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The bone marrow microenvironment interacts with malignant cells and regulates cancer survival and immune evasion in multiple myeloma (MM). We investigated the immune profiles of longitudinal bone marrow samples from patients with newly diagnosed MM (n = 18) using cytometry by time-of-flight. The results before and during treatment were compared between patients with good (GR, n = 11) and bad (BR, n = 7) responses to lenalidomide/bortezomib/dexamethasone-based treatment. Before treatment, the GR group had a lower tumor cell burden and a higher number of T cells with a phenotype shifted toward CD8+ T cells expressing markers attributed to cytotoxicity (CD45RA and CD57), a higher abundance of CD8+ terminal effector cells, and a lower abundance of CD8+ naïve T cells. On natural killer (NK) cells, increased expression of CD56 (NCAM), CD57, and CD16 was seen at baseline in the GR group, indicating their maturation and cytotoxic potential. During lenalidomide-based treatment, the GR patients showed an increase in effector memory CD4+ and CD8+ T-cell subsets. These findings support distinct immune patterns in different clinical contexts, suggesting that deep immune profiling could be used for treatment guidance and warrants further exploration.

Background In this phase 2 study patients received 3 cycles of RVD (lenalidomide, bortezomib and dexamethasone) followed by autologous stem cell transplantation (ASCT) and lenalidomide maintenance. We evaluated the bone marrow (BM) immune profile with CyTOF (cytometry by time-of-flight) at treatment start and during lenalidomide maintenance focusing on two different response groups: good and poor responders at pre- and post-treatment phases. Our hypothesis was that there could be distinct differences in immune cell profiles between these groups, especially in T and NK cell subsets and exhausted T-cells. Methods Twenty-six patients were included in this study, 18 from this trial. BM samples were collected from all 18 patients at diagnosis, from 11 the 1st sample when achieved good response during maintenance after a median of 21 (6-46) months and the 2nd sample if good response was maintained after a median of 56 (45-67) months and from 5 patients at relapse after a median of 6 (2-23) months. Patients in good response cohort (n=11) had progression-free survival (PFS) > 5 years. For comparison we included 4 BM samples, taken at good response after ASCT from MM patients not exposed to lenalidomide and 4 BM samples collected from age-matched, healthy donors. Results With a median follow-up of 81 (13-97) months the median PFS was not reached in the good response cohort and was less than 18 months in the poor response cohort. CyTOF analysis revealed distinct good (GR) and poor responder’s (PR) immune signatures at baseline level. GR, baseline group has shifted phenotype of T cells toward the CD8 T cells, expressing markers, attributed to the cytotoxicity (CD45RA, CD57), as well as having slightly higher abundance of CD8 TE and lower abundance of CD8 naive T cells. Total T cell amounts were significantly higher in good responders. Increased expression of CD56, CD57, and CD16 were also seen on NK cells in good responders at the baseline, indicating both maturation and cytotoxic potential of NKs. In contrast, a significant decrease of CD56 and CD16 expression suggesting reduced cytotoxic potential and increase of CD57 were seen on NKs in poor responders, baseline indicating senescence status a phenotype associated with exhaustion. Treatment stimulates the expression of cytotoxic/effector-like phenotype on T cells which is confirmed by the significantly increased amounts of CD4 and CD8 effector memory cells, with the respective decrease of naive cells. Conclusions Patients responded to the treatment, have higher effector/cytotoxic cells, expressing higher levels of CD57 and/or CD45RA for T cells, and CD57, CD16, and CD56 for NK cells. Additionally, those patients have less degree of tumor burden as well as decreased expression of chemokine receptors (CCR7, CCR6, CXCR4, CXCR3, and CXCR5). Good responders showed the increase in effector memory CD4 and CD8 subsets of T cells abundance, indicating even the higher cytotoxic effect of immune system.

Introduction Melphalan flufenamide (melflufen), is a novel peptide-drug conjugate that targets aminopeptidases and selectively delivers alkylating agents in tumors. Melflufen was recently FDA approved for the treatment of relapsed/refractory multiple myeloma (MM) patients. Considering the challenges in treating this group of patients, and the availability of several new drugs for MM, information that can support treatment selection is urgently needed. To identify potential indicators of response and mechanism of resistance to melflufen, we applied a multiparametric drug sensitivity assay to MM patient samples ex vivo and analyzed the samples by single cell RNA sequencing (scRNAseq). Ex vivo drug testing identified MM samples that were distinctly sensitive or resistant to melflufen, while differential gene expression analysis revealed pathways associated with response. Methods Bone marrow (BM) aspirates from 24 MM patients were obtained after written informed consent following approved protocols in compliance with the Declaration of Helsinki. BM mononuclear cells from 12 newly diagnosed (ND) and 12 relapsed/refractory (RR) patients were used for multi-parametric flow cytometry-based drug sensitivity and resistance testing (DSRT) evaluation to melflufen and melphalan, and for scRNAseq. Based on the results from the DSRT tests and drug sensitivity scores (DSS), we divided the samples into three groups - high sensitivity (HS, DSS > 40 (melflufen) or DSS > 16 (melphalan)), intermediate sensitivity (IS, 31 ≤ DSS ≤ 40 (melflufen) or 10 ≤ DSS ≤ 16 (melphalan)), and low sensitivity (LS, DSS < 31 (melflufen) or DSS < 10 (melphalan)). To identify genes, responsible for the general sensitivity to melphalan-based drugs we conducted differential gene expression (DGE) analyses separately for melphalan and melflufen focusing on the plasma cell populations, comparing gene expression between HS and LS samples for both drugs ("HS vs. LS melphalan" and "HS vs. LS for melflufen", respectively). In addition, to explain the increased sensitivity of RR samples, we conducted the DGE analysis for ND vs. RR samples and searched for similarities between these three datasets. Results DSRT data indicated that samples from RRMM patients were significantly more sensitive to melflufen compared to samples from NDMM (Fig. 1A). In addition, we observed that samples with a gain of 1q (+1q) were more sensitive to melflufen while those with deletion of 13q (del13q) appeared to be less sensitive, although these results lacked significance (Fig. 1A). After separating the samples into different drug sensitivity groups (HS, IS, LS), DGE analysis showed significant downregulation of the drug efflux and multidrug resistance protein family member ABCB9 in the melflufen HS group opposed to the LS group (2.2-fold, p < 0.001). A similar pattern was detected for the melphalan HS vs. LS comparison suggesting that this alteration might be a common indicator of sensitivity to melphalan-based drugs. Furthermore, in the melflufen HS group we observed downregulation of the matrix metallopeptidase inhibitors TIMP1 and TIMP2 (3-fold and 1.6-fold, p < 0.001, respectively), and cathepsin inhibitors CST3 and CSTB (3.2-fold and 1.3-fold, p < 0.001, respectively) (Fig. 1B). This effect was observed in both "ND vs. RR" and "HS vs. LS for melflufen" comparisons, but not for melphalan, suggesting that these changes are associated with disease progression and specific indicators of sensitivity to melflufen. Moreover, gene set enrichment analysis (GSEA) showed activation of pathways related to protein synthesis, as well as amino acid starvation for malignant and normal cell populations in the HS group. Conclusion In summary, our results indicate that melflufen is more active in RRMM compared to NDMM. In addition, samples from MM patients with +1q, which is considered an indicator of high-risk disease, tended to be more sensitive to melflufen. Based on differential GSEA and pathway enrichment, several synergizing mechanisms could potentially explain the higher sensitivity to melflufen, such as decreased drug efflux and increased drug uptake. Although these results indicate potential indicators of response and mechanisms of drug efficacy, further validation of these findings is required using data from melflufen treated patients. Figure 1 Figure 1. Disclosures Slipicevic: Oncopeptides AB: Current Employment. Nupponen: Oncopeptides AB: Consultancy. Lehmann: Oncopeptides AB: Current Employment. Heckman: Orion Pharma: Research Funding; Oncopeptides: Consultancy, Research Funding; Novartis: Research Funding; Celgene/BMS: Research Funding; Kronos Bio, Inc.: Research Funding.

Introduction Here we report the results of one of the secondary endpoints of the Finnish Myeloma Group-MM02 study; composition of bone marrow (BM) immune cell subsets at treatment start and during lenalidomide (Len) maintenance focusing on 2 different response groups: good responders (GRs) and poor responders (PRs) at pre- and post-treatment stages. We evaluated the BM immune profile with CyTOF (cytometry by time-of-flight). Our hypothesis was that there would be distinct differences in immune cell profiles between patients with good and poor response, especially in the T and NK cell subsets. Patients and methods Twenty-two patients were included in this CyTOF study. Eighteen were NDMM patients from FMG-MM02 study who received 3 RVD cycles followed by ASCT. Len started 3 months after ASCT 10 mg/day in 21/28-day cycles until progression or toxicity. BM samples were collected to the Finnish Hematology Registry Clinical Biobank (FHRB Biobank) at several timepoints; from 18 patients at diagnosis, from 11 patients 1 st sample at good response during Len and 2 nd sample if this good response was maintained and from 5 patients at relapse during Len. The patients in the good response cohort (n=11) had progression-free survival (PFS) > 5 years. For comparison, we included 4 BM samples from the FHRB Biobank, taken at a good response after ASCT from MM patients without exposure to Len. Results With a median follow-up of 81 months (13-97) the median PFS was not reached in the good response (GR) cohort and was 18 months in the poor response (PR) cohort. The 1 st GR samples were collected after a median of 21 (6-46) months of Len. The 2 nd samples in GR cohort were collected after a median of 56 (45-67) months of Len. The PR samples were taken after a median of 6 (2-23) months of Len. CyTOF analysis revealed distinct good and poor responder's immune signatures at baseline level. GR, baseline group has shifted phenotype of T cells toward the CD8 T cells, expressing markers, attributed to the cytotoxicity (CD45RA, CD57), as well as having slightly higher abundance of CD8 TE and lower abundance of CD8 naïve T cells. Total T cells amounts were significantly higher in GR. Increased expression of CD56, CD57, and CD16 were also seen on NK cells in GR at the baseline, indicating both maturation and cytotoxic potential of NKs. In contrast, a significant decrease of CD56 and CD16 expression suggesting reduced cytotoxic potential and increase of CD57 were seen on NKs in PR, baseline indicating senescence status a phenotype associated with exhaustion. By using viSNE we discovered two novel populations - MAC1, and MAC2, - associated with disease pathogenesis. We further investigated the composition of these populations, and it appears that MAC1 expressed CD38+CD56+CD45-CD19- presumably malignant plasma cells and MAC2 expressed CD45- CD14+CD38+CD56+TCRgd+CCR7+CCR6+CXCR4+ CXCR3+CXCR5+CD294+, which might be the novel populations, having the features of myeloid suppressor cells. These two immune cells were higher in PR (9.2% and 8.2%, respectively) at baseline as compared to the GR (2.3% and 1.7%). NKs, T cells, and B cells showed a high expression of monocytic marker CD14 and chemokine receptors (CCR7, CCR6, CXCR4, CXCR3, and CXCR5) in PR both at baseline and relapse. This might be attributed to either biological features of MM environment, or the high level of interaction between these populations and monocytes, which left traces of their membranes on the non-monocytic populations. Conclusions Patients, responded to the treatment, have higher abundances of effector/cytotoxic cells, expressing higher levels of CD57 and/or CD45RA for T cells, and CD57, CD16, and CD56 for NK cells indicating proper differentiation and maturation of T, and NK cells to effector and cytotoxic subsets. Additionally, those patients have less degree of tumor burden as well as decreased expression of chemokine receptors. During the therapy administration, good responders show the increase in effector memory CD4 and CD8 subsets of T cells abundance, indicating even the higher cytotoxic effect of immune system. Disclosures Silvennoinen: Amgen: Consultancy, Honoraria, Research Funding; Celgene/BMS: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding. Luoma: Amgen: Honoraria; Janssen: Honoraria; Incyte: Honoraria. Anttila: Amgen: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Takeda: Honoraria. Säily: Takeda: Honoraria; Janssen: Honoraria; Sanofi: Honoraria; Celgene: Honoraria. Partanen: Takeda: Honoraria; Abbvie: Honoraria; Behring: Honoraria. Heckman: Novartis: Research Funding; Orion Pharma: Research Funding; Celgene/BMS: Research Funding; Oncopeptides: Consultancy, Research Funding; Kronos Bio, Inc.: Research Funding.