The Impact of Chain Length and Flexibility in the Interaction between Sulfated Alginates and HGF and FGF‑2

Alginate is a promising polysaccharide for use in biomaterials as it is biologically inert. One way to functionalize alginate is by chemical sulfation to emulate sulfated glycosaminoglycans, which interact with a variety of proteins critical for tissue development and homeostasis. In the present work we studied the impact of chain length and flexibility of sulfated alginates for interactions with FGF-2 and HGF. Both growth factors interact with defined sequences of heparan sulfate (HS) at the cell surface or in the extracellular matrix. Whereas FGF-2 interacts with a pentasaccharide sequence containing a critical 2-O-sulfated iduronic acid, HGF has been suggested to require a highly sulfated HS/heparin octasaccharide. Here, oligosaccharides of alternating mannuronic and guluronic acid (MG) were sulfated and assessed by their relative efficacy at releasing growth factor bound to the surface of myeloma cells. 8-mers of sulfated MG (SMG) alginate showed significant HGF release compared to shorter fragments, while the maximum efficacy was achieved at a chain length average of 14 monosaccharides. FGF-2 release required a higher concentration of the SMG fragments, and the 14-mer was less potent compared to an equally sulfated high-molecular weight SMG. Sulfated mannuronan (SM) was subjected to periodate oxidation to increase chain flexibility. To assess the change in flexibility, the persistence length was estimated by SEC-MALLS analysis and the Bohdanecky approach to the worm-like chain model. A high degree of oxidation of SM resulted in approximately twice as potent HGF release compared to the nonoxidized SM alginate. The release of FGF-2 also increased with the degree of oxidation, but to a lower degree compared to that of HGF. It was found that the SM alginates were more efficient at releasing FGF-2 than the SMG alginates, indicating a greater dependence on monosaccharide identity and charge orientation over chain flexibility and charge density

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