Translatability of findings from cynomolgus monkey to human suggests a mechanistic role for IL-21 in promoting immunogenicity to an anti-PD-1/IL-21 mutein fusion protein

AMG 256 is a bi-specific, heteroimmunoglobulin molecule with an anti-PD-1 antibody domain and a single IL-21 mutein domain on the C-terminus. Nonclinical studies in cynomolgus monkeys revealed that AMG 256 administration led to the development of immunogenicity-mediated responses and indicated that the IL-21 mutein domain of AMG 256 could enhance the anti-drug antibody response directed toward the monoclonal antibody domain. Anti-AMG 256 IgE were also observed in cynomolgus monkeys. A first-in-human (FIH) study in patients with advanced solid tumors was designed with these risks in mind. AMG 256 elicited ADA in 28 of 33 subjects (84.8%). However, ADA responses were only robust and exposure-impacting at the 2 lowest doses. At mid to high doses, ADA responses remained low magnitude and all subjects maintained exposure, despite most subjects developing ADA. Limited drug-specific IgE were also observed during the FIH study. ADA responses were not associated with any type of adverse event. The AMG 256 program represents a unique case where nonclinical studies informed on the risk of immunogenicity in humans, due to the IL-21-driven nature of the response.

AMG 509 (Xaluritamig), an Anti-STEAP1 XmAb 2+1 T-cell Redirecting Immune Therapy with Avidity-Dependent Activity against Prostate Cancer

The tumor-associated antigen STEAP1 is a potential therapeutic target that is expressed in most prostate tumors and at increased levels in metastatic castration-resistant prostate cancer (mCRPC). We developed a STEAP1-targeted XmAb 2+1 T-cell engager (TCE) molecule, AMG 509 (also designated xaluritamig), that is designed to redirect T cells to kill prostate cancer cells that express STEAP1. AMG 509 mediates potent T cell-dependent cytotoxicity of prostate cancer cell lines in vitro and promotes tumor regression in xenograft and syngeneic mouse models of prostate cancer in vivo. The avidity-driven activity of AMG 509 enables selectivity for tumor cells with high STEAP1 expression compared with normal cells. AMG 509 is the first STEAP1 TCE to advance to clinical testing, and we report a case study of a patient with mCRPC who achieved an objective response on AMG 509 treatment.

SIGNIFICANCE

Immunotherapy in prostate cancer has met with limited success due to the immunosuppressive microenvironment and lack of tumor-specific targets. AMG 509 provides a targeted immunotherapy approach to engage a patient's T cells to kill STEAP1-expressing tumor cells and represents a new treatment option for mCRPC and potentially more broadly for prostate cancer. See related commentary by Hage Chehade et al., p. 20. See related article by Kelly et al., p. 76. This article is featured in Selected Articles from This Issue, p. 5.

Histopathology and levels of proteins in plasma associate with survival after colorectal cancer diagnosis

BACKGROUND

The TNM system is used to assess prognosis after colorectal cancer (CRC) diagnosis. Other prognostic factors reported include histopathological assessments of the tumour, tumour mutations and proteins in the blood. As some of these factors are strongly correlated, it is important to evaluate the independent effects they may have on survival.

METHODS

Tumour samples from 2162 CRC patients were visually assessed for amount of tumour stroma, severity of lymphocytic infiltrate at the tumour margins and the presence of lymphoid follicles. Somatic mutations in the tumour were assessed for 2134 individuals. Pre-surgical levels of 4963 plasma proteins were measured in 128 individuals. The associations between these features and prognosis were inspected by a Cox Proportional Hazards Model (CPH).

RESULTS

Levels of stroma, lymphocytic infiltration and presence of lymphoid follicles all associate with prognosis, along with high tumour mutation burden, high microsatellite instability and TP53 and BRAF mutations. The somatic mutations are correlated with the histopathology and none of the somatic mutations associate with survival in a multivariate analysis. Amount of stroma and lymphocytic infiltration associate with local invasion of tumours. Elevated levels of two plasma proteins, CA-125 and PPP1R1A, associate with a worse prognosis.

CONCLUSIONS

Tumour stroma and lymphocytic infiltration variables are strongly associated with prognosis of CRC and capture the prognostic effects of tumour mutation status. CA-125 and PPP1R1A may be useful prognostic biomarkers in CRC.

Abstract 6251: Evaluation of a dual-targeting BCMA-CS1 HLE BiTE® molecule for multiple myeloma

Multiple myeloma (MM) is a cancer of the antibody-producing plasma cells (PC). MM is invariably fatal due to frequent disease relapse and/or treatment refractoriness, and therapies that provide deeper and more durable responses are needed. BiTE® (Bispecific T Cell Engager) molecules are immunotherapy agents that redirect a patient’s T cells to lyse tumor cells by simultaneously engaging a tumor associated antigen (TAA) on cancer cells and CD3ε on T cells. Clinical activity has been observed in MM using BiTE® molecules and other T cell engagers that target B-cell maturation antigen (BCMA). BCMA is an attractive MM TAA due to its broad prevalence and restricted normal tissue profile, mainly PCs and plasmablasts. However, heterogenous expression in MM cancer cells, potential antigen loss, and the presence of high levels of soluble BCMA in MM patient sera present challenges that may prevent BCMA-only-targeted therapies from achieving their full potential. To address these issues, we generated a BiTE® molecule capable of engaging BCMA and a second MM TAA, CS1 (also known as SLAMF7). This BiTE® molecule also contains an Fc-based domain to provide half-life extension (HLE). Here, we evaluated the in vitro and in vivo properties of this BCMA-CS1 HLE BiTE® molecule. The BCMA-CS1 HLE BiTE® molecule had nanomolar binding affinity for human BCMA, CS1, and CD3ε and the non-human primate (NHP) orthologues. In vitro, we observed picomolar activity against human MM cell lines with a range of BCMA and CS1 expression in a T cell dependent cellular cytotoxicity (TDCC) assay using human T cells or NHP peripheral blood mononuclear cells. The BCMA-CS1 HLE BiTE® molecule retained TDCC activity in the presence of soluble BCMA up to 2500 ng/mL as well as against human MM cells engineered to express only BCMA or CS1. In vivo, this BiTE® molecule inhibited tumor growth in a MM xenograft model. We also evaluated the BCMA-CS1 HLE BiTE® molecule in NHP over 15 days (IV dosing; intra-animal dose escalation from 60→240 μg/kg or 180→540 μg/kg on days 1 and 8). We observed hallmarks of BiTE® molecule activity in all groups, including transient decreases in circulating lymphocytes and moderate increases in cytokines like MCP-1. We measured the PC-specific transcripts BCMA and J-chain in NHP bone marrow and blood as surrogates for PC levels using ddPCR. These transcripts were reduced in both treatment groups (≥90%) with the strongest effects occurring in the 180→540 μg/kg group. Lastly, we showed that CS1 is highly and broadly expressed in MM patient samples and is restricted to a few normal hematopoietic cell types including PCs, NK cells, T cells, and some monocytes. These data suggest that the BCMA-CS1 HLE BiTE® molecule has potent in vitro and in vivo activity and may provide therapeutic benefit for MM patients by expanding the population of MM cancer cells that can be eliminated by a BiTE® molecule while overcoming common mechanisms that can impair BCMA-only-targeted MM therapies.

Citation Format: Elizabeth T. Andrews, Stephanie C. Casey, Mohammad Farhad Amani, Grit Lorenczewski, Mozhgan Farshbaf, Lisa Winkel, Matthias Klinger, John M. Harrold, Famke Aeffner, Ana Goyos, Matthias Friedrich, Tara Arvedson, Matthew G. Chun. Evaluation of a dual-targeting BCMA-CS1 HLE BiTE® molecule for multiple myeloma [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 6251.

Abstract 5202: AMG 794, a Claudin 6-targeted half-life extended (HLE) bispecific T cell engager (BITE®) molecule for non-small cell lung cancer and epithelial ovarian cancer

AMG 794 is a half-life extended BiTE® immune therapy targeting the oncofetal antigen Claudin 6 (CLDN6). AMG 794 redirects T cells to kill CLDN6-expressing tumor cells and is being developed for the treatment of non-small cell lung cancer (NSCLC) and epithelial ovarian cancer (EOC). CLDN6 is a compelling tumor antigen that is expressed during embryonic and fetal development, transcriptionally silenced in adult tissues, and re-expressed on the surface of NSCLC and EOC cells. By immunohistochemistry, CLDN6 staining of the cell membrane was observed in 27% of non-squamous NSCLC (n = 63) and 69% of EOC (n = 92) samples, the majority of which were of the high-grade serous ovarian cancer subtype. Expression of CLDN6 protein was not detected in most normal adult tissues, with rare CLDN6 immunostaining limited to individual cells in the pituitary, pancreas, small intestine, kidney, and female reproductive organs. AMG 794 is a fully human BiTE® molecule that binds both human and cynomolgus monkey CLDN6 and CD3. AMG 794 binds human CLDN6 and CD3 with equilibrium dissociation constant (KD) of 13 nM and 36 nM, respectively. In vitro, AMG 794 redirects human T cells to kill CLDN6-expressing cancer cells with a half-maximal lysis concentration (EC50) of 2.6 ± 1.1 pM to 127.4 ± 53.4 pM. Consistent with the mechanism of action of BiTE® immune therapy, AMG 794 induces T cell activation and transient production of cytokines in co-cultures of T cells and CLDN6-expressing tumor cells. Remarkably, AMG 794 binding and cytotoxic activity is selective for CLDN6 over other claudin family proteins, despite high homology in the extracellular loops with CLDN9. Weekly dosing of AMG 794 significantly inhibited the growth of established lung and ovarian xenograft tumors in immunocompromised mice injected with human T cells. Anti-tumor activity was associated with an increase in tumor-infiltrating T cells. AMG 794 was well tolerated in a one-month repeat-dose toxicology study in cynomolgus monkey, with evidence for target engagement. The potent, selective activity of AMG 794 for CLDN6-expressing NSCLC and EOC cells, together with an acceptable nonclinical safety profile, supported the advancement of AMG 794 into clinical development. A first-in-human study to explore the safety, tolerability, pharmacokinetics, and anti-tumor activity of AMG 794 in patients with CLDN6-positive advanced/metastatic non-squamous NSCLC or EOC will be enrolling patients in March 2022.

Citation Format: Elizabeth Pham, Anja Henn, Beate Sable, Joachim Wahl, Kip Conner, Katja Matthes, Shivani Gupta, Rodolfo Yabut, Famke Aeffner, Kristin Lewis Wilson, Jonas Anlahr, Christoph Dahlhoff, Vijay Kale, Matthias Friedrich, Tobias Raum, Peter Kufer, Angela Coxon, Sabine Stienen, Julie M. Bailis. AMG 794, a Claudin 6-targeted half-life extended (HLE) bispecific T cell engager (BITE®) molecule for non-small cell lung cancer and epithelial ovarian cancer [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 5202.

Scientific and Regulatory Policy Committee Points to Consider: Primary Digital Histopathology Evaluation and Peer Review for Good Laboratory Practice (GLP) Nonclinical Toxicology Studies

The Society of Toxicologic Pathology's Scientific and Regulatory Policy Committee formed a working group to consider the present and future use of digital pathology in toxicologic pathology in general and specifically its use in primary evaluation and peer review in Good Laboratory Practice (GLP) environments. Digital histopathology systems can save costs by reducing travel, enhancing organizational flexibility, decreasing slide handling, improving collaboration, increasing access to historical images, and improving quality and efficiency through integration with laboratory information management systems. However, the resources to implement and operate a digital pathology system can be significant. Given the magnitude and risks involved in the decision to adopt digital histopathology, this working group used pertinent previously published survey results and its members' expertise to create a Points-to-Consider article to assist organizations with building and implementing digital pathology workflows. With the aim of providing a comprehensive perspective, the current publication summarizes aspects of digital whole-slide imaging relevant to nonclinical histopathology evaluations, and then presents points to consider applicable to both primary digital histopathology evaluation and digital peer review in GLP toxicology studies. The Supplemental Appendices provide additional tabulated resources.

Scientific and Regulatory Policy Committee Brief Communication: 2019 Survey on Use of Digital Histopathology Systems in Nonclinical Toxicology Studies

Histopathologic evaluation and peer review using digital whole-slide images (WSIs) is a relatively new medium for assessing nonclinical toxicology studies in Good Laboratory Practice (GLP) environments. To better understand the present and future use of digital pathology in nonclinical toxicology studies, the Society of Toxicologic Pathology (STP) formed a working group to survey STP members with the goal of creating recommendations for implementation. The survey was administered in December 2019, immediately before the COVID-19 pandemic, and the results suggested that the use of digital histopathology for routine GLP histopathology assessment was not widespread. Subsequently, in follow-up correspondence during the pandemic, many responding institutions either began investigating or adopting digital WSI systems to reduce employee exposure to COVID-19. Therefore, the working group presents the survey results as a pre-pandemic baseline data set. Recommendations for use of WSI systems in GLP environments will be the subject of a separate publication.

Whole-slide imaging, tissue image analysis, and artificial intelligence in veterinary pathology: An updated introduction and review

Since whole-slide imaging has been commercially available for over 2 decades, digital pathology has become a constantly expanding aspect of the pathology profession that will continue to significantly impact how pathologists conduct their craft. While some aspects, such as whole-slide imaging for archiving, consulting, and teaching, have gained broader acceptance, other facets such as quantitative tissue image analysis and artificial intelligence-based assessments are still met with some reservations. While most vendors in this space have focused on diagnostic applications, that is, viewing one or few slides at a time, some are developing solutions tailored more specifically to the various aspects of veterinary pathology including updated diagnostic, discovery, and research applications. This has especially advanced the use of digital pathology in toxicologic pathology and drug development, for primary reads as well as peer reviews. It is crucial that pathologists gain a deeper understanding of digital pathology and tissue image analysis technology and their applications in order to fully use these tools in a way that enhances and improves the pathologist's assessment as well as work environment. This review focuses on an updated introduction to the basics of digital pathology and image analysis and introduces emerging topics around artificial intelligence and machine learning.

Immunotherapy combinations overcome resistance to bispecific T cell engager treatment in T cell-cold solid tumors

Therapeutic approaches are needed to promote T cell-mediated destruction of poorly immunogenic, "cold" tumors typically associated with minimal response to immune checkpoint blockade (ICB) therapy. Bispecific T cell engager (BiTE) molecules induce redirected lysis of cancer cells by polyclonal T cells and have demonstrated promising clinical activity against solid tumors in some patients. However, little is understood about the key factors that govern clinical responses to these therapies. Using an immunocompetent mouse model expressing a humanized CD3ε chain (huCD3e mice) and BiTE molecules directed against mouse CD19, mouse CLDN18.2, or human EPCAM antigens, we investigated the pharmacokinetic and pharmacodynamic parameters and immune correlates associated with BiTE efficacy across multiple syngeneic solid-tumor models. These studies demonstrated that pretreatment tumor-associated T cell density is a critical determinant of response to BiTE therapy, identified CD8⁺ T cells as important targets and mediators of BiTE activity, and revealed an antagonistic role for CD4⁺ T cells in BiTE efficacy. We also identified therapeutic combinations, including ICB and 4-1BB agonism, that synergized with BiTE treatment in poorly T cell-infiltrated, immunotherapy-refractory tumors. In these models, BiTE efficacy was dependent on local expansion of tumor-associated CD8⁺ T cells, rather than their recruitment from circulation. Our findings highlight the relative contributions of baseline T cell infiltration, local T cell proliferation, and peripheral T cell trafficking for BiTE molecule-mediated efficacy, identify combination strategies capable of overcoming resistance to BiTE therapy, and have clinical relevance for the development of BiTE and other T cell engager therapies.

Preclinical Assessment of a MUC12-Targeted BiTE® (Bispecific T Cell Engager) Molecule

MUC12 is a transmembrane mucin that is highly expressed in >50% of primary and metastatic colorectal tumors. MUC12 is also expressed by normal epithelial cells of the colon and small intestine. While MUC12 localization in normal epithelial cells is restricted to the apical membrane, expression in tumors is depolarized and shows broad membrane localization. The differential localization of MUC12 in tumor cells as compared to normal cells makes it a potential therapeutic target. Here, we evaluated targeting of MUC12 with a BiTE® (bispecific T cell engager) molecule. We generated a panel of proof-of-concept half-life extended (HLE) BiTE molecules that bind MUC12 on tumor cells and CD3 on T cells. We prioritized one molecule based on in vitro activity for further characterization in vivo. In vitro, the MUC12 HLE BiTE molecule mediated T cell redirected lysis of MUC12-expressing cells with half-maximal lysis of 4.4 {plus minus} 0.9 pM to 117 {plus minus} 78 pM. In an exploratory cynomolgus monkey toxicology study, the MUC12 HLE BiTE molecule administered at 200 µg/kg with a step dose to 1000 µg/kg was tolerated with minimal clinical observations. However, higher doses were not tolerated, and there was evidence of damage in the gastrointestinal tract, suggesting dose levels projected to be required for antitumor activity may be associated with on-target toxicity. Together, these data demonstrate that the apically restricted expression of MUC12 in normal tissues is accessible to BiTE molecule target engagement and highlight the difficult challenge of identifying tumor-selective antigens for solid tumor T cell engagers.

Quantitative Image Analysis for Tissue Biomarker Use: A White Paper From the Digital Pathology Association

Tissue biomarkers have been of increasing utility for scientific research, diagnosing disease, and treatment response prediction. There has been a steady shift away from qualitative assessment toward providing more quantitative scores for these biomarkers. The application of quantitative image analysis has thus become an indispensable tool for in-depth tissue biomarker interrogation in these contexts. This white paper reviews current technologies being employed for quantitative image analysis, their application and pitfalls, regulatory framework demands, and guidelines established for promoting their safe adoption in clinical practice.

Special Issue on Digital Pathology, Tissue Image Analysis, Artificial Intelligence, and Machine Learning: Approximation of the Effect of Novel Technologies on Toxicologic Pathology

For decades, it has been postulated that digital pathology is the future. By now it is safe to say that we are living that future. Digital pathology has expanded into all aspects of pathology, including human diagnostic pathology, veterinary diagnostics, research, drug development, regulatory toxicologic pathology primary reads, and peer review. Digital tissue image analysis has enabled users to extract quantitative and complex data from digitized whole-slide images. The following editorial provides an overview of the content of this special issue of Toxicologic Pathology to highlight the range of key topics that are included in this compilation. In addition, the editors provide a commentary on important current aspects to consider in this space, such as accessibility of publication content to the machine learning-novice pathologist, the importance of adequate test set selection, and allowing for data reproducibility.

Developing a Qualification and Verification Strategy for Digital Tissue Image Analysis in Toxicological Pathology

Digital tissue image analysis is a computational method for analyzing whole-slide images and extracting large, complex, and quantitative data sets. However, as with any analysis method, the quality of generated results is dependent on a well-designed quality control system for the entire digital pathology workflow. Such system requires clear procedural controls, appropriate user training, and involvement of specialists to oversee key steps of the workflow. The toxicologic pathologist is responsible for reporting data obtained by digital image analysis and therefore needs to ensure that it is correct. To accomplish that, they must understand the main parameters of the quality control system and should play an integral part in its conception and implementation. This manuscript describes the most common digital tissue image analysis end points and potential sources of analysis errors. In addition, it outlines recommended approaches for ensuring quality and correctness of results for both classical and machine-learning based image analysis solutions, as adapted from a recently proposed Food and Drug Administration regulatory framework for modifications to artificial intelligence/machine learning-based software as a medical device. These approaches are beneficial for any type of toxicopathologic study which uses the described end points and can be adjusted based on the intended use of the image analysis solution.

The Application, Challenges, and Advancement Toward Regulatory Acceptance of Digital Toxicologic Pathology: Results of the 7th ESTP International Expert Workshop (September 20-21, 2019)

With advancements in whole slide imaging technology and improved understanding of the features of pathologist workstations required for digital slide evaluation, many institutions are investigating broad digital pathology adoption. The benefits of digital pathology evaluation include remote access to study or diagnostic case materials and integration of analysis and reporting tools. Diagnosis based on whole slide images is established in human medical pathology, and the use of digital pathology in toxicologic pathology is increasing. However, there has not been broad adoption in toxicologic pathology, particularly in the context of regulatory studies, due to lack of precedence. To address this topic, as well as practical aspects, the European Society of Toxicologic Pathology coordinated an expert international workshop to assess current applications and challenges and outline a set of minimal requirements needed to gain future regulatory acceptance for the use of digital toxicologic pathology workflows in research and development, so that toxicologic pathologists can benefit from digital slide technology.

Abstract PR12: Assessing in vivo mechanisms regulating the therapeutic activity of bi-specific T-cell engager (BiTE®) molecules in immunocompetent mice expressing a chimeric human/mouse CD3ϵ receptor

The development and success of Blincyto®, a Bi-Specific T cell Engager (BiTE®), to treat acute lymphoblastic leukemia has expanded the class of anticancer immunotherapy agents. BiTE® molecules consist of a single-chain Fc antibody containing tandem single-chain variable fragments (scFv) recognizing the CD3 receptor on T lymphocytes and a tumor-associated antigen and induce redirected T-cell cytotoxicity and tumor cell lysis. Despite the clinically validated efficacy of BiTE® molecules, there has been little elucidation of the parameters governing their in vivo activity. This is due, in part, to a lack of immunocompetent murine tumor models that allow for engagement of endogenous T cells in the context of an intact immune system, which more accurately mimic the human therapeutic setting. We have developed a genetically engineered mouse model (huCD3 mouse) in which a human/mouse chimeric CD3ϵ receptor recognized by BiTE® molecules was engineered into the mouse CD3ϵ genomic locus. Here, we characterize the immune cell distribution of the huCD3 mouse and utilize BiTE® molecules and syngeneic tumor models to elucidate pharmacokinetic, pharmacodynamic, and efficacy relationships in vivo. The peripheral B and T cell distribution profile of huCD3 mice and WT littermates are comparable, but T cells isolated from huCD3 mice express lower levels of. In T cell-dependent cytotoxic (TDCC) assays, an anti-huEpCAM BiTE® molecule exhibited similar potency against MC38 mouse cells expressing human EpCAM co-cultured with T cells from the huCD3 mice or a human donor, if mouse T-cells were preactivated in vitro. In vivo, MC38-huEpCAM tumors grew robustly and anti-huEpCAM BiTEÂ treatment resulted in dose-dependent tumor growth inhibition, with several tumor-free animals at higher doses. Flow cytometry analysis of disaggregated tumors and serum cytokine analysis indicated that BiTE® treatment resulted in T-cell activation and a cytokine response at doses that correlate with tumor regression. In vivo studies were also performed using B16F10-huEPCAM cells, which generate tumors with reduced T-cell infiltration compared to MC38-huEpCAM. Additionally, we used WT mice reconstituted with different ratios of huCD3e and WT bone marrow to investigate the T-cell number requirement for optimal BiTE®-mediated efficacy. We also evaluated the efficacy of an anti-mouse CD19 BiTE® molecule against MC38-CD19 tumor cells to compare the requirements for antitumor efficacy versus normal B-cell depletion in the blood and in lymphoid organs. Finally, we performed a rational combination study using BiTE® molecules and a PD1 inhibitor, demonstrating that this combination can lead to the eradication of poorly T cell-infiltrated solid tumors. These data begin to elucidate the in vivo mechanisms regulating the efficacy of BiTE® molecules under physiologically relevant conditions.

This abstract is also being presented as Poster A29.

Citation Format: Brian Belmontes, Hong Tan, Wendy Zhong, Danny Chui, Kevin Cook, Sarah O'Brien, Melissa Martin, Brandy Alexander, Jason Eng, John Harrold, Famke Aeffner, Matthew Chun, Alice Bakker, Mercedesz Balazs, Jason DeVoss, Angela Coxon, Jude Canon, Jackson Egen, Olivier Nolan-Stevaux. Assessing in vivo mechanisms regulating the therapeutic activity of bi-specific T-cell engager (BiTE®) molecules in immunocompetent mice expressing a chimeric human/mouse CD3ϵ receptor [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr PR12.

Digital Microscopy, Image Analysis, and Virtual Slide Repository

Advancements in technology and digitization have ushered in novel ways of enhancing tissue-based research via digital microscopy and image analysis. Whole slide imaging scanners enable digitization of histology slides to be stored in virtual slide repositories and to be viewed via computers instead of microscopes. Easier and faster sharing of histologic images for teaching and consultation, improved storage and preservation of quality of stained slides, and annotation of features of interest in the digital slides are just a few of the advantages of this technology. Combined with the development of software for digital image analysis, digital slides further pave the way for the development of tools that extract quantitative data from tissue-based studies. This review introduces digital microscopy and pathology, and addresses technical and scientific considerations in slide scanning, quantitative image analysis, and slide repositories. It also highlights the current state of the technology and factors that need to be taken into account to insure optimal utility, including preanalytical considerations and the importance of involving a pathologist in all major steps along the digital microscopy and pathology workflow.

Society of Toxicologic Pathology Digital Pathology and Image Analysis Special Interest Group Article*: Opinion on the Application of Artificial Intelligence and Machine Learning to Digital Toxicologic Pathology

Toxicologic pathology is transitioning from analog to digital methods. This transition seems inevitable due to a host of ongoing social and medical technological forces. Of these, artificial intelligence (AI) and in particular machine learning (ML) are globally disruptive, rapidly growing sectors of technology whose impact on the long-established field of histopathology is quickly being realized. The development of increasing numbers of algorithms, peering ever deeper into the histopathological space, has demonstrated to the scientific community that AI pathology platforms are now poised to truly impact the future of precision and personalized medicine. However, as with all great technological advances, there are implementation and adoption challenges. This review aims to define common and relevant AI and ML terminology, describe data generation and interpretation, outline current and potential future business cases, discuss validation and regulatory hurdles, and most importantly, propose how overcoming the challenges of this burgeoning technology may shape toxicologic pathology for years to come, enabling pathologists to contribute even more effectively to answering scientific questions and solving global health issues. [Box: see text]

Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association

In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated patient data to extract information. This review offers a historical perspective and describes the potential clinical benefits from research and applications in this field, as well as significant obstacles to adoption. Best practices for implementing computational pathology workflows are presented. These include infrastructure considerations, acquisition of training data, quality assessments, as well as regulatory, ethical, and cyber-security concerns. Recommendations are provided for regulators, vendors, and computational pathology practitioners in order to facilitate progress in the field. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Animal Models of Peripheral Pain: Biology Review and Application for Drug Discovery

Pain is a complex constellation of cognitive, unpleasant sensory, and emotional experiences that primarily serves as a survival mechanism. Pain arises in the peripheral nervous system and pain signals synapse with nerve tracts extending into the central nervous system. Several different schemes are used to classify pain, including the underlying mechanism, tissues primarily affected, and time-course. Numerous animal models of pain, which should be employed with appropriate Institutional Animal Care and Use approvals, have been developed to elucidate pathophysiology mechanisms and aid in identification of novel therapeutic targets. The variety of available models underscores the observations that pain phenotypes are driven by several distinct mechanisms. Pain outcome measurement encompasses both reflexive (responses to heat, cold, mechanical and electrical stimuli) and nonreflexive (spontaneous pain responses to stimuli) behaviors. However, the question of translatability to human pain conditions and potential treatment outcomes remains a topic of continued scrutiny. In this review we discuss the different types of pain and their mechanisms and pathways, available rodent pain models with an emphasis on type of pain stimulations and pain outcome measures and discuss the role of pathologists in assessing and validating pain models.

Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association

The advent of whole-slide imaging in digital pathology has brought about the advancement of computer-aided examination of tissue via digital image analysis. Digitized slides can now be easily annotated and analyzed via a variety of algorithms. This study reviews the fundamentals of tissue image analysis and aims to provide pathologists with basic information regarding the features, applications, and general workflow of these new tools. The review gives an overview of the basic categories of software solutions available, potential analysis strategies, technical considerations, and general algorithm readouts. Advantages and limitations of tissue image analysis are discussed, and emerging concepts, such as artificial intelligence and machine learning, are introduced. Finally, examples of how digital image analysis tools are currently being used in diagnostic laboratories, translational research, and drug development are discussed.

A Practical Guide to Whole Slide Imaging: A White Paper From the Digital Pathology Association

Context.—

Whole slide imaging (WSI) represents a paradigm shift in pathology, serving as a necessary first step for a wide array of digital tools to enter the field. Its basic function is to digitize glass slides, but its impact on pathology workflows, reproducibility, dissemination of educational material, expansion of service to underprivileged areas, and intrainstitutional and interinstitutional collaboration exemplifies a significant innovative movement with far-reaching effects. Although the benefits of WSI to pathology practices, academic centers, and research institutions are many, the complexities of implementation remain an obstacle to widespread adoption. In the wake of the first regulatory clearance of WSI for primary diagnosis in the United States, some barriers to adoption have fallen. Nevertheless, implementation of WSI remains a difficult prospect for many institutions, especially those with stakeholders unfamiliar with the technologies necessary to implement a system or who cannot effectively communicate to executive leadership and sponsors the benefits of a technology that may lack clear and immediate reimbursement opportunity.

Objectives.—

To present an overview of WSI technology—present and future—and to demonstrate several immediate applications of WSI that support pathology practice, medical education, research, and collaboration.

Data Sources.—

Peer-reviewed literature was reviewed by pathologists, scientists, and technologists who have practical knowledge of and experience with WSI.

Conclusions.—

Implementation of WSI is a multifaceted and inherently multidisciplinary endeavor requiring contributions from pathologists, technologists, and executive leadership. Improved understanding of the current challenges to implementation, as well as the benefits and successes of the technology, can help prospective users identify the best path for success.

Validation of a Muscle-Specific Tissue Image Analysis Tool for Quantitative Assessment of Dystrophin Staining in Frozen Muscle Biopsies

CONTEXT.—

Duchenne muscular dystrophy is a rare, progressive, and fatal neuromuscular disease caused by dystrophin protein loss. Common investigational treatment approaches aim at increasing dystrophin expression in diseased muscle. Some clinical trials include assessments of novel dystrophin production as a surrogate biomarker of efficacy, which may predict a clinical benefit from treatment.

OBJECTIVES.—

To establish an immunofluorescent scanning and digital image analysis workflow that provides an objective approach for staining intensity assessment of the immunofluorescence dystrophin labeling and determination of the percentage of biomarker-positive fibers in muscle cryosections.

DESIGN.—

Optimal and repeatable digital image capture was achieved by a rigorously qualified fluorescent scanning process. After scanning qualification, the MuscleMap (Flagship Biosciences, Westminster, Colorado) algorithm was validated by comparing high-power microscopic field total and dystrophin-positive fiber counts obtained by trained pathologists to data derived by MuscleMap. Next, the algorithm was tested on whole-slide images of immunofluorescent-labeled muscle sections from Duchenne muscular dystrophy, Becker muscular dystrophy, and control patients.

RESULTS.—

When used under the guidance of a trained pathologist, the digital image analysis tool met predefined validation criteria and demonstrated functional and statistical equivalence with manual assessment. This work is the first, to our knowledge, to qualify and validate immunofluorescent scanning and digital tissue image-analysis workflow, respectively, with the rigor required to support the clinical trial environments.

CONCLUSIONS.—

MuscleMap enables analysis of all fibers within an entire muscle biopsy section and provides data on a fiber-by-fiber basis. This will allow future clinical trials to objectively investigate myofibers' dystrophin expression at a greater level of consistency and detail.

Proceedings of the 2017 National Toxicology Program Satellite Symposium

The 2017 annual National Toxicology Program Satellite Symposium, entitled "Pathology Potpourri," was held in Montreal, Quebec, Canada at the Society of Toxicologic Pathology's 36th annual meeting. The goal of this symposium was to present and discuss challenging diagnostic pathology and/or nomenclature issues. This article presents summaries of the speakers' talks along with select images that were used by the audience for voting and discussion. Various lesions and other topics covered during the symposium included renal papillary degeneration in perinatally exposed animals, an atriocaval mesothelioma, an unusual presentation of an alveolar-bronchiolar carcinoma, a paraganglioma of the organ of Zuckerkandl (also called an extra-adrenal pheochromocytoma), the use of human muscle samples to illustrate the challenges of manual scoring of fluorescent staining, intertubular spermatocytic seminomas, medical device pathology assessment and discussion of the approval process, collagen-induced arthritis, incisor denticles, ameloblast degeneration and poorly mineralized enamel matrix, connective tissue paragangliomas, microcystin-LR toxicity, perivascular mast cells in the forebrain thalamus unrelated to treatment, and 2 cases that provided a review of the International Harmonization of Nomenclature and Diagnostic Criteria (INHAND) bone nomenclature and recommended application of the terminology in routine nonclinical toxicity studies.

Abstract 1674: Quantifying tumor-infiltrating leukocytes in hematoxylin stained NSCLC tissue samples using morphometric features

Quantification of tumor-infiltrating lymphocytes (TILs) in non-small cell lung cancers (NSCLC) is valuable for understanding patient prognosis and survival. TILs comprise a subset of tumor-infiltrating leukocytes that modulate immune evasion and response to therapy. Understanding the composition of TIL subsets, especially relative to the total tumor leukocyte population, may provide additional context for understanding NSCLC pathogenesis and patient response to treatment. However, availability of tissues and use of chromogenic assays can limit the number of TIL and leukocyte subset markers assayed in a tissue section. Therefore, this study evaluated the identification of total leukocyte component in NSCLC using morphometric parameters and routine TIL marker monoplex immunohistochemistry (IHC) assays to further identify the composition of TIL subsets. Computational Tissue Analysis (cTA™) tools were used to determine the morphometric parameters which could identify immune cells in the absence of biomarker stain. The morphometric features which characterized immune infiltrates were used to quantify the total immune cell population frequency in the tumor nests and surrounding stroma in hematoxylin-stained tissues. The leukocyte population identified with morphometric parameters was correlated with CD45+ cell frequencies identified by cTA based on biomarker staining in CD45-stained serial sections. This morphometric ruleset was then applied to CD3- and CD8-stained tissues to evaluate the frequency of CD3+ and CD8+ TILs in the context of total infiltrating leukocytes. The relative populations of CD3+ and CD8+ TILs were consistent with available literature demonstrating that the morphometric ruleset could be utilized to enable evaluation of TIL sub-types relative to total leukocyte population without the need for additional IHC stains. The approach could, therefore, provide an added dimension of analysis for tissues stained by IHC for identifying the total immune cell infiltrating component without requiring additional biomarker staining.

Citation Format: Elliott Ergon, Allison S. Harney, Nathan Martin, Will Paces, Famke Aeffner, Kristin Wilson, Janet Patterson-Kane, Karen Ryall, Daniel G. Rudmann, Brooke Hirsch, Joseph Krueger. Quantifying tumor-infiltrating leukocytes in hematoxylin stained NSCLC tissue samples using morphometric features [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1674. doi:10.1158/1538-7445.AM2017-1674

A Primer for Oncoimmunology (Immunooncology)

Oncoimmunology (or immunooncology) is a burgeoning specialty of precision (“personalized”) medicine designed to heighten the antitumor response of the immune system against molecules expressed excessively or only by tumor cells. This focus is necessary, as cancers are polyclonal tissues comprised of antigenically heterogeneous cells, the exact composition of which is shaped by the balance between antitumor immunity and tumor-promoting inflammation. Key targets include enhancing immune system (especially T cell) reactivity, inhibiting immune checkpoints, and promoting tumor cytolysis. Therapeutic modalities to address these targets include administering antibodies, cytokines, or small molecules that directly stimulate the immune system, attack tumor-associated antigens, or interfere with tumor–stroma interactions; adoptive transfer of autologous T cells following ex vivo selection/expansion/activation (typically after lymphoid-depleting regimens and in conjunction with immunostimulatory therapy); and vaccination (against tumor antigens). Pathology involvement in oncoimmunology product development is critical to assess expression of target molecules in tumor cells, stromal cells, and tumor-infiltrating leukocytes.

The Gold Standard Paradox in Digital Image Analysis: Manual Versus Automated Scoring as Ground Truth

CONTEXT

- Novel therapeutics often target complex cellular mechanisms. Increasingly, quantitative methods like digital tissue image analysis (tIA) are required to evaluate correspondingly complex biomarkers to elucidate subtle phenotypes that can inform treatment decisions with these targeted therapies. These tIA systems need a gold standard, or reference method, to establish analytical validity. Conventional, subjective histopathologic scores assigned by an experienced pathologist are the gold standard in anatomic pathology and are an attractive reference method. The pathologist's score can establish the ground truth to assess a tIA solution's analytical performance. The paradox of this validation strategy, however, is that tIA is often used to assist pathologists to score complex biomarkers because it is more objective and reproducible than manual evaluation alone by overcoming known biases in a human's visual evaluation of tissue, and because it can generate endpoints that cannot be generated by a human observer.

OBJECTIVE

- To discuss common visual and cognitive traps known in traditional pathology-based scoring paradigms that may impact characterization of tIA-assisted scoring accuracy, sensitivity, and specificity.

DATA SOURCES

- This manuscript reviews the current literature from the past decades available for traditional subjective pathology scoring paradigms and known cognitive and visual traps relevant to these scoring paradigms.

CONCLUSIONS

- Awareness of the gold standard paradox is necessary when using traditional pathologist scores to analytically validate a tIA tool because image analysis is used specifically to overcome known sources of bias in visual assessment of tissue sections.

Quantitative assessment of pancreatic cancer precursor lesions in IHC-stained tissue with a tissue image analysis platform

Tissue image analysis (tIA) is emerging as a powerful tool for quantifying biomarker expression and distribution in complex diseases and tissues. Pancreatic ductal adenocarcinoma (PDAC) develops in a highly complex and heterogeneous tissue environment and, generally, has a very poor prognosis. Early detection of PDAC is confounded by limited knowledge of the pre-neoplastic disease stages and limited methods to quantitatively assess disease heterogeneity. We sought to develop a tIA approach to assess the most common PDAC precursor lesions, pancreatic intraepithelial neoplasia (PanIN), in tissues from Kras^LSL-G12D/+; Trp53^LSL-R172H/+; Pdx-Cre (KPC) mice, a validated model of PDAC development. tIA profiling of training regions of PanIN and tumor microenvironment (TME) cells was utilized to guide identification of PanIN/TME tissue compartment stratification criteria. A custom CellMap algorithm implementing these criteria was applied to whole-slide images of KPC mice pancreata sections to quantify p53 and Ki-67 biomarker staining in each tissue compartment as a proof-of-concept for the algorithm platform. The algorithm robustly identified a higher percentage of p53-positive cells in PanIN lesions relative to the TME, whereas no difference was observed for Ki-67. Ki-67 expression was also quantified in a human pancreatic tissue sample available to demonstrate the translatability of the CellMap algorithm to human samples. Together, our data demonstrated the utility of CellMap to enable objective and quantitative assessments, across entire tissue sections, of PDAC precursor lesions in preclinical and clinical models of this disease to support efforts leading to novel insights into disease progression, diagnostic markers, and potential therapeutic targets.

Abstract 2225: Image analysis-based PD-L1 companion and complementary diagnostics

The PD-1 pathway, comprised of the immune cell co-receptor Programmed Death 1 (PD-1) and its ligands PD-L1 and PD-L2, mediates local immunosuppression in the tumor microenvironment. Immune checkpoint modulators are designed to block the local immunosuppression caused by this pathway. The FDA approved anti-PD-1 antibody therapies Opdivo® (nivolumab; Bristol-Myers Squibb) and Keytruda® (prembrolizumab; Merck & Co) rely on PD-L1 immunohistochemistry (IHC) in vitro diagnostic (IVD) tests to determine the PD-L1 status in patients in non-small cell lung cancer (NSCLC), in order to predict response to these drugs. The current complementary diagnostic for Opdivo® (Dako 28-8 PharmDx®) relies on a pathologist scoring paradigm which considers any patient with ≥1% positive tumor cells an optimal candidate for Opdivo® treatment. However, overall survival (OS) is further increased when patients have ≥5% or ≥10% PD-L1 positive tumor cells. This scoring approach is vastly different than the PD-L1 scoring approach used in the Keytruda® companion diagnostic (Dako 22C3 PharmDx®), which utilizes a ≥50% positive tumor cells value to predict a positive Overall Response Rate (ORR; OS not yet determined). Thus, the 28-8 test for Opdivo® utilizes a more precise approach than the 22C3 test for Keytruda®, and requires a more calibrated scoring approach. This calibrated approach for Opdivo® requires the difficult challenge of pathologists reliably distinguishing membrane staining to define the fine gradations of 1%, 5% and 10% PD-L1 positive neoplastic cells. To best meet this challenge, we developed a digital Tissue Image Analysis (TIA) solution which enabled accurate, unbiased quantification of PD-L1 on a cell-by-cell basis to classify the percentage positive tumor cells in patients with high granularity. Using Flagship's proprietary CellMapTM algorithm, we evaluated 40 formalin-fixed paraffin-embedded (FFPE) NS-NSCLC samples which were stained using the Dako 28-8 PharmDx® PD-L1 IHC test. The TIA strategy digitally separated tumor cells from other cell types, and quantified membrane staining intensity according to a consistent threshold. The performance of the resulting IHC-TIA assay was evaluated in the context of a CLIA validation study performed by Flagship. The results demonstrated equivalency to the manually scored IVD reference standard; however, the TIA scoring of this assay provided consistent, unbiased, and more detailed scoring of PD-L1 stained tissues for determining the patients with ≥1, ≥5, and ≥10% PD-L1 positive tumor cells with greater confidence than a manual scoring approach. Moving forward, these TIA tools can be utilized to assess PD-L1 positive cell frequencies with greater reliability and granularity to identify optimal treatment cutpoints for these and other PD-L1 IHC tests used to predict response to PD-L1/PD-1 inhibitors.

Citation Format: Joseph S. Krueger, Roberto Gianani, Brooke Hirsch, Stefan Pieterse, Famke Aeffner, David Young. Image analysis-based PD-L1 companion and complementary diagnostics. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2225.

Abstract 4162: Identifying T lymphocytes in IHC-stained tissues independently of CD3+ staining using morphometric features extracted by image analysis

Assessments of leukocyte populations in the context of cancer tissues are typically determined by staining for leukocyte subtype markers in formalin fixed tissues. This requires the identification, categorization, and localization of multiple leukocytes within tissue context utilizing multiple markers. Meeting these demands are challenging due to technical constraints on the number of individual markers which can be visualized or scored in a single slide, and the complexity of staining observed. The use of multispectral imaging with fluorescent multiplexed markers has better enabled the assessment of multiple markers in a single tissue section. However, these wet chemistry and image capture technologies are very complex, and can only be successfully implemented with significant laboratory infrastructure, specialty equipment, and experienced resources. For these reasons, this approach is not widely implementable in the clinical pathology laboratory setting, where such tests are oriented to a companion diagnostic utility. Approaches which rely on widely adopted chromogenic immunohistochemistry (IHC) staining are preferred in the clinical laboratory setting, but the number of assayable markers is limited to 1-3 unique markers in a single tissue. In order to create a useful approach that could be implemented in existing clinical laboratory workflow, Flagship Biosciences has developed an approach for deriving the complex endpoints often necessary in immuno-oncology studies which rely on 1-3 chromagenic stains and computer interpretation of the tissue using only hematoxylin counterstain to identify T-lymphocytes. In a proof-of-concept study, we utilized our Tissue Image Analysis (TIA) tools to identify morphometric parameters which could identify T-lymphocytes, independent of staining for the T-lymphocyte marker CD3. A cohort of non-small cell lung cancer (NSCLC) tissues was stained by CD3 IHC, and both CD3 and isotype-stained tissues were analyzed with Flagship's CellMap™ software to capture the morphometric and staining features of cells in the tissues. The morphometric features which characterized CD3+ cells were used to approximate the T-lymphocyte population frequency in the isotype-stained tissues. This T-lymphocyte classification scheme was defined based on hematoxylin staining alone, and accuracy of T-lymphocyte classification was verified by CD3 staining. Based on this study, the method described herein could be utilized to reasonably estimate the frequency of T-lymphocyte subsets (e.g. CD4+, CD8+, etc.) or different marker-positive leukocyte (e.g. macrophages) subsets relative to the total T-lymphocyte population without an additional T-lymphocyte marker such as CD3. The approach could, therefore, provide an added dimension of analysis for tissues stained by IHC without adding complexity to the wet assay by necessitating a marker for T-lymphocytes.

Citation Format: Nathan T. Martin, Joshua Black, Famke Aeffner, Logan Cerkovnik, Jasmeet Bajwa, Staci J. Kearney, Crystal Pulliam, A.J. Milici, Joseph Krueger. Identifying T lymphocytes in IHC-stained tissues independently of CD3+ staining using morphometric features extracted by image analysis. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4162.

Commentary

Historically, pathologists perform manual evaluation of H&E- or immunohistochemically-stained slides, which can be subjective, inconsistent, and, at best, semiquantitative. As the complexity of staining and demand for increased precision of manual evaluation increase, the pathologist’s assessment will include automated analyses (i.e., “digital pathology”) to increase the accuracy, efficiency, and speed of diagnosis and hypothesis testing and as an important biomedical research and diagnostic tool. This commentary introduces the many roles for pathologists in designing and conducting high-throughput digital image analysis. Pathology review is central to the entire course of a digital pathology study, including experimental design, sample quality verification, specimen annotation, analytical algorithm development, and report preparation. The pathologist performs these roles by reviewing work undertaken by technicians and scientists with training and expertise in image analysis instruments and software. These roles require regular, face-to-face interactions between team members and the lead pathologist. Traditional pathology training is suitable preparation for entry-level participation on image analysis teams. The future of pathology is very exciting, with the expanding utilization of digital image analysis set to expand pathology roles in research and drug development with increasing and new career opportunities for pathologists.

Abstract C109: Quantitative analysis of multiple subtypes of immune system cells in cancer tissues

Current cancer biology acknowledges the key role of the immune system in tumor biology, and promise for the modulation of immune system in cancer treatment. The composition of the inflammatory cell populations in tissues is reflective of the overall state of the Tumor Micro-Environment (TME), and the identification of distinct inflammatory cell types may hold prognostic or predictive value. Immunohistochemistry allows for reliable identification of the cell constituents to facilitate analysis of the TME while remaining in the tissue context.

Establishing a quantitative paradigm for inflammatory cell types and subtype profiling requires unbiased and automated whole-tissue based quantitation methods, which are capable of spatial integration of multiple inflammatory cell markers across the whole tissue. While single slide fluorescent multiplex approaches can address this need, the use of difficult-to-implement wet assay strategies involving multiplexing 6-8 fluorescent markers on the same tissue section are difficult to implement in a global clinical diagnostic lab setting. To answer this need, we combined novel advents in Tissue Image Analysis (TIA) to integrate spatial expression of serial-section stained whole tissue clinical lung cancer specimens.

In this proof-of-principle study,we were able to superimpose specific locations of individual cell types onto 6 serial sections and evaluate different inflammatory cell types. We used serial sections of clinical lung specimens stained for six immune phenotypic markers (CD68, CD4, CD8, CD33, FoxP3, and CD11b) to illustrate a repertoire of inflammatory cell types. Our proprietary CellMap algorithm was utilized to identify, enumerate, and determine the precise location of individual inflammatory cells in tissues on cell-by-cell basis in the tumor microenvironment (TME). Our proprietary FACTS (Feature Analysis on Consecutive Tissue Sections) approach was used to integrate the spatial expression of individual markers onto a reference H&E slide, and/or adjacent slides. Using the aligned FACTS data and our proprietary MultivariateMap approach, we integrated the patterns of each marker based on immune cell type function and their location relative to each other and the tumor epithelial cells.

In this study, we demonstrated how spatial integration of immune cell markers in the context of whole tissues can be applied to the diagnostic setting. By creating a comprehensive landscape of the immune system state in the tissue biopsies, we were able to identify crucial patterns which represent function and role in immune system biology. These approaches provide a robust platform for immuno-oncology applications by providing information on the state of the immune system in cancer using approaches implementable in the clinic. The use of these approaches will benefit further understanding of cancer pathology, and can directly lead to the development of diagnostic tests with clinical utility.

Citation Format: Joseph S. Krueger, Nathan Martin, Famke Aeffner, Anthony Milici, John Alvarez, Micheal Sharp. Quantitative analysis of multiple subtypes of immune system cells in cancer tissues. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr C109.

Abstract C108: Quantifying PD-L1 spatial distribution signatures for patient selection approaches

Inhibitors of inflammatory checkpoints, such as PD-L1 inhibitors, have demonstrated great promise in preclinical and clinical studies. This therapeutic paradigm focuses on controlling natural inflammatory checkpoints to stimulate an elevated inflammatory response against the tumor to increase anti-tumor inflammatory cell infiltrates in the tumor microenvironment or decrease inflammatory suppressor infiltrates. The proteins which control these processes can be found in the tumor cells, cells in the tumor micro-environment (TME), or in both locales. Positive cells are often assessed in a qualitative or semi-quantitative manner using immunohistochemistry and evaluation of a limited number of representative microscopy fields across a particular tissue compartment (tumor vs stroma) or the whole tissue area. However, the locale of the inflammatory suppressors such as PD-L1 may be more revealing than estimating the tumor-wide dispersion of an inflammatory cell type. Unfortunately, the intricate spatial relationships and the often complex distribution of inflammatory cells in tissues pose significant challenges for a meaningful evaluation.

We have developed an approach which can quantify these spatial relationship in a contextual, biologically meaningful score. Immunohistochemistry staining for PD-L1 in whole lung cancer tissue sections was performed, and our CellMap software was used to assess inflammatory cell distribution in the whole tissue sections. PD-L1 positive cells were quantified relative to: 1) the total number of cells in the tumor and stromal tissue compartments, and 2) the number of cells within a distance from the tumor/stroma interface. Interestingly, several unique PD-L1 distribution patterns relative to the tumor/stroma interface were observed in the sample cohort analyzed. Quantifying the distribution of PD-L1 positive cells as a function of distance from the tumor/stroma interface revealed distribution signatures, which could be used to differentiate between samples. In contrast, this differentiation of the same samples was not possible when PD-L1 cells were assessed relative to the total number of cells.

This study provided a novel method for assessing inflammatory cell type spatial distribution relative to a tissue feature, the tumor/stroma interface. The data suggested that unique spatial patterns of inflammatory cell type distribution could be used to uniquely stratify patients compared to existing quantitative methods. Taken together, this proof-of-concept study demonstrates a unique quantitative assessment of inflammatory cell infiltrates in tumors that could be used to gain new insights into inflammatory cell type distributions and interactions in tumors, inflammatory cell spatial responses to oncology therapies, and novel patient selection criteria for traditional and immuno-oncology therapeutics.

Citation Format: Joseph S. Krueger, Nathan Martin, Anthony Milici, Famke Aeffner. Quantifying PD-L1 spatial distribution signatures for patient selection approaches. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr C108.

Ecto-5'-nucleotidase CD73 modulates the innate immune response to influenza infection but is not required for development of influenza-induced acute lung injury

Extracellular nucleotides and nucleosides are important signaling molecules in the lung. Nucleotide and nucleoside concentrations in alveolar lining fluid are controlled by a complex network of surface ectonucleotidases. Previously, we demonstrated that influenza A/WSN/33 (H1N1) virus resulted in increased levels of the nucleotide ATP and the nucleoside adenosine in bronchoalveolar lavage fluid (BALF) of wild-type (WT) C57BL/6 mice. Influenza-induced acute lung injury (ALI) was highly attenuated in A1-adenosine receptor-knockout mice. Because AMP hydrolysis by the ecto-5'-nucleotidase (CD73) plays a central role in and is rate-limiting for generation of adenosine in the normal lung, we hypothesized that ALI would be attenuated in C57BL/6-congenic CD73-knockout (CD73-KO) mice. Infection-induced hypoxemia, bradycardia, viral replication, and bronchoconstriction were moderately increased in CD73-KO mice relative to WT controls. However, postinfection weight loss, pulmonary edema, and parenchymal dysfunction were not altered. Treatment of WT mice with the CD73 inhibitor 5'-(α,β-methylene) diphosphate (APCP) also had no effect on infection-induced pulmonary edema but modestly attenuated hypoxemia. BALF from CD73-KO and APCP-treated WT mice contained more IL-6 and CXCL-10/IFN-γ-induced protein 10, less CXCL-1/keratinocyte chemoattractant, and fewer neutrophils than BALF from untreated WT controls. BALF from APCP-treated WT mice also contained fewer alveolar macrophages and more transforming growth factor-β than BALF from untreated WT mice. These results indicate that CD73 is not necessary for development of ALI following influenza A virus infection and suggest that tissue-nonspecific alkaline phosphatase may be responsible for increased adenosine generation in the infected lung. However, they do suggest that CD73 has a previously unrecognized immunomodulatory role in influenza.

Mouse Models of Acute Respiratory Distress Syndrome: A Review of Analytical Approaches, Pathologic Features, and Common Measurements

Acute respiratory distress syndrome (ARDS) is a severe pulmonary reaction requiring hospitalization, which is incited by many causes, including bacterial and viral pneumonia as well as near drowning, aspiration of gastric contents, pancreatitis, intravenous drug use, and abdominal trauma. In humans, ARDS is very well defined by a list of clinical parameters. However, until recently no consensus was available regarding the criteria of ARDS that should be evident in an experimental animal model. This lack was rectified by a 2011 workshop report by the American Thoracic Society, which defined the main features proposed to delineate the presence of ARDS in laboratory animals. These should include histological changes in parenchymal tissue, altered integrity of the alveolar capillary barrier, inflammation, and abnormal pulmonary function. Murine ARDS models typically are defined by such features as pulmonary edema and leukocyte infiltration in cytological preparations of bronchoalveolar lavage fluid and/or lung sections. Common pathophysiological indicators of ARDS in mice include impaired pulmonary gas exchange and histological evidence of inflammatory infiltrates into the lung. Thus, morphological endpoints remain a vital component of data sets assembled from animal ARDS models.

IKKβ in intestinal epithelial cells regulates allergen-specific IgA and allergic inflammation at distant mucosal sites

Regulation of allergic responses by intestinal epithelial cells (IECs) remains poorly understood. Using a model of oral allergen sensitization in the presence of cholera toxin as adjuvant and mice with cell-specific deletion of inhibitor-κB kinase (IKKβ) in IECs (IKKβ(ΔIEC)), we addressed the contribution of IECs to allergic sensitization to ingested antigens and allergic manifestations at distant mucosal site of the airways. Cholera toxin induced higher pro-inflammatory responses and altered the profile of the gut microbiota in IKKβ(ΔIEC) mice. Antigen-specific immunoglobulin E (IgE) responses were unaltered in IKKβ(ΔIEC) mice, but their IgA antibodies (Abs), T helper type 1 (Th1) and Th17 responses were enhanced. Upon nasal antigen challenge, these mice developed lower levels of allergic lung inflammation, which correlated with higher levels of IgA Abs in the airways. The IKKβ(ΔIEC) mice also recruited a higher number of gut-sensitized T cells in the airways after nasal antigen challenge and developed airway hyper-responsiveness, which were suppressed by treatment with anti-interleukin-17A. Fecal microbiota transplant during allergic sensitization reduced Th17 responses in IKKβ(ΔIEC) mice, but did not affect IgA Ab responses. In summary, we show that IKKβ in IECs shapes the gut microbiota and immune responses to ingested antigens and influences allergic responses in the airways via regulation of IgA Ab responses.

Osseous metaplasia within a canine insulinoma

An 11-year-old male castrated mixed-breed dog was presented for exercise intolerance, tetraparesis, and persistent hypoglycemia. Abdominal ultrasound examination revealed 2 nodules within the right limb of the pancreas. Cytology from one nodule was consistent with a carcinoma of neuroendocrine origin, with a primary differential diagnosis of insulinoma. Histologic evaluation and immunohistochemistry for synaptophysin and insulin confirmed the diagnosis of insulinoma. Additionally, there was a solitary nodule of mineralized compact bone composing approximately 60% of the mass. To the authors' knowledge, this is the first report of osseous metaplasia within an insulinoma (islet cell carcinoma).

Heterozygosity for the F508del mutation in the cystic fibrosis transmembrane conductance regulator anion channel attenuates influenza severity

BACKGROUND

Seasonal and pandemic influenza are significant public health concerns. Influenza stimulates respiratory epithelial Cl(-) secretion via the cystic fibrosis transmembrane conductance regulator (CFTR). The purpose of this study was to determine the contribution of this effect to influenza pathogenesis in mice with reduced CFTR activity.

METHODS

C57BL/6-congenic mice heterozygous for the F508del CFTR mutation (HET) and wild-type (WT) controls were infected intranasally with 10 000 focus-forming units of influenza A/WSN/33 (H1N1) per mouse. Body weight, arterial O2 saturation, and heart rate were monitored daily. Pulmonary edema and lung function parameters were derived from ratios of wet weight to dry weight and the forced-oscillation technique, respectively. Levels of cytokines and chemokines in bronchoalveolar lavage fluid were measured by enzyme-linked immunosorbent assay.

RESULTS

Relative to WT mice, influenza virus-infected HET mice showed significantly delayed mortality, which was accompanied by attenuated hypoxemia, cardiopulmonary dysfunction, and pulmonary edema. However, viral replication and weight loss did not differ. The protective HET phenotype was correlated with exaggerated alveolar macrophage and interleukin 6 responses to infection and was abrogated by alveolar macrophage depletion, using clodronate liposomes.

CONCLUSIONS

Reduced CFTR expression modulates the innate immune response to influenza and alters disease pathogenesis. CFTR-mediated Cl(-) secretion is therefore an important host determinant of disease, and CFTR inhibition may be of therapeutic benefit in influenza.

Intestinal epithelial cells IKKβ regulate allergic responses in the skin (P6053)

The sites where immune responses are initiated are believed to play a key role at shaping subsequent responses at distant mucosal sites. We have previously shown that IKKβ in intestinal epithelial cells (IECs) shapes the immune responses to ingested antigens and influences airway responses to subsequent antigen exposure via regulation of IgA and Th17. People with food allergy often suffer from allergic airway and/or skin diseases like asthma or atopic dermatitis but it is unknown whether T cells sensitized in the gut promote inflammation at different mucosal surfaces through the same mechanism. Using a model of oral antigen sensitization and mice with cell-specific deletion of IKKβ, we addressed the contribution of IECs to regulatory crosstalk between the gut and skin. Control C57BL/6 mice and mice deficient in IKKβ in IEC (IKKβΔIEC) were orally sensitized by administration of ovalbumin and cholera toxin as adjuvant. All groups developed similar levels of antigen-specific IgE and IgG1 responses, but IgG2b responses were enhanced in IKKβΔIEC. Subsequent epicutaneous challenges of control mice with ovalbumin induced skin inflammation characterized by increased epidermal thickness and dermal infiltration of eosinophils. Interestingly, both the epidermal thickness and dermal infiltration of eosinophils were reduced in IKKβΔIEC. Ongoing studies will determine mechanisms underlying the protective effect of IKKβ in intestinal epithelial cells against allergic responses in the skin.