-Author name in bold denotes the presenting author
-Asterisk * with author name denotes a Non-ASH member
Clinically Relevant Abstract denotes an abstract that is clinically relevant.

PhD Trainee denotes that this is a recommended PHD Trainee Session.

Ticketed Session denotes that this is a ticketed session.

3000 A Suboptimal Response in CML Is Associated with Expression of the Immune Checkpoint VISTA

Program: Oral and Poster Abstracts
Session: 631. Myeloproliferative Syndromes and Chronic Myeloid Leukemia: Basic and Translational: Poster II
Hematology Disease Topics & Pathways:
Research, Translational Research, CML, Chronic Myeloid Malignancies, Diseases, Myeloid Malignancies
Sunday, December 11, 2022, 6:00 PM-8:00 PM

Aram Bidikian1*, Sreyashi Basu, PhD2*, He Zhong3*, Himachandana Atluri, MD4, Jabra Zarka, MD5*, Michael Andreeff, MD, PhD1, Koji Sasaki, MD1, Elias Jabbour, MD1, Jorge E. Cortes, MD6, Padmanee Sharma, MD, PhD7* and Ghayas C. Issa, MD1

1Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX
2Department of Immunology, UT M. D. Anderson Cancer Center, Houston, TX
3The University of Texas MD Anderson Cancer Center, Houston, TX
4Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
5Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA
6Georgia Cancer Center, Augusta, GA
7Department of Immunology, The University of Texas M.D. Anderson Cancer Center, Houston, TX

Introduction: Tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of chronic myeloid leukemia (CML) leading to molecular remission in most patients. The next challenges are decreasing resistance and improving the odds of treatment-free remission. Understanding determinants of disease persistence and suboptimal responses is critical for improving these probabilities. The role of the immune system in the control or eradication of CML has been demonstrated in multiple settings including successful graft-vs-leukemia effect and the requirement of active T-cells and natural killer (NK) cells for sustained remission prior to therapy discontinuation. Herein, we aim to demonstrate a comparison of immune determinants of response in CML in those who achieve a deep molecular response (MR4.5) compared to suboptimal responders.

Methods: We prospectively collected longitudinal blood and bone marrow samples from patients receiving treatment for CML and characterized them using cytometry by time of flight (CyTOF). 20 patients that achieved MR4.5 at any time during their treatment were compared to a cohort of 32 patients with suboptimal response to therapy according to the European LeukemiaNet (ELN) response milestones (Table 1). We custom-designed this CyTOF panel (36-plex) to include markers of leukemia/stem progenitor cells, lineage defining, intracellular signaling, immune exhaustion and activation markers. Samples were barcoded, pooled and processed simultaneously to overcome technical variations and batch effects. CD45hi cells (leukocytes) were grouped using PhenoGraph clustering, based on expression of these markers in the earliest samples available, collected at various timepoints during treatment.

Results: Analysis of differential expression patterns revealed 25 distinct clusters. Patients with suboptimal response to therapy had a higher proportion of CD45hiCD3+ cells (T-cells) compared to those with an optimal response (median of 59% vs 53%, P=0.04). Notably, this included a higher proportion of exhausted CD8+ cytotoxic T-cells in patients with suboptimal response characterized by high Eomes and low Tbet expression (median of 8.0% vs 1.9%, P=0.04). In contrast, CD56+ NK-cells were more prevalent in the optimal response group (median of 5.5% vs 3.2%, P=0.04), particularly an interferon gamma releasing (CD56hiCD16loTbet+) subpopulation (median of 4.1% vs 2.5%, P=0.04). While CD68+ cells (macrophages) were detected at similar rates in both the optimal and suboptimal response groups (median of 16.5% vs 15.5%, P=0.07), the phagocytic subpopulation (CD16-CD14+CD68+HLA-DRlo) was more prevalent in those who achieved an optimal response (median of 15.1% vs 13.2%, P=0.02). Patients with suboptimal response had a higher proportion of CD68+HLA-DRloVISTAhi cells (median of 5.6% vs 1.8%, P=0.004), referring to macrophages expressing the immune regulatory ligand V-domain immunoglobulin suppressor of T cell activation (VISTA). Like PD-L1 and other B7 family ligands, VISTA attenuates T-cells response to antigens and VISTA overexpression has been associated with resistance to immune checkpoint inhibitors in solid tumors. Furthermore, cells characterized by CD66b+CXCR4+VISTAlo were increased in patients with optimal response (median of 20.6% vs 0.6%, P=0.01), indicating a higher proportion of mature granulocytes with low expression of VISTA in the optimal response group (Figure 1).

Conclusion: We found that higher expression of the immune checkpoint VISTA, in addition to markers of T-cells exhaustion is associated with suboptimal response to therapy in CML. These findings highlight the importance of the immune microenvironment in response to targeted therapies such as TKIs.

Disclosures: Andreeff: Kintor Pharmaceutical: Research Funding; Daiichi-Sankyo Inc.: Consultancy, Research Funding; Pinot Bio: Research Funding; Syndax: Consultancy, Research Funding; Oncolyze: Current holder of stock options in a privately-held company; Glycomimetics: Consultancy; Oxford Biomedical UK: Research Funding; Leukemia & Lymphoma Society: Membership on an entity's Board of Directors or advisory committees; Cancer UK: Membership on an entity's Board of Directors or advisory committees; Brooklyn ITX: Research Funding; Senti Bio: Consultancy, Research Funding; Chimerix: Current holder of stock options in a privately-held company; Aptose: Consultancy, Membership on an entity's Board of Directors or advisory committees; German Research Council: Membership on an entity's Board of Directors or advisory committees; Medicxi: Consultancy; AstraZeneca: Research Funding; Breast Cancer Research Foundation: Research Funding; CLL Foundation: Membership on an entity's Board of Directors or advisory committees; Reata: Current holder of stock options in a privately-held company; NCI: Membership on an entity's Board of Directors or advisory committees. Sasaki: Pfizer: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; Otsuka Pharmaceuticals: Honoraria; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Jabbour: Takeda: Other: Advisory Role, Research Funding; Bristol Myers Squibb: Other: Advisory Role, Research Funding; Genentech: Other: Advisory Role, Research Funding; Adaptive Biotechnologies: Other: Advisory Role, Research Funding; Pfizer: Other: Advisory Role, Research Funding; Spectrum: Research Funding; Amgen: Other: Advisory Role, Research Funding; AbbVie: Other: Advisory Role, Research Funding. Cortes: Gilead: Consultancy; Kartos: Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; Abbvie: Consultancy, Research Funding; Forma Therapuetic: Consultancy; Pfizer: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Biopath Holdings: Consultancy, Current equity holder in private company; Sun Pharma: Consultancy, Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Issa: Novartis, Kura Oncology, Nuprobe: Consultancy; Celgene, Kura Oncology, Syndax, Merck, Cullinan and Novartis: Research Funding.

*signifies non-member of ASH