Single-Cell Characterization of the Multiple Myeloma (MM) Immune Microenvironment Identifies CD27-Negative T Cells As Potential Source of Tumor-Reactive Lymphocytes

• Published in: Blood Vol. 134; no. Supplement_1; p. 506
• Main Authors: Botta, Cirino, Pérez Ruiz, Cristina, Goicoechea, Ibai, Puig, Noemi, Cedena, María Teresa, Cordon, Lourdes, Zabaleta, Aintzane, Burgos, Leire, Maia, Catarina, Rodríguez, Sara, Rodriguez, Idoia, Sarvide, Sarai, Alignani, Diego, Vilas-Zornoza, Amaia, Lorenzo-Vivas, Erika, Rosinol Dachs, Laura, Oriol, Albert, Blanchard, María Jesús, Rios, Rafael, Sureda, Anna, Martínez, Rafael, Martín, Jesús, Bargay, Joan, De La Rubia, Javier, Rossi, Marco, Tagliaferri, Pierosandro, Tassone, Pierfrancesco, Gentile, Massimo, Merino, Juana, Prosper, Felipe, Orfao, Alberto, Mateos, Maria-Victoria, Lahuerta, Juan-José, Bladé, Joan, San-Miguel, Jesús, Paiva, Bruno
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 13.11.2019
• ISSN: 0006-4971; 1528-0020
• DOI: 10.1182/blood-2019-123974

Background: The broad use of immunomodulatory drugs (IMiDs) and the breakthrough of novel immunotherapies in MM, urge the optimization of immune monitoring to help tailoring treatment based on better prediction of patients' response according to their immune status. For example, current T cells immune monitoring is of limited value because the phenotype of tumor-reactive T cells is uncertain. Aims: To characterize the MM immune microenvironment at the single-cell level and to identify clinically relevant subsets for effective immune monitoring. Methods: We used a semi-automated pipeline to unveil full cellular diversity based on unbiased clustering, in a large flow cytometry dataset of 86 newly-diagnosed MM patients enrolled in the PETHEMA/GEM2012MENOS65 clinical trial, including immune monitoring at diagnosis, after induction with bortezomib, lenalidomide, dexamethasone (VRD), autologous transplant and VRD consolidation. Immunophenotyping was performed using the first 8-color combination (CD19, CD27, CD38, CD45, CD56, CD81, CD117, CD138) of the next-generation flow (NGF) panel for MRD assessment. Results were then validated in additional 145 patients enrolled in the same trial. Deep characterization of T cells was performed using 17-color multidimensional flow cytometry (TIM3, CD160, TIGIT, CD57, CD8, PD1, CD45RA, CD56, BTLA, CD4, CD3, CD39, CD137, CTLA4, CCR7, CD16, CD27) and combined single-cell (sc) RNA/TCR sequencing (10xGenomics). Results: Simultaneous analysis of the entire dataset (n=333 files) unbiasedly identified 25 cell clusters (including 9 myeloid and 13 lymphocytes subsets) in the MM immune microenvironment. Afterwards, we correlated a total of 120 immune parameters derived from the cellular abundance of each cluster and specific cell ratios determined at all time points, with a total of 20 clinical parameters including the International Staging System (ISS) and FISH cytogenetics. Twelve variables had significant impact in progression-free survival (PFS) and the ratio between CD27- vs CD27+ T cells emerged as an independent prognostic factor (HR:0.09, p=0.04) together with the ISS in a Cox regression model. The 3-year PFS rates of patients with high vs low CD27-/CD27+ ratios were 94% vs 71% (p=0.02), respectively; these findings being confirmed in the validation dataset. Thus, we observed in the entire cohort (n=231) that a prognostic score including the CD27-/CD27+ T cell ratio (HR:0.21, p=0.013) and ISS (HR:1.41, p=0.015) outperformed each parameter alone (HR:0.06, p=0.007). To gain further insight into the biological significance of the CD27-/CD27+ T cell ratio, we performed scRNA/TCRseq in 44,969 lymphocytes from 9 MM patients. Downstream analysis unveiled that CD27- T cells were mostly CD8 and included senescent, effector and exhausted clusters. By contrast, CD27+ T cells were mainly CD4 and the remaining CD8 T cells had a predominant immune suppressive phenotype (ie. high GZMK, TIGIT, LAG3 and PD1 expression levels). Such T cell clustering was validated by 17-color multidimensional flow cytometry that confirmed the cellular distribution identified by scRNAseq, as well as higher reactivity for PD1, TIGIT, BTLA and TIM3 in CD27+ vs CD27- T cells. Simultaneous scTCRseq revealed a total of 90 different clonotypes (median of 12 per patient). Interestingly, most clonotypes where found in CD27- (74/90) as opposed to CD27+ T cells and, using the VDJB database, the CDR3 sequences of clonotypic effector/exhausted CD27- T cells were predicted to recognize MM-related epitopes such as MLANA, HM1.24 (CD319), TKT, or IMP2. In selected patients, we performed exome- and RNA-sequencing of tumor cells and analyzed their HLA profile. Using the T Cell Epitopes - MHC Binding Prediction tool from the IEDB Analysis Resource, we found expression of mutated genes (e.g. UBXN1, UPF2, GNB1L) predicted to bind MHC class I molecules on tumor cells and potentially recognized by autologous clonotypic CD27- T cells. Conclusion: We show for the first time that potential MM-reactive T cells are CD27-negative and that their abundance in the immune microenvironment of newly-diagnosed MM patients is prognostic, possibly due to their reactivation after treatment with IMiDs and autologous transplant. Because NGF is broadly used, these results are readily applicable for effective T cell immune monitoring. Puig:Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria; The Binding Site: Honoraria; Takeda: Consultancy, Honoraria. Rosinol Dachs:Janssen, Celgene, Amgen and Takeda: Honoraria. Oriol:Janssen: Consultancy; Takeda: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Celgene Corporation: Consultancy, Speakers Bureau. Rios:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Sureda:Takeda: Consultancy, Honoraria, Speakers Bureau; Novartis: Honoraria; Gilead: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria; Roche: Honoraria; Sanofi: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support; Amgen: Membership on an entity's Board of Directors or advisory committees. De La Rubia:Takeda: Consultancy; Janssen: Consultancy; Celgene Corporation: Consultancy; AMGEN: Consultancy; AbbVie: Consultancy. Mateos:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; EDO: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Lahuerta:Takeda, Amgen, Celgene and Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Bladé:Irctures: Honoraria; Janssen, Celgene, Amgen, Takeda: Membership on an entity's Board of Directors or advisory committees. San-Miguel:Amgen, Bristol-Myers Squibb, Celgene, Janssen, MSD, Novartis, Roche, Sanofi, and Takeda: Consultancy, Honoraria. Paiva:Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, Novartis, Roche, and Sanofi; unrestricted grants from Celgene, EngMab, Sanofi, and Takeda; and consultancy for Celgene, Janssen, and Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau.