Assay (MIMA) to rapidly decompose cancer complexity in drug response and find biomarkers with predictive value for combination therapy efficacy including immunotherapy efficacy. The system deploys a (i) miniaturized implantable microdevice for localized intratumoral drug delivery and (ii) multiplex immunostaining to measure 30+ proteins in single cells at each drug well. Computational analyses of local drug-induced changes provide information about the composition, functional state and spatial cell organization of the tumor and associated TME ultimately bringing new insights into drug mechanisms of action. We used MIMA in genetically engineered mouse models of breast cancer to evaluate effects of five targeted anticancer agents (olaparib, palbociclib, venetoclax, panobinostat, lenvatinib) and two chemotherapies (doxorubicin, paclitaxel) and predicted synergistic antitumor effects with anti-PD-1, anti-CD40, anti-CSF1R immunotherapies and vasculature modulating agents. Some of the most effective combinations were not reported before. A pan-HDAC inhibitor, panobinostat, that synergized with anti-PD-1, induced immunogenic cell death and infiltration of antigen presenting neutrophils. Further longitudinal spatial analyses revealed that mechanisms of resistance co-emerged with these response phenotypes and became prominent over time. We measured fibroblast, protumorigenic macrophage and cytotoxic B cell recruitment associated with heavy deposition of collagen VI, increased immune suppression and emergence of invasive and cancer stem cells. Combination with stroma modulating agent, losartan, improved the efficacy of panobinostat/anti-PD-1 in systemic studies implying that normalization of non-immune stroma might favorably alter aspects of TME for immune and targeted therapy efficacy. All in all, MIMA may represent a new approach to predict effective combination regimens for individual cancer patients. Extended MIMA use and computational modeling of the spatial cell patterns could provide actionable information for development of effective drug doses and schedules.

Citation Format: Zuzana Tatarova, Dylan C. Blumberg, Gordon B. Mills, Lisa M. Coussens, Oliver Jonas, Joe W. Gray. Spatial analysis of local drug induced changes in tumor microenvironment predicts effective treatment combinations in breast cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4916.

Abstract 4293: Strategies and resources for applying a quantitative multiplex IHC imaging workflow to characterize immune contexture in solid tumors

Conventional immunohistochemistry (IHC) is a standardized diagnostic technique used in tissue pathology. However, the capacity to label only one marker per tissue section is a critical limitation. Multiplex immunohistochemistry (mIHC) is a powerful imaging technique used in basic, translational research and clinical settings to simultaneously detect the expression of multiple epitopes in a single formalin-fixed paraffin-embedded (FFPE) tissue section, allowing for characterization and quantification of cells while maintaining their spatial location. This technique allows for a comprehensive view of the immune milieu, expression patterns, and interactions between cell types that can help elucidate the complexity of the tumor-immune microenvironment (TiME). Multiplex imaging has emerged as a powerful tool to better understand tumor progression, response or resistance to therapy, and potentially identify predictive biomarkers. However, this technique requires careful tissue considerations and generates enormous amounts of hierarchical data, including single cell marker expressions, locations, and shape features, resulting in complex and challenging analyses. We previously published a validated platform using nine matched primary and recurrent head and neck squamous cell carcinoma (HNSCC) sections stained sequentially with a panel of 29 antibodies identifying malignant tumor cells, and 17 distinct leukocyte lineages and their functional states1. Here, we have optimized and consolidated important considerations, including tissue quality and QC steps necessary for generating high quality data from multiplex imaging studies. We demonstrate strategies for a streamline analytic pipeline using our quantitative workflow developed to characterize immune cells and infiltration patterns within spatial compartments of solid tumors in FFPE tissues, and herein, provide strategies and resources to practically adapt and utilize our analytic mIHC pipeline.

1. Banik, G., et al., Methods Enzymol., 2020

Citation Format: Shamilene Sivagnanam, Courtney M. Betts, Nell Kirchberger, Konjit Betre, Lisa M. Coussens. Strategies and resources for applying a quantitative multiplex IHC imaging workflow to characterize immune contexture in solid tumors. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4293.

T cell egress via lymphatic vessels is tuned by antigen encounter and limits tumor control

Antigen-specific CD8+ T cell accumulation in tumors is a prerequisite for effective immunotherapy, and yet the mechanisms of lymphocyte transit are not well defined. Here we show that tumor-associated lymphatic vessels control T cell exit from tumors via the chemokine CXCL12, and intratumoral antigen encounter tunes CXCR4 expression by effector CD8+ T cells. Only high-affinity antigen downregulates CXCR4 and upregulates the CXCL12 decoy receptor, ACKR3, thereby reducing CXCL12 sensitivity and promoting T cell retention. A diverse repertoire of functional tumor-specific CD8+ T cells, therefore, exit the tumor, which limits the pool of CD8+ T cells available to exert tumor control. CXCR4 inhibition or loss of lymphatic-specific CXCL12 boosts T cell retention and enhances tumor control. These data indicate that strategies to limit T cell egress might be an approach to boost the quantity and quality of intratumoral T cells and thereby response to immunotherapy.

Axatilimab for Chronic Graft-Versus-Host Disease After Failure of at Least Two Prior Systemic Therapies: Results of a Phase I/II Study

PURPOSE

Chronic graft-versus-host disease (cGVHD) remains the major cause of late morbidity after allogeneic hematopoietic cell transplantation. Colony-stimulating factor 1 receptor (CSF-1R)-dependent macrophages promote cGVHD fibrosis, and their elimination in preclinical studies ameliorated cGVHD. Axatilimab is a humanized monoclonal antibody that inhibits CSF-1R signaling and restrains macrophage development.

PATIENTS AND METHODS

This phase I (phI)/phase II (phII) open-label study (ClinicalTrials.gov identifier: NCT03604692) evaluated safety, tolerability, and efficacy of axatilimab in patients age ≥ 6 years with active cGVHD after ≥ 2 prior systemic therapy lines. Primary objectives in phI were to identify the optimal biologic and recommended phII dose and in phII to evaluate the overall (complete and partial) response rate (ORR) at the start of treatment cycle 7.

RESULTS

Forty enrolled patients (17 phI; 23 phII) received at least one axatilimab dose. In phI, a dose of 3 mg/kg given once every 4 weeks met the optimal biologic dose definition. Two dose-limiting toxicities occurred at the 3 mg/kg dose given once every 2 weeks. At least one treatment-related adverse event (TRAE) was observed in 30 patients with grade ≥ 3 TRAEs in eight patients, the majority known on-target effects of CSF-1R inhibition. No cytomegalovirus reactivations occurred. With the 50% ORR at cycle 7 day 1, the phII cohort met the primary efficacy end point. Furthermore, the ORR in the first six cycles, an end point supporting regulatory approvals, was 82%. Responses were seen in all affected organs regardless of prior therapy. Fifty-eight percent of patients reported significant improvement in cGVHD-related symptoms using the Lee Symptom Scale. On-target activity of axatilimab was suggested by the decrease in skin CSF-1R-expressing macrophages.

CONCLUSION

Targeting profibrotic macrophages with axatilimab is a therapeutically promising novel strategy with a favorable safety profile for refractory cGVHD.

Supervised learning of high-confidence phenotypic subpopulations from single-cell data

Accurately identifying phenotype-relevant cell subsets from heterogeneous cell populations is crucial for delineating the underlying mechanisms driving biological or clinical phenotypes. Here, by deploying a learning with rejection strategy, we developed a novel supervised learning framework called PENCIL to identify subpopulations associated with categorical or continuous phenotypes from single-cell data. By embedding a feature selection function into this flexible framework, for the first time, we were able to select informative features and identify cell subpopulations simultaneously, which enables the accurate identification of phenotypic subpopulations otherwise missed by methods incapable of concurrent gene selection. Furthermore, the regression mode of PENCIL presents a novel ability for supervised phenotypic trajectory learning of subpopulations from single-cell data. We conducted comprehensive simulations to evaluate PENCIĽs versatility in simultaneous gene selection, subpopulation identification and phenotypic trajectory prediction. PENCIL is fast and scalable to analyze 1 million cells within 1 hour. Using the classification mode, PENCIL detected T-cell subpopulations associated with melanoma immunotherapy outcomes. Moreover, when applied to scRNA-seq of a mantle cell lymphoma patient with drug treatment across multiple time points, the regression mode of PENCIL revealed a transcriptional treatment response trajectory. Collectively, our work introduces a scalable and flexible infrastructure to accurately identify phenotype-associated subpopulations from single-cell data.

Dual-modality imaging of immunofluorescence and imaging mass cytometry for whole slide imaging with accurate single-cell segmentation

Imaging mass cytometry (IMC) is a powerful multiplexed tissue imaging technology that allows simultaneous detection of more than 30 makers on a single slide. It has been increasingly used for singlecell-based spatial phenotyping in a wide range of samples. However, it only acquires a small, rectangle field of view (FOV) with a low image resolution that hinders downstream analysis. Here, we reported a highly practical dual-modality imaging method that combines high-resolution immunofluorescence (IF) and high-dimensional IMC on the same tissue slide. Our computational pipeline uses the whole slide image (WSI) of IF as a spatial reference and integrates small FOVs IMC into a WSI of IMC. The high-resolution IF images enable accurate single-cell segmentation to extract robust high-dimensional IMC features for downstream analysis. We applied this method in esophageal adenocarcinoma of different stages, identified the single-cell pathology landscape via reconstruction of WSI IMC images, and demonstrated the advantage of the dual-modality imaging strategy.

Motivation

Highly multiplexed tissue imaging allows visualization of the spatially resolved expression of multiple proteins at the single-cell level. Although imaging mass cytometry (IMC) using metal isotope-conjugated antibodies has a significant advantage of low background signal and absence of autofluorescence or batch effect, it has a low resolution that hampers accurate cell segmentation and results in inaccurate feature extraction. In addition, IMC only acquires mm 2 -sized rectangle regions, which limits its application and efficiency when studying larger clinical samples with non-rectangle shapes. To maximize the research output of IMC, we developed the dual-modality imaging method based on a highly practical and technical improvement requiring no extra specialized equipment or agents and proposed a comprehensive computational pipeline that combines IF and IMC. The proposed method greatly improves the accuracy of cell segmentation and downstream analysis and is able to obtain whole slide image IMC to capture the comprehensive cellular landscape of large tissue sections.

An open protocol for modeling T Cell Clonotype repertoires using TCRβ CDR3 sequences

T cell receptor repertoires can be profiled using next generation sequencing (NGS) to measure and monitor adaptive dynamical changes in response to disease and other perturbations. Genomic DNA-based bulk sequencing is cost-effective but necessitates multiplex target amplification using multiple primer pairs with highly variable amplification efficiencies. Here, we utilize an equimolar primer mixture and propose a single statistical normalization step that efficiently corrects for amplification bias post sequencing. Using samples analyzed by both our open protocol and a commercial solution, we show high concordance between bulk clonality metrics. This approach is an inexpensive and open-source alternative to commercial solutions.

Modulation of myeloid and T cells in vivo by Bruton's tyrosine kinase inhibitor ibrutinib in patients with metastatic pancreatic ductal adenocarcinoma

BACKGROUND

In preclinical studies of pancreatic ductal adenocarcinoma (PDAC), ibrutinib improved the antitumor efficacy of the standard of care chemotherapy. This led to a phase 1b clinical trial to determine the safety, tolerability, and immunologic effects of ibrutinib treatment in patients with advanced PDAC.

METHODS

Previously untreated patients with PDAC were enrolled in a phase 1b clinical trial (ClinicalTrials.gov) to determine the safety, toxicity, and maximal tolerated dose of ibrutinib when administered with the standard regimen of gemcitabine and nab-paclitaxel. To study the immune response to ibrutinib alone, the trial included an immune response arm where patients were administered with ibrutinib daily for a week followed by ibrutinib combined with gemcitabine and nab-paclitaxel. Endoscopic ultrasonography-guided primary PDAC tumor biopsies and blood were collected before and after ibrutinib monotherapy. Changes in abundance and functional state of immune cells in the blood was evaluated by mass cytometry by time of flight and statistical scaffold analysis, while that in the local tumor microenvironment (TME) were assessed by multiplex immunohistochemistry. Changes in B-cell receptor and T-cell receptor repertoire were assessed by sequencing and analysis of clonality.

RESULTS

In the blood, ibrutinib monotherapy significantly increased the frequencies of activated inducible T cell costimulator⁺(ICOS⁺) CD4⁺ T cells and monocytes. Within the TME, ibrutinib monotherapy led to a trend in decreased B-cell abundance but increased interleukin-10⁺ B-cell frequency. Monotherapy also led to a trend in increased mature CD208⁺dendritic cell density, increased late effector (programmed cell death protein 1 (PD-1^-) eomesodermin (EOMES⁺)) CD8⁺ T-cell frequency, with a concomitantly decreased dysfunctional (PD-1⁺ EOMES⁺) CD8⁺ T-cell frequency. When ibrutinib was combined with chemotherapy, most of these immune changes were not observed. Patients with partial clinical responses had more diverse T and B cell receptor repertoires prior to therapy initiation.

CONCLUSION

Ibrutinib monotherapy skewed the immune landscape both in the circulation and TME towards activated T cells, monocytes and DCs. These effects were not observed when combining ibrutinib with standard of care chemotherapy. Future studies may focus on other therapeutic combinations that augment the immunomodulatory effects of ibrutinib in solid tumors.

TRIAL REGISTRATION NUMBER

NCT02562898.

Quantitative Spatial Profiling of Immune Populations in Pancreatic Ductal Adenocarcinoma Reveals Tumor Microenvironment Heterogeneity and Prognostic Biomarkers

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive disease with poor 5-year survival rates, necessitating identification of novel therapeutic targets. Elucidating the biology of the tumor immune microenvironment (TiME) can provide vital insights into mechanisms of tumor progression. In this study, we developed a quantitative image processing platform to analyze sequential multiplexed IHC data from archival PDAC tissue resection specimens. A 27-plex marker panel was employed to simultaneously phenotype cell populations and their functional states, followed by a computational workflow to interrogate the immune contextures of the TiME in search of potential biomarkers. The PDAC TiME reflected a low-immunogenic ecosystem with both high intratumoral and intertumoral heterogeneity. Spatial analysis revealed that the relative distance between IL10+ myelomonocytes, PD-1+ CD4+ T cells, and granzyme B+ CD8+ T cells correlated significantly with survival, from which a spatial proximity signature termed imRS was derived that correlated with PDAC patient survival. Furthermore, spatial enrichment of CD8+ T cells in lymphoid aggregates was also linked to improved survival. Altogether, these findings indicate that the PDAC TiME, generally considered immuno-dormant or immunosuppressive, is a spatially nuanced ecosystem orchestrated by ordered immune hierarchies. This new understanding of spatial complexity may guide novel treatment strategies for PDAC.

SIGNIFICANCE

Quantitative image analysis of PDAC specimens reveals intertumoral and intratumoral heterogeneity of immune populations and identifies spatial immune architectures that are significantly associated with disease prognosis.

A multiplex implantable microdevice assay identifies synergistic combinations of cancer immunotherapies and conventional drugs

Systematically identifying synergistic combinations of targeted agents and immunotherapies for cancer treatments remains difficult. In this study, we integrated high-throughput and high-content techniques-an implantable microdevice to administer multiple drugs into different sites in tumors at nanodoses and multiplexed imaging of tumor microenvironmental states-to investigate the tumor cell and immunological response signatures to different treatment regimens. Using a mouse model of breast cancer, we identified effective combinations from among numerous agents within days. In vivo studies in three immunocompetent mammary carcinoma models demonstrated that the predicted combinations synergistically increased therapeutic efficacy. We identified at least five promising treatment strategies, of which the panobinostat, venetoclax and anti-CD40 triple therapy was the most effective in inducing complete tumor remission across models. Successful drug combinations increased spatial association of cancer stem cells with dendritic cells during immunogenic cell death, suggesting this as an important mechanism of action in long-term breast cancer control.

Abstract A067: Myc drives phenotypic heterogeneity, metastasis, and therapy resistance in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAc) ranks among the top three most aggressive cancers in the United States and is projected to increase in incidence over the next few years. Standard of care treatment for PDAc consists of a cocktail of harsh chemotherapies, which have improved overall survival by only a few percentage points—to a 5-year survival rate of 11%. One commonly deregulated pathway in PDAc is c-MYC (MYC), a potent transcription factor. MYC plays an important role in tumor progression and its deregulation has been correlated with tumor aggressiveness and therapeutic resistance in PDAc and other cancers. Recently, oncogenic MYC expression has been shown to regulate elements of the tumor microenvironment (TME) in mouse models of multiple cancers. In PDAc, MYC’s expression has been linked to a desmoplastic immune suppressive TME, yet the specific mechanism has yet to be described. Here, we present a novel genetically engineered mouse model (GEMM) of PDAc that can be used to better model the disease and to interrogate questions of how MYC regulates the tumor immune and stromal microenvironments. Our KMCERT2 model has inducible Cre-driven expression of both mutant Kras and low deregulated Myc in the pancreas. We show that deregulated MYC cooperates with KRASG12D in the adult pancreas to drive PDAc, and our model recapitulates inter- and intra-tumoral heterogeneity seen within clinical PDAc populations. Currently, a majority of murine studies of PDAc are performed using an embryonic KrasG12D- and p53 loss/mutant-driven PDAc model (KPC). RNA- and DNA sequencing on both microdissected autochthonous tumor specimens and KMCERT2 tumor-derived cell lines was conducted to further understand the mechanisms underlying our observed phenotypes. In contrast to the KPC model, our inducible KMCERT2 model of PDAc displays genetic changes, such as CDKN2A and SMAD4 loss, comparable to human disease. Interestingly, multiplexed immunohistochemistry analysis of immune cell composition of spontaneous KMCERT2 tumors compared to the commonly used KPC shows an increased density of antigen presenting cells (APCs) within MYC-driven tumors. Human PDAc is often resistant to standard of care therapies such as gemcitabine and FOLFIRINOX. Orthotopic therapeutic studies using our KMCERT2 tumor-derived cell lines demonstrate a similar resistance to these therapies, allowing us to use this model to better understand the mechanisms leading to therapeutic resistance and to test new therapies. In addition, we find consistent metastasis to the liver in both spontaneous and orthotopic transplant settings. Together, this work investigates the role of deregulated MYC expression in metastatic behavior, immune phenotypes, and therapeutic response in murine PDAc. It also provides both spontaneous and orthotopic mouse models of PDAc that recapitulate the heterogeneous and highly metastatic nature of the human disease, allowing for important therapeutic testing opportunities.

Citation Format: Isabel A. English, Patrick J. Worth, Amy S. Farrell, Brittany L. Allen-Petersen, Vidhi Shah, Courtney Betts, Carl Pelz, Xiaoyan Wang, Colin J. Daniel, Mary C Thoma, Lisa M Coussens, Ellen M Langer, Rosalie C Sears. Myc drives phenotypic heterogeneity, metastasis, and therapy resistance in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr A067.

A Cancer Cell-Intrinsic GOT2-PPARδ Axis Suppresses Antitumor Immunity

Despite significant recent advances in precision medicine, pancreatic ductal adenocarcinoma (PDAC) remains near uniformly lethal. Although immune-modulatory therapies hold promise to meaningfully improve outcomes for patients with PDAC, the development of such therapies requires an improved understanding of the immune evasion mechanisms that characterize the PDAC microenvironment. Here, we show that cancer cell-intrinsic glutamic-oxaloacetic transaminase 2 (GOT2) shapes the immune microenvironment to suppress antitumor immunity. Mechanistically, we find that GOT2 functions beyond its established role in the malate-aspartate shuttle and promotes the transcriptional activity of nuclear receptor peroxisome proliferator-activated receptor delta (PPARδ), facilitated by direct fatty acid binding. Although GOT2 is dispensable for cancer cell proliferation in vivo, the GOT2-PPARδ axis promotes spatial restriction of both CD4+ and CD8+ T cells from the tumor microenvironment. Our results demonstrate a noncanonical function for an established mitochondrial enzyme in transcriptional regulation of immune evasion, which may be exploitable to promote a productive antitumor immune response.

SIGNIFICANCE

Prior studies demonstrate the important moonlighting functions of metabolic enzymes in cancer. We find that the mitochondrial transaminase GOT2 binds directly to fatty acid ligands that regulate the nuclear receptor PPARδ, and this functional interaction critically regulates the immune microenvironment of pancreatic cancer to promote tumor progression. See related commentary by Nwosu and di Magliano, p. 2237.. This article is highlighted in the In This Issue feature, p. 2221.

Therapeutics That Promote Sympathetic Reinnervation Modulate the Inflammatory Response After Myocardial Infarction

Myocardial infarction (MI) triggers an inflammatory response that transitions from pro-inflammatory to reparative over time. Restoring sympathetic nerves in the heart after MI prevents arrhythmias. This study investigated if reinnervation altered the immune response after MI. This study used quantitative multiplex immunohistochemistry to identify the immune cells present in the heart 2 weeks after ischemia-reperfusion. Two therapeutics stimulated reinnervation, preventing arrhythmias and shifting the immune response from inflammatory to reparative, with fewer pro-inflammatory macrophages and more regulatory T cells and reparative macrophages. Treatments did not alter macrophage phenotype in vitro, which suggested reinnervation contributed to the altered immune response.

Abstract 2149: Biomarker-driven selection of polyADP ribose polymerase inhibitors (PARPi)-based combination therapies in patients with metastatic triple negative breast cancer (mTNBC)

Background: Emerging data supports PARPi combinations, including PARPi with immune checkpoint blockade (ICB), as effective therapies in TNBC. The Adaptive Multi-Drug Treatment of Evolving Cancers (AMTEC) trial (NCT03801369) is evaluating the PARPi + ICB combination of olaparib (ola) + durvalumab (durva) in mTNBC patients (pts). Deep profiling of paired pre- and on-ola monotherapy TNBC biopsies (Bx) is key to identifying: i) predictive biomarkers to select pts who will benefit from PARPi + ICB, and ii) resistance mechanisms that inform on other rational PARPi combinations. We report on biomarker characterization of paired Bxs from 18 AMTEC pts.

Methods: AMTEC pts undergo a pre-ola Bx (Bx1), start one (28-day) cycle of ola monotherapy (300 mg BID), with a repeat on-ola Bx (Bx2) before adding durva (1500 mg Q4W) to ola. Profiling of DNA, RNA and protein signals in Bx1 and Bx2 using WES, RNAseq, RPPA, and spatially resolved single cell proteomics using cycIF and mIHC was correlated with clinical outcomes to identify predictors of ola + durva sensitivity, and adaptive resistance to PARPi therapy.

Results: WES/RNAseq - TNBC subtype (Bx1) was a strong predictor of response, with basal immune activated (BLIA), luminal androgen receptor (LAR), and basal immune suppressed (BLIS) subtypes associated with mPFS of 8.7, 2.5, and 1.7 months, respectively (p<0.05). MutSig3 signature in Bx1 (Yes = 7.4 mo vs. No = 2.5 mo; p<0.05), or increases in IFN signaling in Bx2 (Yes = 6.6 mo vs. No = 2.2 mo; p<0.05) were positive predictors of mPFS.

RPPA - Change in PD-L1 expression on Bx2 (from Bx1) was a positive predictor (p<0.05). RAS-MAPK pathway activation in Bx1 was predictive of a poor response (p<0.05).

mIHC - Two dominant immune cell groups were identified: 1) T cell enriched, and 2) hypoinflammed. On Bx1, most pts in the T cell enriched group achieved a partial response (PR) or stable disease (SD), whereas pts in the hypoinflammed group all had progressive disease (PD, p=0.04). On Bx2, all pts in the T cell enriched group were PR or SD, whereas PD pts comprised the hypoinflammed group (p=0.06).

Conclusions: Findings highlight the value of paired Bxs to identify predictive biomarkers of PARPi + ICB sensitivity. Emerging resistance mechanisms justify amending AMTEC to a PARPi biomarker-driven trial evaluating ola in combination with durva, selumetinib (MEKi), or capivasertib (AKTi).

Citation Format: Zahi I. Mitri, Evthokia A. Hobbs, Shaun M. Goodyear, Jeong Youn Lim, Joanna Pucilowska, Brett Johnson, Allison L. Creason, Courtney Betts, Lisa M. Coussens, Shannon McWeeney, Christopher L. Corless, Joe W. Gray, Gordon B. Mills. Biomarker-driven selection of polyADP ribose polymerase inhibitors (PARPi)-based combination therapies in patients with metastatic triple negative breast cancer (mTNBC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2149.

Deciphering the Immune Complexity in Esophageal Adenocarcinoma and Pre-Cancerous Lesions With Sequential Multiplex Immunohistochemistry and Sparse Subspace Clustering Approach

Esophageal adenocarcinoma (EAC) develops from a chronic inflammatory environment across four stages: intestinal metaplasia, known as Barrett's esophagus, low- and high-grade dysplasia, and adenocarcinoma. Although the genomic characteristics of this progression have been well defined via large-scale DNA sequencing, the dynamics of various immune cell subsets and their spatial interactions in their tumor microenvironment remain unclear. Here, we applied a sequential multiplex immunohistochemistry (mIHC) platform with computational image analysis pipelines that allow for the detection of 10 biomarkers in one formalin-fixed paraffin-embedded (FFPE) tissue section. Using this platform and quantitative image analytics, we studied changes in the immune landscape during disease progression based on 40 normal and diseased areas from endoscopic mucosal resection specimens of chemotherapy treatment- naïve patients, including normal esophagus, metaplasia, low- and high-grade dysplasia, and adenocarcinoma. The results revealed a steady increase of FOXP3+ T regulatory cells and a CD163+ myelomonocytic cell subset. In parallel to the manual gating strategy applied for cell phenotyping, we also adopted a sparse subspace clustering (SSC) algorithm allowing the automated cell phenotyping of mIHC-based single-cell data. The algorithm successfully identified comparable cell types, along with significantly enriched FOXP3 T regulatory cells and CD163+ myelomonocytic cells as found in manual gating. In addition, SCC identified a new CSF1R+CD1C+ myeloid lineage, which not only was previously unknown in this disease but also increases with advancing disease stages. This study revealed immune dynamics in EAC progression and highlighted the potential application of a new multiplex imaging platform, combined with computational image analysis on routine clinical FFPE sections, to investigate complex immune populations in tumor ecosystems.

T-cell dysfunction upon expression of MYC with altered phosphorylation at Threonine 58 and Serine 62

As a transcription factor that promotes cell growth, proliferation and apoptosis, c-MYC (MYC) expression in the cell is tightly controlled. Disruption of oncogenic signaling pathways in human cancers can increase MYC protein stability, due to altered phosphorylation ratios at two highly conserved sites, Threonine 58 (T58) and Serine 62 (S62). The T58 to Alanine mutant (T58A) of MYC mimics the stabilized, S62 phosphorylated, and highly oncogenic form of MYC. The S62A mutant is also stabilized, lacks phosphorylation at both Serine 62 and Threonine 58, and has been shown to be non-transforming in vitro. However, several regulatory proteins are reported to associate with MYC lacking phosphorylation at S62 and T58, and the role this form of MYC plays in MYC transcriptional output and in vivo oncogenic function is understudied. We generated conditional c-Myc knock-in mice in which the expression of wild-type MYC (MYCWT), the T58A mutant (MYCT58A), or the S62A mutant (MYCS62A) with or without expression of endogenous Myc is controlled by the T-cell-specific Lck-Cre recombinase. MYCT58A expressing mice developed clonal T-cell lymphomas with 100% penetrance and conditional knock-out of endogenous Myc accelerated this lymphomagenesis. In contrast, MYCS62A mice developed clonal T-cell lymphomas at a much lower penetrance, and the loss of endogenous MYC reduced the penetrance while increasing the appearance of a non-transgene driven B-cell lymphoma with splenomegaly. Together, our study highlights the importance of regulated phosphorylation of MYC at T58 and S62 for T-cell transformation. Implications: Dysregulation of phosphorylation at conserved T58 and S62 residues of MYC differentially affects T-cell development and lymphomagenesis.

Early detection of cancer

Survival improves when cancer is detected early. However, ~50% of cancers are at an advanced stage when diagnosed. Early detection of cancer or precancerous change allows early intervention to try to slow or prevent cancer development and lethality. To achieve early detection of all cancers, numerous challenges must be overcome. It is vital to better understand who is at greatest risk of developing cancer. We also need to elucidate the biology and trajectory of precancer and early cancer to identify consequential disease that requires intervention. Insights must be translated into sensitive and specific early detection technologies and be appropriately evaluated to support practical clinical implementation. Interdisciplinary collaboration is key; advances in technology and biological understanding highlight that it is time to accelerate early detection research and transform cancer survival.

MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging

Highly multiplexed tissue imaging makes detailed molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of large multichannel images poses a substantial computational challenge. Here, we describe a modular and open-source computational pipeline, MCMICRO, for performing the sequential steps needed to transform whole-slide images into single-cell data. We demonstrate the use of MCMICRO on tissue and tumor images acquired using multiple imaging platforms, thereby providing a solid foundation for the continued development of tissue imaging software.

Safety and Efficacy of Pembrolizumab in Combination with Acalabrutinib in Advanced Head and Neck Squamous Cell Carcinoma: Phase 2 Proof-of-Concept Study

PURPOSE

Programmed cell death-1 (PD-1) receptor inhibitors have shown efficacy in head and neck squamous cell carcinoma (HNSCC), but treatment failure or secondary resistance occurs in most patients. In preclinical murine carcinoma models, inhibition of Bruton's tyrosine kinase (BTK) induces myeloid cell reprogramming that subsequently bolsters CD8+ T cell responses, resulting in enhanced antitumor activity. This phase 2, multicenter, open-label, randomized study evaluated pembrolizumab (anti-PD-1 monoclonal antibody) plus acalabrutinib (BTK inhibitor) in recurrent or metastatic HNSCC.

PATIENTS AND METHODS

Patients received pembrolizumab 200 mg intravenously every 3 weeks, alone or in combination with acalabrutinib 100 mg orally twice daily. Safety and overall response rate (ORR) were co-primary objectives. The secondary objectives were progression-free survival (PFS) and overall survival.

RESULTS

Seventy-six patients were evaluated (pembrolizumab, n = 39; pembrolizumab + acalabrutinib, n = 37). Higher frequencies of grade 3-4 treatment-emergent adverse events (AE; 65% vs. 39%) and serious AEs (68% vs. 31%) were observed with combination therapy versus monotherapy. ORR was 18% with monotherapy versus 14% with combination therapy. Median PFS was 2.7 [95% confidence interval (CI), 1.4-6.8] months in the combination arm and 1.7 (95% CI, 1.4-4.0) months in the monotherapy arm. The study was terminated due to lack of clinical benefit with combination treatment. To assess how tumor immune contexture was affected by therapy in patients with pre- and post-treatment biopsies, spatial proteomic analyses were conducted that revealed a trend toward increased CD45+ leukocyte infiltration of tumors from baseline at day 43 with pembrolizumab (monotherapy, n = 5; combination, n = 2), which appeared to be higher in combination-treated patients; however, definitive conclusions could not be drawn due to limited sample size.

CONCLUSIONS

Despite lack of clinical efficacy, immune subset analyses suggest that there are additive effects of this combination; however, the associated toxicity limits the feasibility of combination treatment with pembrolizumab and acalabrutinib in patients with recurrent or metastatic HNSCC.

Single-cell spatial architectures associated with clinical outcome in head and neck squamous cell carcinoma

There is increasing evidence that the spatial organization of cells within the tumor-immune microenvironment (TiME) of solid tumors influences survival and response to therapy in numerous cancer types. Here, we report results and demonstrate the applicability of quantitative single-cell spatial proteomics analyses in the TiME of primary and recurrent human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) tumors. Single-cell compositions of a nine patient, primary and recurrent (n = 18), HNSCC cohort is presented, followed by deeper investigation into the spatial architecture of the TiME and its relationship with clinical variables and progression free survival (PFS). Multiple spatial algorithms were used to quantify the spatial landscapes of immune cells within TiMEs and demonstrate that neoplastic tumor-immune cell spatial compartmentalization, rather than mixing, is associated with longer PFS. Mesenchymal (αSMA⁺) cellular neighborhoods describe distinct immune landscapes associated with neoplastic tumor-immune compartmentalization and improved patient outcomes. Results from this investigation are concordant with studies in other tumor types, suggesting that trends in TiME cellular heterogeneity and spatial organization may be shared across cancers and may provide prognostic value in multiple cancer types.

Abstract P5-13-05: Multiplex spatial systems analysis of responses to spatially separate nanoliter doses of drug predicts systemic immune-modulating combination treatments in breast cancer

Most targeted and chemotherapeutic agents in use today affect both the tumor and the associated tumor microenvironment (TME) and should be combined to achieve effective control by simultaneously attacking tumor intrinsic vulnerabilities, enhancing immune surveillance, and mitigating stromal mediators of resistance. We have developed an integrated technological platform that enables rapid identification of such combinations by effective, fast and harmless assessment of TME responses to multiple drugs or drug combinations. This approach uses an implantable microdevice for delivery of dozens of treatments into spatially separated regions of a single living tumor and multiplexed histology analyses with probes for 30+ proteins to interrogate the responses of tumor epithelial cells, cancer associated fibroblasts, endothelial cells, lymphoid and myeloid immune lineages. Responses of interest include changes in differentiation state, antigenicity and immunogenic cell death. We demonstrated the utility of this platform by performing an unbiased in vivo screen to assess the effects of seven FDA approved drugs and combinations thereof on two late-stage mouse models of breast cancer with intact immunity. These studies indicated that the most effective, immunogenic, tumor cell kill was produced by the epigenetic modulator, panobinostat, and was linked with upregulation of MHC-I expression on tumor cells, and recruitment of antigen presenting macrophages and cytotoxic neutrophils. Increased expression of Galectin-3 and Neuropilin-1 on cancer stem cells and neutrophils, respectively, correlated with the therapeutic response three days after drug exposure, suggesting a functional role of these two proteins in early events of induced anti-tumor immunity. Our spatial systems analyses also revealed a key role for density of cancer stem cells (CSCs) and formation of fibroblasts/ECM barriers as potential resistance mechanisms. Addition of the BCL2 inhibitor, venetoclax, enhanced panobinostat anti-tumor activity, and the local phenotypic cell responses involving dendritic cell recruitment and clustering to CSC microculture suggested the use of anti-CD40 immunotherapy to induce maximum therapeutic effect. We demonstrated that a panobinostast-venetoclax-anti-CD40 therapeutic combination predicted from microdevice analyses was effective in whole animal studies in multiple models of breast cancer and often resulted in complete tumor control. Generalization of this approach promises to enable rapid design of personalized drug combination regimens that maximize tumor cell eradication by direct action on the tumor cells and by creating effective antitumor microenvironments. We demonstrated the utility of the approach in model systems but application in humans is now underway.

Citation Format: Zuzana Tatarova, Dylan C Blumberg, Lisa M Coussens, Gordon B Mills, Oliver Jonas, Joe W Gray. Multiplex spatial systems analysis of responses to spatially separate nanoliter doses of drug predicts systemic immune-modulating combination treatments in breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-13-05.

An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer

Mechanisms of therapeutic resistance and vulnerability evolve in metastatic cancers as tumor cells and extrinsic microenvironmental influences change during treatment. To support the development of methods for identifying these mechanisms in individual people, here we present an omic and multidimensional spatial (OMS) atlas generated from four serial biopsies of an individual with metastatic breast cancer during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata that includes treatment times and doses, anatomic imaging, and blood-based response measurements to clinical and exploratory analyses, which includes comprehensive DNA, RNA, and protein profiles; images of multiplexed immunostaining; and 2- and 3-dimensional scanning electron micrographs. These data report aspects of heterogeneity and evolution of the cancer genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples of how integrative analyses of these data reveal potential mechanisms of response and resistance and suggest novel therapeutic vulnerabilities.

Abstract PO-061: Myc drives phenotypic heterogeneity, metastasis, and therapy resistance in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) ranks among the top three most aggressive cancers in the United States and is projected to increase in incidence over the next few years. Standard of care treatment for PDAC consists of a cocktail of harsh chemotherapies, which have improved overall survival by only a few percentage points – to a 5-year survival rate of 10%. One commonly deregulated pathway in PDAC is c-MYC (MYC), a potent transcription factor. MYC plays an important role in tumor progression and its deregulation has been correlated with tumor aggressiveness and therapeutic resistance in PDAC and other cancers. Recently, oncogenic MYC expression has been shown to regulate elements of the tumor microenvironment (TME) in mouse models of multiple cancers. In PDAC, MYC’s expression has been linked to a desmoplastic immune suppressive TME, yet the specific mechanism has yet to be described. Here, in order to better model the disease and to interrogate questions of how MYC regulates the tumor immune and stromal microenvironment, we have generated a novel genetically engineered mouse model (GEMM) of PDAC. Our model (KMCERT2) has inducible Cre-driven expression of both mutant Kras and low deregulated Myc in the pancreas. We have found that deregulated MYC cooperates with KRASG12D in the adult pancreas to drive PDAC in our inducible KMCERT2 mouse model and that our model recapitulates inter- and intra-tumoral heterogeneity seen within clinical PDAC populations as well as consistent metastasis to liver in both spontaneous and orthotopic transplant settings. Currently, a majority of murine studies of PDAC are performed using an embryonic KrasG12D- and p53 loss/mutant-driven PDAC model (KPC). In contrast to the KPC model, our inducible KMCERT2 model of PDAC displays genetic changes, such as CDKN2A and SMAD4 loss, comparable to human disease. Interestingly, multiplexed immunohistochemistry analysis of immune cell composition of spontaneous KMCERT2 tumors compared to the commonly used KPC shows an increased density of antigen presenting cells (APCs) within MYC-driven tumors. Human PDAC is often resistant to standard of care therapies such as gemcitabine and FOLFIRINOX. Orthotopic therapeutic studies using our KMCERT2 cell lines demonstrate a similar resistance to these therapies. To further understand the mechanisms underlying our observed phenotypes, we have conducted RNAseq and DNA sequencing on both microdissected autochthonous tumor specimens and KMCERT2 tumor-derived cell lines. Together, this work investigates the role of deregulated MYC expression in metastatic behavior, immune phenotypes, and therapeutic response in murine PDAC. It also provides both spontaneous and orthotopic mouse models of PDAC that recapitulate the heterogeneous and highly metastatic nature of the human disease, allowing for important therapeutic testing opportunities.

Citation Format: Isabel A. English, Patrick J. Worth, Amy T. Farrell, Brittany L. Allen-Petersen, Vidhi Shah, Courtney Betts, Xiaoyan Wang, Colin J. Daniel, Mary C. Thoma, Lisa M. Coussens, Ellen M. Langer, Rosalie C. Sears. Myc drives phenotypic heterogeneity, metastasis, and therapy resistance in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-061.

Spatial Profiles of Intratumoral PD-1+ Helper T Cells Predict Prognosis in Head and Neck Squamous Cell Carcinoma

Background

Functional interactions between immune cells and neoplastic cells in the tumor immune microenvironment have been actively pursued for both biomarker discovery for patient stratification, as well as therapeutic anti-cancer targets to improve clinical outcomes. Although accumulating evidence indicates that intratumoral infiltration of immune cells has prognostic significance, limited information is available on the spatial infiltration patterns of immune cells within intratumoral regions. This study aimed to understand the intratumoral heterogeneity and spatial distribution of immune cell infiltrates associated with cell phenotypes and prognosis in head and neck squamous cell carcinoma (HNSCC).

Methods

A total of 88 specimens of oropharyngeal squamous cell carcinoma, categorized into discovery (n = 38) and validation cohorts (n = 51), were analyzed for immune contexture by multiplexed immunohistochemistry (IHC) and image cytometry-based quantification. Tissue segmentation was performed according to a mathematical morphological approach using neoplastic cell IHC images to dissect intratumoral regions into tumor cell nests versus intratumoral stroma.

Results

Tissue segmentation revealed heterogeneity in intratumoral T cells, varying from tumor cell nest-polarized to intratumoral stroma-polarized distributions. Leukocyte composition analysis revealed higher ratios of TH1/TH2 in tumor cell nests with higher percentages of helper T cells, B cells, and CD66b+ granulocytes within intratumoral stroma. A discovery and validation approach revealed a high density of programmed death receptor-1 (PD-1)+ helper T cells in tumor cell nests as a negative prognostic factor for short overall survival. CD163+ tumor-associated macrophages (TAM) provided the strongest correlation with PD-1+ helper T cells, and cases with a high density of PD-1+ helper T cells and CD163+ TAM had a significantly shorter overall survival than other cases.

Conclusion

This study reveals the significance of analyzing intratumoral cell nests and reports that an immune microenvironment with a high density of PD-1+ helper T cells in tumoral cell nests is a poor prognostic factor for HNSCC.

Multiomics analysis of serial PARP inhibitor treated metastatic TNBC inform on rational combination therapies

In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic stress engendered by poly-ADP-ribose polymerase (PARP) inhibitors (PARPi). In a BRCA-mutant basal breast cancer exceptional long-term survivor, a striking tumor destruction was accompanied by a marked infiltration of immune cells containing CD8 effector cells, consistent with pre-clinical evidence for association between STING mediated immune activation and benefit from PARPi and immunotherapy. Tumor cells in the exceptional responder underwent extensive protein network rewiring in response to PARP inhibition. In contrast, there were minimal changes in the ecosystem of a luminal androgen receptor rapid progressor, likely due to indifference to the effects of PARP inhibition. Together, identification of PARPi-induced emergent changes could be used to select patient specific combination therapies, based on tumor and immune state changes.

Redirecting tumor macrophage activity to fight cancer: Make room for the next era of anti-cancer drugs

Functionally significant proteins expressed by tumor macrophages have emerged as promising anti-cancer targets. In this issue of Cancer Cell, Sun et al. identify two FDA-approved agents that together safely reprogram tumor macrophages into potent anti-tumor effectors, demonstrating the power of engaging both immune system arms to fight cancer.

Neoadjuvant Selicrelumab, an Agonist CD40 Antibody, Induces Changes in the Tumor Microenvironment in Patients with Resectable Pancreatic Cancer

PURPOSE

CD40 activation is a novel clinical opportunity for cancer immunotherapy. Despite numerous active clinical trials with agonistic CD40 monoclonal antibodies (mAb), biological effects and treatment-related modulation of the tumor microenvironment (TME) remain poorly understood.

PATIENTS AND METHODS

Here, we performed a neoadjuvant clinical trial of agonistic CD40 mAb (selicrelumab) administered intravenously with or without chemotherapy to 16 patients with resectable pancreatic ductal adenocarcinoma (PDAC) before surgery followed by adjuvant chemotherapy and CD40 mAb.

RESULTS

The toxicity profile was acceptable, and overall survival was 23.4 months (95% confidence interval, 18.0-28.8 months). Based on a novel multiplexed immunohistochemistry platform, we report evidence that neoadjuvant selicrelumab leads to major differences in the TME compared with resection specimens from treatment-naïve PDAC patients or patients given neoadjuvant chemotherapy/chemoradiotherapy only. For selicrelumab-treated tumors, 82% were T-cell enriched, compared with 37% of untreated tumors (P = 0.004) and 23% of chemotherapy/chemoradiation-treated tumors (P = 0.012). T cells in both the TME and circulation were more active and proliferative after selicrelumab. Tumor fibrosis was reduced, M2-like tumor-associated macrophages were fewer, and intratumoral dendritic cells were more mature. Inflammatory cytokines/sec CXCL10 and CCL22 increased systemically after selicrelumab.

CONCLUSIONS

This unparalleled examination of CD40 mAb therapeutic mechanisms in patients provides insights for design of subsequent clinical trials targeting CD40 in cancer.

Abstract CT005: T cell inflammation in the tumor microenvironment after agonist CD40 antibody: Clinical and translational results of a neoadjuvant clinical trial

Deploying CD40 activation to stimulate T cell responses upstream of immune checkpoint molecules is a novel clinical opportunity for cancer immunotherapy. Despite numerous active clinical trials with agonistic CD40 monoclonal antibodies (mAb), biological treatment effects especially treatment-related modulation of the tumor microenvironment (TME), remain poorly understood. Here, we performed a neoadjuvant clinical trial of agonistic CD40 mAb (selicrelumab) administered intravenously with or without chemotherapy (gemcitabine and nab-paclitaxel) to 16 resectable patients with pancreatic ductal adenocarcinoma (PDAC) prior to surgery followed by adjuvant chemotherapy and CD40 mAb. The toxicity profile was acceptable, including only grade 1 or 2 cytokine release syndrome and expected toxicities from chemotherapy. Disease-free survival was 13.8 months (95% CI 2.9 - 24.8 months) and median overall survival was 23.4 months (95% CI 18.0 - 28.8), with 8 patients alive at a median of 20.0 months after surgery (follow-up range 12.2 to 34.8 months). Neoadjuvant selicrelumab induced major pharmacodynamic differences in the TME, as revealed by a multiplex imaging platform auditing the immune ecosystem, compared to resection specimens from PDAC patient previously untreated or given neoadjuvant chemotherapy/chemoradiotherapy only. For tumors resected after selicrelumab, 82% (9/11) were T-cell enriched, compared to 37% (38/104) (p=0.004) of untreated tumors and 23% (93/13) of chemotherapy/chemoradiation-treated tumors (p=0.012). Moreover, for selicrelumab tumors, tumor-associated fibrosis was less, “M2” macrophages were fewer, dendritic cells were more mature, and T cells were activated and proliferative, compared to the non-selicrelumab groups. In the periphery, CD8+ and CD4+ T cells were more activated and proliferative, and serum inflammatory cytokines CXCL10 and CCL22 increased after treatment. This study provides proof-of-concept in patients that agonistic CD40 mAb alters the TME, enhances T-cell infiltration, and modulates systemic inflammatory responses. These findings inform design of next-generation CD40 clinical trials.

Citation Format: Katelyn T. Byrne, Courtney B. Betts, Rosemarie Mick, Shamilene Sivagnanam, David L. Bajor, Daniel A. Laheru, E. Gabriela Chiorean, Mark H. O'Hara, Shannon M. Liudahl, Craig Newcomb, Cécile Alanio, Ana P. Ferreira, Byung S. Park, Takuya Ohtani, Austin P. Huffman, Sara A. Väyrynen, Andressa Dias Costa, Judith C. Kaiser, Andreanne M. Lacroix, Colleen Redlinger, Martin Stern, Jonathan A. Nowak, E. John Wherry, Martin A. Cheever, Brian M. Wolpin, Emma E. Furth, Elizabeth M. Jaffee, Lisa M. Coussens, Robert H. Vonderheide. T cell inflammation in the tumor microenvironment after agonist CD40 antibody: Clinical and translational results of a neoadjuvant clinical trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr CT005.

Correction to: High IRF8 expression correlates with CD8 T cell infiltration and is a predictive biomarker of therapy response in ER-negative breast cancer

An amendment to this paper has been published and can be accessed via the original article.

Beyond Programmed Death-Ligand 1: B7-H6 Emerges as a Potential Immunotherapy Target in SCLC

INTRODUCTION

The programmed death-ligand 1 (PD-L1) immune checkpoint inhibitors, atezolizumab and durvalumab, have received regulatory approval for the first-line treatment of patients with extensive-stage SCLC. Nevertheless, when used in combination with platinum-based chemotherapy, these PD-L1 inhibitors only improve overall survival by 2 to 3 months. This may be due to the observation that less than 20% of SCLC tumors express PD-L1 at greater than 1%. Evaluating the composition and abundance of checkpoint molecules in SCLC may identify molecules beyond PD-L1 that are amenable to therapeutic targeting.

METHODS

We analyzed RNA-sequencing data from SCLC cell lines (n = 108) and primary tumor specimens (n = 81) for expression of 39 functionally validated inhibitory checkpoint ligands. Furthermore, we generated tissue microarrays containing SCLC cell lines and patient with SCLC specimens to confirm expression of these molecules by immunohistochemistry. We annotated patient outcomes data, including treatment response and overall survival.

RESULTS

The checkpoint protein B7-H6 (NCR3LG1) exhibited increased protein expression relative to PD-L1 in cell lines and tumors (p < 0.05). Higher B7-H6 protein expression correlated with longer progression-free survival (p = 0.0368) and increased total immune infiltrates (CD45+) in patients. Furthermore, increased B7-H6 gene expression in SCLC tumors correlated with a decreased activated natural killer cell gene signature, suggesting a complex interplay between B7-H6 expression and immune signature in SCLC.

CONCLUSIONS

We investigated 39 inhibitory checkpoint molecules in SCLC and found that B7-H6 is highly expressed and associated with progression-free survival. In addition, 26 of 39 immune checkpoint proteins in SCLC tumors were more abundantly expressed than PD-L1, indicating an urgent need to investigate additional checkpoint targets for therapy in addition to PD-L1.

Tumour-associated macrophages drive stromal cell-dependent collagen crosslinking and stiffening to promote breast cancer aggression

Stromal stiffening accompanies malignancy, compromises treatment and promotes tumour aggression. Clarifying the molecular nature and the factors that regulate stromal stiffening in tumours should identify biomarkers to stratify patients for therapy and interventions to improve outcome. We profiled lysyl hydroxylase-mediated and lysyl oxidase-mediated collagen crosslinks and quantified the greatest abundance of total and complex collagen crosslinks in aggressive human breast cancer subtypes with the stiffest stroma. These tissues harbour the highest number of tumour-associated macrophages, whose therapeutic ablation in experimental models reduced metastasis, and decreased collagen crosslinks and stromal stiffening. Epithelial-targeted expression of the crosslinking enzyme, lysyl oxidase, had no impact on collagen crosslinking in PyMT mammary tumours, whereas stromal cell targeting did. Stromal cells in microdissected human tumours expressed the highest level of collagen crosslinking enzymes. Immunohistochemical analysis of biopsies from a cohort of patients with breast cancer revealed that stromal expression of lysyl hydroxylase 2, an enzyme that induces hydroxylysine aldehyde-derived collagen crosslinks and stromal stiffening, correlated significantly with disease specific mortality. The findings link tissue inflammation, stromal cell-mediated collagen crosslinking and stiffening to tumour aggression and identify lysyl hydroxylase 2 as a stromal biomarker.

High IRF8 expression correlates with CD8 T cell infiltration and is a predictive biomarker of therapy response in ER-negative breast cancer

Background

Characterization of breast cancer (BC) through the determination of conventional markers such as ER, PR, HER2, and Ki67 has been useful as a predictive and therapeutic tool. Also, assessment of tumor-infiltrating lymphocytes has been proposed as an important prognostic aspect to be considered in certain BC subtypes. However, there is still a need to identify additional biomarkers that could add precision in distinguishing therapeutic response of individual patients. To this end, we focused in the expression of interferon regulatory factor 8 (IRF8) in BC cells. IRF8 is a transcription factor which plays a well-determined role in myeloid cells and that seems to have multiple antitumoral roles: it has tumor suppressor functions; it acts downstream IFN/STAT1, required for the success of some therapeutic regimes, and its expression in neoplastic cells seems to depend on a cross talk between the immune contexture and the tumor cells.

The goal of the present study was to examine the relationship between IRF8 with the therapeutic response and the immune contexture in BC, since its clinical significance in this type of cancer has not been thoroughly addressed.

Methods

We identified the relationship between IRF8 expression and the clinical outcome of BC patients and validated IRF8 as predictive biomarker by using public databases and then performed in silico analysis. To correlate the expression of IRF8 with the immune infiltrate in BC samples, we performed quantitative multiplex immunohistochemistry.

Results

IRF8 expression can precisely predict the complete pathological response to monoclonal antibody therapy or to select combinations of chemotherapy such as FAC (fluorouracil, adriamycin, and cytoxan) in ER-negative BC subtypes. Analysis of immune cell infiltration indicates there is a strong correlation between activated and effector CD8⁺ T cell infiltration and tumoral IRF8 expression.

Conclusions

We propose IRF8 expression as a potent biomarker not only for prognosis, but also for predicting therapy response in ER-negative BC phenotypes. Its expression in neoplastic cells also correlates with CD8⁺ T cell activation and infiltration. Therefore, our results justify new efforts towards understanding mechanisms regulating IRF8 expression and how they can be therapeutically manipulated.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01418-7.

Leukocyte Heterogeneity in Pancreatic Ductal Adenocarcinoma: Phenotypic and Spatial Features Associated with Clinical Outcome

Immunotherapies targeting aspects of T cell functionality are efficacious in many solid tumors, but pancreatic ductal adenocarcinoma (PDAC) remains refractory to these treatments. Deeper understanding of the PDAC immune ecosystem is needed to identify additional therapeutic targets and predictive biomarkers for therapeutic response and resistance monitoring. To address these needs, we quantitatively evaluated leukocyte contexture in 135 human PDACs at single-cell resolution by profiling density and spatial distribution of myeloid and lymphoid cells within histopathologically defined regions of surgical resections from treatment-naive and presurgically (neoadjuvant)-treated patients and biopsy specimens from metastatic PDAC. Resultant data establish an immune atlas of PDAC heterogeneity, identify leukocyte features correlating with clinical outcomes, and, through an in silico study, provide guidance for use of PDAC tissue microarrays to optimally measure intratumoral immune heterogeneity. Atlas data have direct applicability as a reference for evaluating immune responses to investigational neoadjuvant PDAC therapeutics where pretherapy baseline specimens are not available. SIGNIFICANCE: We provide a phenotypic and spatial immune atlas of human PDAC identifying leukocyte composition at steady state and following standard neoadjuvant therapies. These data have broad utility as a resource that can inform on leukocyte responses to emerging therapies where baseline tissues were not acquired.This article is highlighted in the In This Issue feature, p. 1861.

Composition, Spatial Characteristics, and Prognostic Significance of Myeloid Cell Infiltration in Pancreatic Cancer

PURPOSE

Although abundant myeloid cell populations in the pancreatic ductal adenocarcinoma (PDAC) microenvironment have been postulated to suppress antitumor immunity, the composition of these populations, their spatial locations, and how they relate to patient outcomes are poorly understood.

EXPERIMENTAL DESIGN

To generate spatially resolved tumor and immune cell data at single-cell resolution, we developed two quantitative multiplex immunofluorescence assays to interrogate myeloid cells (CD15, CD14, ARG1, CD33, HLA-DR) and macrophages [CD68, CD163, CD86, IFN regulatory factor 5, MRC1 (CD206)] in the PDAC tumor microenvironment. Spatial point pattern analyses were conducted to assess the degree of colocalization between tumor cells and immune cells. Multivariable-adjusted Cox proportional hazards regression was used to assess associations with patient outcomes.

RESULTS

In a multi-institutional cohort of 305 primary PDAC resection specimens, myeloid cells were abundant, enriched within stromal regions, highly heterogeneous across tumors, and differed by somatic genotype. High densities of CD15+ARG1+ immunosuppressive granulocytic cells and M2-polarized macrophages were associated with worse patient survival. Moreover, beyond cell density, closer proximity of M2-polarized macrophages to tumor cells was strongly associated with disease-free survival, revealing the clinical significance and biologic importance of immune cell localization within tumor areas.

CONCLUSIONS

A diverse set of myeloid cells are present within the PDAC tumor microenvironment and are distributed heterogeneously across patient tumors. Not only the densities but also the spatial locations of myeloid immune cells are associated with patient outcomes, highlighting the potential role of spatially resolved myeloid cell subtypes as quantitative biomarkers for PDAC prognosis and therapy.

MR imaging of tumor-associated macrophages

Tumor associated macrophages (TAMs) in breast cancers foster several aspects of tumor progression and metastasis, and represent a biomarker associated with an unfavorable clinical outcome. As new therapeutic agents selectively targeting leukocytes enter the clinic whose mechanism of action involves diminishing macrophage infiltration or presence in tumors, it becomes increasingly important to identify those tumors heavily infiltrated by TAMs, as well as monitoring TAM response to therapy. MR imaging with iron oxide nanoparticles enables noninvasive quantification of TAMs in tumors, and thus, provides an easily accessible ex vivo assessment of TAMs for prognosis and related treatment decisions.

Ibrutinib in combination with nab-paclitaxel and gemcitabine for first-line treatment of patients with metastatic pancreatic adenocarcinoma: phase III RESOLVE study

BACKGROUND

First-line treatment of metastatic pancreatic ductal adenocarcinoma (PDAC) includes nab-paclitaxel/gemcitabine. Ibrutinib, a Bruton's tyrosine kinase inhibitor, exhibits antitumor activity through tumor microenvironment modulation. The safety and efficacy of first-line ibrutinib plus nab-paclitaxel/gemcitabine treatment in patients with PDAC were evaluated.

PATIENTS AND METHODS

RESOLVE (NCT02436668) was a phase III, randomized, double-blind, placebo-controlled study. Patients (histologically-confirmed PDAC; stage IV diagnosis ≥6 weeks of randomization; Karnofsky performance score ≥70) were randomized to once-daily oral ibrutinib (560 mg) or placebo plus nab-paclitaxel (125 mg/m²) and gemcitabine (1000 mg/m²). Primary endpoints were overall survival (OS) and investigator-assessed progression-free survival (PFS); overall response rate and safety were assessed.

RESULTS

In total, 424 patients were randomized (ibrutinib arm, n = 211; placebo arm, n = 213). Baseline characteristics were balanced across arms. After a median follow-up of 25 months, there was no significant difference in OS between ibrutinib plus nab-paclitaxel/gemcitabine versus placebo plus nab-paclitaxel/gemcitabine (median of 9.7 versus 10.8 months; P = 0.3225). PFS was shorter for ibrutinib plus nab-paclitaxel/gemcitabine compared with placebo plus nab-paclitaxel/gemcitabine (median 5.3 versus 6.0 months; P < 0.0001). Overall response rates were 29% and 42%, respectively (P = 0.0058). Patients in the ibrutinib arm had less time on treatment and received lower cumulative doses for all agents compared with the placebo arm. The most common grade ≥3 adverse events for ibrutinib versus placebo arms included neutropenia (24% versus 35%), peripheral sensory neuropathy (17% versus 8%), and anemia (16% versus 17%). Primary reasons for any treatment discontinuation were disease progression and adverse events.

CONCLUSIONS

Ibrutinib plus nab-paclitaxel/gemcitabine did not improve OS or PFS for patients with PDAC. Safety was consistent with known profiles for these agents.

Immune Surveillance in Clinical Regression of Preinvasive Squamous Cell Lung Cancer

Before squamous cell lung cancer develops, precancerous lesions can be found in the airways. From longitudinal monitoring, we know that only half of such lesions become cancer, whereas a third spontaneously regress. Although recent studies have described the presence of an active immune response in high-grade lesions, the mechanisms underpinning clinical regression of precancerous lesions remain unknown. Here, we show that host immune surveillance is strongly implicated in lesion regression. Using bronchoscopic biopsies from human subjects, we find that regressive carcinoma in situ lesions harbor more infiltrating immune cells than those that progress to cancer. Moreover, molecular profiling of these lesions identifies potential immune escape mechanisms specifically in those that progress to cancer: antigen presentation is impaired by genomic and epigenetic changes, CCL27-CCR10 signaling is upregulated, and the immunomodulator TNFSF9 is downregulated. Changes appear intrinsic to the carcinoma in situ lesions, as the adjacent stroma of progressive and regressive lesions are transcriptomically similar. SIGNIFICANCE: Immune evasion is a hallmark of cancer. For the first time, this study identifies mechanisms by which precancerous lesions evade immune detection during the earliest stages of carcinogenesis and forms a basis for new therapeutic strategies that treat or prevent early-stage lung cancer.See related commentary by Krysan et al., p. 1442.This article is highlighted in the In This Issue feature, p. 1426.

Abstract 3862: Defining immune contexture in small cell lung cancer: Implications for immunotherapy

Introduction: Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy with limited treatment options and median survival approximately 1 year after diagnosis even with treatment. SCLC patients typically respond to platinum-based cytotoxic chemotherapy, but drug resistance and resultant disease progression rapidly develop, driving the 5-year patient survival rate to &lt;5%. The emergence of immunotherapy (IO) offers promising therapeutics for this disease. However, recently FDA approved immunotherapies only improve overall survival (OS) of SCLC patients by 2 months (chemotherapy OS: 10 mos.; chemotherapy + IO OS: 12 mos.). Little is known about the immune landscape in SCLC. We assert that a better understanding of this immune contexture, defined as abundance, type, and location of immune cells, in SCLC may provide important criteria for patient stratification.

Objectives: The primary objective of this study is to comprehensively and quantitatively identify immune cell subsets and their associated functional states in small cell lung cancer to address critical knowledge gaps in the tumor biology of the disease.

Methods: To broadly/robustly audit immune contexture in SCLC, we generated tissue-microarrays containing &gt;200 unique patient specimens with fully annotated clinical data. Next, we used an innovative and highly multiplex immunohistochemistry (mIHC) platform consisting of a panel of highly validated antibodies and a computational pipeline. Importantly, mIHC enables cell classification via image cytometry, for identification of immune cell subsets, including: T cells (CD3+, CD4, CD8), B cells (CD20+), granulocytes (CD66b+) Th2-skewed monocytes and macrophages (CD11b+ CD68+ CD163+), and dendritic cells (CD68− CD11c+ HLA-DR+, DC-LAMP+/−). Further, functional markers provide insight into immune checkpoints (PD-1, PD-L1), proliferation (Ki67), and T cell functionality (EOMES, granzyme B).

Results: Preliminary observations show a wide variability in total immune cell (CD45+) infiltrate, with most infiltrate excluded or peripheral to tumor nests. Further, myeloid immune infiltrates often dominate over lymphoid infiltrates in terms of overall abundance, however variability exists. In particular CD8+ T cells are relatively low in abundance and often excluded from tumor nests in most tumors. Future analysis will deeply phenotype immune cell types and localization, as well as capture interpatient heterogeneity.

Conclusions: Understanding the immune landscape of SCLC could further understanding of SCLC immune suppression and evasion, ultimately leading to optimal single-agent immunotherapy deployment and rational, effective combination therapy for patients with SCLC.

Citation Format: Portia L. Thomas, Courtney Betts, Giovanney Gonzalez, Lisa M. Coussens, Christine M. Lovly. Defining immune contexture in small cell lung cancer: Implications for immunotherapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3862.