Loss of the Immune Checkpoint Cd85j/LILRB1 on Malignant Plasma Cells

Loss of the Immune Checkpoint CD85j/LILRB1 on Malignant Plasma Cells Contributes to Immune Escape in Multiple Myeloma This information is current as of September 29, 2021. Ester Lozano, Tania Díaz, Mari-Pau Mena, Guillermo Suñe, Xavier Calvo, Marcos Calderón, Lorena Pérez-Amill, Vanina Rodríguez, Patricia Pérez-Galán, Gaël Roué, M. Teresa Cibeira, Laura Rosiñol, Ignacio Isola, Luis-Gerardo Rodríguez-Lobato, Beatriz Martin-Antonio, Joan Bladé and Carlos Fernández de Larrea Downloaded from J Immunol 2018; 200:2581-2591; Prepublished online 12 March 2018; doi: 10.4049/jimmunol.1701622

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The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2018 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology

Loss of the Immune Checkpoint CD85j/LILRB1 on Malignant Plasma Cells Contributes to Immune Escape in Multiple Myeloma

Ester Lozano,*,† Tania Dıáz,*,† Mari-Pau Mena,*,† Guillermo Sun˜e,*,‡ Xavier Calvo,* Marcos Calderoń,*,† Lorena Pe´rez-Amill,*,‡ Vanina Rodrı´guez,† Patricia Pe´rez-Galań,† Gae¨l Roue´,†,x M. Teresa Cibeira,* Laura Rosinõl,* Ignacio Isola,* Luis-Gerardo Rodrı´guez- Lobato,* Beatriz Martin-Antonio,*,‡ Joan Blade´,*,‡ and Carlos Fernańdez de Larrea*,†,‡

Mechanisms of immune regulation may control proliferation of aberrant plasma cells (PCs) in patients with monoclonal gammopathy of undetermined significance (MGUS) preventing progression to active multiple myeloma (MM). We hypothesized that Downloaded from CD85j (LILRB1), an inhibitory immune checkpoint for B cell function, may play a role in MM pathogenesis. In this study, we report that patients with active MM had significantly lower levels of CD85j and its ligand S100A9. Decreased CD85j expression could also be detected in the premalignant condition MGUS, suggesting that loss of CD85j may be an early event promoting tumor immune escape. To gain insight into the molecular mechanisms underlying CD85j functions, we next enforced expression of CD85j in human myeloma cell lines by lentiviral transduction. Interestingly, gene expression profiling of CD85j-overexpressing cells revealed a set of downregulated genes with crucial functions in MM pathogenesis. Furthermore, in vitro functional assays http://www.jimmunol.org/ demonstrated that CD85j overexpression increased susceptibility to T cell– and NK-mediated killing. Consistently, ligation of CD85j decreased the number of PCs from individuals with MGUS but not from patients with MM. In conclusion, downregulation of inhibitory immune checkpoints on malignant PCs may provide a novel mechanism of immune escape associated with myeloma pathogenesis. The Journal of Immunology, 2018, 200: 2581–2591.

ultiple myeloma (MM) is a clonal B cell malignancy marrow (BM) cells and PCs may show aberrant expression of characterized by neoplastic proliferation of a plasma receptors such as CD56 and CD117 (c-Kit). However, the annual M cell (PC) clone. Malignant PCs produce monoclonal rate of malignant transformation from MGUS to MM is 1% (6), Igs, which usually results in organ or tissue impairment (1, 2). MM indicating that mechanisms of control may prevent proliferation of by guest on September 29, 2021 accounts for approximately 13% of hematologic cancers and its aberrant PCs. The molecular mechanisms that maintain the frequency is likely to increase in the near future as the population MGUS state and the mechanisms that trigger progression from ages (1, 3). MM remains incurable although the median survival MGUS to MM are poorly understood. has recently increased due to the introduction of autologous stem- Immune cells must be tightly regulated to mount a speciﬁc cell transplantation and the availability of new agents such as immune response while avoiding autoimmunity. One mechanism of thalidomide, lenalidomide, and bortezomib (4, 5). MM is usually immune regulation is the presence of inhibitory immune check- preceded by the asymptomatic condition monoclonal gammopathy points on the surface of immune cells. Immune checkpoints may of undetermined signiﬁcance (MGUS). In the asymptomatic contain ITIM, which can recruit phosphatases and deliver inhib- MGUS, the frequency of PCs may be up to 10% of the bone itory signals into the cell (7). Upregulation of ligands for inhibitory

*Amyloidosis and Myeloma Unit, Department of Hematology, Hospital Clıńic, Au- cytometry data analysis; V.R., P.P.-G., and G.R. performed gene expression analysis; gust Pi i Sunyer Biomedical Research Institute, University of Barcelona, 08036 B.M.-A., L.P.-A., and G.S. provided reagents and helped with functional NK cyto- Barcelona, Spain; †Division of Hematology and Oncology, August Pi i Sunyer Bio- toxicity assays; M.T.C., L.R., I.I., L.-G.R.-L., J.B., and C.F.d.L. provided patient medical Research Institute, 08036 Barcelona, Spain; ‡Josep Carreras Leukaemia samples and clinical data, designed research, and wrote the manuscript; all authors Research Institute, University of Barcelona, 08036 Barcelona, Spain; and xLabora- reviewed and approved the manuscript. tory of Experimental Hematology, Department of Hematology, Vall d’Hebron Insti- The microarray data presented in this article have been submitted to the Gene Ex- tute of Oncology, Vall d’Hebron University Hospital, 08035 Barcelona, Spain pression Omnibus database (http://www.ncbi.nlm.nih.gov/geo/) under accession ORCIDs: 0000-0002-6307-9807 (E.L.); 0000-0001-7934-9130 (X.C.); 0000- number GSE89793. 0003-0245-2257 (G.R.); 0000-0001-5694-0921 (L.-G.R.-L.); 0000-0003-0612- Address correspondence and reprint requests to Dr. Carlos Fernańdez de Larrea, 2693 (B.M.-A.). Amyloidosis and Myeloma Unit, Department of Hematology, Hospital Clıńic de Received for publication November 27, 2017. Accepted for publication February 13, Barcelona, Institut d’Investigacions Biome`diques August Pi i Sunyer, Villarroel, 2018. 170, 08036 Barcelona, Spain. E-mail address: [email protected] This work was supported in part by Grants RD12/0036/0046 and PI16/00423 from The online version of this article contains supplemental material. Instituto de Salud Carlos III (Ministerio de Economıá y Competitividad, Cofinan- Abbreviations used in this article: BM, bone marrow; CR, complete remission; ciado por Fondo Europeo de Desarrollo Regional, Union Europea, Una Manera de DAVID, Database for Annotation, Visualization, and Integrated Discovery; MGUS, Hacer Europa). This work was partially funded by a Generalitat de Catalunya grant monoclonal gammopathy of undetermined significance; MM, multiple myeloma; PC, (2014SGR-552), the CERCA Programme/Generalitat de Catalunya, and a Josep plasma cell; PD-1, programmed cell death protein 1; VGPR, very good partial Carreras Leukaemia Research Institute grant (CEL029). C.F.d.L. was the recipient response. of an Institut d’Investigacions Biome`diques August Pi i Sunyer starting grant (II040060). Copyright Ó 2018 by The American Association of Immunologists, Inc. 0022-1767/18/$35.00 E.L. performed experiments, analyzed data, and wrote the manuscript; T.D., M.-P.M., and M.C. performed experiments and analyzed results; X.C. performed flow www.jimmunol.org/cgi/doi/10.4049/jimmunol.1701622 2582 LOSS OF CD85j IN MULTIPLE MYELOMA checkpoints on the surface of tumor cells is one escape mecha- BM mononuclear cells from patients with MGUS or MM were obtained + nism that cancer cells may develop to inhibit the host immune by density gradient centrifugation (Ficoll; Sigma-Aldrich). Fresh CD138 system (8, 9). Blockade of inhibitory immune checkpoints has PCs were isolated with anti-CD138 mAb-coated immunomagnetic beads (Miltenyi Biotec, San Diego, CA) using an AutoMacs cell sorter (Miltenyi been approved for the treatment of solid tumors and hematologic Biotec). RNA from PCs was isolated using Trizol reagent and total RNA malignancies (10–12). However, the roles of inhibitory immune was retrotranscribed using High Capacity cDNA Reverse Transcription kit checkpoints when immune cells become tumor cells remain un- (Thermo Fisher Scientific). TaqMan Universal PCR Master Mix and known. We hypothesized that inhibitory immune checkpoints on probes were from Thermo Fisher Scientific. Reactions were run on a 7900 Real-Time PCR System (Thermo Fisher Scientific). Values are represented the surface of PCs may play a role in maintaining immune control as the difference in cycle threshold values normalized to endogenous in the premalignant condition MGUS. Thus, loss of these mech- control b-glucuronidase for each sample as per the following formula: anisms may confer a selective advantage to the aberrant clone relative RNA expression = 22d cycle threshold. promoting progression to MM. Flow cytometry analysis In this study, we focus on CD85j (also known as LILRB1 and ILT2), which is expressed predominantly on B cells, monocytes, Flow cytometry analysis was performed following procedures standardized by dendritic cells, NK, and T cells (13–15). CD85j is a receptor for the EuroFlow Consortium (23). To identify PCs with aberrant phenotypes, an eight-color panel of Abs was used: CD38-FITC (clone HB-7), CD56-PE class I MHC Ags including HLA-A, HLA-B, HLA-C, and HLA-G (clone MY31), CD19-PerCPCy5.5 (clone SJ25C1), CD81-APCH7 (clone (16). Its cytoplasmic tail contains four ITIM motifs (17) and li- JS-81), CD45-V450 (clone 2D1), CD138-BV510 (clone MI15), which were gation of CD85j inhibits IFN production by NK and T cells (13, from BD Biosciences, CD117-PC7 (clone 104D2D1) from Beckman Coul- 14). It has also been reported that binding of HLA-G to CD85j ter; and human ILT2/CD85j APC-conjugated Ab (clone 292305) was purchased from R&D Systems A minimum of 500,000 events was acquired for suppresses B cell responses (15). CD85j is also expressed on BM each sample using a BD FACSCanto II flow cytometer with FACSDiva Downloaded from PCs from healthy donors (18). MM cell line growth may be re- software (BD Biosciences). Data were analyzed with FlowJo Software. duced by HLA-G/CD85j interaction (19). Interestingly, S100A9 ELISA (also known as MRP14) has been recently identified as a novel ligand for CD85j (20) and its role in MM remains to be elucidated. Human S100A9 levels were determined in BM plasma and peripheral The aim of this study is to investigate the contribution of the plasma using ELISA kits DY5578 and DY008 according to the manufacturer’s instructions (R&D Systems). CD85j-S100A9 axis to immune regulation in MGUS and pro- http://www.jimmunol.org/ gression from MGUS to MM. To this end, we first analyzed CD85j overexpression by lentiviral transduction primary PCs from patients with MGUS, active MM, and with MM Lentiviral particles were generated using HEK293T cells and the Lenti- in complete remission (CR). This work has established that vpak packaging kit (packaging plasmids and MegaTran1.0 transfection malignant PCs downregulate the expression of both the inhibitory reagent) with Lenti open reading frame clone of human LILRB1, transcript receptor CD85j and its ligand S100A9 in patients with MM. To variant 1, pLenti-C-mGFP vector purchased from OriGene Technologies. gain insight into the mechanisms underlying the loss of immune MM cell lines were lentivirally transduced to express CD85j-GFP or GFP- control in the presence of 8 mg/ml polybrene (Sigma-Aldrich). After 3 d, regulation in MM, we enforced expression of CD85j in myeloma cells were FACS-sorted on a BDAria sorter (BD Biosciences). cells and explored changes in gene expression profiling and functional activity in immune assays. Transcriptional analysis Gene expression profiling and gene set enrichment analysis by guest on September 29, 2021 showed that CD85j overexpression was associated to downreg- RNA samples had an RNA integrity number above eight determined using a ulation of genes with essential roles in the pathogenesis of MM, Bioanalyzer 2100 instrument (Agilent Technologies). cRNA was hybridized on suggesting that loss of CD85j in MM may confer selective the HT HG-U219 GeneChip (Affymetrix) following standardized protocols. advantage for the pathogenic clone. Furthermore, we demon- Scanning was processed in a Gene Titan instrument and analyzed with Gen- eChip Command Console Software (Affymetrix). Raw data were normalized strated that specific killing by NK cells is increased against using the Robust Multichip Analysis algorithm implemented in the Expression CD85j-overexpressing myeloma cells. Accordingly, ligation of Console Software v1.1 (Affymetrix). For identification of differentially CD85j with a specific Ab decreased PC survival in MGUS but not expressed genes, MultiExperiment Viewer platform (v4.9) and a Rank Products , in MM. In summary, loss of this inhibitory axis CD85j-S100A9 test were used, applying a paired analysis with a p value 0.001. Functional annotation of enrichment analysis was performed using Database for Anno- may promote tumor cell functions and immune escape in mye- tation, Visualization and Integrated Discovery (DAVID) v6.7 (National Insti- loma. Thus, downregulation of inhibitory checkpoints on the tute of Allergy and Infectious Diseases, National Institutes of Health) (24). surface of immune-derived cancer cells may provide a novel Further pathway analysis was done using gene set enrichment analysis soft- mechanism to escape immune control in human malignancies. ware provided by the Broad Institute. The microarray data have been deposited in the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo/) under accession number GEO:GSE89793. Materials and Methods Patients Cell proliferation assays BM aspiration samples and peripheral blood were collected from 69 patients MM cell lines RPMI-8226, U266, and ARP-1 were cultured in RPMI 1640 with MGUS, 75 patients with MM, and 17 patients with MM in CR di- medium supplemented with 10–15% FBS, 2 mM glutamine, 100 U/ml agnosed at the Amyloidosis and Myeloma Unit in the Department of penicillin, and 100 mg/ml streptomycin, and maintained at 37˚C and 5% Hematology (Hospital Clıńic of Barcelona). Clinical characteristics of the CO2. MM cell lines were obtained from the Division of Hematology and recruited patients are summarized in Table I. Sample collection and clin- Oncology, Institut d’Investigacions Biome`diques August Pi i Sunyer (Dr. ical record review were performed after informed written consent in ac- D. Colomer). CD85j-overexpressing cells were cultured at 50,000 cells per cordance with the Declaration of Helsinki. Study protocol was approved by well in 100 ml of RPMI 1640 medium supplemented with 10% FBS in the Institutional Review Board at Hospital Clıńic of Barcelona. Patients the presence of indicated concentrations of dexamethasone (Merck, S.L.), were diagnosed according to standard International Myeloma Working lenalidomide (Selleck Chemicals), and bortezomib (Janssen-Cilag Inter- Group criteria (21). national). After 48 h viable cells were analyzed using the MTT colori- metric assay (Sigma-Aldrich). MTT reagent was added for one additional Gene expression analysis hour before cell lysis and spectrophotometric measurement. The Gene Expression Omnibus database was used to find previously Functional cytotoxicity assays published human PC data sets such as GSE47552, including BM PCs from 5 healthy donors, 20 patients with MGUS, and 41 newly diagnosed untreated Given that cord blood–derived NK cells are being investigated as a cellular patients with MM, and analyzed by hybridizing RNA to Human Gene 1.0 therapy against MM (25), we isolated cord blood–derived NK cells and ST Array (Affymetrix) (22). cocultured them with MM target cells in 96-well U-bottom plates for 4 h. The Journal of Immunology 2583

FIGURE 1. Loss of inhibitory immune checkpoint CD85j and its ligand S100A9 in active MM. Microarray data from the Gene Ex- pression Omnibus database, accession number GSE47552 was used to analyze (A) CD85j (LILRB1) mRNA expression and its ligand S100A9 mRNA expression in normal PCs (nPCs) (n = 5), PCs from individuals with MGUS (n = 20), and patients with MM (n = 41). Data are pre- Downloaded from sented as mean 6 SEM. (B) CD85j (LILRB1) and S100A9 gene expression was quantified in isolated CD138+ PCs and CD1382 cells of BM from MM patients (n = 20) and individuals with MGUS (n = 20) by http://www.jimmunol.org/ real-time PCR. (C) Confirmation study at protein level with a second cohort of MM patients (n = 21) and individuals with MGUS (n = 26). Representative dot plots of BM samples and their corresponding histograms with the mean fluorescence intensity values of CD85j expression determined by eight- color flow cytometry. Complete by guest on September 29, 2021 gating strategy is not shown. (D) Statistical analysis of CD85j expression on PCs. (E) S100A9 con- centration measured by ELISA in BM plasma and in peripheral plasma from patients with MGUS (n = 20) compared with active MM (n = 20). *p , 0.05, **p , 0.01, ***p , 0.001.

Cytotoxicity was analyzed in europium-release assays following the Ex vivo BM functional assays manufacturer’s instructions (DELFIA EuTDA Cytotoxicity kit; Perki- nElmer). Specific cytotoxicity was calculated as follows: % cytotoxicity = BM mononuclear cells were isolated by Ficoll density gradient centrifu- (experimental release – spontaneous release) 3 100/(maximal release gation and cultured in the presence of 10 mg/ml of functional human ILT2/ – spontaneous release). T cell cytotoxicity assays were performed with CD85j Ab (clone 292319) or IgG2B Isotype Control (clone 20116) from CD3+ T cells isolated from PBMC of healthy donors with CD3 R&D Systems. After 18 h, the PC number was measured in triplicate Microbeads (Miltenyi Biotec). Isolated T cells were then activated with acquiring 50 ml per run on an Attune Acoustic Focusing Cytometer anti-CD3 (1 mg/ml) and anti-CD28 (1 mg/ml) in the presence of IL2 (10 U/ml) (Thermo Fisher Scientific). for 72 h. After polyclonal T cell stimulation, we performed the cytotoxicity Statistical analysis assay at a 10:1 ratio. To assess S100A9 blockade, 20 mg/ml of neutralizing Ultra-LEAF purified anti-human S100A8/A9 heterodimer Ab (clone Kruskal–Wallis test followed by Dunn multiple comparison tests were used A15105B) from BioLegend or isotype control was added 2 h prior to coculture to analyze differences in gene expression between independent groups of with NK cells. The number of target cells per well was analyzed by flow patients. One-way ANOVA followed by Tukey multiple comparison test was cytometry with the addition of 50 ml of CountBright Absolute Counting Beads used to analyze differences in protein expression between independent (Thermo Fisher Scientific) per sample. groups of patients. Differences in CD85j expression on normal and aberrant 2584 LOSS OF CD85j IN MULTIPLE MYELOMA

PCs were statistically evaluated using the Mann–Whitney U test. Two-tailed eight-color panel (23) containing CD38, CD138, CD45, CD19, CD81, paired t test was used to compare data in active MM patients before and after CD56, CD117, and CD85j. Aberrant PCs may show multiple com- , treatment. Differences were considered statistically significant at p values binations of abnormal phenotypes such as decreased CD38, CD452, 0.05. All statistical analyses were performed using GraphPad Prism, v6.02 2 + + 2 2 (GraphPad Software). CD19 ,CD56,CD117,CD27 ,andCD81 . In BM samples from patients with MGUS may coexist normal and aberrant PCs. How- Results ever, given that only a small fraction of individuals with MGUS Downregulation of the inhibitory receptor CD85j and its will develop MM, we used the terms aberrant or phenotypically ligand S100A9 in malignant PCs from patients with MM abnormal PCs but not malignant for PCs in patients with MGUS. Microarray expression analysis performed by Davies et al. (26) As shown in Fig. 2, flow cytometry analysis identified three dis- identified 74 genes differentially expressed in PCs from patients tinct patterns of expression in MGUS: 1) normal PCs expressing high with MGUS (n = 7) compared with newly diagnosed patients with only CD85j ; 2) PCs coexpressing both CD85j and CD56; and MM (n = 24). Among them, CD85j (LILRB1) was one of the most 3) PCs expressing CD56, which lost CD85j expression like most downregulated genes in PCs from patients with MM compared with of the pathologic PCs in MM (Fig. 2A). Similar results were MGUS (26). To confirm these data, we first analyzed another obtained with aberrant expression of CD117 (Fig. 2B). Given that publicly available human PC data set GSE47552, comparing PCs some aberrant PCs may express CD85j, no significant differ- from healthy donors (n = 5), individuals with MGUS (n = 20) and ences were found comparing expression of CD85j in normal PCs patients with MM (n = 41) (22). According to this data set, CD85j versus aberrant PCs (Fig. 2C, 2D). However, when the fre- expression on normal PCs was significantly higher compared with quency of aberrant PCs was superior to 40% of total PCs, we both MGUS and MM (Fig. 1A) but no significant differences were observed a significant decrease in CD85j expression on aberrant Downloaded from found in MM compared with MGUS. Interestingly, its recently PCs (Fig. 2E), suggesting that the loss of this inhibitory discovered ligand S100A9 was significantly downregulated in pa- immune checkpoint may be an early event associated with an tients with MM compared with MGUS (Fig. 1A). To better un- increased number of aberrant PCs in asymptomatic individuals derstand these discrepant results, we isolated PCs from BM with MGUS. aspirates from individuals with MGUS and patients with active + 2 CD85j expression recovered in patients with MM after MM, and both fractions CD138 and CD138 were analyzed by http://www.jimmunol.org/ effective treatment real-time PCR. Thus, we found that CD85j expression was significantly downregulated in BM PCs from patients with MM com- We next wanted to investigate the axis CD85j-S100A9 in pa- pared with MGUS (Fig. 1B, Table I), consistent with the results tients in CR defined by absence of monoclonal protein in the reported by Davies et al. (26). Accordingly, S100A9 was also sig- serum and urine by immunofixation, along with ,5% BM PCs nificantly decreased in PCs from MM compared with MGUS (27). As shown in Fig. 3, patients with MM in CR showed (Fig. 1B). Moreover, CD1382 BM cells also showed significantly significantly higher levels of CD85j expression than patients lower expression of S100A9 in patients with MM compared with with active MM. Additionally, patients who needed a second BM MGUS. aspirate allowed us to analyze CD85j expression before and after To validate our findings at a protein level, we next analyzed therapeutic intervention. CD85j expression significantly increased by guest on September 29, 2021 CD85j on PC cell surface expression by flow cytometry in a after treatment compared with the first sample in patients who second cohort of patients with MGUS and active MM. Consis- achieved CR or very good partial response (VGPR) after tently, CD85j expression was significantly decreased on malig- bortezomib-based induction therapy (Fig. 3B). Conversely, CD85j nant PCs from patients with MM compared with MGUS (Fig. 1C, 1D). expression did not recover but continued decreasing in patients that In addition, CD85j expression was also analyzed on the other subsets were in progression despite the induction treatment (Fig. 3B). Thus, of the B cell linage in these BM aspirates. Thus, pre–B cells showed CD85j expression on malignant PCs may increase in patients with low expression of CD85j whereas mature B cells showed significantly VGPR, and CD85j expression on normal PCs from patients in CR is higher levels of CD85j compared with pre–B cells in MGUS and MM, similar to the values found in individuals with MGUS. Taken to- indicating that high CD85j expression is associated to late differenti- gether, our data indicate that CD85j could be a useful marker to ation stages in the B cell linage (Supplemental Fig. 1A–C). We also assess malignant PCs versus normal PCs in patients treated with studied other BM cell subsets that may express CD85j, such as NK therapeutic Abs. cells, monocytes, and dendritic cells but no significant differences were observed in MM compared with MGUS (Supplemental Fig. Downregulation of inhibitory receptors CD85d and CD85a 1D–G). expression in MM Interestingly, levels of S100A9 were significantly reduced in Genes encoding members of the LILR family (LILRB1-5)are both BM plasma and peripheral plasma from patients with active located on chromosome 19, in the leukocyte receptor complex, MM compared with individuals with MGUS (Fig. 1E). Therefore, which comprises a large cluster of cell surface receptors such as downregulation of the inhibitory axis CD85j-S100A9 could rep- KIRs,OSCAR,LAIR,FCAR,andGPV1(28)(Fig.4A).We resent a novel mechanism to avoid intrinsic negative signals into next wanted to investigate whether these ITIM-bearing LILRB the myeloma cell to escape immune surveillance. receptors are also downregulated in MM. Indeed, LILRB2 (CD85d) and LILRB3 (CD85a) were significantly decreased in CD85j downregulation in individuals with MGUS was PCs from patients with MM (Fig. 4B). No significant differ- associated with increased frequency of aberrant PCs ences were found in LILRB4 and LILRB5 expression (data not Based on these results, we hypothesized that loss of the inhib- shown). Accordingly, flow cytometry analysis confirmed that itory receptor CD85j may be one of the molecular mechanisms expression of both inhibitory receptors CD85d and CD85a was involved in immune escape in the premalignant state MGUS, significantly lower on PCs from patients with MM (Fig. 4C, which precedes MM. To investigate whether expression of CD85j 4D), suggesting that downregulation of this inhibitory receptor was decreased in the aberrant PCs in MGUS, we analyzed family may contribute to impairment of immune regulation phenotypically normal and aberrant PCs in MGUS based on an in MM. The Journal of Immunology 2585

Table I. Clinical characteristics of patients with MGUS, active MM, and patients with MM in CR

MGUS (n = 69) MM (n = 75) CR (n =17) Median age, y (range) 69 (41–88) 67 (38–88) 60 (41–83) Gender (female/male) 34/35 37/38 9/8 Immunological subtype, n (%) IgG 50 (73%) 38 (51%) 8 (47%) IgA 9 (13%) 22 (29%) 8 (47%) Only light chains 3 (4%) 7 (9%) 1 (6%) Others 7 (10%) 8 (11%) — Light chain subtype, n (%) k 34 (49%) 52 (69%) 12 (71%) l 35 (51%) 23 (31%) 5 (29%) Median serum M-spike, g/l (range) 11 (4.8–27) 31 (3.8–76.6) — International stage system, n (%) I — 16 (21%) 6 (35%) II — 27 (36%) 6 (35%) III — 32 (43%) 5 (29%) Median BM PCs % (range) 5 (2–9) 36 (4–94) 3 (1–4) —, not applicable. Downloaded from

CD85j overexpression negatively regulated genes playing that loss of CD85j found in MM may be associated with tran- essential roles in the pathogenesis of MM scriptional changes promoting MM pathogenesis. To gain insight into the molecular mechanisms associated with CD85j expression on MM cells, we enforced CD85j expression by CD85j expression rendered myeloma cells more susceptible to lentiviral transduction in MM cell lines and analyzed changes in NK and T cell–mediated antitumor activity http://www.jimmunol.org/ gene expression proﬁle compared with GFP-transduced cells. The We next analyzed the functional relevance of CD85j overexpression microarray data have been deposited in the Gene Expression in myeloma cells. As depicted in Fig. 6, CD85j-overexpressing cells Omnibus database under the accession number GEO:GSE89793. did not show reduced viability or increased sensitivity to current Similar to primary myeloma cells, MM cell lines showed very low treatments. Given that NK cells play a prominent role in con- basal levels of CD85j expression before transduction (Fig. 5A). trolling myeloma cell growth through cytotoxic activity and the Robust Multiarray Average analysis and a Rank Products test release of inﬂammatory cytokines, we wanted to investigate indicated that 121 transcripts (90 genes mapped through UniGene) whether loss of CD85j would provide a selective advantage to

were upregulated in CD85j-overexpressing MM cell lines com- escape immune attack. Our functional cytotoxicity assays with by guest on September 29, 2021 pared with control-GFP MM cell lines (p , 0.001) (Supplemental CD85j-transduced cells showed that overexpression of CD85j on Table I). DAVID’s algorithm for pathway and functional analysis MM cells significantly enhanced NK-mediated killing (Fig. 6B). revealed that the list of upregulated genes was enriched in anno- In accordance with our findings in NK-mediated cytotoxicity as- tations related to GO:0060333 ∼ IFN-g–mediated signaling says, T cell–mediated cytotoxicity assays also demonstrated that pathway (HLA-DRA, HLA-C, HLA-DPA1, NMI, CD44, MT2A), CD85j-transduced cells were more susceptible to specific killing GO:0031295 ∼ T cell costimulation (CD80, CD86, TRAC), than GFP-transduced control cells (Fig. 6C), confirming that and GO:0006955 ∼ immune response (CD70, CD74, GPR183, loss of CD85j in MM may promote resistance to cytotoxic cell– CCL3, IL7, CCL22, TNFRSF10D) (Fig. 5B, Supplemental mediated tumor killing. Table II). To provide direct evidence of the role of S100A9, we also Furthermore, 158 transcripts (116 genes mapped through performed cytotoxicity assays in the presence of blocking anti- UniGene) were downregulated in CD85j-overexpressing MM cells S100A9. We first evaluated intracellular S100A9 expression in (p , 0.001) (Supplemental Table I). Functional annotation analysis NK cells by flow cytometry. Before the cytotoxicity assay, of downregulated genes showed a significant enrichment for GO: 20–50% of NK cells were positive for S100A9 (Fig. 6D). NK 0019731 ∼ antibacterial humoral response (Bonferroni test p = cells were preincubated with neutralizing anti-human S100A8/ 6.7 3 10212) (Supplemental Table II). Of note, the list of down- A9 heterodimer Ab or isotype control. As shown in Fig. 6E, regulated genes contained 13 out of 116 genes whose products are CD85j expression increased the specific lysis compared with involved in the pathogenesis and progression of MM (UCHL1, control target cells. However, this increase was partially FGFR3, ADM, CAV1, MAF, FOXO3, PRDM1, ITGB1, DEPTOR, overcome by blocking S100A9, suggesting that S100A9 is in- SDC1, ST3GAL6, HSPB1, FAM46C) (Fig. 5C). Indeed, gene set volved in the increase in cytotoxicity against CD85j-expressing enrichment analysis showed that CD85j overexpression negatively myeloma cells (Fig. 6D, 6E). regulated genes found elevated in MM gene sets (Fig. 5D). Finally, to further investigate whether expression of CD85j For instance, caveolin-1 (CAV1) is required for vascular endo- on primary normal PCs may be associated with a better immune thelial growth factor–triggered MM cell migration (29) and was control by cytotoxic cells, we next cultured BM cells from found downregulated in CD85j-transduced MM cell lines by real- patients with MGUS and MM in the presence of the anti-CD85j time PCR (Fig. 5E). Moreover, this gene set also contained genes Ab or isotype control. After 18 h, no differences in viability frequently overexpressed in MM cells and required for their sur- were observed by Trypan blue staining in the presence of anti- vival such as PRDM1 (Blimp1) (30), DEPTOR (mTOR inhibitor) CD85j mAb (data not shown). In line with our previous results, (31), syndecan-1 (SDC1), and HspB1 (Hsp27) (Fig. 5E). Taken flow cytometry analysis showed that CD85j ligation signifi- together, CD85j overexpression negatively regulated genes cantly decreased the number of PCs from MGUS patients playing essential roles in the pathogenesis of MM, suggesting (Fig. 6F). All BM samples from MGUS (eight samples with 2586 LOSS OF CD85j IN MULTIPLE MYELOMA Downloaded from FIGURE 2. Flow cytometry analysis of CD85j expression in aberrant PCs from individuals with asymptomatic MGUS. (A) Flow analysis of coexpression of CD85j and aberrant expression of CD56 on PCs from representative patients with B

MGUS and active MM. ( ) Flow data of http://www.jimmunol.org/ coexpression of CD85j and aberrant expression of CD117 on PCs in MGUS and MM. Representative dot plots of BM samples from representative patients with MGUS and active MM. (C) Representa- tive analysis of BM samples from individuals with MGUS comparing normal phenotype PCs with aberrant PCs. Com- plete gating strategy is not shown. (D)

Statistical analysis of CD85j mean ﬂuo- by guest on September 29, 2021 rescence intensity values in normal versus aberrant PCs from individuals with asymptomatic MGUS (n =27).(E) Expression of CD85j on aberrant PCs comparing samples with ,40% and $40% of abnormal PCs (n = 27). *p , 0.05.

normal PCs and two samples with aberrant PCs) were positive at the same conditions as functional assays with BM cells, and for CD85j. Additionally, to evaluate whether the Ab binding to no signiﬁcant differences were found in viability or prolifer- PCs could mediate direct effects on the PCs, we incubated ation, suggesting that this Ab did not have an agonistic func- CD85j-overexpressing cells with anti-CD85j or isotype control tion (data not shown). Taken together, our results suggest that The Journal of Immunology 2587

FIGURE 3. CD85j expression increased in patients with MM in CR but not in progression. (A) CD85j Downloaded from expression on PCs from patients with active MM (n = 25), VGPR (n = 13), and CR (n = 17). (B) Longi- tudinal flow analysis of patients with MM before and after therapeutic intervention. Percentage of PCs and CD85j mean fluorescence intensity, http://www.jimmunol.org/ first sample (filled histogram), and second sample (open histogram) are depicted. Data summary of CD85j expression in patients with MM in CR (n = 4), VGPR (n = 3), and MM in progression (n = 3). *p , 0.05, **p , 0.01. by guest on September 29, 2021

the decrease in PC number could be mediated by induction of (12), such as blockade of the inhibitory programmed cell death Ab-dependent cellular cytotoxicity. On the contrary, malignant protein 1 (PD-1) in Hodgkin’s lymphoma (34). In MM, although PCs from patients with MM were resistant to treatment with PCs may express PD-1 ligand 1, BM cytotoxic T cells express low anti-CD85j Ab (Fig. 6F). Thus, ex vivo functional assays in- levels of PD-1, suggesting that PD-1 blockade may not be sufﬁ- dicated that CD85j expression in normal PCs is associated cient to activate T cells as a single agent (35–37). Accordingly, with immune control in asymptomatic MGUS. In contrast, loss several clinical trials evaluating PD-1 blockade in patients with of CD85j expression could contribute to survival and immune MM have achieved better responses in combination with escape of malignant PCs in patients with MM. approved therapies (lenalidomide/dexamethasone, pomalidomide) than as a monotherapy (38, 39). Combinatorial approaches Discussion based on blockade of negative immune checkpoints offer ex- Costimulatory and coinhibitory immune checkpoints tightly reg- traordinary opportunities to improve the treatment of hematologic ulate the immune response upon activation (32). It has recently malignancies. become clear that tumor cells can upregulate ligands for inhibitory To explore new targets for checkpoint blockade in MM, in this immune receptors to avoid immune attack (33). Therapeutic ma- study we focus on investigating the role of the ITIM-bearing receptor nipulation of inhibitory immune checkpoints has proven to be CD85j in controlling PC functions. CD85j delivers a cell-intrinsic effective against solid tumors (10) and hematologic malignancies inhibitory signal for NK cells (13), T cells (14), and B cells (15). 2588 LOSS OF CD85j IN MULTIPLE MYELOMA

FIGURE 4. Downregulation of inhibitory receptors CD85d and CD85a in MM. (A)

Schematic gene cluster of LILRB family at Downloaded from chromosomal region 19q13.4. (B) Gene expression of LILRB2 (CD85d) and LILRB3 (CD85a) was quantiﬁed in isolated CD138+ PCs and CD1382 cells of BM from patients with MGUS and MM (n = 20) by real-time PCR. (C) Con- ﬁrmation study at the protein level with a second

cohort of patients with MGUS and MM. Ex- http://www.jimmunol.org/ pression of LILRB2 (CD85d) was determined by ﬂow cytometry by measuring its mean ﬂuores- cence intensity (MFI) on CD38+ cells. (D) Rep- resentative dot plots gating on CD38+ cells and showing their corresponding histograms with the MFI values of LILRB3 (CD85a) expression. **p , 0.01, ***p , 0.001. by guest on September 29, 2021

Indeed, HLA-G binds to CD85j with high affinity, promoting im- In this study, we found that loss of inhibitory CD85j may take mune tolerance (40). In patients with MGUS and MM, serum HLA- place in early stages of MM pathogenesis in patients with G concentrations were higher compared with healthy donors, but no asymptomatic MGUS associated with a higher frequency of prognostic value was observed (41). In contrast, high expression of aberrant PCs. In the early steps of MM evolution (43, 44), HLA-G on the PC surface was associated with poor prognosis in avoiding immune regulation may be one of the first challenges MM (42). Based on studies with MM cell lines, the interaction of that the pathologic plasma clone has to overcome to proliferate. CD85j and HLA-G has been recently proposed as a suitable target Considering that interaction with the BM microenvironment is in B cell malignancies (19). However, we characterized expression crucial for MM clone proliferation (45, 46), loss of inhibitory of CD85j from a large cohort of patients from asymptomatic stages immune checkpoints may provide a selective advantage for the to active MM and demonstrated that malignant PCs significantly malignant cell clone promoting immune escape in early stages downregulated not only CD85j (LILRB1) but also other inhibitory of MM. members of the LILR family such as LILRB2 and LILRB3. Our Previous functional assays showed that neutralizing CD85j on findings exclude these negative checkpoints as suitable targets and NK cells did not increase cytotoxicity against MM cell lines (47). uncover a novel mechanism of immune escape by downregulating In this study, we focus on the role of CD85j on PC function. Due inhibitory checkpoints on the surface of malignant cells. to the paucity of normal BM PCs and their low proliferation rate The Journal of Immunology 2589 Downloaded from http://www.jimmunol.org/ by guest on September 29, 2021

FIGURE 5. Gene expression profiling of CD85j-overexpressing myeloma cells. (A) Enforced expression of CD85j in three myeloma cell lines (U266, RPMI-8226, ARP-1) by lentiviral transduction and specific selection by FACS. (B) Heat map of 121 transcripts found upregulated in CD85j-overexpressing myeloma cells with p , 0.001. Annotations related to GO:0060333 ∼ IFN-g–mediated signaling pathway (green lines) using DAVID. (C) Heat map of 158 transcripts found downregulated in CD85j-overexpressing myeloma cells with p , 0.001. Significant enrichment for GO:0019731 ∼ antibacterial humoral response (blue lines) and genes involved in MM (red lines). (D) Gene set enrichment analysis of CD85j-overexpressing cells differentially expressed genes significantly correlated with gene sets upregulated in MM such as SHAFFER_IRF4_TARGETS_IN_MYELOMA_VS_MATURE_B_LYM-PHOCYTE and ZHAN_MULTIPLE_MYELOMA_MS_UP. C2 curated gene sets from online pathway databases, publications in PubMed, and knowledge of domain experts. The enrichment score (ES), nominal enrichment score (NES), nominal p value (NOM p-val), and false discovery rate (FDR) for each gene set are shown. (E) Real-time PCR validation of selected differentially expressed genes between CD85j-overexpressing cells and GFP-control cells (mean 6 SEM, n = 3). *p , 0.05. in vitro, knockdown experiments on normal PCs were not feasible. S100A9 blockade partially abrogates the increase in cytotoxicity On the contrary, we demonstrated that enforced expression of against CD85j-expressing myeloma cells, suggesting that S100A9 CD85j on MM cell lines was associated with downregulation of may contribute to the immune control of aberrant PCs from the genes involved in MM and a higher susceptibility to cell MGUS state to active MM. cytotoxic-mediated killing. Our data indicate that loss of CD85j To the best of our knowledge, this is the first report showing on malignant PCs may eliminate an inhibitory cell-intrinsic signal downregulation of inhibitory immune checkpoints on tumor cells. increasing PC resistance to NK attack and promoting immune This novel mechanism of immune escape may be particularly escape in myeloma patients. Recently, S100A9 has been identified relevant in hematological malignancies as cancer cells derive from as a novel ligand for CD85j and its interaction was implicated in immune cells tightly regulated by stimulatory and inhibitory im- the control of HIV type 1 replication by NK cells (20). Our results mune checkpoints. Therefore, although therapeutic manipulation show that S100A9 was significantly decreased at the mRNA and of inhibitory immune checkpoints on cancer cells with agonistic protein level in both BM and peripheral plasma from patients with Abs could represent an attractive approach, it is first necessary to active MM, revealing a new immune-regulatory role for S100A9 carefully analyze their expression on primary cancer cells from in myeloma. Dysregulated expression of S100 proteins is a com- patients at different stages of disease. Our data support the concept mon feature of human cancers promoting proliferation, metastasis, that PCs may negatively regulate their inhibitory receptors when and immune evasion (48). Expression of S100A9 is upregulated transforming into malignant cells, which raises the question of in breast cancer, melanoma, thymus, and prostate cancers (48). whether the loss of inhibitory checkpoints on cancer cells is a In contrast, S100A9 was one of the most downregulated genes in common mechanism contributing to tumor progression in other he- MLL-associated leukemia (49). In this study, we demonstrate that matological malignances such as chronic lymphocytic leukemia. 2590 LOSS OF CD85j IN MULTIPLE MYELOMA

FIGURE 6. CD85j expression on myeloma cells increased specific killing by NK and T cells. (A) Cell viability was assessed by MTT assay. Cells were treated with dexamethasone (0.05 and 0.1 mM), lenalidomide/dexamethasone (L/D) (5 and 0.05 mM), and bortezomib (5 and 10 nM) for 48 h. Data represent mean 6 SEM from three independent experiments. (B) Cytolytic activity of Downloaded from cord-blood NK cells against CD85j- overexpressing myeloma cell lines (U266, RPMI-8226, ARP-1) target cells at indicated E:T ratios analyzed by a standard 4 h europium release assay. Data from three independent experiments with CB-NK cells prepared from different http://www.jimmunol.org/ donors were combined. (C) Cytotoxicity assays of CD3+ T cells from healthy donors against CD85j-overexpressing myeloma cell lines (U266, RPMI-8226, ARP-1) target cells at an E:T ratio of 10:1 were analyzed by flow cytometry. (D) Representative histogram showing % of intracellular S100A9 expression in NK cells (open histogram) and isotype control (filled histogram). (E) NK cells were by guest on September 29, 2021 preincubated with 20 mg/ml of blocking anti-human S100A8/A9 heterodimer (clone A15105B) or isotype control. Af- ter 2 h, target cells ARP1-GFP or CD85j- expressing ARP1 were added at a ratio of 10:1 for 4 h (n = 3). (F) Ex vivo BM cells from patients with MGUS (n = 10) and MM (n = 6) cultured in the presence of 10 mg/ml of anti-CD85j Ab (clone 292319) or isotype control. After 18 h, CD38+ PC number was quantified by flow cytometry. Ligation of CD85j selectively decreased PC number in MGUS but not in MM. Differences in percentage of change in PC cell number are depicted. *p , 0.05, ***p , 0.001. The Journal of Immunology 2591

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EuroFlow antibody panels 49.Li,Z.,R.T.Luo,S.Mi,M.Sun,P.Chen,J.Bao,M.B.Neilly,N.Jayathilaka, for standardized n-dimensional flow cytometric immunophenotyping of normal, D. S. Johnson, L. Wang, et al. 2009. Consistent deregulation of gene expression between reactive and malignant leukocytes. Leukemia 26: 1908–1975. human and murine MLL rearrangement leukemias. Cancer Res. 69: 1109–1116. A B C Pre-B cells B cellscells Plasma cells *** ** ** *** x 9

1 ** Ma

MGUS f (MFI)

CD19 CD o (MFI)

% of Max Max of % % MM

MGUS

85j x CD85j CD in MM(MFI) 19 MM (MFI) MGUS in CD85j CD19 CD of Ma % of Max Max of % Pre-BP Bll cells Bll B cells PC Pre-B cells B cells PC CD38CD38 CD85jCD85j D E 3.5 34 3.6 18

MGUS 5.86

0.8 2.7

36 1.4 5.1 12

MM 3.9

0.6 7.9 CD85j inBM NK cells (MFI) SSC SSC CD38 CD19 MGUS MM CR CD85j CD56 CD20 F G 41 MGUS MGUSUS 5.9

MM 11 MM CD85j inBM DC (MFI) x a M 14 f of

SSC SSC CD123+ CD11c+ CD123+ CD11c+ CD14 CD CD123 % of Max Max of % %fM CD85j HLA-DR CD11c CD85j MGUS MM CD123+ CD11c- HLADR+CD45+CD14-CD3-CD19-CD56- Plasmacytoid DC

CD11c+ CD123- HLADR+CD45+CD14-CD3-CD19-CD56- Myeloid DC

Supplementary Fig. S1. Higher CD85j expression is associated with terminally differentiated B cell linage in bone marrow samples. (A) CD85j expression on B progenitors cells, B cells and PCs in BM aspirates from patients with MGUS. B cells were identified using a combined CD19/scatter (SSC)/forward scatter (FSC)/CD20. Progenitors B cells were separated from mature B cells using an additional CD19 vs. CD38 gate in BM from patients with MGUS and MM. Complete gating strategy is not shown. (B) Flow data summarized 20 samples per group from patients with MGUS and (C) with active MM. (D) Representative dot plots showing expression of CD85j in the whole BM compartment. (E) Low CD85j expression on NK from patients with MGUS, active MM and patients with MM in complete remission (CR). (F) Excluding the B cell lineage, most of the CD85j+ cells were CD14+ monocytes. (G) Dendritic cells (DC) also expressed CD85j, in particular; myeloid DC showed higher levels than plasmacytoid DC. No significant differences were observed in MM compared to MGUS. *p<0.05, **p<0.01 and ***p<0.001.

Supplementary Table S1. Genes differentially expressed in CD85j-overexpressing MM cells.

Upregulated genes in CD85j-overexpressing MM cells Gene Symbol p-Values q-Values RP-Values p-Values q-Values RP-Values Mean std. Dev (Down) (Down) (Down) (Up) (Up) (Up) LILRB1 0.999982 1.000043 48630.98 0 0 28.1177 5.041968 1.56083 HLA-DRA 0.994906 1.002089 44094.24 2.02E-07 0.005 48.46652 9.872869 3.51452 LILRB1 | LILRB2 0.999106 1.001011 46452.16 1.01E-06 0.016667 111.3594 4.859245 1.075464 HLA-DRA 0.982031 1.001168 41184.44 1.21E-06 0.015 118.3725 10.11554 3.28639 HLA-C 0.99975 1.000479 47499.7 3.44E-06 0.034 163.5515 8.805524 3.82125 CD74 0.997159 1.001743 45042.27 1.09E-05 0.09 223.1265 8.396598 2.783316 CD74 0.981517 1.001099 41104.75 1.38E-05 0.097143 235.3239 8.621048 2.883696 SLAMF1 0.999994 0.999994 48863.02 1.58E-05 0.0975 244.9993 5.47341 1.595815 HLA-DPA1 0.969697 0.999488 39540.07 3.04E-05 0.166667 324.5681 9.901462 3.813661 STEAP1 0.998031 1.001478 45552.53 3.14E-05 0.155 327.7962 8.888161 2.287679 CD74 0.896219 0.990305 33984.67 3.60E-05 0.161818 346.187 8.393406 2.806557 FAM65B 0.999963 1.000105 48421.64 4.07E-05 0.1675 363.5515 5.321765 0.864437 IGHG1 | IGHG3 | 0.999965 1.000086 48441.23 5.26E-05 0.2 396.7554 6.369349 2.499381 MMAA 0.999984 1.000024 48649.91 5.31E-05 0.187143 400.0954 5.618737 1.193815 HLA-DPA1 0.934183 0.995481 36365.31 5.43E-05 0.178667 402.4331 9.159699 3.74023 MCOLN2 0.998268 1.00131 45711.53 6.54E-05 0.201875 429.7778 7.236346 3.01058 RUNX3 0.90989 0.991458 34774.66 6.76E-05 0.196471 435.3457 7.430126 2.048298 BIRC3 0.997633 1.001547 45304.1 7.21E-05 0.197778 445.3074 6.910955 2.927658 PREX1 0.999989 1.00001 48744.61 7.65E-05 0.198947 454.3681 6.276042 1.908861 IFIT2 0.999773 1.000442 47566.64 8.67E-05 0.214 474.3042 4.878416 1.010586 LMO3 0.984337 1.00139 41572.47 8.85E-05 0.208095 477.7662 5.514417 1.335751 HLA-DQA1 | 0.979384 1.001385 40782.93 8.91E-05 0.2 479.3658 7.367815 3.366085 KAL1 0.999796 1.000404 47625.76 9.01E-05 0.185417 481.606 5.602461 1.726144 NR2F2 0.996441 1.001878 44699.13 9.01E-05 0.185417 482.2821 7.390465 3.363096 FAM65B 0.998631 1.001186 46002.9 9.70E-05 0.1916 493.4868 6.902623 1.671684 HLA-DPB1 0.98656 1.001712 41978.03 1.03E-04 0.195 500.1549 7.50666 3.010274 DMKN 0.999982 1.000063 48610.73 1.03E-04 0.189259 501.8851 6.200258 2.362339 ANXA1 0.476697 1.013699 19620.19 1.21E-04 0.213571 533.4844 5.402247 1.311353 FAM65B 0.998641 1.001155 46011.81 1.21E-04 0.206897 535.6658 5.586642 1.28196 IKZF2 0.997004 1.001771 44961 1.23E-04 0.202667 537.7506 7.071061 2.509565 CD70 0.984968 1.001496 41683.83 1.33E-04 0.212258 553.4954 8.060287 3.372018 CCL22 0.930079 0.995274 36077.41 1.34E-04 0.207188 555.7268 8.195998 4.186595 MMP7 0.996595 1.001869 44767.88 1.69E-04 0.253636 604.9279 7.104551 3.68241 ANXA1 0.936355 0.995669 36523.01 1.77E-04 0.256765 614.444 5.231271 1.218084 HLA-DPA1 0.911149 0.991539 34849.49 1.78E-04 0.250857 616.1361 9.318608 3.955881 HLA-DPA1 0.961815 0.998344 38695.91 1.80E-04 0.2475 620.098 8.828541 3.850339 ZDHHC14 0.999888 1.000334 47955.07 1.82E-04 0.242432 621.9424 5.939859 1.038301 SP140 0.999947 1.00015 48306.2 1.83E-04 0.237895 623.392 5.698265 1.221141 GLIS3 0.999249 1.00083 46628.82 1.92E-04 0.242821 634.4353 5.080627 0.943649 SASH3 0.997999 1.001487 45531.3 1.97E-04 0.24375 640.986 7.958142 2.031305 HLA-DQB1 | 0.999913 1.000216 48070.73 1.98E-04 0.23878 641.9634 6.035094 1.43447 HCP5 0.945754 0.997033 37241.79 2.43E-04 0.285476 695.9296 7.352978 2.72107 CD86 0.999147 1.000951 46508.47 2.46E-04 0.282093 698.9653 7.231705 3.452777 CD82 0.999916 1.000199 48085.92 2.59E-04 0.284444 716.0557 6.979796 2.592057 PTPRC 0.999925 1.000168 48143.95 2.59E-04 0.284444 716.4642 6.482904 2.727456 HMOX1 0.999955 1.000138 48356.19 2.66E-04 0.285652 723.4048 6.809374 0.856205 YME1L1 0.999968 1.000069 48468.68 2.67E-04 0.281064 725.4542 6.691758 1.852235 FGR 0.99996 1.000122 48396.78 2.74E-04 0.282292 732.1028 6.000603 1.490376 HLA-F 0.997242 1.001724 45084.4 2.86E-04 0.288571 742.9478 8.462542 2.340346 IL7 0.998037 1.001464 45557.23 2.92E-04 0.2884 748.7856 4.964946 1.329185 ANXA1 0.634497 0.988838 24075.76 2.98E-04 0.288431 753.5312 5.642057 1.201862 PTPRC 0.999777 1.000425 47576.43 3.04E-04 0.288462 758.0108 6.734039 2.895072 HLA-F 0.998613 1.001228 45987.11 3.05E-04 0.284151 759.0084 7.774705 2.076247 HLA-DQA1 | 0.883244 0.988127 33293.18 3.12E-04 0.285185 764.2493 8.227576 4.064154 HLA-F 0.992658 1.002196 43384 3.25E-04 0.291818 773.3065 8.934346 2.457163 PLEK 0.999885 1.000351 47938.9 3.37E-04 0.296964 785.99 7.068707 3.047286 HLA-DPB1 0.982045 1.0011 41187 3.50E-04 0.303333 798.1633 6.941301 2.723632 RUNX3 0.941362 0.996295 36897.81 3.50E-04 0.303333 798.3801 7.271208 1.408837 CD109 0.999841 1.000347 47781.71 3.55E-04 0.297458 804.9943 6.186646 0.91399 ATP1B1 0.999771 1.00048 47557.74 3.58E-04 0.294333 807.4394 7.690291 2.941936 MMP7 0.999618 1.000591 47207.73 3.75E-04 0.303607 818.9743 6.888569 2.825505 IFITM1 0.812359 0.982229 30102.68 3.81E-04 0.303871 823.6065 10.44203 1.701043 IFITM1 0.949126 0.997119 37521.07 3.83E-04 0.300317 825.0129 10.4068 1.534183 NLRC5 0.999328 1.000706 46737.29 3.89E-04 0.300156 828.8532 6.750536 0.930468 LMO3 0.958886 0.997925 38407.93 3.91E-04 0.296769 829.9669 4.209131 0.835175 SPINK2 0.073373 1.052448 7234.121 4.18E-04 0.312424 847.7315 5.491201 2.181236 PLAC8 0.999354 1.000671 46772.21 4.22E-04 0.311194 851.2158 5.254221 1.112892 HLA-F 0.983791 1.001268 41476.22 4.29E-04 0.311471 856.8535 9.452239 2.270719 LMO3 0.999773 1.000461 47565.43 4.31E-04 0.308696 857.9879 5.165162 1.40824 DMKN 0.99841 1.001289 45816.06 4.44E-04 0.313 866.507 6.238406 2.380309 PPP1R3B 0.966672 0.999415 39199.61 4.48E-04 0.311831 870.0522 6.32497 1.325478 FAM65B 0.999369 1.000626 46795.24 4.50E-04 0.30875 871.7875 5.312436 0.795702 MKNK2 0.999937 1.00016 48227.49 4.62E-04 0.312466 880.8102 5.765718 1.025046 HLA-DQB1 | 0.993647 1.002006 43681.63 4.63E-04 0.309324 882.0148 8.100247 3.641307 NBEAL2 0.999821 1.000368 47712.59 4.73E-04 0.311467 887.41 5.948127 0.593428 MFHAS1 0.999906 1.000271 48042.77 4.74E-04 0.308026 887.9542 7.003314 1.572437 NMI 0.996806 1.001755 44866.14 4.85E-04 0.311299 896.5738 7.643825 2.012471 TSPAN12 0.999908 1.000252 48050.4 5.03E-04 0.318205 909.4387 5.831832 1.707001 C14orf105 0.999638 1.000509 47248.16 5.11E-04 0.319494 915.7806 6.65662 2.889699 MS4A1 0.976198 1.001132 40344.75 5.36E-04 0.330875 931.6271 7.751305 4.08113 PCDH17 0.974062 1.00025 40070.9 5.53E-04 0.337284 942.1806 4.671246 1.011141 LMO3 0.999851 1.000337 47817.9 5.58E-04 0.335976 944.7844 4.102638 0.775715 DYNC1H1 0.091722 1.068599 8037.299 5.65E-04 0.336386 948.7963 5.876919 0.725361 STAG3 0.999117 1.000961 46470.89 5.67E-04 0.333571 949.915 6.426348 2.673431 PIK3CD 0.998609 1.001245 45983.84 5.69E-04 0.330706 951.2003 4.590853 0.739251 RUNX3 0.429069 1.026249 18326.42 5.73E-04 0.329186 954.911 6.88198 1.431333 CCL3 0.992554 1.002193 43356.22 6.18E-04 0.350805 982.6239 9.002639 2.500063 TRAC | TRAJ17 0.999515 1.00071 47010.22 6.54E-04 0.366818 1002.51 5.997766 2.007663 TESPA1 0.808663 0.982233 29956.15 6.55E-04 0.363708 1003.537 5.522532 1.695121 CD48 0.999905 1.000289 48032.7 6.56E-04 0.359889 1003.929 7.204808 0.951663 ZMYM6 0.602344 0.990786 23127.78 6.65E-04 0.360879 1008.999 5.214225 0.593003 LINC00158 0.917508 0.992966 35240.64 6.78E-04 0.363696 1016.571 7.42318 4.017969 LAT2 0.994998 1.002079 44127.7 6.83E-04 0.362581 1018.963 6.544524 1.338415 PLS1 0.999793 1.000421 47616.94 6.87E-04 0.361064 1022.27 6.846965 2.340993 TNFRSF10D 0.90658 0.991131 34577.31 6.97E-04 0.362526 1028.639 7.77286 2.304091 ALOX5AP 0.923375 0.994153 35621.53 7.10E-04 0.365104 1034.873 9.423654 1.592668 PACRGL 0.993609 1.00207 43669.11 7.21E-04 0.367217 1039.562 4.829552 0.404245 OR5H6 0.963804 0.998604 38894.86 7.33E-04 0.369184 1044.234 5.305377 1.28942 HLA-DPB1 0.948327 0.997128 37454.01 7.36E-04 0.367273 1046.021 7.21454 3.079184 NMI 0.982264 1.001157 41223.05 7.58E-04 0.3742 1058.423 8.319423 2.090582 MRPS11 0.994316 1.002047 43891.87 7.63E-04 0.373267 1060.658 4.844696 0.471698 CD44 0.998976 1.001166 46313.51 7.64E-04 0.369804 1061.016 7.534641 2.28627 --- 0.980214 1.001217 40906.63 7.71E-04 0.369806 1064.954 4.570632 0.737693 SLC9A7 0.99992 1.000183 48111.95 7.73E-04 0.367115 1065.997 4.913298 1.044323 HLA-DPB1 0.995203 1.00204 44207.66 7.81E-04 0.367143 1070.327 7.277245 2.944067 BCL2A1 0.988808 1.001831 42433.25 8.21E-04 0.382359 1092.397 7.395057 3.822832 CREB5 | 0.524395 1.003285 20923.8 8.29E-04 0.382523 1097.204 5.495524 1.514765 CPEB1 0.997539 1.001534 45251.48 8.46E-04 0.386852 1105.536 4.066673 0.612831 AAGAB 0.797215 0.982121 29504.53 8.53E-04 0.38633 1107.758 6.169582 0.584365 PRRX1 0.998536 1.001355 45920.57 8.80E-04 0.394909 1121.192 6.616998 2.742794 SKAP1 0.47102 1.013762 19464.42 9.11E-04 0.405315 1136.48 7.791151 1.563339 CD80 0.998783 1.001114 46132.88 9.36E-04 0.412857 1148.172 6.529991 2.786228 LRCH1 0.989058 1.001817 42490.21 9.54E-04 0.416814 1155.447 4.350341 0.371247 LMNA 0.99764 1.001533 45306.79 9.55E-04 0.41386 1156.043 8.693904 1.536389 HLA-DQA1 | 0.768322 0.980931 28424.07 9.56E-04 0.410435 1156.293 8.377069 4.309893 MT2A 0.930812 0.995303 36127.82 9.58E-04 0.407931 1157.292 11.2289 2.578884 VCAN 0.99884 1.001151 46182.64 9.66E-04 0.407778 1161.214 4.982957 0.881198 GPR183 0.999894 1.000319 47978.84 9.72E-04 0.406695 1163.837 6.047065 2.012494 PTPRC 0.993629 1.002008 43676.32 9.87E-04 0.409664 1170.366 6.825653 2.967039 SLITRK6 0.887447 0.98873 33511.96 9.93E-04 0.408583 1173.235 5.687835 1.822324 BTN3A3 0.98733 1.001855 42129.95 9.94E-04 0.40562 1173.905 5.42565 1.2982 Downregulated genes in CD85j-overexpressing MM cells Gene Symbol p-Values q-Values RP-Values p-Values q-Values RP-Values Mean std. Dev (Down) (Down) (Down) (Up) (Up) (Up) RAP1A 0 0 1.817121 1 1 49384.33 8.946828 3.991914 CTHRC1 8.10E-07 0.02 102.6426 0.998158 1.002339 45638.1 6.477659 3.052639 SDC1 1.21E-06 0.02 115.3319 0.999916 1.000503 48087.13 7.760902 3.672593 EMC10 1.21E-06 0.02 115.8247 0.996815 1.002764 44870.06 8.147416 3.895482 DEPTOR 1.42E-06 0.014 122.8198 0.999986 1.000088 48706.73 7.628511 3.327848 DEPTOR 2.23E-06 0.018333 135.6626 0.999943 1.000327 48270.97 8.275993 3.357752 IGJ 2.23E-06 0.018333 144.0136 0.897457 0.991029 34054.88 9.135604 3.826184 MGST2 2.63E-06 0.01625 148.2506 0.999998 1.000038 49018.15 6.223787 2.34462 IGJ 2.83E-06 0.015556 151.0693 0.923996 0.9948 35662.34 9.926764 3.732183 ST3GAL6 7.90E-06 0.039 207.1415 0.999999 1.000019 49138.42 6.851967 3.015651 CTHRC1 7.90E-06 0.039 208.7439 0.960118 0.999566 38529.25 5.436716 2.592764 PRDM1 1.72E-05 0.070833 252.1296 0.995518 1.003217 44326.24 8.469302 3.158411 ITM2B 1.96E-05 0.074615 267.4757 0.98925 1.003782 42531.16 7.631747 3.546187 MAN1A1 2.00E-05 0.066 269.8793 0.999997 1.000058 48998.4 6.232025 1.370096 REEP1 2.00E-05 0.066 270.2051 0.999794 1.000706 47619.44 5.163288 2.317947 CHPT1 2.21E-05 0.068125 280.0551 0.950095 0.998391 37603.69 7.38634 3.281808 BZW2 2.39E-05 0.069412 286.6931 0.98485 1.003297 41663.75 8.021938 3.352757 HSPB1 2.65E-05 0.072778 306.779 0.99997 1.000153 48496.17 8.53412 3.206559 GALNT1 2.81E-05 0.073158 311.3224 0.951224 0.998558 37701.88 7.416794 2.550189 OAT 3.38E-05 0.0835 341.8523 0.99965 1.000866 47273.69 7.383634 3.134735 EVI2A 3.60E-05 0.084762 346.7972 0.996484 1.003065 44716.79 7.734199 3.190231 CTSB 4.21E-05 0.094545 367.2976 0.650034 0.988989 24542.19 7.93791 3.508932 FAM46C 4.23E-05 0.09087 368.0718 0.997147 1.002588 45036 7.572172 3.383921 NAP1L2 4.47E-05 0.092083 376.8525 0.999995 1.000076 48882.83 5.562822 1.746636 HIST1H2BK 4.78E-05 0.0944 385.0695 0.998476 1.002026 45872.09 10.84186 2.43382 BZW2 4.86E-05 0.088889 388.1301 0.994556 1.003599 43971.7 7.406572 3.345976 HIST1H2AG | 4.86E-05 0.088889 388.2231 0.999934 1.00042 48201.48 5.59334 1.86962 DEPTOR 5.14E-05 0.090714 393.1644 0.999938 1.000343 48229.07 7.335974 3.046466 CYB561 5.35E-05 0.091034 401.6275 0.991624 1.004025 43102.6 7.457168 3.221392 TWSG1 5.47E-05 0.09 402.6697 0.999963 1.000186 48421.88 5.62375 1.852347 FUCA2 5.53E-05 0.088065 405.5057 0.894801 0.990355 33906.18 7.138769 3.46278 APP 5.73E-05 0.088438 411.5617 0.744599 0.984467 27584.65 6.822347 3.125264 PRDM1 7.67E-05 0.114848 455.2282 0.974636 1.001319 40141.41 7.612625 2.780155 CTHRC1 7.82E-05 0.113529 457.6188 0.916384 0.993579 35170.12 5.850292 2.73125 APP 7.92E-05 0.111714 462.0934 0.926714 0.994994 35846.38 6.799336 3.208237 METTL7A 7.98E-05 0.109444 463.2628 0.956121 0.998879 38143.82 8.318757 3.212201 CTSB 8.91E-05 0.118919 479.1602 0.541128 1.004516 21387.59 7.832486 3.442147 S100A11 9.66E-05 0.125526 491.8095 0.999895 1.000604 47985.2 7.415381 3.328351 ABLIM1 1.04E-04 0.132308 505.2244 0.999476 1.001138 46945.83 5.26781 1.338088 APLP2 1.05E-04 0.12925 505.8985 0.888356 0.989096 33559.55 8.169789 2.637175 NDFIP1 1.05E-04 0.127073 506.3587 0.966666 1.000268 39199.08 7.281133 3.158694 COTL1 1.07E-04 0.125476 508.8855 0.999529 1.00107 47036.59 6.351185 2.396061 AMPD1 1.11E-04 0.127209 517.8104 0.997674 1.002465 45326.45 6.946305 2.723859 APP 1.16E-04 0.130455 526.1586 0.997768 1.002538 45385.69 6.675953 2.929521 IGHA1 1.17E-04 0.128889 527.1032 0.563151 1.000279 22006.56 8.199583 3.445952 ITM2B 1.21E-04 0.130435 536.0976 0.973194 1.001191 39962.01 7.753211 3.385693 IGH | IGHA1 | 1.23E-04 0.129574 538.0627 0.625918 0.991773 23821.3 7.392437 3.74145 NBPF1 1.32E-04 0.135833 550.46 0.999924 1.000471 48138.09 7.045 2.008072 CPEB4 1.33E-04 0.134286 554.1166 0.99996 1.000243 48393.66 5.755141 1.111762 REEP1 1.33E-04 0.134286 554.2524 0.999977 1.000139 48575.79 5.224894 1.711204 MACROD2 1.40E-04 0.13549 564.7139 0.694145 0.986392 25912.99 6.680708 3.091002 ADM 1.44E-04 0.136346 569.8236 0.992694 1.003812 43393.49 7.195353 3.18419 TPBG 1.58E-04 0.14717 590.4048 0.999638 1.000915 47247.22 5.102583 1.095914 AGTRAP 1.64E-04 0.14963 599.7513 0.999736 1.00079 47457.61 7.266592 1.435723 ITGB1 1.69E-04 0.152182 604.7935 0.992518 1.003799 43345.4 7.452557 3.147807 REXO2 1.72E-04 0.151429 609.1834 0.997929 1.002558 45484.87 7.777522 2.667794 ITGA6 1.72E-04 0.148947 609.5966 0.999982 1.000104 48632.69 5.031933 1.31272 TPM1 1.74E-04 0.148103 611.7682 0.999888 1.000637 47949.43 5.379451 1.106996 AQP3 1.78E-04 0.148644 615.734 0.938082 0.996754 36649.77 6.360984 2.427861 FAM46C 1.84E-04 0.151333 623.8317 0.981995 1.002828 41178.01 7.004073 3.294757 SPECC1 1.86E-04 0.15082 627.129 0.996546 1.002963 44745.8 4.615854 1.036475 IGH 1.87E-04 0.148871 628.7897 0.946181 0.997824 37275.56 7.20025 3.155459 STOM 1.94E-04 0.152381 637.59 0.999959 1.000263 48374.21 6.911115 2.522043 CNOT6L 1.96E-04 0.150938 639.1497 0.998051 1.002395 45568.56 6.937239 2.608952 HIST1H2BD 2.07E-04 0.157538 654.0844 0.999961 1.000225 48414.23 6.465129 2.008978 COCH 2.24E-04 0.167576 671.8218 0.999962 1.000205 48416.65 5.174547 1.490286 HIST1H2BC | 2.26E-04 0.166418 674.191 0.999339 1.001265 46752.44 4.947573 1.457702 HPCAL1 2.35E-04 0.170441 686.6169 0.818108 0.983762 30336.06 8.188382 2.758875 IGH | IGHA2 2.38E-04 0.17 690.5972 0.667001 0.988611 25061.61 8.874199 3.507435 TWSG1 2.39E-04 0.168714 692.4295 0.999787 1.00074 47600.27 5.579195 1.941456 FUCA2 2.43E-04 0.169155 696.1792 0.626148 0.991628 23827.99 7.24895 3.314306 SLC46A3 2.43E-04 0.166944 697.1993 0.999981 1.000123 48607.68 5.682735 1.079681 TCEAL1 2.47E-04 0.16726 700.9454 0.999558 1.001037 47086.05 6.161452 1.502088 FOXO3 | 2.53E-04 0.168784 708.5206 0.990153 1.003894 42738.87 9.200766 2.369172 BZW2 2.60E-04 0.170933 716.5115 0.974178 1.001327 40084.97 6.891653 2.924615 MDK 2.66E-04 0.172895 723.0238 0.999921 1.000488 48113.28 5.961921 1.988242 ZNF75A 2.66E-04 0.172895 723.2412 0.999954 1.000279 48351.63 5.054979 1.154584 STOM 2.67E-04 0.169359 725.2571 0.998861 1.001721 46200 6.474247 2.806655 SFRP2 2.67E-04 0.169359 725.3783 0.995016 1.003468 44135.36 4.156391 0.859968 BZW2 2.69E-04 0.165875 727.1706 0.987141 1.003539 42093.27 6.809831 3.113894 APP 2.81E-04 0.171111 738.4315 0.704117 0.986175 26233.41 6.915389 3.202629 TES 2.86E-04 0.172439 742.8316 0.985334 1.003355 41749.4 7.062534 2.977605 BAG4 2.92E-04 0.173855 749.1368 0.300586 1.03911 14814.08 6.01886 0.955088 IGHA1 3.03E-04 0.177857 756.887 0.799535 0.982846 29595.11 8.311678 3.507483 SDC1 3.12E-04 0.181176 764.2251 0.999717 1.000852 47410.38 6.511529 2.396112 FOXO3 3.20E-04 0.183954 770.2574 0.999706 1.000881 47386.18 7.062241 1.99836 MYBPC2 3.30E-04 0.187126 778.8239 0.994369 1.003554 43909.94 7.632471 3.289088 PRKACB 3.83E-04 0.215 824.8983 0.999927 1.000454 48153.68 6.344884 1.654969 HTATIP2 3.83E-04 0.215 825.1242 0.999965 1.000167 48441.18 5.807018 1.935315 HSPA1A | 3.85E-04 0.211111 826.3782 0.936534 0.996867 36535.28 6.538122 3.49052 AQP3 3.93E-04 0.213516 831.1774 0.999434 1.001136 46883.82 4.858983 1.200519 FGFR3 3.93E-04 0.213516 831.2749 0.980227 1.002661 40908.62 5.44759 3.455073 CLEC2B 4.01E-04 0.213011 835.946 0.821921 0.984153 30492.59 5.100328 3.597956 TENM3 4.04E-04 0.21234 838.5728 0.999947 1.000292 48307.61 6.040156 2.588159 HSPA6 | HSPA7 4.17E-04 0.216526 846.8983 0.650662 0.988847 24561.04 6.28919 2.051519 FAM213A 4.17E-04 0.214583 847.0873 0.99526 1.003428 44229.52 6.700031 2.72712 PCDH1 4.26E-04 0.216804 854.4793 0.998428 1.002121 45829.91 4.618787 0.91635 KIAA0125 | 4.44E-04 0.223571 866.4161 0.997077 1.002599 44997.33 7.89301 2.216695 YPEL5 4.45E-04 0.222222 868.2434 0.998621 1.001826 45993.97 7.218917 1.878313 TIGD7 4.60E-04 0.2273 879.7075 0.998605 1.001851 45979.99 5.256242 1.640049 LOC100509445 | 4.61E-04 0.225446 879.9136 0.999099 1.001573 46445.16 7.632586 2.520425 CMTM7 4.72E-04 0.228333 886.1611 0.999209 1.001338 46577.68 6.575469 2.82594 FOXP1 4.74E-04 0.227476 888.2593 0.900151 0.9913 34206.18 6.448881 2.732592 PPIC 4.77E-04 0.224381 889.8445 0.985595 1.003269 41797.35 5.147021 1.552583 MACROD2 4.77E-04 0.224381 889.8513 0.999337 1.001283 46749.56 5.518372 2.279231 APP 4.83E-04 0.225094 895.1133 0.994017 1.003527 43796.5 7.008736 3.437067 IGH | IGHA2 4.85E-04 0.224019 896.6881 0.572161 0.998472 22260.41 8.112621 3.211016 H1FX 4.95E-04 0.226389 903.299 0.695307 0.986481 25950.68 7.441085 2.939426 TUFT1 4.97E-04 0.225321 905.4934 0.999581 1.00102 47133.06 5.904376 1.96119 APP 5.06E-04 0.227091 911.533 0.987596 1.003403 42184 6.496718 3.024477 GYPC 5.07E-04 0.225496 912.0949 0.983177 1.003206 41376 7.487533 2.325877 GRAMD3 5.19E-04 0.229018 920.949 0.95125 0.998521 37704.13 4.305205 1.044001 CTSB 5.20E-04 0.227168 921.2158 0.957137 0.999052 38240.06 6.984734 2.974248 GRAMD3 5.20E-04 0.225439 921.8969 0.991093 1.003941 42965.69 4.77852 1.614658 MAF 5.26E-04 0.225739 925.6022 0.993586 1.003625 43662 6.74614 3.601378 KANK1 5.35E-04 0.227672 931.2228 0.693561 0.98627 25893.83 7.237242 3.274709 PLIN2 5.58E-04 0.235556 945.0948 0.99979 1.000722 47609.41 6.336972 2.029168 STOM 6.06E-04 0.253559 976.1825 0.999131 1.001504 46486.13 7.183655 3.082306 SNCAIP 6.25E-04 0.259412 987.2777 0.956342 0.998898 38164.44 4.626559 1.004166 C11orf71 6.28E-04 0.258583 988.6255 0.999908 1.000557 48054.63 6.390508 1.575161 CAV1 6.32E-04 0.257769 990.5013 0.995153 1.003463 44187.44 7.752215 2.526842 ELK3 6.33E-04 0.254065 991.4763 0.962174 0.999472 38731.38 7.026692 2.709804 PIK3CG 6.33E-04 0.254065 991.5084 0.999902 1.000571 48023.73 4.597274 0.631429 SERPINB1 6.45E-04 0.256855 997.6331 0.999886 1.000656 47944.82 6.089438 2.449172 ITM2C 6.58E-04 0.25992 1004.917 0.933942 0.996234 36347.81 7.423804 2.702957 FOXO3 | 6.67E-04 0.261587 1010.805 0.99536 1.003345 44266.42 8.372184 2.18995 APP 6.94E-04 0.27 1026.919 0.98407 1.003433 41525.13 6.777678 3.00148 UCHL1 7.16E-04 0.276406 1037.955 0.918262 0.993566 35288.98 5.326146 3.417247 ZNRF2 7.42E-04 0.284186 1049.586 0.995321 1.003326 44252.51 4.872591 1.148406 RRAGD 7.46E-04 0.283231 1051.701 0.99801 1.002496 45538.82 6.760084 2.839166 IGH | IGHA1 | 7.60E-04 0.286412 1059.013 0.497301 1.009691 20182.49 7.580088 3.427707 MDK 7.63E-04 0.28553 1060.492 0.997585 1.002477 45275.62 5.721571 1.299168 ZNF544 7.79E-04 0.289323 1069.872 0.996544 1.002982 44745.09 5.8069 1.859768 TNFRSF18 7.95E-04 0.293134 1078.93 0.999868 1.000658 47872.78 5.791623 1.740376 HIST1H2BJ 8.02E-04 0.293481 1081.851 0.999945 1.00031 48293.4 6.286015 2.088477 NUB1 8.07E-04 0.293162 1085.09 0.958243 0.999319 38345.82 6.262593 1.617541 REXO2 8.12E-04 0.290652 1087.207 0.994938 1.003554 44105.51 7.577467 2.876939 STAU2 8.12E-04 0.290652 1087.217 0.999936 1.000362 48218.47 7.136847 1.099901 MXI1 8.17E-04 0.290432 1090.326 0.999846 1.000677 47803.5 6.451098 1.685873 MGAT1 8.19E-04 0.288857 1091.354 0.999935 1.000401 48209.15 7.206955 1.053352 HSPA13 8.20E-04 0.287376 1092.006 0.937321 0.996803 36593.74 5.838448 0.873585 C1orf53 8.35E-04 0.290423 1100.21 0.625027 0.991729 23794.38 6.26704 1.916376 FOXO3 8.43E-04 0.291259 1103.933 0.995398 1.003342 44279.46 8.135 2.330797 CAV1 8.45E-04 0.289653 1104.516 0.996966 1.002692 44943.57 7.663863 2.596669 GRAMD3 8.45E-04 0.287931 1104.878 0.767183 0.98357 28382.36 4.511858 1.387082 GNG7 8.57E-04 0.289932 1110.08 0.612457 0.993653 23422.8 7.303236 2.773072 PPP1R1A 8.57E-04 0.288027 1110.224 0.99587 1.003101 44462.29 4.343754 0.841887 CYTIP 8.82E-04 0.294257 1122.232 0.999899 1.000588 48010.76 4.776947 0.803011 SEPT10 8.87E-04 0.294094 1124.658 0.812959 0.983725 30127.07 5.498345 1.35423 BTG2 8.91E-04 0.293333 1127.976 0.999914 1.000542 48079.02 5.343866 1.20372 TCEAL4 9.19E-04 0.300464 1140.388 0.993398 1.003784 43601.62 8.248315 0.971823 SLC25A20 9.30E-04 0.302039 1144.569 0.999935 1.00038 48209.64 7.792193 1.423574 DERL3 9.37E-04 0.302484 1148.57 0.931992 0.996047 36209.22 6.164647 1.522277 SPIN3 9.40E-04 0.301299 1150.067 0.99971 1.000866 47396.77 6.775266 1.210838 BLOC1S5- 9.64E-04 0.307226 1160.27 0.907897 0.992395 34654.87 11.16417 2.104875 FYN 9.69E-04 0.306731 1162.258 0.995782 1.003217 44428.77 6.68599 2.649441 LOC101929740 | 9.84E-04 0.309618 1169.522 0.998049 1.002413 45565.86 6.564261 1.930025 FUCA1 9.99E-04 0.312152 1176.012 0.999748 1.000782 47492.78 5.102075 1.518295 Supplementary Table S2. Functional Analysis of genes differentially expressed in CD85j-overexpressing MM cells Functional Analysis of upregulated genes in CD85j-overexpressing MM cells Term Cou % PValue Genes List Pop Pop Fold Bonferroni Benjamini FDR nt Total Hits Total Enrich ment GO:0060333~interferon-gamma-mediated 14 13.9 4.67E-17 HLA-DQB1, NMI, HLA-DRB1, HLA-DRB3, HLA-C, HLA- 90 71 16787 36.779 3.28E-14 3.28E-14 7.05E-14 signaling pathway DQA1, HLA-F, CD44, MT2A, HLA-DRB4, HLA-DRB5, HLA- DPA1, HLA-DPB1, HLA-DRA

GO:0002504~antigen processing and 10 9.9 6.06E-16 HLA-DQB1, HLA-DRB1, HLA-DRB3, HLA-DRB4, HLA- 90 21 16787 88.82 3.90E-13 1.95E-13 8.33E-13 presentation of peptide or polysaccharide DRB5, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA- antigen via MHC class II DRA GO:0031295~T cell costimulation 12 11.9 2.86E-13 HLA-DQB1, CD86, TRAC, HLA-DRB1, CD80, HLA-DRB3, 90 78 16787 28.696 2.01E-10 6.71E-11 4.32E-10 HLA-DRB4, HLA-DRB5, HLA-DPA1, HLA-DPB1, HLA- DQA1, HLA-DRA GO:0006955~immune response 20 19.8 5.60E-13 HLA-DQB1, GPR183, CCL3, HLA-DRB1, IL7, HLA-DRB3, 90 420 16787 8.882 3.93E-10 9.83E-11 8.44E-10 HLA-C, CD70, CD74, HLA-DQA1, HLA-F, LILRB2, CD86, CCL22, TNFRSF10D, HLA-DRB4, HLA-DRB5, HLA-DPA1, HLA-DPB1, HLA-DRA GO:0050852~T cell receptor signaling pathway 13 12.9 2.02E-11 HLA-DQB1, PTPRC, TRAC, HLA-DRB1, HLA-DRB3, 90 149 16787 16.274 1.42E-08 2.84E-09 3.05E-08 PIK3CD, HLA-DRB4, HLA-DRB5, HLA-DPA1, HLA-DPB1, SKAP1, HLA-DQA1, HLA-DRA GO:0019886~antigen processing and 11 10.9 5.28E-11 HLA-DQB1, HLA-DRB1, HLA-DRB3, HLA-DRB4, HLA- 90 92 16787 22.302 3.71E-08 6.19E-09 7.97E-08 presentation of exogenous peptide antigen via DRB5, HLA-DPA1, HLA-DPB1, DYNC1H1, CD74, HLA- MHC class II DQA1, HLA-DRA GO:0002381~immunoglobulin production 5 5.0 1.10E-08 HLA-DQB1, HLA-DRB1, HLA-DRB3, HLA-DRB4, HLA- 90 6 16787 155.44 7.72E-06 1.10E-06 1.66E-05 involved in immunoglobulin mediated immune DRB5 response GO:0002455~humoral immune response 5 5.0 5.08E-08 HLA-DQB1, HLA-DRB1, HLA-DRB3, HLA-DRB4, HLA- 90 8 16787 116.58 3.57E-05 4.47E-06 7.67E-05 mediated by circulating immunoglobulin DRB5

GO:2001179~regulation of interleukin-10 4 4.0 5.74E-07 HLA-DRB1, HLA-DRB3, HLA-DRB4, HLA-DRB5 90 4 16787 186.52 4.03E-04 4.48E-05 8.66E-04 secretion GO:0002250~adaptive immune response 9 8.9 9.99E-07 LILRB1, GPR183, LILRB2, LAT2, CD86, PIK3CD, ANXA1, 90 145 16787 11.577 7.02E-04 7.02E-05 0.0015078 IGHM, SKAP1 GO:0032673~regulation of interleukin-4 4 4.0 1.43E-06 HLA-DRB1, HLA-DRB3, HLA-DRB4, HLA-DRB5 90 5 16787 149.22 0.0010045 9.14E-05 0.0021571 production GO:0042130~negative regulation of T cell 6 5.9 1.64E-06 LILRB1, LILRB2, HLA-DRB1, HLA-DRB3, HLA-DRB4, HLA- 90 38 16787 29.451 0.0011487 9.58E-05 0.0024671 proliferation DRB5 GO:0019882~antigen processing and 6 5.9 4.32E-06 HLA-DRB1, HLA-C, HLA-DPA1, CD74, HLA-DQA1, HLA- 90 46 16787 24.329 0.0030314 2.34E-04 0.0065162 presentation DRA Functional Analysis of downregulated genes in CD85j-overexpressing MM cells Term Cou % PValue Genes List Pop Pop Fold Bonferroni Benjamini FDR nt Total Hits Total Enrich ment GO:0019731~antibacterial humoral response 12 9.2 7.96E-15 APP, HIST1H2BC, HIST1H2BD, ADM, HIST1H2BK, 116 45 16787 38.591 6.71E-12 6.71E-12 1.23E-11 HIST1H2BE, HIST1H2BF, HIST1H2BG, HIST1H2BI, HIST1H2BJ, IGHA1, IGHA2 GO:0002227~innate immune response in 8 6.1 2.56E-10 HIST1H2BC, HIST1H2BD, HIST1H2BK, HIST1H2BE, 116 25 16787 46.309 2.14E-07 1.07E-07 3.95E-07 mucosa HIST1H2BF, HIST1H2BG, HIST1H2BI, HIST1H2BJ

GO:0050830~defense response to Gram- 10 7.6 6.45E-09 APP, HIST1H2BC, HIST1H2BD, ADM, HIST1H2BK, 116 85 16787 17.025 5.41E-06 1.80E-06 9.96E-06 positive bacterium HIST1H2BE, HIST1H2BF, HIST1H2BG, HIST1H2BI, HIST1H2BJ GO:0006334~nucleosome assembly 10 7.6 1.25E-07 HIST1H2BC, HIST1H2BD, HIST1H2BK, HIST1H2BE, 116 119 16787 12.161 1.05E-04 2.62E-05 1.93E-04 HIST1H2BF, HIST1H2BG, HIST1H2BI, HIST1H2BJ, H1FX, NAP1L2 GO:0006342~chromatin silencing 6 4.6 1.51E-05 HIST1H2AG, HIST1H2AI, HIST1H2AH, HIST1H2AK, 116 46 16787 18.876 0.0126261 0.0025381 0.02339 HIST1H2AM, HIST1H2AL GO:0070370~cellular heat acclimation 3 2.3 2.77E-04 HSPA6, HSPA1A, HSPA1B 116 4 16787 108.54 0.2071647 0.0379511 0.426458 GO:0031397~negative regulation of protein 4 3.1 0.0029599 CAV1, FYN, HSPA1A, HSPA1B 116 42 16787 13.782 0.9168432 0.2990296 4.475387 ubiquitination GO:0042026~protein refolding 3 2.3 0.0046085 HSPA6, HSPA1A, HSPA1B 116 15 16787 28.943 0.9792545 0.3839508 6.8861007 GO:0045665~negative regulation of neuron 4 3.1 0.0084471 CAV1, APP, FOXO3, ITGB1 116 61 16787 9.4895 0.999189 0.5465201 12.280726 differentiation GO:1904722~positive regulation of mRNA 2 1.5 0.0136546 HSPA1A, HSPA1B 116 2 16787 144.72 0.9999902 0.6844728 19.132774 endonucleolytic cleavage involved in unfolded protein response GO:1902380~positive regulation of 2 1.5 0.0136546 HSPA1A, HSPA1B 116 2 16787 144.72 0.9999902 0.6844728 19.132774 endoribonuclease activity GO:0042476~odontogenesis 3 2.3 0.0156572 SDC1, TUFT1, AQP3 116 28 16787 15.505 0.9999982 0.6999085 21.632045 GO:0045214~sarcomere organization 3 2.3 0.0167426 TPM1, ITGB1, FOXP1 116 29 16787 14.971 0.9999993 0.6928736 22.956154 GO:0046718~viral entry into host cell 4 3.1 0.0175642 HSPA1A, HSPA1B, CTSB, ITGB1 116 80 16787 7.2358 0.9999997 0.6813429 23.944559 GO:0070434~positive regulation of nucleotide- 2 1.5 0.0204124 HSPA1A, HSPA1B 116 3 16787 96.477 1 0.7094388 27.279864 binding oligomerization domain containing 2 signaling pathway GO:2000035~regulation of stem cell division 2 1.5 0.0204124 SFRP2, NAP1L2 116 3 16787 96.477 1 0.7094388 27.279864

GO:0051384~response to glucocorticoid 4 3.1 0.021245 CAV1, SDC1, ADM, MDK 116 86 16787 6.731 1 0.6991401 28.22882