The interaction between m⁶A-methylated RNA and chromatin modification remains largely unknown. We found that targeted inhibition of bromodomain-containing protein 4 (BRD4) by siRNA or its inhibitor (JQ1) significantly decreases mRNA m⁶A levels and suppresses the malignancy of breast cancer (BC) cells via increased expression of demethylase AlkB homolog 5 (ALKBH5). Mechanistically, inhibition of BRD4 increases the mRNA stability of ALKBH5 via enhanced binding between its 3' untranslated regions (3'UTRs) with RNA-binding protein RALY. Further, BRD4 serves as a scaffold for ubiquitin enzymes tripartite motif containing-21 (TRIM21) and ALKBH5, resulting in the ubiquitination and degradation of ALKBH5 protein. JQ1-increased ALKBH5 then demethylates mRNA of extra spindle pole bodies like 1 (ESPL1) and reduces binding between ESPL1 mRNA and m⁶A reader insulin like growth factor 2 mRNA binding protein 3 (IGF2BP3), leading to decay of ESPL1 mRNA. Animal and clinical studies confirm a critical role of BRD4/ALKBH5/ESPL1 pathway in BC progression. Further, our study sheds light on the crosstalks between histone modification and RNA methylation.

Objective:To study the effect of programmed cell death-1/programmed cell death-ligand 1 (PD-1/PD-L1) regulating dendritic cells (DC) on the immune status of sepsis, and analyze the effect of PD-1/PD-L1 on prognosis.Methods:Twenty-five patients with sepsis in the intensive care unit (ICU) of the Affiliated Hospital of Zunyi Medical University from October 2018 to September 2019 were collected and followed up for 28 days. According to the 28-day survival of patients, patients were divided into survival group and death group. Among them, 10 cases were in the survival group and 15 cases were in the death group. Simultaneously, 20 healthy subjects in our hospital during the same period served as the healthy control group. Peripheral blood of patients with sepsis was taken within 24 hours after diagnosis, and the healthy control group was taken at the time of enrollment. Flow cytometry was used to detect the proportion of CD4 +T and CD8 +T cells, the ratio of T cell subsets (CD4/CD8), the expression of PD-1 on CD4 +T and CD8 +T cells, and the expression of PD-L1 and CD86 in DC. Enzyme linked immunosorbent assay (ELISA) was used to detect the levels of interleukin-10 (IL-10) and tumor necrosis factor-α(TNF-α) in serum. Spearman correlation analysis was used to analyze the correlation between CD11c +PD-L1 and CD4 +PD-1, CD8 +PD-1, TNF-α, DC, CD11c +CD86, T cell subpopulation ratio, CD4 +T cells, CD8 +T cells, and IL-10. Binary Logistic regression was used to analyze the risk factors affecting the death of patients with sepsis, and receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of independent risk factors on the prognosis of patients. Results:The scores of acute physiology and chronic health evaluationⅡ (APACHEⅡ) and sequential organ failure assessment (SOFA) in the death group were higher than that in the survival group (APACHEⅡ score: 27.0±7.3 vs. 17.0±3.9, SOFA score: 15.1±4.1 vs. 10.7±2.7, both P < 0.05). The ratio of T cell subsets in the survival group and the death group was less than 1, the death group was lower than that in the survival group (CD4/CD8: 0.54±0.15 vs. 0.79±0.09, P < 0.05), and the ratio of T cell subsets in the healthy control group was greater than 1. Compared with healthy control group, the levels of CD4 +T cells, CD8 +T cells, CD11c +DC, CD11c +CD86, IL-10 and TNF-α in survival group and death group were significantly decreased, the level of CD4 +PD-1, CD8 +PD-1, CD11c +PD-L1 were significantly increased, and the changes in the above indicators in the death group were significant compared with the survival group [CD4 +T cells: 0.14±0.07 vs. 0.22±0.08, CD8 +T cells: 0.24±0.07 vs. 0.28±0.10, CD11c +DC: 0.84±0.14 vs. 0.93±0.03, CD11c +CD86: (58.83±20.77)% vs. (78.24±9.39)%, IL-10 (ng/L): 34.22±13.98 vs. 18.49±5.55, TNF-α(ng/L): 95.30±29.33 vs. 67.00±20.16, CD4 +PD-1: (39.58±10.08)% vs. (27.03±6.35)%, CD8 +PD-1: (38.77±11.91)% vs. (29.15±8.37)%, CD11c +PD-L1: (21.13±11.54)% vs. (12.11± 8.34)%, all P < 0.05]. Spearman correlation analysis showed that CD11c +PD-L1 was positively correlated with CD4 +PD-1, CD8 +PD-1, and IL-10 ( r values were 0.748, 0.713, 0.898, all P < 0.05), while was negatively correlated with DC, CD11c +CD86, T cell subpopulation ratio, CD4 +T cells, CD8 +T cells, and TNF-α( r values were -0.587, -0.906, -0.840, -0.706, -0.513, -0.820, all P < 0.05). Multivariate binary Logistic regression analysis showed that CD4 +T PD-1 was an independent risk factor for the prognosis of sepsis patients [odds ratio ( OR) = 1.463, 95% confidence interval (95% CI) = 1.032-2.074, P = 0.033]. ROC curve analysis showed that CD4 +TPD-1 had certain predictive value for the prognosis of patients with sepsis [area under ROC curve (AUC) = 0.857, 95% CI was 0.709-1.000, P < 0.01). When the best predictive value was 34.48%, the sensitivity, specificity, and accuracy were 66.7%, 90.0%, and 85.7% respectively. Conclusions:Up-regulation of PD-1/PD-L1 in peripheral blood could inhibit the activation and proliferation of DC, affect the activation of T cells, and induce immunosuppressive state. PD-1/PD-L1 can reflect the immune status of patients with sepsis. The expression of PD-1 on CD4 +T cells may have important significance for the evaluation of prognosis.

ObjectiveByreportinga fatalcaseof severelupusnephritis(LN) complicated with invasive aspergilluspneumonia and meningitis and reviewing the associated literatures,to provide a way of early diagnosis andproper management for the patients suffering from systemic lupus erythematosus(SLE) and invasive fungus infection(IFI).MethodsThe onset,diagnosis and treatment course of the disease were described and associated literatures werereviewed to analyze and summary the diagnostic methods,common pathogenic bacteria and predisposing factors of SLE patients with IFI.ResultsApplication of IFI guideline for cancer patients and those undergoing hematopoietic stem cell transplantation could be helpful in the early diagnosis and treatment of SLE patients complicated with IFI.The most common pathogen of SLE patient suffering from IFI was cryptococcus neoformans and aspergillus,not candida albicans.The mainpredisposingfactorswerehighlupusactivityandimmunosuppressant.Conclusions Guideline of IFI for cancer patients and those undergoing hematopoietic stem cell transplantation is also helpful for the SLE patients complicated with IFI.The most common pathogens of IFI in SLE patients are cryptococcusneoformansand aspergillus.The predisposing factors are high lupus activity and immunosuppressant.