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The identification of diagnostic and therapeutic biomarkers for Alzheimer’s Disease (AD) remains a crucial area of research. In this study, utilizing the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm, we identified RHBDF2 and TNFRSF10B as feature genes associated with AD pathogenesis. Analyzing data from the GSE33000 dataset, we revealed significant upregulation of RHBDF2 and TNFRSF10B in AD patients, with correlations to age and gender. Interestingly, their expression profile in AD differs notably from that of other neurodegenerative conditions. Functional analysis unveiled their involvement in immune response and various signaling pathways implicated in AD pathogenesis. Furthermore, our study demonstrated the potential of RHBDF2 and TNFRSF10B as diagnostic biomarkers, exhibiting high discrimination power in distinguishing AD from control samples. External validation across multiple datasets confirmed the robustness of the diagnostic model. Moreover, utilizing molecular docking analysis, we identified dinaciclib and tanespimycin as promising small molecule drugs targeting RHBDF2 and TNFRSF10B for potential AD treatment. Our findings highlight the diagnostic and therapeutic potential of RHBDF2 and TNFRSF10B in AD management, shedding light on novel strategies for precision medicine in AD.

BackgroundCoronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) are closely related. The function of immunocytes in the pathogenesis of CAD and T2DM has not been extensively studied. The quantitative bioinformatics analysis of the public RNA sequencing database was applied to study the key genes that mediate both CAD and T2DM. The biological characteristics of associated key genes and mechanism of CD8+ T and NK cells in CAD and T2DM are our research focus.MethodsWith expression profiles of GSE66360 and GSE78721 from the Gene Expression Omnibus (GEO) database, we identified core modules associated with gene co-expression relationships and up-regulated genes in CAD and T2DM using Weighted Gene Co-expression Network Analysis (WGCNA) and the ‘limma’ software package. The enriched pathways of the candidate hub genes were then explored using GO, KEGG and GSEA in conjunction with the immune gene set (from the MSigDB database). A diagnostic model was constructed using logistic regression analysis composed of candidate hub genes in CAD and T2DM. Univariate Cox regression analysis revealed hazard ratios (HRs), 95% confidence intervals (CIs), and p-values for candidate hub genes in diagnostic model, while CIBERSORT and immune infiltration were used to assess the immune microenvironment. Finally, monocytes from peripheral blood samples and their immune cell ratios were analyzed by flow cytometry to validate our findings.ResultsSixteen candidate hub genes were identified as being correlated with immune infiltration. Univariate Cox regression analysis revealed that NPEPPS and ABHD17A were highly correlated with the diagnosis of CAD and T2DM. The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM. The bioinformatics results on immune infiltration were well validated by flow cytometry.ConclusionsA series of bioinformatics studies have shown ABHD17A and NPEPPS as key genes for the co-occurrence of CAD and T2DM. Our study highlights the important effect of CD8+ T and NK cells in the pathogenesis of both diseases, indicating that they may serve as viable targets for diagnosis and therapeutic intervention.

The NLRP1 inflammasome functions as canonical cytosolic sensor in response to intracellular infections and is implicated in auto-inflammatory diseases. But the regulation and signal transduction mechanisms of NLRP1 are incompletely understood. Here, we show that the T60 variant of CARD8, but not the canonical T48 isoform, negatively regulates the NLRP1 inflammasome activation by directly interacting with the receptor molecule NLRP1 and inhibiting inflammasome assembly. Furthermore, our results suggest that different ASC preference in three types of inflammasomes, namely the ASC-indispensable NLRP1 inflammasome, ASC-dispensable mNLRP1b inflammasome and ASC-independent CARD8 inflammasome, is mainly caused by the CARD domain, not the UPA subdomain. Based on the systematic site-directed mutagenesis and structural analysis, we find that signal transduction of the NLRP1 inflammasome relies on multiple interaction surfaces at its CARD domain. Finally, our results partly explain how mutations in NLRP1 lead to its constitutive activation in auto-inflammatory diseases. In conclusion, our study not only reveals how CARD8 downregulates the NLRP1 inflammasome activation, but also provides insights into the assembly mechanisms of CARD-containing inflammasomes.

Grass carp haemorrhagic disease caused by grass carp reovirus II is a serious disease of the aquaculture industry and vaccination is the only effective method of GCRV protection. In this study, Lactococcus lactis was used as oral vaccine delivery to express the GCRV II VP6 protein. We evaluated the protective efficacy of the live vaccine strain to induce mucosal immune protection. After oral administration, the recombinant strains remained in the hindgut for antigen presentation and increased the survival rate 46.7% and the relative percent survival 42.9%, respectively versus control vaccination. Though L. lactis alone can induce the inflammatory response by stimulating the mucosal immune system, the recombinant L. lactis expressing VP6 greatly enhanced nonspecific immune responses via expression of immune related genes of the fish. Furthermore, both systemic and mucosal immunity was elicited following oral immunization with the recombinant strain and this strain also elicited an inflammatory response and cellular immunity to enhance the protective effect. L. lactis can therefore be utilized as a mucosal immune vector to trigger high levels of immune protection in fish at both the systemic and mucosal levels. L. lactis is a promising candidate for oral vaccine delivery.

Radiotherapy is an effective local treatment modality of NSCLC. Its capabilities of eliminating tumor cells by inducing double strand DNA (dsDNA) damage and modulating anti-tumor immune response in irradiated and nonirradiated sites have been elucidated. The novel ICIs therapy has brought hope to patients resistant to traditional treatment methods, including radiotherapy. The integration of radiotherapy with immunotherapy has shown improved efficacy to control tumor progression and prolong survival in NSCLC. In this context, biomarkers that help choose the most effective treatment modality for individuals and avoid unnecessary toxicities caused by ineffective treatment are urgently needed. This article summarized the effects of radiation in the tumor immune microenvironment and the mechanisms involved. Outcomes of multiple clinical trials investigating immuno-radiotherapy were also discussed here. Furthermore, we outlined the emerging biomarkers for the efficacy of PD-1/PD-L1 blockades and radiation therapy and discussed their predictive value in NSCLC.

BackgroundPoly (ADP-ribose) polymerases-1 (PARP1) alterations are associated with PARP1 inhibitor resistance, regulating the function of Treg cells and PDL1 expression in tumor cells, and high PARP1 expression is significantly associated with aggressive behavior and chemotherapeutic resistance in several tumors. However, a comprehensive analysis of the predictive values of PARP1 alteration for immune checkpoint inhibitor (ICI) effectiveness in tumors remains unclear, and the associations between its expression and immunotherapy signatures also needs to be explored further.MethodsWe performed some analyses with the cBioPortal online database (https://www.cbioportal.org), TIMER2.0 (Tumor Immune Estimation Resource 2.0, http://timer.comp-genomics.org/) and TCGA database (https://xenabrowser.net or https://portal.gdc.cancer.gov/). Survival analysis was conducted using Kaplan–Meier method, and the associations between PARP1 transcription levels and immune checkpoint gene expression, the number of neoantigens, tumor mutation burden (TMB) levels, and microsatellite instability (MSI) event are analyzed by spearman correlation analysis and visualization of those mentioned above is performed using R, version 3.6.3 (http://www.r-project.org/).ResultsWe found that PARP1 was altered in 1338 (2.9%) out of 45604 patients with diverse tumors, which was associated with markedly higher TMB levels in a variety of tumors (P < 0.01). Impressively, patients with PARP1 alterations in advanced tumors showed better overall survival (OS) in the ICI-treated cohort (P = 0.016). PARP1 altered group was substantially correlated with higher immune infiltrates across most tumors, including CD8+ T cells in colorectal adenocarcinoma (P = 0.0061), endometrial carcinoma (P = 0.0033), stomach cancer (P = 0.033), and cervical cancer (P = 0.026), respectively. The PARP1 altered group showed high expression in transcription (P < 0.001), and higher expression of LAG3, PDCD1, CTLA-4, and TIGIT (P < 0.05). Higher PARP1 expression was present in 27 tumor compared the corresponding normal tissues using the GTEx and TCGA databases and it had a worse OS in several tumors (P < 0.05). Further, high PARP1 expression was significantly associated with six immune cells (B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells) in most tumors, including colon adenocarcinoma (COAD), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), and liver hepatocellular carcinoma (LIHC) (P < 0.05). In particular, CD8+T cell infiltration, was also positively correlated with high PARP1 expression in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), kidney renal papillary cell carcinoma (KIRP), brain lower grade glioma (LGG), LIHC, pancreatic adenocarcinoma (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), testicular germ cell tumors (TGCT), thymoma (THYM), uterine corpus endometrial carcinoma (UCEC), uveal melanoma (UVM) (P < 0.05, no data shown), and PARP1 expression was significantly positively correlated with the transcription levels of some of the 47 immune checkpoint genes, such as CD274, CTLA4, and PDCD1 in several tumors, including PAAD, LIHC, KIRC, HNSC, and BLCA (P < 0.05). A significant positive association between PARP1 expression and the number of immune neoantigen was found within COAD, KIRC, lung adenocarcinoma (LUAD), PAAD and THYM (P < 0.05), and there were also significantly positive correlations between PARP1 expression and TMB in many tumors like adrenocortical carcinoma (ACC), COAD, kidney chromophobe (KICH), LGG, LUAD, READ, skin cutaneous melanoma (SKCM) and stomach adenocarcinoma (STAD) (P < 0.05). In addition, high PARP1 expression was positively associated with microsatellite instability event in COAD, KIRP, BRCA, glioblastoma multiforme (GBM), lung squamous cell carcinoma (LUSC), LGG, READ, UCEC, SKCM and LUAD (P < 0.05).ConclusionsOur results highlight the significance of PARP1 alterations as pan-cancer predictive biomarkers for ICI treatment, and its expression levels seem to be correlated with the status of immunotherapy-associated signatures, thus may be a promising biomarker for predicting ICI response in several tumors.

Background: Coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) are closely related. The function of immunocytes in the pathogenesis of CAD and T2DM has not been extensively studied. The quantitative bioinformatics analysis of the public RNA sequencing database was applied to study the key genes that mediate both CAD and T2DM. The biological characteristics of associated key genes and mechanism of CD8+ T and NK cells in CAD and T2DM are our research focus. Methods: With expression profiles of GSE66360 and GSE78721 from the Gene Expression Omnibus (GEO) database, we identified core modules associated with gene co-expression relationships and up-regulated genes in CAD and T2DM using Weighted Gene Co-expression Network Analysis (WGCNA) and the 'limma' software package. The enriched pathways of the candidate hub genes were then explored using GO, KEGG and GSEA in conjunction with the immune gene set (from the MSigDB database). A diagnostic model was constructed using logistic regression analysis composed of candidate hub genes in CAD and T2DM. Univariate Cox regression analysis revealed hazard ratios (HRs), 95% confidence intervals (CIs), and p-values for candidate hub genes in diagnostic model, while CIBERSORT and immune infiltration were used to assess the immune microenvironment. Finally, monocytes from peripheral blood samples and their immune cell ratios were analyzed by flow cytometry to validate our findings. Results: Sixteen candidate hub genes were identified as being correlated with immune infiltration. Univariate Cox regression analysis revealed that NPEPPS and ABHD17A were highly correlated with the diagnosis of CAD and T2DM. The results indicate that CD8+ T cells (p = 0.04) and NKbright cells (p = 3.7e-3) are significantly higher in healthy controls than in individuals with CAD or CAD combined with T2DM. The bioinformatics results on immune infiltration were well validated by flow cytometry. Conclusions: A series of bioinformatics studies have shown ABHD17A and NPEPPS as key genes for the co-occurrence of CAD and T2DM. Our study highlights the important effect of CD8+ T and NK cells in the pathogenesis of both diseases, indicating that they may serve as viable targets for diagnosis and therapeutic intervention. [ABSTRACT FROM AUTHOR]