Genetic Reduction of IRF5 Expression after Disease Initiation Reduces Disease in a Mouse Lupus Model by Impacting Systemic and End-Organ Pathogenic Pathways.

Gain-of-function polymorphisms in the transcription factor IFN regulatory factor 5 (IRF5) are associated with an increased risk of developing systemic lupus erythematosus. Global homozygous or heterozygous deficiency of IRF5 from birth confers protection in many lupus mouse models. However, less is known about the effects of IRF5 targeting after autoimmunity has already developed. This is an important point to clarify when considering IRF5 as a potential therapeutic target in lupus. In this study, we demonstrate that genetic reduction of IRF5 expression after disease initiation reduces disease severity in the FcγRIIB-/- Y-linked autoimmune accelerating mouse lupus model. Reduction of IRF5 expression resulted in a decrease in splenomegaly and lymphadenopathy and a reduction in splenic B cell activation and plasmablast numbers. Splenic T cell activation and differentiation were also impacted as demonstrated by an increase in the number of naive CD4+ and CD8+ T cells and a reduction in the number of memory/effector CD4+ and CD8+ T cells. Although serum antinuclear autoantibody levels were not altered, reduction in IRF5 expression led to decreased immune complex deposition and complement activation, diminished glomerular and interstitial disease, and a reduction in immune cell infiltrate in the kidney. Mechanistically, myeloid cells in the kidney produced less inflammatory cytokines after TLR7 and TLR9 activation. Overall, we demonstrate that genetic reduction of IRF5 expression during an active autoimmune process is sufficient to reduce disease severity. Our data support consideration of IRF5 as a therapeutic target and suggest that approaches targeting IRF5 in systemic lupus erythematosus may need to impact IRF5 activity both systemically and in target organs.

The pan-cancer landscape of abnormal DNA methylation and intratumor microorganisms.

Microorganisms play very important roles in carcinogenesis, tumor progression, and resistance upon treatment. Due to the challenge of accurately acquiring samples and quantifying low-biomass tissue microorganisms, most studies have focused on the effect of gut microorganisms on cancer treatments, especially the efficacy of immunotherapy. Although recent publications reveal the potential interactions between intratumor microorganisms and the immune microenvironment, whether and to what extent the intratumor microorganism could affect progression and treatment outcome remain controversial. This study is aiming to evaluate the associations among intratumor microorganisms, DNA methylation cancer driver genes, immune response, and clinical outcomes from a pan-cancer perspective, using 6,876 TCGA samples across 21 cancer types. We revealed that tumor microorganism dysbiosis is closely associated with the abnormal tumor methylome and/or tumor microenvironment, which might serve to enhance the proliferation ability and fitness for the therapy of tumors. These findings shed the light on a better understanding of the interactions between tumor cells and carcinogens during and after tumor formation, as well as microorganism-associated methylation alterations that could further serve as biomarkers for clinical outcome assessment.

A pulsed tangential-flow ultrafiltration technique for studying protein-drug binding.

We describe a pulsed tangential-flow ultrafiltration technique for rapid analysis of protein-drug binding. A protein-drug pulse was injected into a tangential-flow membrane device and made to flow parallel to the surface of a protein-retaining ultrafiltration membrane. The protein and protein-drug complexes were flushed out of the device in the retentate stream, whereas the free drug present in the permeate stream was quantified using on-line UV detector. The height of the permeate drug peak and its area under the curve were both found to be proportional to the free drug concentration in the injected sample. The fraction of bound drug was determined by comparison with peak obtained with protein-free drug sample. The characteristics of the permeate drug peak such as residence time, peak width, and peak height depended on both feed and permeate flow rates. The proposed technique in addition to being fast was "self-priming" in nature because the injected samples were flushed out of the module along with the retentate and permeate. This feature makes this technique particularly suitable for automated sample analysis. The technique was validated using three-model protein-drug combinations: bovine serum albumin (BSA)-antipyrine, BSA-tryptophan, and BSA-aspirin.