Abstract B63: Immune gene expression profiling of acute myeloid leukemia identifies predictors of survival and actionable targets for treatment

• Published in: Cancer immunology research 2020-04, Vol.8 (4_Supplement), p.B63-B63
• Main Authors: Rutella, Sergio, Vadakekolathu, Jayakumar, Hood, Tressa, Reeder, Stephen, Warren, Sarah E., Danaher, Patrick, Davidson-Moncada, Jan, Cesano, Alessandra, Beechem, Joseph M., Tasian, Sarah K., Minden, Mark D.
• Format: Article
• Language: English
• ISSN: 2326-6066; 2326-6074
• DOI: 10.1158/2326-6074.TUMIMM18-B63

Background: Acute myeloid leukemia (AML) is characterized by clonal expansion of poorly differentiated myeloid precursors, resulting in impaired hematopoiesis and often bone marrow (BM) failure. The general therapeutic approach in patients with AML has not changed substantially in more than 30 years. Investigation of new strategies, including immunotherapy, remains a priority. Tumor phenotypes are dictated not only by major oncogene drivers, but also by the tumor immunologic microenvironment (TIME) which is inherently immunosuppressive, is equipped to hamper effector T-cell function and includes immune and inflammatory cells, soluble mediators such as interferon (IFN)-gamma and extracellular matrix components. Herein, we profiled the TIME of AML to identify gene signatures that are reflective of general immune status and predictive of antileukemia immune potential. Methods: We used the hybridization-based nCounter® system (NanoString Technologies®, Seattle, WA) and the RNA Pan-Cancer Immune Profiling PanelTM to analyze BM aspirates from 290 adults and 40 children with newly diagnosed, nonpromyelocytic AML. Data were normalized to a set of reference genes and log2-transformed for bioinformatics analysis. The clinical relevance of the association between immune gene signatures and patient outcome was further validated in silico using publicly available cancer transcriptomic datasets (The Cancer Genome Atlas; TCGA). Results: We identified distinct sets of co-expressed genes corresponding to innate immunity, adaptive immunity and IFN-gamma signaling. BM samples with IFN-gamma-dominant gene expression profiles showed up-regulation of actionable immune checkpoints, such as B7-H3, PD-L1 and CTLA-4. A set of 4 differentially expressed immune genes between children and adults with AML (FDR