Dictyostelium Differentiation-inducing Factor Derivatives Reduce the Glycosylation of PD-L1 in MDA-MB-231 Human Breast Cancer Cells.

Objectives: Triple-negative breast cancer (TNBC) is a metastatic and intractable cancer with limited treatment options. Refractory cancer cells often express the immune checkpoint molecules programmed death-ligand 1 (PD-L1) and PD-L2, which inhibit the anticancer effects of T cells. Differentiation-inducing factors, originally found in Dictyostelium discoideum, and their derivatives possess strong antiproliferative activity, at least in part by reducing cyclin D1 expression in various cancer cells, but their effects on PD-L1/PD-L2 have not been examined. In this study, we investigate the effects of six DIF compounds (DIFs) on the expression of PD-L1/PD-L2 and cyclin D1/D3 in MDA-MB-231 cells, a model TNBC cell line. Methods: MDA-MB-231 cells were incubated for 5 or 15 h with or without DIFs, and the mRNA expression of cyclin D1, PD-L1, and PD-L2 were assessed by quantitative polymerase chain reaction (qPCR). Whereas, MDA-MD-231 cells were incubated for 12 or 24 h with or without DIFs, and the protein expression of cyclins D1 and D3, PD-L1, and PD-L2 were assessed by Western blotting. Results: As expected, some DIFs strongly reduced cyclin D1/D3 protein expression in MDA-MB-231 cells. Contrary to our expectation, DIFs had little effect on PD-L1 mRNA expression or increased it transiently. However, some DIFs partially reduced glycosylated PD-L1 and increased non-glycosylated PD-L1 in MDA-MB-231 cells. The level of PD-L2 was very low in these cells. Conclusions: Since PD-L1 glycosylation plays an important role in preventing T cells from attacking cancer cells, such DIFs may promote T cell attack on cancer cells in vivo.

Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2.

Dozens of Cu zeolites with MOR, FAU, BEA, FER, CHA and MFI frameworks are tested for direct oxidation of CH4 to CH3OH using H2O2 as oxidant. To investigate the active structures of the Cu zeolites, 15 structural variables, which describe the features of the zeolite framework and reflect the composition, the surface area and the local structure of the Cu zeolite active site, are collected from the Database of Zeolite Structures of the International Zeolite Association (IZA). Also analytical studies based on inductively coupled plasma-optical emission spectrometry (ICP-OES), X-ray fluorescence (XRF), N2 adsorption specific surface area measurement and X-ray absorption fine structure (XAFS) spectral measurement are performed. The relationships between catalytic activity and the structural variables are subsequently revealed by data science techniques, specifically, classification using unsupervised and supervised machine learning and data visualization using pairwise correlation. Based on the unveiled relationships and a detailed analysis of the XAFS spectra, the local structures of the Cu zeolites with high activity are proposed.