PDL1 Expression on Plasma and Dendritic Cells in Myeloma Bone Marrow Suggests Benefit of Targeted anti PD1-PDL1 Therapy

<div><p>In this study we set out to investigate whether anti PDL1 or PD–1 treatment targeting the immune system could be used against multiple myeloma. DCs are important in regulating T cell responses against tumors. We therefore determined PDL1 and PDL2 expression on DC populations in bone marrow of patients with plasma cell disorders using multicolour Flow Cytometry. We specifically looked at CD141⁺ and CD141^- myeloid and CD303⁺ plasmacytoid DC. The majority of plasma cells (PC) and DC subpopulations expressed PDL1, but the proportion of positive PDL1+ cells varied among patients. A correlation between the proportion of PDL1⁺ PC and CD141⁺ mDC was found, suggesting both cell types could down-regulate the anti-tumor T cell response.</p></div

Expression of PDL1 on PC and monocytes in myeloma bone marrow.

<p>(A) PDL1 on plasma cells: Bone marrow cells were stained with antibodies against CD45, CD138, CD38, CD19, and CD274 (PDL1). Gates were set on FSC and SSC and doublets and CD19+ cells were excluded. Gating strategy is shown in Fig A in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139867#pone.0139867.s002" target="_blank">S2 File</a>. The distribution of % PDL1⁺ PC in the bone marrow of patients (n = 14) is shown. (B) Proportion of PDL1⁺ PC does not increase with tumor load. The % PDL1⁺ gated CD38⁺CD19^- PC versus % bone marrow plasma cells is plotted. Each dot represents one patient. P values were calculated from a Spearman’s test (n = 14). (C) PDL1 on monocytes and DCs: Bone marrow cells were stained with antibodies against lineage (CD3, CD19, CD56, CD138, CD15, CD34, and CD235a), CD45, HLADR, and CD11c. The gating strategy is shown in Supplementary S1B Fig. Gates were set on FSC and SSC, doublets excluded, and gates further set on lineage- CD45⁺cells. Figure shows distribution of % PDL1+ monocytes/DC in the bone marrow of patients (n = 14). (D) Correlation of % PDL1+ PC and monocytes/DC; % PDL1⁺CD11c⁺DR⁺ monocytes/DC versus % PDL1⁺CD38⁺CD19^- plasma cells is plotted. Each dot represents one patient. P value was calculated from a Spearman’s test.</p

DC subtypes express PDL1 in myeloma bone marrow.

<p>Bone marrow and blood were stained with antibodies against CD141, lineage (CD3, CD19, CD56, CD138, CD15, CD34, and CD235a), CD45, HLADR, CD303, CD1c, and CD11c. The gating strategy is shown in Fig D in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139867#pone.0139867.s002" target="_blank">S2 File</a>). Three DC populations were analysed; CD141⁺ (CD141⁺DC) (panels A-C), CD141^- (CD141^-DC) (panels D-F), and CD303⁺DC (pDC) (panels G-I). PDL1 staining on one representative patient (panels A, D, G). Fluorescence minus one (FMO), (dotted line), was used as negative control and the percentage indicates PDL1⁺ cells of the gated DC population. Panels B, E, and H show percentage of PDL1⁺ cells within the (B) CD141⁺ DC, (E) CD141^- DC and (H) CD303⁺ pDC populations in the bone marrow (n = 19), blood (n = 8) from patients, or blood from age matched (median age 61) healthy controls (n = 9). (median age of patients 61). Statistical analysis was performed with Mann Whitney Test. Panels C, F, and I show concomitant expression levels on bone marrow DC subtypes and plasma cells in individual patients. Each dot represents one patient. P values were calculated from Spearman’s tests.</p

Additional file 1: of Chemerin is elevated in multiple myeloma patients and is expressed by stromal cells and pre-adipocytes

Figure S1. Expression of CCRL2 and CMKLR1 in primary myeloma cells (pMM, n = 24) and cell lines (n = 9) analyzed by qPCR. GAPDH was used as an endogenous control. (DOCX 51 kb

DataSheet_1_Mutational analysis and protein profiling predict drug sensitivity in multiple myeloma cell lines.zip

IntroductionMultiple myeloma (MM) is a heterogeneous disease where cancer-driver mutations and aberrant signaling may lead to disease progression and drug resistance. Drug responses vary greatly, and there is an unmet need for biomarkers that can guide precision cancer medicine in this disease.MethodsTo identify potential predictors of drug sensitivity, we applied integrated data from drug sensitivity screening, mutational analysis and functional signaling pathway profiling in 9 cell line models of MM. We studied the sensitivity to 33 targeted drugs and their association with the mutational status of cancer-driver genes and activity level of signaling proteins.ResultsWe found that sensitivity to mitogen-activated protein kinase kinase 1 (MEK1) and phosphatidylinositol-3 kinase (PI3K) inhibitors correlated with mutations in NRAS/KRAS, and PI3K family genes, respectively. Phosphorylation status of MEK1 and protein kinase B (AKT) correlated with sensitivity to MEK and PI3K inhibition, respectively. In addition, we found that enhanced phosphorylation of proteins, including Tank-binding kinase 1 (TBK1), as well as high expression of B cell lymphoma 2 (Bcl-2), correlated with low sensitivity to MEK inhibitors.DiscussionTaken together, this study shows that mutational status and signaling protein profiling might be used in further studies to predict drug sensitivities and identify resistance markers in MM.</p