PF205 RNA BASED IMMUNE SIGNATURES MAY PREDICT RESPONSES TO PD‐1 INHIBITION AND AZACITIDINE TREATMENT IN ACUTE MYELOID LEUKEMIA (AML): A SUBSET ANALYSIS OF A PHASE 2 STUDY
Authors: Abbas H. , Alfayez M. , Wang F. , Garcia‐manero G. , Ravandi F. , Kadia T. , Jabbour E. , DiNardo C. , Mathews J. , Flores W. , Andreeff M. , Kornblau S. , Borthakur G. , Konopleva M. , Cortes J. , Neelapu S. , Kantarjian H. , Davis R. , Daver N. 
Published: June 2019

Background:

Combining PD‐1/PD‐L1 blockade with hypomethylating agents (HMA) showed encouraging efficacy in relapsed/refractory (R/R) AML, but immune biomarkers of response are needed to optimize patient selection.

Aims:

Deciphering immune predictors of response to PD‐1 blockade in AML.

Methods:

We treated 70 R/R AML patients with azacitidine (AZA) (75 mg/m2 on Days 1 through 7) and nivolumab (Nivo) (3 mg/kg on Days 1 and 14 of a 28 to 35 day cycle) in a phase 2 clinical trial (Daver N et al Cancer Discovery 2018). Herein, we discuss results of 11 patients (5 responders and 6 non‐responders) who had pretreatment bone marrow (BM) NanoString RNA expression profiling of 1468 immune‐relevant genes. 17‐color established immune panel flow cytometric analysis were performed at baseline and end of cycle (EOC)1, 2 and/or 4 treatments on BMs. Results were correlated with clinical, pathological and molecular data.

Results:

11 patients with R/R AML, median age 65 years (range 47–73 years), 63% with adverse cytogenetics, 27% with TP53 mutation, 6/11 (55%) with prior hypomethylating agent‐based therapy had indepth flow‐cytometry and NanoString immune profiling.The median administered courses of AZA+Nivo was 3 (range 1–17). The CR/CRi rate was 45% (including 2 CR, 1 CRi, 1 CRn and 1 CRp), with a median time to response of 1.8 months (range 0.8–4.9 months). The median overall survival was 13 months with 27% patients alive at 1 year. We found significant positive correlations between proportions of T‐effector cells in baseline BM, and CD3+, CD8+, and T‐regulatory cells in EOC 1 BM (r>0.75, p < 0.01 for all). At EOC2, these correlations were no longer significant. However, there was a significant positive correlation between proportion of T‐effector cells in baseline BM and T‐regulatory cells (r = 1, p < 0.001) in EOC4 BM.

Using NanoString analysis on pretreatment BM samples, we found 133 differentially expressed genes (fold change = 2, q<0.1) between responders (5/11) and non‐responders (NRs) (6/11). Pretreatment pathway analysis of differentially expressed BM genes between responders and non‐responders demonstrated enrichment of innate immune response, cytokine activity, cell adhesion, and chemotaxis pathways (q<0.05) in responders. Hallmark signaling pathway analysis also demonstrated significant enrichment of IL2‐STAT5, IL6‐JAK‐STAT3, IFN‐aand TNF signaling pathways (q<0.05) in pretherapy BM in responders compared with NRs. We then utilized z‐score distribution analysis to quantify the degree of activation of known immunologic pathways. We found signatures highly specific to neutrophils and macrophages were significantly (p < 0.05) upregulated in the pretreatment BMs of responders compared with NRs.

Summary/Conclusion:

Immune regulatory signatures related to IL2, IL6, IFNa, chemotaxis, neutrophils and macrophages in pretreatment BMs may be associated with augmented clinical response to PD‐1 based therapies in AML. Similar underlying pathways (primarily IL2‐STAT5 and IFNa), have consistently predicted for responses to PD‐1 inhibition in solid cancers. Further, responses to PD‐1 based therapy was higher in patients with more active innate immune system as demonstrated by macrophage and neutrophil up‐regulated signatures, suggesting a possible prerequisite of active innate immunity for optimal PD‐1 blockade responses. Identifying such predictive signatures may help select AML patients most likely to benefit from PD‐1 based approaches, further enhancing the benefit‐risk ratio with such therapies.

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