SAT0187 DISCRIMINATION OF SYSTEMIC LUPUS (SLE) PATIENTS WITH CLINICAL RESPONSE TO OBEXELIMAB (XMAB®5871) BASED ON A PATTERN OF IMMUNOLOGIC MARKERS

Background:

We recently reported Phase 2 SLE trial results of obexelimab, an FcγRIIb agonist (suppressor of B cell activation). Obexelimab did not meet the primary endpoint (% of patients without flare at Day 225) (p=0.183) but other endpoints such as time to flare (p=0.025) were met.

Objectives:

1. To assign SLE patients to phenotypic subsets based on patterns of gene expression in immune-related pathways.12. To explore the association of immune patterns and clinical response to obexelimab.

Methods:

This analysis included 71 of the 104 participants in the obexelimab study, those who either completed the protocol or terminated for disease flare, if there were adequate blood samples (biomarker subset). At screening, patients were assigned to clusters based on 41 SLE co-expression signature modules from the Human Immune Phenotyping Consortium via unsupervised random forest and K-means clustering.2Other markers of SLE disease were also examined. TheBOLD3study design mandated withdrawal of background immunosuppressants, supporting less ambiguous pharmacodynamic analysis as the trial progressed.

Results:

Immune pathway expression patterns of 7 patient clusters (Fig 1a) confirmed our prior characterization of 200 non-overlapping SLE patients.2The biomarker subset retained a trend of longer time to first flare in patients receiving obexelimab (n=38) vs placebo (n=33) (Fig1b, HR 0.61, p=0.11). A smaller set of only Clusters 3 and 6 demonstrated marked increased time to flare in the obexelimab group (n=13) compared to placebo (n=14) (Fig 1c, HR 0.22, p=0.025). Obexelimab had no effect on other clusters (Fig 1d). The responder clusters shared low expression of inflammation modules (p < 0.001) compared to other clusters and high expression of T Cell, immune response, cell cycle, mitochondrial modules (all p < 0.001) and B Cell modules (p=0.006). We therefore sorted patients by these specific features regardless of cluster assignment. Figure 2 shows significant impact of obexelimab on time to flare in 64 patients with B Cell pathway activation (HR 0.5, p=0.038), although less robust by itself than found in Clusters 3 and 6. In a group with high B or plasma cell modules but low inflammation (n=46), treatment effect increased (HR 0.35, p=0.019). Between Screening and Baseline, as brief steroids were given and background treatments withdrawn, expression of B Cell and Plasma Cell pathways increased. Both then decreased after treatment with obexelimab but not placebo (p< 0.0001 and p< 0.001 respectively), an effect not seen with other immune pathway modules.

Conclusion:

Precision medicine for SLE has been hampered by heterogenous immune signals with variable expression. Clustering of patients by gene co-expression pathways enabled an efficient, hierarchical array that reduplicated results of a prior SLE cohort, suggesting these are not random phenotypes. Of these 7 reproducible SLE subsets, the combination of clusters 3 and 6 distinguished an obexelimab responder population of 27 out of 71 subjects (38%) with high expression of B and T Cell modules and cell activation pathways. Focus on the defining features shared by these clusters revealed specific factors associated with response, enabling inclusion of some patients from other clusters in an optimized responder population of 46/71 (65% of subjects). B Cell and Plasma Cell pathways demonstrated mechanism-related pharmacodynamic effects of obexelimab. Lack of responders with high expression of inflammation modules could implicate inhibitory factors to obexelimab within inflammatory pathways, potentially targetable by complementary treatments.

References:

[1]Banchereau Cell 165:1548 2016

[2]Lu ACR Abstract #2977 2017

[3]Merrill Arthritis Rheumatol 69: 1257 2017

Disclosure of Interests: :

Joan T Merrill Grant/research support from: Xencor, Bristol Myers Squibb, Glaxo Smith Kline, Consultant of: Xencor, Abbvie, UCB, Glaxo Smith Kline, EMD Serono, Astellas, Remegen, Celgene/Bristol Myers Squibb, Exagen, Astra Zeneca, Amgen, Jannsen, Servier, ILTOO, Daitchi Sankyo, Lilly, Paid instructor for: Abbvie, Bristol Myers Squibb, Joel Guthridge Grant/research support from: Xencor, Bristol Myers Squibb, DXterity, Debra Zack Shareholder of: Xencor, Employee of: Xencor, Paul Foster Shareholder of: Xencor Inc, Employee of: Xencor Inc, Bart Burington Shareholder of: Xencor Inc, Employee of: Xencor Inc, Ly Tran: None declared, Miles Smith: None declared, Judith A. James Grant/research support from: Progentec Diagnostics, Inc, Consultant of: Abbvie, Novartis, Jannsen

A randomized phase II study of the telomerase inhibitor imetelstat as maintenance therapy for advanced non-small-cell lung cancer

BACKGROUND

Continuation or 'switch' maintenance therapy is commonly used in patients with advancd non-small-cell lung cancer (NSCLC). Here, we evaluated the efficacy of the telomerase inhibitor, imetelstat, as switch maintenance therapy in patients with advanced NSCLC.

PATIENTS AND METHODS

The primary end point of this open-label, randomized phase II study was progression-free survival (PFS). Patients with non-progressive, advanced NSCLC after platinum-based doublet (first-line) chemotherapy (with or without bevacizumab), any histology, with Eastern Cooperative Oncology Group performance status 0-1 were eligible. Randomization was 2 : 1 in favor of imetelstat, administered at 9.4 mg/kg on days 1 and 8 of a 21-day cycle, or observation. Telomere length (TL) biomarker exploratory analysis was carried out in tumor tissue by quantitative PCR (qPCR) and telomerase fluorescence in situ hybridization.

RESULTS

Of 116 patients enrolled, 114 were evaluable. Grade 3/4 neutropenia and thrombocytopenia were more frequent with imetelstat. Median PFS was 2.8 and 2.6 months for imetelstat-treated versus control [hazard ratio (HR) = 0.844; 95% CI 0.54-1.31; P = 0.446]. Median survival time favored imetelstat (14.3 versus 11.5 months), although not significantly (HR = 0.68; 95% CI 0.41-1.12; P = 0.129). Exploratory analysis demonstrated a trend toward longer median PFS (HR = 0.43; 95% CI 0.14-1.3; P = 0.124) and overall survival (OS; HR = 0.41; 95% CI 0.11-1.46; P = 0.155) in imetelstat-treated patients with short TL, but no improvement in median PFS and OS in patients with long TL (HR = 0.86; 95% CI 0.39-1.88; and HR = 0.51; 95% CI 0.2-1.28; P = 0.145).

CONCLUSIONS

Maintenance imetelstat failed to improve PFS in advanced NSCLC patients responding to first-line therapy. There was a trend toward a improvement in median PFS and OS in patients with short TL. Short TL as a predictive biomarker will require further investigation for the clinical development of imetelstat.

Evaluation of a gene signature to predict single agent dacetuzumab (SGN-40) activity in patients with DLBCL

11063

Background: Dacetuzumab (SGN-40) is a humanized IgG1 monoclonal antibody that binds to CD40, mediates effector cell functions, and activates downstream apoptosis signaling pathways. Dacetuzumab has shown single-agent activity in relapsed/refractory DLBCL in phase I and phase II trials, with multiple objective responses and 1/3 of patients demonstrating tumor shrinkage, defined as a decrease in tumor volume (SPD) of at least 10%. We previously reported a 14-gene signature (ASH 2008 #1593) that was strongly associated with dacetuzumab sensitivity in DLBCL cell lines. Here, we report an initial evaluation of the gene signature as a classifier of patients likely to demonstrate tumor shrinkage after dacetuzumab therapy. Methods: The original 14 microarray probes were chosen for high correlation with in vitro dacetuzumab sensitivity (IC25) in 31 NHL cell line models. Matching qRT-PCR probes were developed and confirmed to correlate with the microarray probes in paired cell line samples. In this retrospective analysis, archived paraffin blocks from a 26 patient subset of the phase I and II trials, with a diagnosis of DLBCL and available tumor measurements, were assayed by qRT-PCR. Results: Overall, 42% of patients (11/26) exhibited decreased SPD of at least 10%. Of those who were marker +, 10 out of 13 (78%) had 10% or better decreases in SPD, whereas only 1 of 13 patients who were marker - demonstrated tumor shrinkage (8%). The overall accuracy for predicting tumor shrinkage was 85% (one-sided P=0.002, by permutation test). Among the 14 genes contributing to the multivariate signature, CD22 and VNN2 were the most strongly down-regulated in specimens from patients without at least a 10% decrease in SPD (P=0.14 and P=0.10, respectively), while IGF1R and CTSC were the most strongly up-regulated (P=0.05 and P=0.08, respectively). Conclusions: A 14-gene signature appears to predict tumor shrinkage in DLBCL patients receiving dacetuzumab in single-agent clinical trials (P=0.002). A larger clinical data set will be analyzed to further evaluate the correlation of this gene signature with objective clinical response rates..

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