Background: MEDI0680 is a humanized anti-programmed cell death-1 (PD-1) antibody and durvalumab is an anti-PD-L1 antibody. Combining treatment using these antibodies may improve efficacy versus blockade of PD-1 alone. This phase 2 study evaluated antitumor activity and safety of MEDI0680 plus durvalumab versus nivolumab monotherapy in immunotherapy naïve patients with advanced clear cell renal cell carcinoma who received at least one prior line of anti-angiogenic therapy. Methods: Patients received either MEDI0680 (20 mg/kg) with durvalumab (750 mg) or nivolumab (240 mg), all IV Q2W. The primary endpoint was investigator-assessed objective response rate (ORR). Secondary endpoints included best overall response, progression-free survival (PFS), safety, overall survival (OS), and immunogenicity. Exploratory endpoints included changes in circulating tumor DNA (ctDNA), baseline tumor mutational burden (TMB), and tumor-infiltrated immune cell profiles. Results: Sixty-three patients were randomized (combination, n = 42; nivolumab, n = 21). ORR was 16.7% (7/42; 95% CI, 7.0-31.4) with combination treatment and 23.8% (5/21; 95% CI, 8.2- 47.2) with nivolumab. Median PFS was 3.6 months in both arms; median OS was not reached in either arm. Due to AEs, 23.8% of patients discontinued MEDI0680 and durvalumab and 14.3% of patients discontinued nivolumab. In the combination arm, reduction in ctDNA fraction was associated with longer PFS. ctDNA mutational analysis did not demonstrate an association with response in either arm. Tumor-infiltrated immune profiles showed an association between immune cell activation and response in the combination arm. Conclusions: MEDI0680 combined with durvalumab was safe and tolerable; however, it did not improve efficacy versus nivolumab monotherapy.

BackgroundThe pathologist’s visual assessment of tumor proportion score (TPS) with 25% cutoff on PD-L1 stained tissue samples is an established method to select metastatic NSCLC patients that are likely to respond to an anti-PD-L1 monotherapy.1 However, manual scoring is often subject to subjectivity in human perception2 and there remains a critical need for more objective and quantitative methods to assess PD-L1 expression in immuno-oncology.MethodsWe used deep learning (DL) based image analysis (IA) to generate a novel PD-L1 Quantitative Continuous Score (QCS)3 in tumor cells. PD-L1 QCS consists of two DL models to first segment epithelial regions and second detect membranes, cytoplasm and nuclei of each tumor cell in PD-L1 immunohistochemically (IHC) stained tissue slides. The PD-L1 expression of each tumor cell compartment was estimated by the respective optical density (OD) of DAB, and tumor cells with a membrane OD greater than ODmin are considered as PD-L1-positive. A slide comprising at greater percentage of PD-L1-positive tumor cells than a cutoff value (CoV) is considered QCS-positive. The ODmin and CoV parameters were linked to patient overall survival (OS), by minimizing the Kaplan Meier log-rank p-values and keeping at least 50% prevalence in the QCS-positive subgroup.Fully supervised QCS-IA models were extensively trained using pathologists’ annotations and the performance was validated on unseen data to ensure its generalization and robustness.3 4 The QCS IA was locked and blindly applied on clinical trial data (NCT01693562, durvalumab-treated late-stage NSCLC cohort) without further refinement.ResultsData analytics techniques were used to determine optimal PD-L1 QCS parameters for the clinical trial cohort of N=162 late-stage NSCLC patients. A PD-L1 QCS algorithm (ODmin=8, CoV=57%) is able to stratify durvalumab-treated NSCLC patients at a higher prevalence and more significant log rank p-value (64%, p=0.0001) for OS (figure 1) compared to pathologist TPS (59%, p=0.01). Median OS times of (19.2 months vs 7.9 months) was observed in the QCS-positive vs negative subgroups, respectively. The box plots (figure 2) indicate an overall good agreement (72% concordance) of the fully automated QCS with the pathologists TPS, which quantitatively supports the positive visual assessment of the cell segmentation accuracy.Abstract 365 Figure 1Kaplan Meier (KM) curves for OS stratification. KM curves for Overall Survival (OS) stratification with (left) manual PD-L1 TPS score (25% cutoff), and (right) automated QCS (57% cutoff).Abstract 365 Figure 2QCS scores within TPS positive and negative groups. Box plot indicating percent positive cells (OD≥8) as measured by PD-L1 QCS within the PD-L1 high (red) and low (blue) groups as per pathologist assessment by TPS.ConclusionsThe novel Quantitative Continuous Scoring (QCS) provides an objective way of correlating a quantitative estimate of PD-L1 IHC expression on tumor cells with survival of durvalumab-treated NSCLC patients. This data establishes a first proof-of-concept demonstrating the potential utility of PD-L1 QCS towards precision medicine in immuno-oncology.ReferencesRebelatto M, et al. Development of a programmed cell death ligand-1 immunohistochemical assay validated for analysis of non-small cell lung cancer and head and neck squamous cell carcinoma. Diagnostic Pathology 2016.Tsao M S, et al. PD-L1 immunohistochemistry comparability study in real-life clinical samples: results of blueprint phase 2 project. Journal of Thoracic Oncology 2018.Gustavson M, et al. Novel approach to HER2 quantification: digital pathology coupled with AI-based image and data analysis delivers objective and quantitative HER2 expression analysis for enrichment of responders to trastuzumab deruxtecan (T-DXd; DS-8201), specifically in HER2-low patients. (2021) DOI: 10.1158/1538-7445.SABCS20-PD6-01Kapil A, et al. Domain adaptation-based deep learning for automated tumor cell (TC) scoring and survival analysis on PD-L1 stained tissue images. IEEE Transactions on Medical Imaging DOI: 10.1109/TMI.2021.3081396Ethics ApprovalClinical study NCT01693562, from which data in this report were obtained, was carried out in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines. The study protocol, amendments, and participant informed consent document were approved by the appropriate institutional review boards.

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Introduction: Predictive biomarkers of anti‒PD-(L)1 therapies have largely focused on the tumor - T cell axis where tumor cell PD-L1 expression has demonstrated its clinical utility in predicting overall survival (OS) in patients with advanced non-small cell lung cancer (NSCLC). Although, other immune cell subsets were shown to be associated with clinical efficacy, their relative impact and combined effect in predicting improved long-term survival warrant further investigation. Using computational image analysis of multiplex immunofluorescence (mIF) and immunohistochemistry (IHC) immune marker panels, we sought to identify single and combined biomarkers of the tumor immune contexture in association with long-term OS in advanced NSCLC patients treated with Durvalumab. Methods: Pre-treatment tumor samples from advanced NSCLC patients (n = 210) enrolled in durvalumab nonrandomized phase 1/2 trial (10 mg/kg Q2W, CP1108/NCT01693562), were stained using IHC and 6-marker mIF panels to detect markers of immune cells, cell functional state and tertiary lymphoid structure (TLS) (PD-L1, CD8, PD-1, Ki67, CD68, CD20, CD1c, NKp46, CD66b, ICOS, FOXP3). Cell marker density (cells/mm2), distribution and proximity were quantified and analyzed in association with overall survival. Results: Computational image analysis of the tumor immune contexture revealed a greater immune inflamed phenotype, both innate (macrophages, dendritic cells) and adaptive (T and B cells), in NSCLC patients with long OS >2 years compared to those with short OS < 1 year (fold change > 2, p < 0.0001). Patient subgroup with high density of individual immune subsets show a median OS (mOS) of 10-20 months (p < 0.01 high vs. low subgroups) while combined markers of innate and adaptive immune cells show an improved mOS > 2 years (p < 0.001). Specifically, among the key findings, combined biomarkers of CD68+ PD-L1+ macrophages and CD8+ T cells predicts for a significant increase in OS for patients with high vs low marker density (HR = 0.21, 95%CI 0.12 - 0.39, p <10-7; mOS 39.5 months [high], 6.5 months [low]). Whereas, in patients with high density of either single biomarkers CD68+ PD-L1+ macrophage or CD8+ T cells mOS is 20.2 or 18.4 months respectively. Moreover, high density of CD20+ B cells, reflective of presence of TLS, associates with improved OS (mOS NR [high], 11 months [low], p = 0.003). In addition, TLS enriched tumors show an increased level of macrophages expressing PD-L1 in synapsis with CD8+ T cells (activated PD1+ or proliferative Ki67+ T cells). Conclusion: These findings demonstrate the importance of both tertiary lymphoid structure and high pre-existing innate-adaptive immunity in driving long-term overall survival of durvalumab-treated patients with NSCLC and highlight the need for the development of multiparametric predictive biomarkers beyond tumor-T cell axis. Citation Format: Lina Meinecke, Jorge Blando, Thomas Herz, Michael Surace, Thomas Padel, Monica Azqueta Gavaldon, Harald Hessel, Farzad Sekhavati, Megha Saraiya, Anmarie Boutrin, Karma Da Costa, Jaime Rodriguez Canales, Ashok Gupta, Carl Barrett, Zachary Aaron Cooper, Ikbel Achour. Presence of TLS and combined high densities of PD-L1+ macrophages & CD8+ T cells predict long-term overall survival for patients with advanced NSCLC treated with durvalumab [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 1235.