Whole Blood Storage Duration Alters Fibrinogen Levels and Thrombin Formation

INTRODUCTION

Whole blood resuscitation for hemorrhagic shock in trauma represents an opportunity to correct coagulopathy in trauma while also supplying red blood cells. The production of microvesicles in stored whole blood and their effect on its hemostatic parameters have not been described in previous literature. We hypothesized that microvesicles in aged stored whole blood are procoagulant and increase thrombin production via phosphatidylserine.

METHODS

Whole blood was obtained from male C57BL/6 male mice and stored in anticoagulant solution for up to 10 days. At intervals, stored whole blood underwent examination with rotational thromboelastography and platelet poor plasma was prepared for analysis of thrombin generation. Microvesicles were prepared from 10 day old whole blood aliquots and added to fresh whole blood or platelet poor plasma to assess changes in coagulation and thrombin generation. Microvesicles were treated with recombinant mouse lactadherin prior to addition to plasma to inhibit phosphatidylserine's role in thrombin generation.

RESULTS

Aged murine whole blood had decreased fibrin clot formation compared to fresh samples with decreased plasma fibrinogen levels. Thrombin generation in plasma from aged blood increased over time of storage. The addition of microvesicles to fresh plasma resulted in increased thrombin generation compared to controls. When phosphatidylserine on microvesicles was blocked with lactadherin, there was no difference in the endogenous thrombin potential but the generation of thrombin was blunted with lower peak thrombin levels.

CONCLUSIONS

Cold storage of murine whole blood results in decreased fibrinogen levels and fibrin clot formation. Aged whole blood demonstrates increased thrombin generation and this is due in part to microvesicle production in stored whole blood. One mechanism by which microvesicles are procoagulant is by phosphatidylserine expression on their membranes.

LEVEL OF EVIDENCE

Basic Science.

Abstract 1140: Enfortumab vedotin, a Nectin-4 directed ADC, demonstrates compelling tolerability and anti-tumor activity with intravesical instillation in preclinical models of non-muscle invasive bladder cancer

Enfortumab vedotin (EV) is a monomethyl auristatin E (MMAE) containing antibody-drug conjugate directed to Nectin-4, which is highly expressed in bladder cancers. Preclinically, EV has demonstrated tumor cell-killing by direct cytotoxicity, bystander toxicity, and induction of the hallmarks of immunogenic cell death. In EV-301, a phase 3 clinical study, EV monotherapy showed an overall survival (OS) benefit vs chemotherapy in patients with locally advanced or metastatic urothelial carcinoma (la/mUC) who had previously received platinum-based therapy and a PD-1 or PD-L1 inhibitor (Powles 2021). EV also has encouraging activity in combination with pembrolizumab in previously untreated la/mUC (73% ORR)(Friedlander 2021). Most newly diagnosed bladder cancer cases are non-muscle invasive (Chang 2016; Woldu 2017; Kates 2020; Li 2020). Standard treatment of high risk NMIBC involves transurethral resection of the bladder tumor followed by intravesical (IVES) Bacillus Calmette-Guerin (BCG) or chemotherapy. Although response to BCG is high, many patients recur within 1-5 years (Matulay 2021). For patients unresponsive to BCG, treatment options are limited; radical cystectomy remains the standard of care. Due to the morbidity associated with radical cystectomy there remains a significant unmet need for a safe and effective therapy. We demonstrate that NMIBC have a high Nectin-4 expression pattern by RNA analyses and immunohistochemistry (IHC) similar to la/mUC, using an anti-Nectin-4 antibody (clone M22-321b41.1). The anti-tumor activity of EV was demonstrated in vitro and in vivo in human bladder cancer cells overexpressing Nectin-4. The superiority of EV vs MMAE alone was shown via in vitro pulsed (2hr) exposure cytotoxicity assays mimicking IVES administration. In a luciferase expressing orthotopic xenograft mouse model of NMIBC, EV-mediated anti-tumor activity was confirmed by both bioluminescence imaging of tumor burden and IHC for h-Nectin-4 expressing cancer cells. Tumor uptake of EV was further confirmed by IHC detection of EV in the engrafted tumor cells. Repeat-dose IVES administration of EV was well tolerated in a GLP study with minimal local and no systemic toxicities at doses up to 6-fold the intravenous maximum tolerated dose. Consistent with the lack of systemic toxicities, IVES administration was associated with low systemic absorption (<1% of the dose-normalized ADC Cmax observed in intravenous toxicity studies) and undetectable systemic MMAE. In this preclinical model, increased levels of MMAE in the targeted bladder tissue were associated with increasing the total dose and concentration of EV more than changing either the volume instilled or dwell time. These findings provide evidence to support further investigation of intravesical EV in NMIBC patients.

Citation Format: Christopher Carosino, Devra Olson, Katie Snead, Anthony Lee, Lauren Farr, Amit Garg, Christine O'Day, Esther Trueblood, Jennifer Wright, Mark Bieda, Charles Caldwell, Kelly Hensley, Sean Allred, Bernard Liu, Masashi Shimazaki, Sharsti Sandall. Enfortumab vedotin, a Nectin-4 directed ADC, demonstrates compelling tolerability and anti-tumor activity with intravesical instillation in preclinical models of non-muscle invasive bladder 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 1140.

A digital assay for programmed death-ligand 1 (22C3) quantification combined with immune cell recognition algorithms in non-small cell lung cancer

PD-L1 (22C3) checkpoint inhibitor therapy represents a mainstay of modern cancer immunotherapy for non-small cell lung cancer (NSCLC). In vitro diagnostic (IVD) PD-L1 antibody staining is widely used to predict clinical intervention efficacy. However, pathologist interpretation of this assay is cumbersome and variable, resulting in poor positive predictive value concerning patient therapy response. To address this, we developed a digital assay (DA) termed Tissue Insight (TI) 22C3 NSCLC, for the quantification of PD-L1 in NSCLC tissues, including digital recognition of macrophages and lymphocytes. We completed clinical validation of this digital image analysis solution in 66 NSCLC patient samples, followed by concordance studies (comparison of PD-L1 manual and digital scores) in an additional 99 patient samples. We then combined this DA with three distinct immune cell recognition algorithms for detecting tissue macrophages, alveolar macrophages, and lymphocytes to aid in sample interpretation. Our PD-L1 (22C3) DA was successfully validated and had a scoring agreement (digital to manual) higher than the inter-pathologist scoring. Furthermore, the number of algorithm-identified immune cells showed significant correlation when compared with those identified by immunohistochemistry in serial sections stained by double immunofluorescence. Here, we demonstrated that TI 22C3 NSCLC DA yields comparable results to pathologist interpretation while eliminating the intra- and inter-pathologist variability associated with manual scoring while providing characterization of the immune microenvironment, which can aid in clinical treatment decisions.

Loss of STING expression is prognostic in non-small cell lung cancer

BACKGROUND

Stimulator of interferon (IFN) genes (STING) is a protein that promotes type I IFN production essential for T-cell activation. In this study, we aim to characterize STING expression comprehensively using The Cancer Genome Atlas (TCGA) database, cell lines, and patient tumor samples stained with immunohistochemistry.

METHODS

Two cohorts were evaluated comprising 721 non-small cell lung cancer (NSCLC) patients and 55 NSCLC cell lines for STING and cyclic GMP-AMP synthase (cGAS) expression using immunohistochemistry. Moreover, an independent cohort of n = 499 patients from the TCGA database was analyzed. Methylation was evaluated on STING and cGAS in five STING-negative NSCLC cell lines.

RESULTS

STING RNA expression positively correlates with T cell function and development genes, negatively correlates with cell proliferation and associated with increased survival (5-year-overall survival [OS] 47.3% vs. 38.8%, p = 0.033). STING protein expression is significantly higher in adenocarcinoma (AC) and is lost with increasing stages of AC. STING-positivity is significantly higher in mutant EGFR and KRAS tumors. STING-positive NSCLC patients identified with immunohistochemistry (H-score > 50) have increased survival (median OS: 58 vs. 35 months, p = 0.02). Treatment of STING-negative cell lines with a demethylating agent restores STING expression.

CONCLUSIONS

STING is ubiquitously expressed in NSCLC and associated with T cell function genes, AC histology, EGFR, and KRAS mutations and improved overall survival.

48 Immune environment correlates with NSCLC and CRC patient survival

Background

Immune cells within the tumor microenvironment (TME) play a vital role in regulating tumor progression. Therefore, immunotherapies that stimulate anti-tumor responses are of great interest for the treatment of various cancers. PD-L1 expression on immune cells is positively correlated with increased patient survival. Our hypothesis is that non-small cell lung carcinoma (NSCLC) and colorectal cancer (CRC) patients with high immune infiltration and greater amounts of anti-tumor immune cells within the tumor compartment have an increased time of survival compared to cancers with immune excluded or immune desert environments.

Methods

One NSCLC and one CRC tumor microarray (TMA) containing primary tumors, metastases, and normal tissue were stained via multiplex immunofluorescence (mIF) for 6 different immune markers: CD3, CD8, CD56, CD68, CD163, and PD-L1. This multiplex panel was designed to evaluate the immune cell population as well as tumor and immune cell PD-L1 status to aid in research for immunotherapies, specifically anti-PD-L1 therapies. The stained TMAs were analyzed utilizing Flagship Biosciences’ proprietary image analysis platform. Machine learning algorithms stratified cells as belonging to the tumoral or stromal space based on their cellular features. Core level expression data was pulled and represented on a whole-cohort basis. All staining and image analysis outputs were reviewed by a board-certified, MD pathologist. Kaplan-meier curves were generated based on survival data in relation to the levels of immune cells present within the tumor cores as well as the percentage of immune cells infiltrating into the tumor.

Results

There is a clear correlation between patient survival and the presence or absence of various types of immune cells, including helper T cells, cytotoxic T cells, M1 macrophages, M2, macrophages, NK cells, as well as PDL1 expression on tumor and immune cells. Specifically, the increased presence of anti-tumor immune cells as well as increased expression of PD-L1 on immune cells within the tumor compartment correlates with an increase in patient survival.

Conclusions

Data generated through Flagship Biosciences’ image analysis platform showed a strong relationship between immune cell presence and localization and NSCLC and CRC patient survival. Altering the immune cells within the tumor to an anti-tumor immune environment could increase patient survival times. Combining immune checkpoint inhibitors with current FDA approved therapies for NSCLC and CRC are of interest to further extend patient survival. Further, utilizing Flagship Biosciences’ image analysis software to understand cancer immune microenvironments should be further utilized to aid in diagnosis and treatment decisions.

1437 Histological Examination in Search of Helicobacter Pylori in Iron Deficiency Anaemia: An Unnecessary Expense?

Aim

The British Society of Gastroenterology guidelines recommend Helicobacter pylori (HP) testing in patients with iron deficiency anaemia (IDA). This quality improvement project evaluates the utility of histological examination for HP in IDA patients, the consequent expenditure and whether a more cost-effective alternative exists.

Method

A retrospective search was conducted of patients within a four-month period who underwent an oesophago-gastroduodenoscopy (OGD) for IDA. Patients with an identifiable cause of IDA, ferritin >40ug/mL and haemoglobin (Hb) >12g/L in women or > 13g/L in men were excluded. The costings of a single tissue biopsy and HP stool testing were sought from our local departments.

Results

Ninety-nine patients’ results were analysed after exclusions (n = 99/127, 78.0%). All patients had biopsies taken at OGD. On average, three biopsies were obtained per patient. Forty-two patients had no abnormalities visualized on OGD and all ninety-nine patients were HP negative. A single biopsy costs £70; £65 per hematoxylin and eosin based histological examination and £5 per single-use biopsy forceps. Accounting for forty-two patients with macroscopically normal OGDs leads to a total expenditure of £8820. A HP stool test costs £14.

Conclusions

Guidelines recommend HP testing either non-invasively or at OGD as an alternative strategy, based on weak evidence that HP may cause IDA. HP prevalence is falling; histological examination of biopsies obtained at OGD therefore appears expensive and unnecessary. It is more cost effective to perform a stool test in the case of a normal OGD and commence treatment accordingly with biopsies reserved when otherwise clinically indicated and not solely for HP testing.

Abstract 435: A novel image analysis assay for determining programmed death-ligand 1 (22C3) in non-small cell lung cancer that accounts for tissue and alveolar macrophages

The Dako PD-L1 (22C3) antibody is used in immunohistochemistry (IHC) to measure tumor programmed death-ligand 1 (PD-L1) levels, serving as a common companion diagnostic to the check point inhibitor drug pembrolizumab in non-small cell lung cancer (NSCLC). Yet for the practicing pathologist, interpretation of the PD-L1 (22C3) IHC assay is cumbersome and time-consuming resulting in poor intra- and inter-pathologist precision. We have developed a clinically validated PD-L1 (22C3) image analysis (IA) assay that was previously shown to perform equivalently to manual pathologist scoring, require less labor, and produce standardized and reproducible results with greater precision than manual scoring across repeated assessment. However, there is growing literature on the significance of macrophage PD-L1 positivity for predicting treatment response, highlighting the need to differentiate PD-L1 positivity in tumor cells versus macrophages. This need is further underscored by the tendency of manual and digital reads to confuse alveolar macrophages as tumor cells. In this study, we have applied a novel machine learning solution for tissue and alveolar macrophage detection to our PD-L1 (22C3) IA assay to improve its digital scoring accuracy in NSCLC as well as generate additional complementary data on the presence and PD-L1 positivity status of tissue and alveolar macrophages.

24 whole tissue NSCLC samples were purchased and IHC stained for PD-L1. Stained slides were scanned at 20X magnification and analyzed using Flagship's IA solutions that separate tumor and stromal compartments, identify tissue and alveolar macrophages, and quantify PD-L1 expression. Resulting image markups of cell detection and PD-L1 expression were reviewed by an MD pathologist for acceptance. PD-L1 staining was evaluated by digital IA and manual pathology in the sample's tumor compartment for Tumor Proportion Score (TPS). Applying the tissue and alveolar macrophage solution to the PD-L1 (22C3) assay successfully removed macrophages from the digital TPS assessment and generated additional data on tissue and alveolar macrophages (% present, % PD-L1 positive) without significantly impacting the integrity of the IA assay (i.e., the correlation between the digital and manual TPS remained high). This preliminary data demonstrates the robust performance of the clinically validated PD-L1 (22C3) IA assay, even when accounting for tissue and alveolar macrophages. Ongoing experiments include testing the macrophage algorithm on a larger sample of NSCLC tissues to determine the correlation and treatment cut-off concordance between digital and manual scoring obtained by three pathologists. A follow-up clinical validation study of the sensitivity, specificity, accuracy, and precision of this updated PD-L1 (22C3) IA assay is also pending.

Citation Format: Roberto Gianani, Will Paces, Elliott Ergon, Vitria Adisetiyo, Charles Caldwell. A novel image analysis assay for determining programmed death-ligand 1 (22C3) in non-small cell lung cancer that accounts for tissue and alveolar macrophages [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 435.

Abstract 433: Clinical validation of a Dickkopf-1 (DKK1) chromogenic in-situ hybridization (CISH) assay for manual and image-analysis assisted pathologist interpretation

Dickkopf-1 (DKK1) is a secreted modulator of Wnt signaling that is frequently overexpressed in tumors and associated with a poor prognosis. In this study we demonstrate an approach for clinically validating a RNAscope chromogenic in situ hybridization (CISH) assay for determining the level of DKK1 RNA in Gastric (G) and Gastroesophageal (GEJ) tumor tissues according to CLIA guidelines. This two-step process validated first the performance of the wet assay along with the ability of a pathologist to manually score the CISH signal according to a dot-based H-score paradigm, and second the ability of image analysis (IA) software (Flagship Biosciences) to unbiasedly and reproducibly quantify DKK1 staining in the same set of samples. The DKK1 CISH assay for manual scoring passed all pre-determined criteria of sensitivity, specificity, accuracy, and precision. 100% of the 40 evaluated G/GEJ tissues demonstrated acceptable staining in target tumor cells and absence in non-target cells. 100% of the evaluated tissues passed sensitivity with a broad dynamic range of signal expression across target cells, and negligible background staining. Reproducibility was measured by blinded pathology scoring of a serial subset of 12 cases, resulting in 11/12 (92%) with concordant DKK1 H-scores. Accuracy was assessed with a DKK1 qPCR assay on a 20-sample subset and a significant correlation with the H-score data was observed. The IA algorithm also passed all pre-determined criteria of sensitivity, specificity, accuracy, and precision. 36/40 samples (90%) passed analytical specificity with the IA algorithm correctly classifying staining on true cells belonging to the tumor. Failed samples were attributed to non-specific alkaline phosphatase activity, which in practice would be disregarded by the reviewing pathologist. 100% of samples passed the sensitivity criteria of appropriate cell identification and classification. IA precision compared H-scores across 3 days of staining, with 11/12 (92%) cases having concordant DKK1 H-scores and an ICC of 0.9009 (95% CI: 0.7117-0.9601). Digital H-scores were highly correlated to the validated manual H-scores of the 40-sample set (r = 0.72, p <0.0001). Taken together, these data demonstrate a clinically validated DKK1 RNAscope CISH laboratory-derived test (LDT) for manual and IA-assisted pathologist interpretation. The DKK1 RNAscope LDT is currently being applied as part of a phase 2 clinical study of DKN-01 in combination with tislelizumab to prospectively identify previously treated G/GEJ adenocarcinoma patients with elevated DKK1 tumor expression (NCT04363801).

Citation Format: Charles Caldwell, Mike Kagey, Sofia Reitsma, Will Paces, Elizabeth Bueche, Vitria Adisetiyo, Roberto Gianani. Clinical validation of a Dickkopf-1 (DKK1) chromogenic in-situ hybridization (CISH) assay for manual and image-analysis assisted pathologist interpretation [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 433.

Abstract 1801: Development of a comprehensive biomarker strategy to support phase 1 clinical trial of SRK-181 the latent TGFβ1 inhibitor

TGFβ signaling appears to be a key mediator of primary resistance to programmed cell death protein (PD-1) pathway blockade. SRK-181 is an investigational stage, high-affinity, fully human antibody that selectively binds to latent TGFβ1 and inhibits its activation. Preclinical data demonstrate that combining SRK-181 with a PD-1 inhibitor modulates tumor microenvironment (TME), including an influx of CD8 positive T cells that correlates with anti-tumor responses. The ongoing DRAGON trial is a multi-center, open-label, Phase 1, first in-human (FIH), dose-escalation, and dose-expansion study. The goal of the trial is to evaluate the safety, tolerability, pharmacokinetics (PK), pharmacodynamics (PD), and efficacy of SRK-181 administered alone and in combination with an anti-PD-(L)-1 in adult patients with locally advanced or metastatic solid tumors. To support this ongoing DRAGON clinical trial and further explore the mechanism of action of SRK-181, a comprehensive biomarker strategy is being developed to assess the alternation of immune profile in TME and potential predictors of therapeutic response to SRK-181. Here we describe the development and refinement of several biomarker assays. First, an image analysis-based algorithm for CD8 immunohistochemistry (IHC) is established utilizing human cancer tissue in a pre-clinical study. This novel digital pathology analysis enables identification of CD8 positive T cells in discrete compartments, including the tumor nests, stroma and tumor/stromal margins, to better capture the heterogeneity of the CD8 signal within tissues. Second, we describe methods to evaluate the TGFβ pathway including quantitative analysis of tumor tissue phospho-Smad2 and circulatory levels of TGFβ1 ligand. A companion assay to exclude blood samples with nonspecific background signals has been characterized and will be performed in parallel when evaluating circulatory TGFβ1 in clinic. In summary, we present several novel, tailored biomarker readouts that are part of a broader biomarker strategy aimed at maximizing detection of relevant clinical data to both support the ongoing clinical trial and provide further insight into the mechanism of action of SRK-181.

Citation Format: Christopher Brueckner, Ryan Faucette, Charles Caldwell, Jr., Sofia Reitsma, Stefan Wawersik, Ashish Kalra, Lu Gan, Si Tuen Lee-Hoeflich. Development of a comprehensive biomarker strategy to support phase 1 clinical trial of SRK-181 the latent TGFβ1 inhibitor [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 1801.

A digital pathologist support tool for accurate detection of PD-L1 in head and neck squamous cell carcinoma

e18031

Background: The programmed death-ligand 1 (PD-L1) (22C3) antibody is a companion diagnostic to the check-point inhibitor drug pembrolizumab for head and neck squamous cell carcinoma (HNSCC). Specifically, PD-L1 expression, as determined by a Combined Positive Score (CPS) ≥ 1, defines the clinical decision point for treatment. However, to calculate the CPS, pathologists must account for PD-L1+ tumor cells (TC) and immune cells (IC, i.e., lymphocytes, macrophages) – a cumbersome and time-consuming task that is prone to intra/inter-pathologist variability. We developed a digital image analysis (IA) based solution as a pathologist support tool that accurately and precisely scores images of PD-L1 stained HNSCC tissues. Here we compared the performance of the digital method with manual pathology. To address the literature on the differential regulation of PD-L1 by IC and TC in treatment response, we also examined how PD-L1+ IC contribute to the CPS as compared to PD-L1+ TC. Methods: 19 HNSCC samples were immunohistochemically stained for PD-L1 (22C3). Slides were assessed for CPS by manual pathology: CPS = (# PD-L1 staining cells [TC, lymphocytes, macrophages]/total # viable TC) x 100; wherein CPS < 1 (no PD-L1 expression; no treatment) and CPS ≥ 1 (PD-L1 expression; treatment). Slides were scanned at 20X and analyzed using proprietary IA solutions that identify and separate TC from IC and quantify their PD-L1 expression. Resulting IA markups of cell detection and PD-L1 expression were reviewed by an MD pathologist for accurate cell recognition and stain classification. Upon pathologist approval of the IA performance, PD-L1 staining was evaluated by digital IA for CPS, % PD-L1+ TC, and % PD-L1+ IC. Pearson’s correlation analyses were conducted to assess the concordance between manual and digital CPS along with the association between CPS and PD-L1+ IC versus PD-L1+ TC. Results: Digital and manual CPS were significantly correlated ( r = 0.76, p = 0.00016) and concordant in treatment binning for 14/19 samples; for the 5 discordant samples, manual CPS binned them for no treatment while digital CPS binned them for treatment. Digital CPS significantly correlated with the % PD-L1+ IC ( r = 0.90, p < 0.00001) along with the % PD-L1+ TC ( r = 0.98, p < 0.00001). All 6 samples binned for no treatment by digital CPS had < 1% PD-L1+ IC, whereas all but 2/13 samples binned for treatment by digital CPS had ≥ 1% PD-L1+ IC. Conclusions: The digital method for assessing PD-L1 expression in HNSCC performs similarly to manual pathology with improved accuracy for detecting and quantifying IC versus TC in the CPS calculation. Moreover, the % of PD-L1+ IC seems to contribute substantially to the CPS, to a similar degree as the % of PD-L1+ TC. Given the concordance with manual pathology, this digital method can support pathologists as a clinical diagnostic tool. As such, a clinical validation study of this digital method in a larger HNSCC cohort is underway.

Abstract 3879: Image analysis-based identification and quantification of macrophages in PD-L1 (22C3) stained NSCLC tissue sections without additional macrophage-specific staining

PD-L1 positivity in tumor-associated macrophages has been related to a favorable response to anti-PD-1 and PD-L1 targeted therapies. This concept has driven interest in specifically identifying macrophages in PD-L1 stained tissues, but pathologists often have difficulty in performing this task reliably.

Thus, there is a clear need for tools capable of detecting and classifying tumor-associated macrophages in the context of a standardized PDL1 assay. One such method relies on the utilization of image analysis (IA) which measures hundreds of defining cellular features. This is necessary because macrophages identification based on few features would be difficult due to their varying morphologies and similarity with tumor cells. In order to isolate macrophages using multiple aspects of their cellular characteristics, AI and machine learning algorithms were leveraged to provide robust models for their identification.

In this study we compare two artificial intelligence (AI) assisted macrophage classification methods for their accuracy in specifically identifying CD68 positive macrophages. Both approaches are based on interrogating a cohort of 20 NSCLC sections with two tumor-associated macrophage recognition algorithms, the first based on a neural network (NN), and the second on a decision tree (DT) model. These classifiers were developed by training a learning model on the morphometric and chromogenic PD-L1 staining features measured on detected cells, using their fluorescent CD68 expression profile as an indicator of their macrophage lineage.

These classification algorithms were trained on images developed using procedures wherein tissue sections were stained by immunofluorescence with antibody to the macrophage associated CD68 marker and subsequently scanned to obtain a digital image. After removal of the coverslip and stripping of the CD68 antibodies, the sections were then stained with the anti-PDL1 22C3 antibody and rescanned to obtain a second digital image. Coregistration of the two digital images allowed for the identification of CD68 positive cells in the context of only the 22C3 PDL1 assay. The accuracy of each classification algorithm was determined by comparing the positivity for macrophage lineage among algorithm predicted macrophage to CD68 positivity.

For both the NN and the DT classifier, we demonstrated a &gt; 90% accuracy classification of macrophages identification. The decision tree method achieved similarly accurate predictions

These data indicate that both NN and DT methods allow for independent identification of macrophages using only a 22C3 IHC PD-L1 assay, making it possible to isolate the contribution of PD-L1 macrophage positivity to successful checkpoint therapy response.

Citation Format: Will Paces, Roberto Gianani, Huong Nguyen, Bradley Long, Michael Argyres, Cris Luengo, Rebecca Kim, Charles Caldwell. Image analysis-based identification and quantification of macrophages in PD-L1 (22C3) stained NSCLC tissue sections without additional macrophage-specific staining [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 3879.

Abstract 3130: Using digital pathology based “IO Scorecards” to describe relationships between PD-L1 expression and CD8 positive immune cell infiltration

Several studies have shown that the location and expression of infiltrating immune cells in patient tumors can better identify which patients are more likely to respond to anti- PD-1/PD-L1 therapy. In particular, immunohistochemistry-based studies have shown that the spatial location of PD-L1 expression has particular biological relevance, as PD-L1 expression in the tumor cells or immune cells in the tumor syncytium, tumor microenvionment (TME), or tumor-stroma boundary all describe differential PD-L1 biology.

Here, we use Flagship’s digital pathology platform (cTA®) to investigate IHC based PD-L1 and CD8 staining patterns in Non-Small Cell Lung (NSCLC) and Urothelial Carcinoma (UC) tissue biopsies. The cTA platform creates thousands of per-cell Biofeatures™ derived from the digital pathology images of the IHC stained tissue, and applies Artificial Intelligence (AI) to the data to summary score endpoints for patient and cohort classification. In this approach, each tissue’s IO landscape is represented using an “IO Scorecard“, which summarizes the IHC biomarker data in a summary score which captures a comprehensive analysis of the tissue sample. The AI-determined scorecard models can be used to monitor changes before and after drug treatment and/or create predictive models for patient response outcomes.

In this study, NSCLC and Urothelial Carcinoma samples were sectioned and stained using either the FDA-approved Dako 22C3 or SP263 PD-L1 IHC assays. Serial sections of each tissue specimen were also stained for CD8 expression. The cTA process detected all cells, assigned them to the tumor or TME compartments, and recorded the Biofeatures™ data which characterized PD-L1 or CD8 staining in the Tumor, Tumor/TME margin, or TME compartments. The method was validated by its ability to reproduce pathologist scoring for PD-L1 and CD8. Using the accepted data, we used the AI system to create novel Scorecard based patient classifications which describe differential PD-L1 status, CD8 status, and PD-L1/CD8 status combined. The AI Scorecard approach demonstrated that certain PD-L1 staining Biofeatures™ may also predict the CD8 status of a tumor, suggesting that additional CD8 staining may not be necessary to understand important expression patterns pertaining to cytotoxic T-cells.

In summary, we demonstrated how the “IO Scorecards” are able to classify patients into differential immune status cohorts using a novel AI based scoring system, which relies only on PD-L1 IHC staining, by creating a comprehensive, contextual profile of PD-L1 staining that does not require additional CD8 IHC staining to characterize the impact of cytotoxic T-cells in a tissue sample.

Citation Format: Charles Caldwell, Will Paces, Jeni Caldara, Bharathi Vennapusa, Joseph S. Krueger. Using digital pathology based “IO Scorecards” to describe relationships between PD-L1 expression and CD8 positive immune cell infiltration [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3130.

The immune checkpoint, HVEM may contribute to immune escape in non-small cell lung cancer lacking PD-L1 expression

BACKGROUND

Herpes Virus Entry Mediator (HVEM) is an important immune checkpoint in cancer recognition. HVEM expressed on tumor cell membranes activates immune cell signaling pathways leading to either inhibition of activity (B- and T-lymphocyte attenuator, BTLA) or activation of immune activity (LIGHT). The aim of this study is to investigate the prevalence of HVEM expression and its association with PDL1 expression in NSCLC.

METHODS

A TMA of 527 resected NSCLC samples and 56 NSCLC cell lines were evaluated for HVEM and PD-L1 expression. The IHC assay for HVEM was optimized on the Dako Link48 autostainer using a polyclonal antibody from R&D Systems(AF356). PD-L1 IHC was performed on the Dako Link48 autostainer using the PD-L1 28-8 pharmDx kit. Scoring HVEM employed the H-score system while for PD-L1 the tumor proportion score (TPS) was used.

RESULTS

HVEM expression in the NSCLC resected samples and cell lines revealed a positive H-score more than 1 was 18.6% (77/415) and 48.2% (27/56) respectively. HVEM expression was significantly higher in patients with lymph node N2 metastasis (25.5% vs 7.9% vs 17.5%, p = 0.046) when comparing with N1 or no lymph node metastasis, and was marginally significantly higher in patients with stage III/IV disease (24.5% vs 16.4%, p = 0.059). Subgroup analysis showed that HVEM (median 45 vs 36 months, p = 0.706) and PD-L1 expression (median 45 vs 48 months, p = 0.178) status was not predictive of overall survival. HVEM was found to have a significant negative correlation with PD-L1 expression (r=-0.274, p < 0.001) in patients with NSCLC and also a weak negative correlation in NSCLC cell lines (r=-0.162, p = 0.352).

CONCLUSION

HVEM was found to be overexpressed in NSCLC patients of N2 lymph node metastasis or later stage and has a negative co-relationship with PD-L1 expression. HVEM was not prognostic for NSCLC patients.

EGFR-directed monoclonal antibodies in combination with chemotherapy for treatment of non-small-cell lung cancer: an updated review of clinical trials and new perspectives in biomarkers analysis

Lung cancer still represents one of the most common and fatal neoplasm, accounting for nearly 30% of all cancer-related deaths. Targeted therapies based on molecular tumor features and programmed death-1 (PD-1)/programmed death ligand-1 (PDL-1) blockade immunotherapy have offered new therapeutic options for patients with advanced non-small-cell lung cancer (NSCLC). Activation of the epidermal growth factor receptor (EGFR)-pathway promotes tumor growth and progression, including angiogenesis, invasion, metastasis and inhibition of apoptosis, providing a strong rationale for targeting this pathway. EGFR expression is detected in up to 85% of NSCLC and has been demonstrated to be associated with poor prognosis. Two approaches for blocking EGFR signaling are available: prevention of ligand binding to the extracellular domain with monoclonal antibodies (mAbs) and inhibition of the intracellular tyrosine kinase activity with small molecules. There is a strong rationale to consider the tumor's level of EGFR expression as one of the most significant predictive biomarkers in this setting. In this paper we provide an update focusing on the current status of EGFR-directed mAbs use for the treatment of patients with advanced NSCLC, through a review of all clinical trials involving anti-EGFR mAbs in combination with chemotherapy (CT) for advanced disease and with chemo-radiotherapy for stage III disease. Here we also discuss the current status of predictive biomarkers for anti-EGFR mAbs when added to first-line CT in patients with advanced NSCLC. Finally, we focused on the relevance of EGFR fluorescence in situ hybridization (FISH)+ and immunohistochemistry (IHC)-Score ≥ 200 as predictive biomarkers for the selection of patients who would be most likely to derive a clinical benefit from treatment with CT in combination with anti-EGFR mAbs, with particular reference also to histology.

Abstract 3637: Expression of an immune checkpoint- Poliovirus Receptor (PVR) in small cell lung cancer

Background: Although immunotherapy has renewed hopes for the improved treatment of SCLC, the “classical” PD-1/PD-L1 pathway is not commonly expressed in SCLC. PVR (CD155) is expressed at low levels in a number of cell types of epithelial origin and is overexpressed in various carcinomas with epithelial and neurological origins, including colorectal carcinoma, breast carcinoma, neuroblastoma and glioblastoma. In this study, we evaluated the expression of PVR in SCLC cell lines and a cohort of patient tumors with association to clinical characteristics.

Methods: Immunohistochemistry (IHC) was performed to evaluate PVR protein expression in 39 SCLC cell lines as well as a cohort of 77 resected tumors from SCLC patients with clinical data using a monoclonal PVR antibody (D8A5G,Cell Signaling, MA). Scoring data was generated using both the H-score and tumor proportion score (TPS) systems. PVR expression was correlated with characteristics of both the cell lines and the clinical cohort.

Results: The SCLC cell lines were evaluated by the H-score system only. A total of 39 SCLC cell lines in a TMA were evaluated in which 37 cell lines (95%, 37/39) demonstrated PVR staining &gt; 0 and 85% of the cell lines showed positive staining with an arbitrary H-score cutoff of 50. PVR expression was higher in cell lines established from pre-treated SCLC patients as compared to those established from treatment-naïve patients (P=0.037). There was no correlation between PVR expression and cell line growth as suspension versus adherent cells. In the SCLC patient cohort, PVR expression was found to be predominantly on the membrane of tumor cells, with minimal expression observed on immune cells in the tumor microenvironment. PVR expression in the SCLC patient cohort was 82% with H-score cutoff of ≥ 50. SCLC patients with positive PVR expression demonstrated a poorer prognosis, however the difference was not statistically significant (p=0.05). Positive PVR expression was also correlated with advanced stage (P=0.0073) and higher in male patients (P=0.04). With a TPS score system (cutoff of ≥ 50%) the prevalence of PVR expression is 79%. Using the TPS system, higher PVR expression was associated with poor prognosis and advanced stage (P=0.046,

and P=0.045). PVR expression also as evaluated with the TPS score system was correlated with large tumor diameter (P=0.043) and older age of patients (P=0.046).

Conclusion: PVR was broadly expressed in SCLC cell lines and tumor tissues. High PVR expression was associated with poor prognosis, advanced tumor stage, large tumor diameter, and advanced age of patients. We also found that PVR expression may correlate with chemotherapy treatment history in SCLC cell lines. These data suggest that the PVR-TIGIT pathway may be a promising target for immunotherapy in SCLC.

Citation Format: Hui Yu, Camilla Koczara, Andrzej Badzio, Dexiang Gao, Christopher J. Rivard, Kim Ellison, Kenichi Suda, Shengxiang Ren, Charles Caldwell, Kristine A. Brovsky, Leslie Rozeboom, Fred R. Hirsch. Expression of an immune checkpoint- Poliovirus Receptor (PVR) in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3637.

A miRNA Panel Predicts Sensitivity of FGFR Inhibitor in Lung Cancer Cell Lines

PURPOSE

To test whether a microRNA (miRNA) panel may serve as an alternative biomarker of fibroblast growth factor receptor (FGFR) tyrosine kinase inhibitor sensitivity in lung cancer.

METHODS

Histologically diverse lung cancer cell lines were submitted to assays for ponatinib and AZD4547 sensitivity. miRNAs, FGFR1 messenger RNA, gene copy number, and protein expression were detected by real-time quantitative PCR, fluorescence in-situ hybridization, and immunoblotting in 34 lung cancer cell lines.

RESULTS

Among 34 cell lines, 14 exhibited ponatinib sensitivity and 20 exhibited AZD4547 sensitivity (drug concentration causing 50% inhibition values < 100 nmol/L). A total of 39 of the 377-miRNA set were initially identified from the 4 paired ponatinib-sensitive or -insensitive cell lines to have at least an 8-fold differential expression and then were detected in all the 34 cell lines. A predictive panel of 3 miRNAs (let-7c, miRNA155, and miRNA218) was developed that had an area under the curve (AUC) of 0.886 with a sensitivity of 71.4% and specificity of 77.3% to predict response to ponatinib. The miRNA panel performed similar to FGFR1 protein expression (AUC = 0.864) and messenger RNA expression (AUC = 0.939), and better than FGFR1 amplification (AUC = 0.696). Furthermore, we validated this panel using data for sensitivity to AZD4547 in the cell line cohort with an AUC of 0.931 and a sensitivity of 73.3% and specificity of 76.2%, respectively.

CONCLUSION

The developed miRNA panel (let-7c, miRNA155, and miRNA218) may be useful in predicting response to FGFR tyrosine kinase inhibitors, either ponatinib or AZD4547 in lung cancer cell lines, and warrants further validation in the clinical setting.

Identification and Validation of a PD-L1 Binding Peptide for Determination of PDL1 Expression in Tumors

Blocking the interaction between Programmed Death Ligand 1 (PD-L1) and its receptor, PD-1, is an effective method of treating many types of cancers. Certain tumors overexpress PD-L1, causing host immune cells that express PD-1 to bind PD-L1 and cease killing the tumor. Inhibition of PD-L1 and PD-1 binding can restore host immunity towards tumor killing, and many new drugs have been developed to target this interaction. Current methods of PD-L1 diagnosis have shown to vary based on the antibody, detection kit brand, antigen retrieval method, and clinically defined methods by the FDA. To refine detection of PD-L1, we have identified a peptide, RK-10, and used it to detect PD-L1 expressing tumors with immunohistochemistry or flow cytometry. Flow cytometry was performed on cell lines and patient tissues using a fluorescent peptide (RK-10-Cy5). Immunohistochemistry using a biotin-modified peptide (RK-10-Biotin) was tested against the FDA-approved SP263 clone on biopsied patient tissues. For this study, we evaluated specificity of RK-10 using IHC in over 200 patient tissues, including NSCLC and Hodgkin's Lymphoma. RK-10 shows staining in the tumor regions of FFPE tissues where the SP263 kit does not. RK-10-Cy5 peptide also demonstrates PD-L1 detection in NSCLC, breast, squamous cell carcinoma, and melanoma.

Invariant natural killer T (iNKT) cells prevent autoimmunity, but induce pulmonary inflammation in cystic fibrosis

BACKGROUND/AIMS

Inflammation is a major and critical component of the lung pathology in the hereditary disease cystic fibrosis. The molecular mechanisms of chronic inflammation in cystic fibrosis require definition.

METHODS

We used several genetic mouse models to test a role of iNKT cells and ceramide in pulmonary inflammation of cystic fibrosis mice. Inflammation was determined by the pulmonary cytokine profil and the abundance of inflammatory cells in the lung.

RESULTS

Here we provide a new concept how inflammation in the lung of individuals with cystic fibrosis is initiated. We show that in cystic fibrosis mice the mutation in the Cftr gene provokes a significant up-regulation of iNKT cells in the lung. Accumulation of iNKT cells serves to control autoimmune disease, which is triggered by a ceramide-mediated induction of cell death in CF organs. Autoimmunity becomes in particular overt in cystic fibrosis mice lacking iNKT cells and although suppression of the autoimmune response by iNKT cells is beneficial, IL-17(+) iNKT cells attract macrophages and neutrophils to CF lungs resulting in chronic inflammation. Genetic deletion of iNKT cells in cystic fibrosis mice prevents inflammation in CF lungs.

CONCLUSION

Our data demonstrate an important function of iNKT cells in the chronic inflammation affecting cystic fibrosis lungs. iNKT cells suppress the auto-immune response induced by ceramide-mediated death of epithelial cells in CF lungs, but also induce a chronic pulmonary inflammation.

Genome-wide DNA methylation analysis reveals novel epigenetic changes in chronic lymphocytic leukemia

We conducted a genome-wide DNA methylation analysis in CD19 (+) B-cells from chronic lymphocytic leukemia (CLL) patients and normal control samples using reduced representation bisulfite sequencing (RRBS). The methylation status of 1.8-2.3 million CpGs in the CLL genome was determined; about 45% of these CpGs were located in more than 23,000 CpG islands (CGIs). While global CpG methylation was similar between CLL and normal B-cells, 1764 gene promoters were identified as being differentially methylated in at least one CLL sample when compared with normal B-cell samples. Nineteen percent of the differentially methylated genes were involved in transcriptional regulation. Aberrant hypermethylation was found in all HOX gene clusters and a significant number of WNT signaling pathway genes. Hypomethylation occurred more frequently in the gene body including introns, exons, and 3'-UTRs in CLL. The NFATc1 P2 promoter and first intron was found to be hypomethylated and correlated with upregulation of both NFATc1 RNA and protein expression levels in CLL suggesting that an epigenetic mechanism is involved in the constitutive activation of NFAT activity in CLL cells. This comprehensive DNA methylation analysis will further our understanding of the epigenetic contribution to cellular dysfunction in CLL.

A pathologist-in-the-loop IHC antibody test selection using the entropy-based probabilistic method

Background:

Immunohistochemistry (IHC) is an important tool to identify and quantify expression of certain proteins (antigens) to gain insights into the molecular processes in a diseased tissue. However, it is a challenge for pathologists to remember the discriminative characteristics of the growing number of such antigens across multiple diseases. The complexity of their expression patterns, fueled by continuous discoveries in molecular pathology, gives rise to a combinatorial explosion that places an unprecedented burden on a practicing pathologist and therefore increases cost and variability of IHC studies.

Materials and Methods:

To tackle these issues, we have developed antibody test optimized selection method, a novel informatics tool to help pathologists in improving the IHC antibody selection process. The method uses extensions of Shannon's information entropies and Bayesian probabilities to dynamically build an efficient diagnostic tree.

Results:

A comparative analysis of our method with the expert and World Health Organization classification guidelines showed that the proposed method brings threefold reduction in number of antibody tests required to reach a diagnostic conclusion.

Conclusion:

The developed method can significantly streamline the antibody test selection process, decrease associated costs and reduce inter- and intrapathologist variability in IHC decision-making.

Combined liver kidney transplantation: critical analysis of a single-center experience

Combined liver kidney transplantation (LKT) can be successfully performed on patients with liver and renal failure; however, outcomes are inferior to liver transplantation alone (OLT). Our aim was to determine the indications for and outcome of LKT and whether patients with longer wait times required more frequent LKT versus OLT alone. We included 18/93 adults who underwent LKT from August 2007 to August 2010 for hepatitis C virus (HCV, n = 7), alcohol (n = 5), nonalcoholic steatohepatitis (n = 2), primary biliary sclerosis, polycystic kidney disease with liver involvement, hepatic adenomatosis, and ischemic hepatitis. Eleven were originally listed for LKT and 7 required listing for-kidney transplantation while awaiting OLT. Eight were on dialysis when first listed and 10 had a low glomerular filtration rate or known kidney disease. The mean calculated Model for End-Stage Liver Disease (MELD) score for LKT was 31.2 ± 3.54. Seven had hepatocellular carcinoma in explants. Two patients had acute cellular kidney rejection that responded to treatment. Recurrence of HCV was documented in 5 patients within 6 months of LKT; 2/5 received HCV therapy (interferon and ribavirin) without renal allograft rejection. One-year liver graft/patient survival was 94% after LKT. One patient died at 6 months post LKT due to severe HCV recurrence. Last mean serum creatinine level was 1.35 ± 0.28 mg/dL for LKT patients. LKT is a safe procedure with favorable outcomes even in patients with a high MELD score. Transplantation of patients with a high MELD score due to regional variations in organ allocation results in additional use of kidneys by OLT patients. Improved organ allocation algorithms in OLT would help to reduce combined transplants, sparing more kidneys.

Abstract 168: Genome-wide survey of CpG methylation across the spectrum of B-cell lymphomas

Introduction: An international consortium was established to create comprehensive methylomes of B-cell lymphoma cell lines representing multiple stages of B-cell differentiation. One of the consortium's long-term goals is to identify genes and pathways that are perturbed by methylation in these cell lines either individually, or wholly, so that this information may be utilized to identify novel targets of aberrant methylation in patient samples.

Experimental procedures: The B-cell derived tumor cell lines included in this study represent the spectrum of B-cell development: chronic lymphocytic leukemia (Mec1); mantle cell lymphoma (Granta); diffuse large B-cell lymphoma (Val and Ly10); follicular lymphoma (RL); Burkitt's lymphoma (Raji); and multiple myeloma (U266B1).

Three methods were employed in this study: 1) Methylated CpG island amplification (MCA) and Agilent CpG island arrays; 2) HpaII tiny fragment enrichment by ligation-mediated PCR (HELP) and Agilent CpG island arrays; and 3) Bisulfite treatment in conjunction with the Illumina Infinium Methylation BeadChip.

Data summary: Comprehensive genome-wide methylation profiles were constructed for each tumor cell line using the data generated from three different methods. The number of detected differentially methylated probes, genes and gene promoters differed for each method. The number of unique methylated genes identified ranged from 25 for Granta to more than 200 for U266B1. Recurrent aberrant methylation was detected in ∼100 genes in all seven cell lines included in this study. Methylation of key miRNAs was identified in each of the cell lines.

Gene lists that included genes with promoter methylation were submitted to the database for annotation, visualization and integrated discovery (DAVID) to identify enriched functional-related gene groups. Cell differentiation, transcription factor activity and HOX were among the top three functionally enriched gene groups in all cell lines. Genes associated with the Wnt, MAPK and Hedgehog pathways were also enriched in select cell lines.

Conclusions: All approaches suffer from limitations in their ability to detect methylated sequences. The probes assayed on the Agilent CpG island array are limited to sequences that are contained within the restriction fragments produced in the MCA and HELP assays. The MCA method relies on the co-hybridization of a sample of interest to a “normal control” which may introduce biases if the “proper” control is not used. Finally, the Illumina Infinium BeadChip assays, on average, only 2 probes per gene and is the least informative of the detection assays. Despite these shortcomings, the combination of the data generated by each method has allowed the identification of novel genes and pathways that can be used to design screening assays for large numbers of patient samples.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 168.