Abstract 3283: GEN1046 (DuoBody®-PD-L1x4-1BB) in combination with PD-1 blockade potentiates anti-tumor immunity

GEN1046 (DuoBody®-PD-L1x4-1BB) is an investigational, potential first-in-class bispecific immunomodulatory antibody designed to elicit an anti-tumor immune response by simultaneous and complementary blockade of PD-L1 on tumor or immune cells and conditional 4-1BB stimulation on T cells and NK cells. Previously, we described encouraging preclinical and early clinical activity of GEN1046 (Muik, et al., 2022, Cancer Discovery). We hypothesized that combining GEN1046 with PD-1 blockade would further potentiate anti-tumor activity through distinct and complementary immune modulatory effects. Addition of an anti-PD-1 agent would free up PD-L1 for binding to GEN1046, thus promoting PD-L1-dependent 4-1BB conditional agonism, while maintaining complete blockade of the PD-1 pathway by inhibiting interactions with both PD-L1 and PD-L2. ​Here we provide preclinical evidence supportive of therapeutic synergy by the combination of GEN1046 and anti-PD-1 and describe the mechanisms of enhanced anti-tumor immunity elicited by the combination. In in vitro studies, combining GEN1046 with an anti-PD-1 agent potentiated cytokine release in mixed lymphocyte reaction assays (using either unstimulated T cells or T cells exhausted by repeated CD3/CD28 co-stimulation) and enhanced T-cell expansion and cytokine secretion in antigen-specific proliferation assays compared to each single agent. In in vivo studies in mice bearing syngeneic subcutaneous MC38 tumors, the combination of an anti-mouse PD-L1x4-1BB bispecific antibody with anti-mouse PD-1 potentiated anti-tumor activity with significant enhancement of survival (P≤0.001) and durable, complete tumor regressions (CR) in 7/10 mice compared to no CR observed with either single agent, suggesting therapeutic synergy with the combination. The combination treatment elicited long-lasting immune memory response, as animals with CR were protected from tumor outgrowth upon rechallenge with MC38 cells. Mechanistically, animals treated with the combination showed a trend for ≥1.5-fold increase in the average density of CD3+ and CD4+ tumor-infiltrating lymphocytes (TILs), as well as proliferating (Ki67+) and cytotoxic (GZMB+) CD8+ TILs relative to each single agent, consistent with an amplified anti-tumor immune response. Together, these preclinical results suggest that combining GEN1046-induced conditional 4-1BB stimulation with complete PD-1 blockade can improve the anti-tumor immune response via distinct and complementary immune modulatory effects. The combination of GEN1046 with pembrolizumab is currently being investigated in ongoing clinical studies in patients with advanced NSCLC, who are treatment-naïve (NCT03917381) or have progressed on prior CPI-containing therapy (NCT05117242).

Citation Format: Michela Capello, Angelica Sette, Theo Plantinga, Vanessa Spires, Kristina Nuermberger, Jordan Blum, Alexander Muik, Carol Costa Sa, Omar Jabado, Saskia Burm, Aras Toker, Sina Fellermeier-Kopf, Tahi Ahmadi, Brandon Higgs, Suzana Couto, Özlem Türeci, Mark Fereshteh, Ugur Sahin, Maria Jure-Kunkel, Nora Pencheva. GEN1046 (DuoBody®-PD-L1x4-1BB) in combination with PD-1 blockade potentiates anti-tumor immunity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3283.

Abstract 3248: Pharmacodynamic activity of epcoritamab (GEN3013; CD3xCD20) as monotherapy is maintained in combination with standard of care therapies in patients with diffuse large B-cell lymphoma

Introduction: B-cell lymphoma is a heterogeneous disease with an unmet medical need for efficacious, well tolerated, off-the-shelf therapies that can combine with standard of care (SOC) regimens. Epcoritamab is an IgG1 bispecific antibody that simultaneously binds to CD3 on T cells and CD20 on malignant B cells, inducing activation and cytotoxic activity of T cells and enabling killing of target lymphoma cells. Epcoritamab is well suited for combination therapy due to its distinct mechanism of action from that of many SOC regimens that may lead to improved clinical responses. Herein we evaluated the longitudinal pharmacodynamic (PD) effects of epcoritamab in clinical trial patients with diffuse large B-cell lymphoma (DLBCL) treated as monotherapy (EPCORE NHL-1: NCT03625037) and in combination with SOC therapies (EPCORE NHL-2: NCT04663347).

Methods: Patients with relapsed/refractory (R/R) DLBCL from EPCORE NHL-1 expansion phase received subcutaneous epcoritamab administered in 28-d cycles. Patients with newly diagnosed or R/R DLBCL from EPCORE NHL-2 received epcoritamab administered with a dosing schedule similar to that in EPCORE NHL-1, in combination with SOC therapies: R-CHOP, R-DHAX/C and GemOx. Biomarkers in fresh whole blood were assessed using validated flow cytometry assays. Cytokine levels in plasma were tested using a validated multiplex immunoassay.

Results: Epcoritamab monotherapy induced rapid (within the first cycle), sustained depletion of circulating peripheral B cells (CD19+) in patients with detectable peripheral B cells at baseline. A similar pattern of peripheral B-cell depletion was observed for epcoritamab in combination with SOC. Approximately 24 h following the first full dose, epcoritamab monotherapy induced a moderate but transient elevation of circulating cytokines IFNγ, IL-6 and IL-10. These cytokine patterns were similar for epcoritamab in combination with SOC. Within the first 8 wk of dosing, both epcoritamab monotherapy and in combination with SOC induced a transient elevation of percentages of peripheral CD8+ T cells expressing proliferation (Ki67) and activation (HLA-DR) markers. Expansion of peripheral CD8+ T cells and their effector memory subsets was observed with epcoritamab monotherapy, as well as in combination with SOC in later cycles. Peripheral CD4+ T cells demonstrated patterns similar to most of the biomarker observations in CD8+ T cells with epcoritamab as monotherapy and in combination.

Conclusion: These biomarker analyses show that the PD characteristics of epcoritamab monotherapy are maintained overall in combination with SOC therapies containing chemotherapeutic agents with or without rituximab and support the ongoing clinical studies investigating the combination of epcoritamab with SOC therapies in patients with DLBCL.

Citation Format: Jimin Zhang, Han Si, Monica Wielgos-Bonvallet, David Soong, Edith Szafer-Glusman, Herve Ghesquieres, Chan Y. Cheah, Lorenzo Falchi, Joshua Brody, Mariana Sacchi, Ali Rana, Brandon Higgs, Brian Elliot, Maria Jure-Kunkel, Christopher W. Chiu. Pharmacodynamic activity of epcoritamab (GEN3013; CD3xCD20) as monotherapy is maintained in combination with standard of care therapies in patients with diffuse large B-cell lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3248.

Abstract 459: Identification of the PDAC immunogenic subtype using deep learning with multi-scaled digital H&E images

Background: Pancreatic ductal adenocarcinoma (PDAC) has proven a difficult cancer to treat. To improve treatment strategies, molecular subtypes have been identified, one being immunogenic with significant immune infiltrate and better prognosis. These subtypes have been determined by RNA profiling, which often exhibits technical challenges in a clinical setting. Here we present a deep learning-based method to identify PDAC immunogenic patients using H&E images. This method is robust to RNA quality issues and can elucidate unique morphological features not obtainable with RNA profiling to refine the selection of patients with this phenotype.

Methods: Patients (n=265) were primarily stage II or IV, treated previously with gemcitabine+nab-paclitaxel or FOLFIRINOX. Ground truth for immunogenic subtype (n=105) was defined with RNASeq. Whole slide images were subdivided into non-overlapping, fixed-size tiles at 4 magnifications: 2.5x, 5x, 10x, 20x, followed by feature extraction using a ResNet50 convolutional neural network. Principal component (PC) analysis reduced dimensionality of extracted features in each tile. The dataset was split into 80% training, 20% testing. Posterior probabilities from a linear model were inputs to a support vector machine to predict outcome (2-step model). Progression- free survival (PFS) was evaluated using the Kaplan Meier method.

Results: ImageNet-trained ResNet50 model extracted 2048 features from each tile and the first 75 PCs, explaining 87% variance, were input into the 2-step model; average AUC=0.77 (95% CI=0.70,0.83) across the 4 magnification datasets. A multi-scale ensemble approach combining these 4 magnifications improved the AUC to 0.80 (95% CI=0.66,0.93). Accuracy, sensitivity, and specificity were 0.79, 0.76, and 0.81, respectively. The predicted immunogenic subtype showed significantly improved PFS compared to the other 3 subtypes (HR 95%CI = 0.54 (0.36,0.81), p=0.003), while the RNASeq-derived immunogenic subtype had less differentiation (HR 95%CI = 0.64 (0.42,0.98), p=0.04).

Conclusions: This study presents a deep learning 2-step model approach using tumor H&E images to identify PDAC immunogenic subtype, with improved prognostic potential to that identified by RNA profiling, suggesting possible application in clinical settings for patient stratification. Future work will expand the model to larger independent cohorts.

Citation Format: Han Si, Steven Xu, Anantharaman Muthuswamy, Ryan Liang, Kate Sasser, Hisham K. Hamadeh, Suzana Couto, Brandon Higgs. Identification of the PDAC immunogenic subtype using deep learning with multi-scaled digital H&E images [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 459.

Abstract 5547: EGFR inhibition decreases immunosuppressive cytokines and reduces growth in STK11 mutant NSCLC

Mutations in the tumor suppressor gene STK11 have been associated with innate resistance to immune checkpoint inhibitors in NSCLC. Although this resistance mechanism is not fully defined, previous work has suggested a role for increased infiltration of suppressive immune cells in the tumor microenvironment. We investigated the ability of various treatments to alter immunosuppression associated with STK11 mutations to inform future treatment strategies in NSCLC.

Comparison of STK11 mt and wt cell lines revealed 10-1,000-fold increased levels of the immunosuppressive cytokines IL-6 and IL-8 in STK11 mt lines. STK11 mt lines were treated with inhibitors of clinically actionable pathways (MEKi, ERKi, or EGFRi at 0.001-10 uM) and evaluated for changes in cell growth and cytokine production. Treatment with EGFRi significantly decreased IL-6 and IL-8 (≥25 fold) and inhibited cell growth (2-3 fold decreased IC50) in STK11 mt lines, which is particularly interesting since STK11 mt lines are EGFR wt. Both MEKi and ERKi also reduced cytokine production (≤7 fold for MEKi, ≤2 fold for ERKi), but neither recapitulated the magnitude of the changes observed with EGFRi. Genomic changes associated with increased sensitivity of STK11 mt lines to EGFRi included down-regulation (≥ 1.5-fold) of genes involved in EGFR signaling (BTC), as well as neutrophil and Treg recruitment (CXCL8, PPRB, CXCL1, CCL20). These alterations were associated with a substantial reduction of infiltrating neutrophils in a tumor spheroid model using STK11 mt NSCLC lines treated with EGFRi compared to control (0.8% vs. 13.6%).

The in vitro effects of EGFRi were confirmed in vivo in STK11 mt NSCLC PDX models. Treatment with 100mg/kg of EGFRi led to 30% tumor growth inhibition compared to vehicle control and a decrease (≥1.7 fold) in cytokines (IL-6, IL-8, CXCL1, CXCL5) involved in recruitment of suppressive immune cells by day 13. The effect of this modification in cytokine secretion was an observed decrease (2.2 fold) in the absolute count of mMDSCs in tumors from EGFRi treated mice compared to vehicle control at day 7. A decrease in inflammatory cytokines and MDSCs was also observed with a lower dose of 6.25mg/kg of EGFRi.

Our results suggest that EGFRi decreases cytokines/chemokines responsible for recruiting and maintaining neutrophils and other immunosuppressive cells in the TME of STK11 mt NSCLC. This, combined with the reduced growth of STK11 mt cells, indicate that EGFRi may promote important changes in the TME that could overcome innate resistance to checkpoint inhibition.

Citation Format: Yelena Lazdun, Lydia Greenlees, Song Wu, Nicholas Holoweckyj, Fernanda Pilataxi, Susana Hayes, Brandon Higgs, Katie Streicher. EGFR inhibition decreases immunosuppressive cytokines and reduces growth in STK11 mutant NSCLC [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 5547.

Abstract 2034: Spatial transcriptomics identifies unique pharmacodynamic effects of checkpoint inhibitor treatment on the tumor microenvironment in NSCLC

Background: Immune checkpoint inhibitor (ICI) therapy has improved outcomes in non-small cell lung cancer (NSCLC), particularly in patients with high tumor infiltrating lymphocytes (TILs). Identifying the pharmacodynamic (PD) impact of ICI on immune cells in the tumor microenvironment (TME) can inform therapeutic development for patients with progressive disease. We sought to identify PD changes in the TME from patients before and after ICI therapy using a spatial transcriptomics platform that allows highly multiplexed profiling of 1,800 genes (Nanostring Digital Spatial Profiler [DSP]).

Methods: Formalin fixed, paraffin embedded (FFPE) tumor tissue from 22 patients was sourced commercially. Patients were treated with neoadjuvant chemotherapy, then underwent a surgical tumor resection. After surgery an adjuvant chemotherapy was administered until progression; patients then received monotherapy ICI (nivolumab or pembrolizumab). Once progressed on ICI, another resection was performed. Patients were then treated with chemotherapy and followed until progression and/or death. The DSP technology was used to independently profile RNA from PanCK+ (tumor) and PanCK- (stroma) regions in the tissue based on fluorescence staining. Six circular regions of 600μm in diameter were selected for analysis using the GeoMx instrument; each area contained CD3+ cells. Additionally, immunohistochemistry for PDL1 and CD3 was performed, images were scored by a pathologist and analyzed with digital pathology algorithms.

Results: Spatial transcriptomic analysis of pre- vs post-ICI treatment in stroma revealed significant increases in T cell genes (CD3E, TCRB, NKG7), T-cell activation markers (CD69, IFNG, OX40, GZMB, ICOS), costimulatory signaling (CD28, CD80, CD86), and immune checkpoints (CTLA4, TIGIT). Ayers et al., JCI 2017 identified 28 genes predictive of ICI response, 12 were significantly upregulated in the stroma post-ICI (26 were present in the DSP panel). We identified genes in the pre-ICI stromal microenvironment that were highly expressed in patients with partial response to ICI, the most significant genes were involved in immune regulation (IFIT1) and extracellular matrix remodeling (MMP3). In contrast, stromal genes highly expressed in patients with progressive disease were associated with T-cell maintenance (ETS1, IL7R, CCL19).

Conclusions: In this study we used spatial transcriptomics to profile tissue regions where T-cells were in close proximity to tumor cells (microns). This focused, local PD analysis confirmed activated T-cells are present post-ICI. Ongoing studies in a larger cohort will be used to identify tumoral mechanisms of resistance and immune dysfunction to inform future therapeutics and combinations.

Citation Format: Li Fan, Omar Jabado, Nora Pencheva, Patricia Coutinho de Souza, Brandon Higgs, Angelo Harris, Patrick Franken, Anantharaman Muthuswamy, Maria Jure-Kunkel, Suzana Couto, Kate Sasser, Mark Fereshteh. Spatial transcriptomics identifies unique pharmacodynamic effects of checkpoint inhibitor treatment on the tumor microenvironment in NSCLC [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 2034.

833 A scalable deep learning framework for rapid automated annotation of histologic and morphologic features from large unlabeled pan-cancer H&E datasets

Background

Recent advances in machine learning and digital pathology have enabled a variety of applications including predicting tumor grade and genetic subtypes, quantifying the tumor microenvironment (TME), and identifying prognostic morphological features from H&E whole slide images (WSI). These supervised deep learning models require large quantities of images manually annotated with cellular- and tissue-level details by pathologists, which limits scale and generalizability across cancer types and imaging platforms. Here we propose a semi-supervised deep learning framework that automatically annotates biologically relevant image content from hundreds of solid tumor WSI with minimal pathologist intervention, thus improving quality and speed of analytical workflows aimed at deriving clinically relevant features.

Methods

The dataset consisted of >200 H&E images across >10 solid tumor types (e.g. breast, lung, colorectal, cervical, and urothelial cancers) from advanced disease patients. WSI were first partitioned into small tiles of 128μm for feature extraction using a 50-layer convolutional neural network pre-trained on the ImageNet database. Dimensionality reduction and unsupervised clustering were applied to the resultant embeddings and image clusters were identified with enriched histological and morphological characteristics. A random subset of representative tiles (<0.5% of whole slide tissue areas) from these distinct image clusters was manually reviewed by pathologists and assigned to eight histological and morphological categories: tumor, stroma/connective tissue, necrotic cells, lymphocytes, red blood cells, white blood cells, normal tissue and glass/background. This dataset allowed the development of a multi-label deep neural network to segment morphologically distinct regions and detect/quantify histopathological features in WSI.

Results

As representative image tiles within each image cluster were morphologically similar, expert pathologists were able to assign annotations to multiple images in parallel, effectively at 150 images/hour. Five-fold cross-validation showed average prediction accuracy of 0.93 [0.8–1.0] and area under the curve of 0.90 [0.8–1.0] over the eight image categories. As an extension of this classifier framework, all whole slide H&E images were segmented and composite lymphocyte, stromal, and necrotic content per patient tumor was derived and correlated with estimates by pathologists (p<0.05).

Conclusions

A novel and scalable deep learning framework for annotating and learning H&E features from a large unlabeled WSI dataset across tumor types was developed. This automated approach accurately identified distinct histomorphological features, with significantly reduced labeling time and effort required for pathologists. Further, this classifier framework was extended to annotate regions enriched in lymphocytes, stromal, and necrotic cells – important TME contexture with clinical relevance for patient prognosis and treatment decisions.

915 Molecular characterization of AXL in solid tumor malignancies using real-world data

Background

The receptor tyrosine kinase AXL is aberrantly expressed in many cancer types and associated with epithelial-to-mesenchymal transition (EMT), poor prognosis, and therapy resistance. To better understand the expression of this gene across specific disease subtypes, correlated pathways, and how certain therapies potentially modulate AXL expression, we investigated real-world clinical and molecular data across five solid tumor types before and after chemotherapy or immune checkpoint inhibitor (CPI) therapy.

Methods

Whole transcriptome and exome sequencing were derived from patient tumor specimens obtained either prior to treatment or following chemotherapy or CPI therapies. RNA reads were mapped using STAR and data was normalized using transcripts per million. DNA reads were mapped using Novoalign and variants were called using Freebayes and Pindel. Clinical data was curated from multiple sources, QC’d and deidentified according to standard protocols. Five diseases were included: non-small cell lung cancer (NSCLC, n=1181), ovarian cancer (OV, n=300), urothelial carcinoma (UC, n=140), pancreatic ductal adenocarcinoma (PDAC, n=942), and skin cutaneous melanoma (SKCM, n=157). PD-L1 positivity was defined as ≥1% tumor cells with PD-L1 immunohistochemical staining at any intensity.

Results

AXL mRNA levels were highest in PDAC followed by NSCLC, SKCM, UC and OV. Within OV, AXL expression levels were higher in tumors pre-treated with chemotherapy relative to untreated. For other tumor types, chemotherapy or CPI pre-treated tumors had AXL mRNA levels comparable to untreated tumors. Copy number amplifications of AXL were rare across all tumor types (<3%) and did not associate with mRNA expression. Distinct molecular subtypes in several cancers displayed relatively high AXL mRNA levels, including the mesenchymal subtype in OV and the stromal rich subtypes in PDAC. AXL levels also correlated with an EMT mRNA signature across all tumors (rho=0.67). Further, higher AXL expression was associated with PD-L1 positivity in NSCLC, UC and PDAC (p<0.01), but not OV where only a few tumors were PD-L1 positive.Oncogenic KRAS mutations were associated with higher AXL expression in NSCLC and PDAC (p<0.001) and lower AXL expression in OV (p=0.01). Loss of KDM6A, known to induce tumorigenesis in PDAC, was associated with higher AXL expression in PDAC (p<0.01). Loss-of-function mutations in ARID1A, previously implicated as CPI sensitizing, were associated with lower AXL mRNA levels in OV tumors (p<0.001).

Conclusions

Analyses of real-world mRNA datasets showed that AXL was upregulated in specific tumor and treatment settings as well as in patient populations with specific mutations and disease subtypes. Findings here should be validated with independent datasets.

516 Peripheral and tumoral immune activity in the expansion part of the first-in-human DuoBody®-PD-L1×4–1BB (GEN1046) trial

Background

DuoBody-PD-L1×4-1BB (GEN1046) is a class-defining, bispecific immunotherapy designed to induce an antitumor immune response by simultaneous and complementary PD-L1 blockade and conditional 4-1BB stimulation. Encouraging clinical activity and manageable safety were observed during dose escalation in the ongoing phase 1/2a trial in patients with advanced solid tumors (NCT03917381). We report exploratory pharmacodynamic analyses and potential biomarkers of response in an expansion cohort of patients with PD-(L)1–R/R NSCLC.

Methods

Patients with metastatic/unresectable NSCLC who had multiple lines of prior systemic therapy, including a checkpoint inhibitor, received flat-dose DuoBody-PD-L1×4-1BB (100 mg) intravenously every 3 weeks. Immunophenotyping of peripheral blood and measurements of soluble immune mediators were evaluated in serial blood samples in cycles 1–2. Tumor PD-L1 and 4-1BB expression and additional immune markers were evaluated by immunohistochemistry in core needle tumor biopsy specimens collected before treatment and at cycle 2.

Results

As of May 2021, 40 patients with PD-(L)1–R/R NSCLC were enrolled (median age, 63 years). Treatment with DuoBody-PD-L1×4-1BB elicited pharmacodynamic modulation of immune endpoints within the first 2 cycles. Induction of peripheral IFN-y, CXCL9/10, and expansion of peripheral CD8+ effector memory T cells and activated NK cells were observed starting at cycle 1 (>2-fold from baseline) and maintained or increased through cycle 2. Based on 9 paired tumor biopsy samples, increased PD-L1 and 4-1BB expression and cytotoxic CD8+/GZMB+ cell density were detected following treatment. In a subset of patients with clinical response (n=5 confirmed PRs), a trend of greater induction of IFN-y, CXCL9/10, and activated NK cells was observed vs nonresponders. Disease control rates were higher in patients who had progressed on prior anti–PD-1 therapy within 8 months (64% [16/25]) from the first dose of DuoBody-PD-L1×4-1BB. As expected, among patients with evaluable baseline tumors (n=26), most with any degree of tumor reduction (best change, <0%) harbored PD-L1+ tumors (≥1% tumor positive score; 7/10) and showed close spatial proximity between PD-L1+ and 4-1BB+ cells. Conversely, most patients without any degree of tumor reduction presented with PD-L1− tumors (12/16).

Conclusions

In patients with NSCLC who progressed on PD-(L)1 therapy, DuoBody-PD-L1×4-1BB elicited pharmacodynamic effects consistent with its proposed mechanism of action. Relationships between disease control and PD-L1 tumoral expression, as well as time from last prior anti–PD-1 therapy, were observed. These findings support that patient selection and/or anti–PD-1 combination therapy may lead to improved clinical efficacy. Further analyses are ongoing and updated results will be presented.

Acknowledgements

The authors thank Hrefna Kristin Johannsdottir, Lei Pang, and Kate Sasser at Genmab A/S and Friederike Gieseke at BioNTech SE for their valuable contributions. This trial was funded by Genmab A/S and BioNTech SE.

Trial Registration

NCT03917381

Ethics Approval

This trial is undertaken following full approval of the final protocol, amendments, informed consent form, applicable recruiting materials, and subject compensation programs by the Independent Ethics Committee/Institutional Review Board.

Consent

Written informed consent, in accordance with principles that originated in the Declaration of Helsinki 2013, current ICH guidelines including ICH-GCP E6(R2), applicable regulatory requirements, and sponsor policy, was provided by the patients.

Abstract 3158: Prediction of overall survival in urothelial cancer patients using tumor sizes and baseline risk factors: longitudinal modeling approach for durvalumab and durvalumab + tremelimumab

Background: Durvalumab [D] is a human mAb that binds to PD-L1 and blocks its interaction with PD-1 and CD80. Tremelimumab [T] blocks the inhibitory effects of CTLA-4, and therefore enhances T-cell activation. The objectives of this analysis were to develop a model linking overall survival (OS) to baseline risk factors and changes in tumor size during treatment to identify key factors impacting response to D or D +T.

Methods: The analysis dataset included UC patients from two clinical trials: Study 1108 (D 10 mg/kg Q2W; n=201) and Study 10 (D 20 mg/kg Q4W + T 1 mg/kg Q4W for 4 doses, followed by D 20 mg/kg Q4W alone; n=168). Longitudinal tumor size data were analyzed using a nonlinear mixed effect model with key parameters describing tumor growth, tumor killing, and delay in immune response. Subsequently, a parametric survival model was developed to link baseline risk factors and predicted percent change in tumor size at week 8 to OS.

Results: Tumor kinetic model adequately described the longitudinal tumor size data from UC patients. Baseline tumor size (p&lt;0.01) and PD-L1 status (p&lt;0.01) were identified as significant covariates for tumor killing rate. The most influential factor associated with faster tumor growth was liver metastasis (p&lt;0.01), while higher hemoglobin levels (p&lt;0.01) were associated with decreased tumor growth rate. Based on parametric survival modeling, liver metastasis (~34% decrease in OS, p&lt;0.0001), albumin (~ 1-fold increase in OS per 1g/dL increase, p&lt;0.0001), and percent change in tumor size at week 8 (~52% increase in OS with 30% tumor shrinkage at week 8, p&lt;0.0001) were found to be significant and clinically relevant predictors of OS.

Conclusions: The parametric survival model coupled with tumor kinetic model adequately described clinical outcomes in UC patients treated with D or D+T and enabled identification of key factors potentially impacting response to immune therapy in UC. This approach can be a useful tool for guiding patient selection/enrichment strategies and optimizing trial designs for immuno-oncology (IO) therapies. Further validation and prospective evaluation of this model may be conducted in other IO trials.

Citation Format: Mei Tang, Yu Jiang, Han Si, Yanan Zheng, Chen Gao, Guozhi Gao, Natasha Angra, Shaad Abdullah, Brandon Higgs, Lorin Roskos, Rajesh Narwal. Prediction of overall survival in urothelial cancer patients using tumor sizes and baseline risk factors: longitudinal modeling approach for durvalumab and durvalumab + tremelimumab [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 3158.

Abstract 3245: Durvalumab induces an NK cell response associated with clinical benefit of patients with advanced NSCLC

Introduction: The role of CD8 cells in determining clinical outcome to programmed death ligand-1 (PD-L1) blocking treatments has been well characterized, however, the contribution of NK cells is not well understood. This is partly due to the paucity of NK cell-specific markers that can identify NK cells in the tumor microenvironment (TME). We developed an NK cell-specific transcriptional signature to estimate the NK cell abundance in the TME. This signature, together with NK-chemokines shown to modulate the priming of adaptive immunity1 were investigated in patients with advanced non-small cell lung cancer (NSCLC) treated with a PD-L1 inhibitor, durvalumab.

Methods: Peripheral blood mononuclear cells (PBMCs) and Fluorescence-Activated Cell Sorted (FACS) NK/ CD8 populations from three heathy donors were subjected to single cell RNA sequencing (scRNAseq, 10X Genomics) and transcriptome analysis (Affymetrix), respectively. Fresh frozen tumor biopsies from 97 NSCLC were profiled with RNA sequencing prior to durvalumab treatment; 29 of these had paired tumors procured 29 days following treatment with durvalumab. Kaplan Meier (KM) analyses were performed to identify predictive effects of the NK cell-specific signature. Clinical trial:1108/NCT01693562

Results: Transcripts over-expressed in sorted NK relative to CD8 cells were first identified (p &lt;0.01; fold &gt;3) and intersected with 28 mRNAs up-regulated in the NK cell cluster determined by scRNAseq, providing an 8 gene NK cell-specific transcriptional signature defined as MEDI-NK. MEDI-NK correlated with NK signatures recently described2, and included chemokines shown to induce an effective NK- response1. When evaluated in TCGA, higher expression of MEDI-NK was associated with good prognosis (Overall Survival, OS) of patients with melanoma and breast cancer (p value =0.03 and =0.001, respectively).

At baseline, MEDI-NK was highly correlated with the previously identified IFNγ signature3 and was associated with Progression Free Survival (PFS p value &lt; 0.02) of NSCLC patients treated with durvalumab. Following treatment with durvalumab, the increased expression of MEDI-NK and of additional genes leading to NK-priming of adaptive immunity1 was observed to be associated with patients’ overall survival (OS p value &lt;0.01). Similar findings were not observed prior to durvalumab treatment.

Conclusions: Using single cell analysis, an NK cell-specific signature was developed to better define the role of NK cells in anti-PDL1 therapy. The increased expressions of the NK cell-specific signature and of genes leading to NK-cell priming of adaptive immune response were associated with clinical benefit to durvalumab.

References:

1. Böttcher JP et al, Cell, 2018.

2. Barry KC et al, Nature Medicine, 2018

3. Higgs B et al, Clinical Cancer Res, 2018

Citation Format: Maria Libera Ascierto, Yashaswi Shrestha, Qu Zhang, Jixin Wang, Han Si, Lydia Greenlees, Rebecca Halpin, Ikbel Achour, Zachary Aaron Cooper, Rajiv Raja, Shaad Abdullah, Katie Streicher, Brandon Higgs. Durvalumab induces an NK cell response associated with clinical benefit of patients with advanced NSCLC [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 3245.

Abstract 4186: Syngenomic fingerprint: the biomic characterization of the mouse syngeneic tumor models

The pre-clinical assessment of immuno-oncology (IO) therapies can be enabled by the use of murine syngeneic tumors established in immuno-competent mice. With the aims of selecting relevant models and of minimizing animal experimentation by reducing the number of models tested, the full characterisation of syngeneic models at the transcriptomic and genomic level is a key objective for pre-clinical scientists.

Model characterisation includes global aCGH, exon array analysis and FACS profiling alongside exome sequencing. The model data is undergoing hypothesis free and driven analyses which are already generating valuable insights. Comparison of in vivo tumor samples with their in vitro equivalents has highlighted enrichment for a number of immune pathways; as has the comparison of different tumor lines. The genomic, transcriptomic and ‘proteomic’ model data are being integrated to give a functional output which will act as a ‘Syngenomic Fingerprint’ for each model.

The resulting Syngenomic fingerprints will help pre-clinical scientists to refine their in vivo plans through an improved understanding of the limits and advantages as well as the clinical relevance of some of our preclinical models. It is also supporting the targeted modification of models to better match specific human cancer types.

Citation Format: John E. Prime, Suzanne Mosely, Jens-Oliver Koopmann, Dennis YQ Wang, Danielle Greenawalt, James Harper, Miika J. Ahdesmaki, Rebecca Leyland, Olivia Harris, Ross Stewart, Philip Brohawn, Brandon Higgs, Bryony Langford, Athula Herath, Robert Kozarski, Jane Coates-Ulrichsen, Judith Anderton, Michelle Morrow, Richard C. A Sainson, Robert W. Wilkinson. Syngenomic fingerprint: the biomic characterization of the mouse syngeneic tumor models. [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 4186.

In Vivo Loss of Function Screening Reveals Carbonic Anhydrase IX as a Key Modulator of Tumor Initiating Potential in Primary Pancreatic Tumors

Reprogramming of energy metabolism is one of the emerging hallmarks of cancer. Up-regulation of energy metabolism pathways fuels cell growth and division, a key characteristic of neoplastic disease, and can lead to dependency on specific metabolic pathways. Thus, targeting energy metabolism pathways might offer the opportunity for novel therapeutics. Here, we describe the application of a novel in vivo screening approach for the identification of genes involved in cancer metabolism using a patient-derived pancreatic xenograft model. Lentiviruses expressing short hairpin RNAs (shRNAs) targeting 12 different cell surface protein transporters were separately transduced into the primary pancreatic tumor cells. Transduced cells were pooled and implanted into mice. Tumors were harvested at different times, and the frequency of each shRNA was determined as a measure of which ones prevented tumor growth. Several targets including carbonic anhydrase IX (CAIX), monocarboxylate transporter 4, and anionic amino acid transporter light chain, xc- system (xCT) were identified in these studies and shown to be required for tumor initiation and growth. Interestingly, CAIX was overexpressed in the tumor initiating cell population. CAIX expression alone correlated with a highly tumorigenic subpopulation of cells. Furthermore, CAIX expression was essential for tumor initiation because shRNA knockdown eliminated the ability of cells to grow in vivo. To the best of our knowledge, this is the first parallel in vivo assessment of multiple novel oncology target genes using a patient-derived pancreatic tumor model.

Abstract 1109: In vivo loss of function screening reveals carbonic anhydrase IX (CAIX) as a key modulator of tumor initiating potential in primary pancreatic tumors

Re-programming of energy metabolism is one of the emerging hallmarks of cancer. Upregulation of energy metabolism pathways fuels cell growth and division, a key characteristic of neoplastic disease, and can lead to dependency on specific metabolic pathways. Thus targeting energy metabolism pathways might offer the opportunity for novel therapeutics. Here we describe the application of a novel in vivo screening approach for the identification of genes involved in cancer metabolism using a patient derived pancreatic xenograft model. Lenti-viruses expressing shRNAs targeting twelve different cell surface protein transporters were separately transduced into the primary pancreatic tumor cells. Transduced cells were pooled and implanted into mice. Tumors were harvested at different times and the frequency of each shRNA was determined as a measure of which ones prevented tumor growth. Several targets including CAIX, MCT4, and xCT were identified in these studies and shown to be required for tumor initiation and growth. Interestingly, CAIX was overexpressed in the tumor initiating cell population. CAIX expression alone correlated with a highly tumorigenic subpopulation of cells. Furthermore, CAIX expression was essential for tumor initiation since shRNA knockdown eliminated the ability of cells to grow in vivo. To the best of our knowledge, this is the first parallel in vivo assessment of multiple novel oncology target genes using a patient derived pancreatic tumor model.

Citation Format: Nabendu Pore, Sanjoo Jalla, Brandon Higgs, Roger Liu, David A. Tice, Robert Hollingsworrth, Emil Michelotti, Claudio Sorio, Aldo Scarpa. In vivo loss of function screening reveals carbonic anhydrase IX (CAIX) as a key modulator of tumor initiating potential in primary pancreatic tumors. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1109. doi:10.1158/1538-7445.AM2015-1109

Abstract 4954: Serine/arginine splicing factor 1 (SRSF1) mediates DNA repair and chemo-sensitivity and drives growth in small cell lung cancer

Small cell lung cancer (SCLC) is the most aggressive subtype of lung cancer. Despite a high response rate to chemotherapy, more than 95% of patients eventually die from SCLC. We have identified that Serine/Arginine Splicing Factor 1 (SRSF1) DNA copy number gain and mRNA over-expression in tumor is strongly associated with poor survival based on whole exome sequencing (WES) and transcriptomic sequencing of primary tumors from 99 Chinese SCLC patients. Here, SRSF1 is evaluated as a tumor driver in SCLC. Treatment of SCLC cell lines in vitro with a low dose of cisplatin or topotecan (two of the most common standard of care in SCLC) only induced a modest decrease of cell growth. However, knockdown of SRSF1 with siRNA along with a sub-lethal dose of cisplatin or topotecan enhanced the overall growth inhibition effect compared to the chemotherapy alone. SRSF1 siRNA alone induced modest but significant caspase-3 activation, similar to cisplatin or topotecan treatment alone. The combination of SRSF1 siRNA with chemotherapy treatments produced a significantly higher caspase induction. DNA-damage induction as a potential mechanism of SRSF1 knockdown was assessed. Phosphorylation of H2AX and Chk2, established markers of DNA-strand breaks and DNA-repair response, was consistently induced upon SRSF1 abrogation in cells, and further increased the phosphorylation of these proteins when combined with cisplatin or topotecan treatment. The knockdown of SRSF1 in SCLC cells also resulted in significant growth inhibition when cells were grown as 3D spheroids. Cells transfected with non-targeting siRNA produced large and well-organized spheroids; in contrast, cells transfected with SRSF1 siRNA did not form well-organized structures but mainly existed as single cells with poor viability. Results were confirmed by colony formation assays and could be rescued with a siRNA-resistant SRSF1 expression construct. Finally, we investigated the impact of SRSF1 loss on kinase signaling pathways in SCLC cells through phospho-kinase array profiling. Strong phospho-AKT and ERK signals were observed in control siRNA-transfected cells, and were abrogated by SRSF1 siRNA. Western blot confirmed this in several SCLC cell lines. These targeting studies demonstrate that SRSF1 plays a key role in DNA repair, chemo-sensitivity and cell proliferation. Together, these data reveal SRSF1 as a therapeutic target in SCLC and provide a rationale for personalized therapy in SCLC.

Citation Format: Sarah J. Conley, Xin Yao, Jiaqi Huang, Brandon Higgs, Zhibin Hu, Zhan Xiao, Haihong Zhong, Zheng Liu, Philip Brohawn, Xiaoxiao Ge, Meggan Czapiga, Vaheh Oganesyan, Haihua Fu, David Tice, Ronald Herbst, Xinying Su, Yi Gu, Jianren Gu, Baohui Han, Laura Richman, Bahija Jallal, Liyan Jiang, Hongbing Shen, Yihong Yao. Serine/arginine splicing factor 1 (SRSF1) mediates DNA repair and chemo-sensitivity and drives growth in small cell lung cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4954. doi:10.1158/1538-7445.AM2015-4954

Abstract 2377: Low frequency KRAS mutations in colorectal cancer patients and the presence of multiple mutations in oncogenic drivers in non-small cell lung cancer patients

Intratumor heterogeneity can confound the results of mutation analyses in oncodriver genes using traditional methods thereby challenging the application of targeted cancer therapy strategies for patients. Ultradeep sequencing can detect low frequency and expanded clonal mutations in primary tumors to better inform treatment decisions. KRAS coding exons in 61 treatment-naïve colorectal cancer (CRC) tumors and KRAS, EGFR, ALK, and MET in lung tumors from three Chinese non-small cell lung cancer (NSCLC) patients were sequenced using ultradeep sequencing methods. Forty-one percent of CRC patients (25/61) harbored mutations in the KRAS active domain, eight of which (13%) were not detected by Sanger sequencing. Three (of eight) had frequencies less than 10% and one patient harbored more than one mutation. Low frequency KRAS active (G12R) and EGFR kinase domain mutations (G719A) were identified in one NSCLC patient. A second NSCLC patient showed an EML4-ALK fusion with ALK, EGFR, and MET mutations. A third NSCLC patient harbored multiple low frequency mutations in KRAS, EGFR, and MET as well as ALK gene copy number increases. Within the same patient, multiple low frequency mutations occurred within a gene. A complex pattern of intrinsic low frequency driver mutations in well-known tumor oncogenes may exist prior to treatment, resulting in resistance to targeted therapies. Current targeted cancer therapies usually lack durability and demonstrate limited overall efficacy in patients. The types of low frequency concurrent mutations in candidate oncogenes presented here suggest necessary modifications both to methods for detection of these variants and to general treatment strategies. To date, Sanger sequencing has been effectively used for detection of treatment-relevant somatic mutations. However, in a heterogeneous mixture of cancerous and normal tissue, Sanger sequencing will likely fail to detect low frequency mutations. More sensitive and cost-effective sequencing methods are required to systematically assess the mutation status within cancer pathway genes or at the whole genome level. Furthermore, because patients often develop resistance to targeted therapy over time that is due to the preexistence of low frequency mutations in oncogenes, treatment strategies based on combination therapy might prove to be the most optimal treatment approach for cancer patients. Ultradeep sequencing can characterize intratumor heterogeneity and identify such mutations to ultimately affect treatment decisions.

Citation Format: Christopher Morehouse, Liyan Jiang, Jiagi Huang, Wei Zhu, Susana Korolevich, Xiaoxiao Ge, Kim Lehmann, Zheng Lui, Christine Kiefer, Meggan Czapiga, Xinying Su, Philip Brohawn, Yi Gu, Brandon Higgs, Yihong Yao. Low frequency KRAS mutations in colorectal cancer patients and the presence of multiple mutations in oncogenic drivers in non-small cell lung cancer patients. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2377. doi:10.1158/1538-7445.AM2014-2377

Right heart pressures in acute myocardial infarction

Images