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Objectives: This study aims to retrospectively assess C-lectin-like molecule 1 (CLL-1) bimodal expression on CD34+ blasts in acute myeloid leukemia (AML) patients (total N = 306) and explore potential CLL-1 bimodal associations with leukemia and patient-specific characteristics. Methods: Flow cytometry assays were performed to assess the deeper immunophenotyping of CLL-1 bimodality. Cytogenetic analysis was performed to characterize the gene mutation on CLL-1-negative subpopulation of CLL-1 bimodal AML samples. Results: The frequency of a bimodal pattern of CLL-1 expression of CD34+ blasts ranged from 8% to 65% in the different cohorts. Bimodal CLL-1 expression was most prevalent in patients with MDS-related AML (P = .011), ELN adverse risk (P = .002), NPM1 wild type (WT, P = .049), FLT3 WT (P = .035), and relatively low percentages of leukemia-associated immunophenotypes (P = .006). Additional immunophenotyping analysis revealed the CLL-1- subpopulation may consist of pre-B cells, immature myeloblasts, and hematopoietic stem cells. Furthermore, (pre)-leukemic mutations were detected in both CLL-1+ and CLL-1- subfractions of bimodal samples (N = 3). Conclusions: C-lectin-like molecule 1 bimodality occurs in about 25% of AML patients and the CLL-1- cell population still contains malignant cells, hence it may potentially limit the effectiveness of CLL-1-targeted therapies and warrant further investigation. Keywords: CD34+ blasts; CLL-1; acute myeloid leukemia; bimodality; bone marrow aspirates; flow cytometry.

The 14th edition of the Workshop on Recent Issues in Bioanalysis (14th WRIB) was held virtually on June 15-29, 2020 with an attendance of over 1000 representatives from pharmaceutical/biopharmaceutical companies, biotechnology companies, contract research organizations, and regulatory agencies worldwide. The 14th WRIB included three Main Workshops, seven Specialized Workshops that together spanned 11 days in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy and vaccine. Moreover, a comprehensive vaccine assays track; an enhanced cytometry track and updated Industry/Regulators consensus on BMV of biotherapeutics by LCMS were special features in 2020. As in previous years, this year's WRIB continued to gather a wide diversity of international industry opinion leaders and regulatory authority experts working on both small and large molecules to facilitate sharing and discussions focused on improving quality, increasing regulatory compliance and achieving scientific excellence on bioanalytical issues. This 2020 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop, and is aimed to provide the Global Bioanalytical Community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2020 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication covers the recommendations on (Part 2A) BAV, PK LBA, Flow Cytometry Validation and Cytometry Innovation and (Part 2B) Regulatory Input. Part 1 (Innovation in Small Molecules, Hybrid LBA/LCMS & Regulated Bioanalysis), Part 3 (Vaccine, Gene/Cell Therapy, NAb Harmonization and Immunogenicity) are published in volume 13 of Bioanalysis, issues 4, and 6 (2021), respectively.

Introduction:Programmed death-ligand 1 (PD-L1) contributes to tumor escape from immune surveillance by binding to programmed death-1 (PD-1), a negative regulator of T-cell responses. PD-L1 is expressed by both tumor cells and immune cells in the tumor microenvironment. In contrast, the role of PD-L2 in tumor immunity is unclear. To better understand the contribution of PD-L1/L2 to immune escape in marrow-based hematologic malignancies, we used multi-color flow cytometry and immunohistochemistry (IHC) to characterize cell-specific PD-L1/PD-L2 expression in patients with multiple myeloma (MM), myelodysplastic syndrome (MDS) and acute myelogenous leukemia (AML). Results:PD-L1 was detectable (> 2% positive cells) in 100% of patients, with distinct disease-specific patterns. PD-L1 was expressed most widely in MM, predominantly by malignant plasma cells (median, 95% of plasma cells; n = 5) and lymphocytes (median, 12% of marrow lymphocytes; n = 5). In contrast, in MDS and AML, PD-L1 was more commonly expressed by non-tumor hematopoietic cells: MDS median, 36% of CD34− myeloid precursors and 47% of lymphocytes (n = 13) vs 12% of CD34+ myeloid blasts; AML median, 19% of CD34− myeloid precursors and 26% of lymphocytes (n = 7) vs 16% of CD34+ myeloid blasts were PD-L1+. A higher proportion of CD8+ T cells expressed PD-L1 compared with CD4+ T cells in all 3 malignancies: the CD8:CD4 ratio for PD-L1+ T cells was 3.02 in MM (n = 11), 1.92 in MDS (n = 10), and 1.29 in AML (n = 7). PD-L2 expression was largely absent in AML and MDS (< 2% of CD34+ blasts or lymphocytes expressed PD-L2 (n = 13 MDS and n = 7 AML) but was expressed in a subset of patients with MM on plasma cells (median, 18%; n = 5) but not lymphocytes (< 2%). Across all indications on both tumor cells and lymphocytes, PD-L1 was expressed by a larger fraction of cells than PD-L2 (AML: CD34+ blasts, P < .01 and lymphocytes, P = .005 [n = 7]; MDS: CD34+ blasts, P < .01 and lymphocytes, P = .0001 [n = 13]; MM: plasma cells, P = .03 and lymphocytes, P = .04 [n = 5]). These results were confirmed in a distinct set of 16 cases of primary AML analyzed independently, with detectable PD-L1 expression on myeloid blasts in 14 of 16 cases (88%) without co-expression of PD-L2 (0 of 16 cases). Comparisons of flow cytometry and IHC revealed that some IHC methods may underestimate the prevalence of PD-L1/PD-L2 in marrow-based hematologic malignancies, and results comparing different methods for detecting PD-L1/PD-L2 in the bone marrow will be presented. Conclusions:PD-L1 is highly prevalent in MM, MDS and AML, with significant expression by non-tumor hematopoietic cells, particularly CD8+ T cells. PD-L2 expression was largely absent in myeloid diseases but detectable in MM. Interestingly, PD-L1 expression was most common on tumor cells in MM and on non-tumor hematopoietic cells in MDS, whereas expression on non-tumor and tumor cells in AML was comparable. These data support clinical development of anti-PD-L1/PD-1 therapies in MM, MDS and AML. Future analyses will determine whether different patterns of PD-L1 expression are associated with clinical efficacy. Authors M Dail, L Yang, S Rodig, and J Venstrom contributed equally to this work. Disclosures Dail: Genentech, Inc.: Employment. Green:Genentech, Inc.: Employment. Ma:Genentech, Inc.: Employment. Robert:Genentech, Inc.: Employment. Kadel:Genentech, Inc.: Employment. Koeppen:Roche: Employment, Equity Ownership. Adamkewicz:Genentech, Inc.: Employment. Byon:Genentech, Inc.: Employment. Woodard:Genentech, Inc.: Employment. Rodig:Bristol-Myers Squibb: Honoraria, Research Funding; Perkin Elmer: Membership on an entity's Board of Directors or advisory committees. Venstrom:Genentech: Employment.

Introduction:TIGIT (T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif [ITIM] domain) is an inhibitory immunoreceptor expressed by T and natural killer (NK) cells that is an important regulator of anti-tumor and anti-viral immunity. TIGIT shares its high-affinity ligand PVR (CD155) with the activating receptor CD226 (DNAM-1). We have recently shown that TIGIT blockade, together with PD-L1/PD-1 blockade, provides robust efficacy in syngeneic tumor and chronic viral infection models. Importantly, CD226 blockade abrogates the benefit of TIGIT blockade, suggesting additional benefit of TIGIT blockade through elaboration of CD226-mediated anti-tumor immunity, analogous to CTLA-4/CD28 regulation of T-cell immunity. Whether TIGIT and CD226 are expressed in patients with multiple myeloma (MM) and how TIGIT expression relates to PD-L1/PD-1 expression is unknown. Here we evaluate expression of TIGIT, CD226, PD-1 and PD-L1 in patients with MM to inform novel immunotherapy combinations. Methods:We performed multi-color flow cytometry (n = 25 patients), and multiplex qRT-PCR (n = 7) on bone marrow specimens from patients with MM to assess expression of TIGIT, CD226, PD-1, and PD-L1 on tumor and immune cells. Cells were stained with fluorescently conjugated monoclonal antibodies to label T cells (CD3, CD4, CD8), NK cells (CD56, CD3), plasma cells (CD38, CD45, CD319, CD56), inhibitory/activating receptors (PD-1, TIGIT, PD-L1, CD226), and an amine-reactive viability dye (7-AAD). Stained and fixed cells were analyzed by flow cytometry using BD FACSCanto™ and BD LSRFortessa™. Results:TIGIT, CD226 and PD-L1/PD-1 were detectable by flow cytometry in all patients with MM who were tested, with some overlapping and distinct expression patterns. TIGIT was commonly expressed by marrow-infiltrating CD8+ T cells (median, 65% of cells), CD4+ T cells (median, 12%) and NK cells. In contrast, CD226 was more commonly expressed by marrow-infiltrating CD4+ T cells (median, 74%) compared with CD8+ T cells (median, 38%). PD-1 was expressed by marrow-infiltrating CD8+ T cells (median 38%) and CD4+ T cells (median, 16%). TIGIT was co-expressed with PD-1 on CD8+ T cells (67%-97% TIGIT+ among PD-1+), although many PD-1-negative CD8+ T cells also expressed TIGIT (39%-78% of PD-1-negative). PD-L1 was also expressed by CD8+ (median, 23%) and CD4+ (median, 8%) T cells in addition to MM plasma cells (median, 95%), albeit with significantly lower intensity on T cells compared with plasma cells. The expression of TIGIT and PD-L1 mRNA was highly correlated (R2 = 0.80). Analysis of PVR expression will also be presented. Conclusions: TIGIT, CD226, PD-1, and PD-L1 were commonly expressed in MM bone marrow, but with different patterns. Among CD8+ T cells, the frequency of TIGIT+ T cells was almost twice that of PD-1+ T cells, whereas the majority of CD4+ T cells expressed CD226. TIGIT blockade may complement anti-PD-L1/PD-1 immunotherapy by activating distinct T-cell/NK-cell subsets with synergistic clinical benefit. These results provide new insight into the immune microenvironment of MM and rationale for targeting both the PD-L1/PD-1 interaction and TIGIT in MM. Disclosures Yadav: Genentech, Inc.: Employment. Green:Genentech, Inc.: Employment. Ma:Genentech, Inc.: Employment. Robert:Genentech, Inc.: Employment. Glibicky:Makro Technologies Inc.: Employment; Genentech, Inc.: Consultancy. Nakamura:Genentech, Inc.: Employment. Sumiyoshi:Genentech, Inc.: Employment. Meng:Genentech, Inc.: Employment, Equity Ownership. Chu:Genentech Inc.: Employment. Wu:Genentech: Employment. Byon:Genentech, Inc.: Employment. Woodard:Genentech, Inc.: Employment. Adamkewicz:Genentech, Inc.: Employment. Grogan:Genentech, Inc.: Employment. Venstrom:Roche-Genentech: Employment.