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Background: Lymphocyte antigen 96 (LY96) plays an important role in innate immunity and has been reported to be associated with various neurological diseases. However, its role in Parkinson's disease (PD) remains unclear., Methods: Transcriptome data from a total of 49 patients with PD and 34 healthy controls were downloaded from the Gene Expression Omnibus (GEO) database to analyse the expression pattern of LY96 and its relationship with gene function and immune-related markers. In addition, peripheral blood samples were collected from clinical patients to validate LY96 mRNA expression levels. Finally, an in vitro cell model of PD based on highly differentiated SH-SY5Y cells was constructed, with small interfering RNA-silenced LY96 expression, and LY96 mRNA level, cell viability, flow cytometry, and mitochondrial membrane potential assays were performed., Results: The results of the analyses of the GEO database and clinical samples revealed significantly abnormally high LY96 expression in patients with PD compared with healthy controls. The results of cell experiments showed that inhibiting LY96 expression alleviated adverse cellular effects by increasing cell viability, reducing apoptosis, and reducing oxidative stress. Gene set enrichment analysis showed that LY96 was positively correlated with T1 helper cells, T2 helper cells, neutrophils, natural killer T cells, myeloid-derived suppressor cells, macrophages, and activated CD4 cells, and may participate in PD through natural killer cell-mediated cytotoxicity pathways and extracellular matrix receptor interaction pathways., Conclusion: These findings suggested that LY96 might be a novel potential biomarker for PD, and offer insights into its immunoregulatory role., Competing Interests: Declaration of competing interest The authors have no relevant financial or non-financial interests to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The neutrophil-to-lymphocyte ratio (NLR) is an inflammatory index calculated by the absolute neutrophil count dividing the absolute lymphocyte count, and its prognostic role in esophageal cancer (EC) patients with anti-PD-1 therapy remains unclear. Methods: A total of 140 unresectable or metastatic EC patients receiving PD-1 inhibitor treatment were included from Jan 2016 to Mar 2020. Kaplan–Meier method and log-rank test were used for comparing overall survival (OS) and progression-free survival (PFS) between groups. Multivariate Cox analysis was performed to assess the prognostic value of NLR. Results: The cutoff value of NLR was set at 5, and the median follow-up time was 20.0 months. Patients with pretreatment NLR <5 had higher ORR (46.7% vs. 12.1%; p < 0.001) and DCR (85.0% vs. 69.7%; p = 0.047) than those with NLR ≥5. Kaplan–Meier curves showed that pretreatment NLR <5 was associated with longer PFS (median: 10.0 vs. 3.5 months, p < 0.0001) and OS (median: 22.3 vs. 4.9 months, p < 0.0001). Multivariate analysis demonstrated that pretreatment NLR ≥5 independently and significantly increased the risk of disease progression (hazard ratio (HR), 1.77 (95% confidence interval (CI), 1.12–2.82); p = 0.015) and death (HR, 4.01 (95% CI, 2.28–7.06); p < 0.001). Subgroup analysis showed that pretreatment NLR ≥5 was associated with poor efficacy and survival in most subsets. Conclusions: Our findings showed that pretreatment NLR was independently and significantly associated with the efficacy and prognosis of EC patients treated with PD-1 inhibitors. NLR could serve as a convenient and useful prognostic biomarker for EC patients with anti-PD-1 therapy. [ABSTRACT FROM AUTHOR]

Background: Viral infections are prevalent in human cancers and they have great diagnostic and theranostic values in clinical practice. Recently, their potential of shaping the tumor immune microenvironment (TIME) has been related to the immunotherapy of human cancers. However, the landscape of viral expressions and immune status in human cancers remains incompletely understood.Methods: We developed a next-generation sequencing (NGS)-based pipeline to detect viral sequences from the whole transcriptome and used machine learning algorithms to classify different TIME subtypes.Results: We revealed a pan-cancer landscape of viral expressions in human cancers where 9 types of viruses were detected in 744 tumors of 25 cancer types. Viral infections showed different tissue tendencies and expression levels. Multi-omics analyses further revealed their distinct impacts on genomic, transcriptomic and immune responses. Epstein-Barr virus (EBV)-infected stomach adenocarcinoma (STAD) and Human Papillomavirus (HPV)-infected head and neck squamous cell carcinoma (HNSC) showed decreased genomic variations, significantly altered gene expressions, and effectively triggered anti-viral immune responses. We identified three TIME subtypes, in which the "Immune-Stimulation" subtype might be the promising candidate for immunotherapy. EBV-infected STAD and HPV-infected HNSC showed a higher frequency of the "Immune-Stimulation" subtype. Finally, we constructed the eVIIS pipeline to simultaneously evaluate viral infection and immune status in external datasets.Conclusions: Viral infections are prevalent in human cancers and have distinct influences on hosts. EBV and HPV infections combined with the TIME subtype could be promising biomarkers of immunotherapy in STAD and HNSC, respectively. The eVIIS pipeline could be a practical tool to facilitate clinical practice and relevant studies. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a common neurodegenerative disease in the elderly population. However, there are no reliable diagnostic biomarkers for PD, and the pathogenesis of PD still needs further study. The aim of the current study was to identify potential biomarkers and explore the pathogenesis of PD. We conducted an integrative analysis of messenger RNA (mRNA), microRNA (miRNA), and long noncoding RNA (lncRNA) expression profiles of PD using data from the Gene Expression Omnibus (GEO). The GSE110720, GSE110719 and GSE133347 data sets were selected and analysed. Gene ontology (GO) enrichment and gene set variation analysis (GSVA) were performed for annotation, visualization, and integrated discovery. Protein–protein interaction (PPI) and competing endogenous RNA (ceRNA) networks were constructed, and hub genes were identified. Meanwhile, the immune infiltration analysis of hub genes was analysed. Moreover, receiver operating characteristic (ROC) curves were generated to verify the diagnostic value of the differentially expressed genes (DEGs). Finally, the genes with high area under the curve (AUC) values were verified by human samples. We identified 464 DEGs closely related to PD, including 154 mRNAs, 134 miRNAs, and 176 lncRNAs. The GO analyses indicated that changes in PD were mainly enriched in receptor ligand activity and cytokine receptor binding. The KEGG enrichment analysis showed that these DEGs were significantly involved in cytokine-cytokine receptor interactions, signalling pathways regulating the pluripotency of stem cells and Th17 cell differentiation. GSVA suggested that growth factor binding, IL2-stat5 signalling, and IL6-jak-stat3 signalling were crucial in the development of PD. A total of five hub genes (NPBWR2, CXCL10, CXCL5, S1PR5, and GALR1) were selected via the PPI network. A ceRNA network of the CXCL5, CXCL10 and S1PR5 genes was constructed, and target genes of the three genes were screened. The immune infiltration analysis showed that there were significant differences in a variety of immune cells between the hub genes. The expression of DEGs was validated in clinical human samples by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The expression levels of hsa-miR6895–5p, hsa-miR6791–5p, hsa-miR518f-5p, hsa-miR455–3p and TEKT4P2 were decreased, while the levels of TPTE2P6 were increased in human samples. These findings are consistent with the bioinformatics analysis results. We found that the immune inflammatory response and immune cell regulation were involved in the pathogenesis of PD. Five hub genes involved in the immune infiltration biological processes of PD based on bioinformatics. We verified the DEGs with significant differences by qRT-PCR. These findings might provide new insight into the pathogenesis of PD and the development of diagnostic and therapeutic strategies for PD. • A total of 464 differentially expressed genes in Parkinson's disease were identified by bioinformatics. • Five hub genes were identified by network construction. • The relationship between hub gene expression and immune infiltration was analysed. • The interesting and meaningful genes were verified by qRT-PCR. [ABSTRACT FROM AUTHOR]

Cognitive impairment is a serious nonmotor symptom in patients with Parkinson's disease (PD). Currently, there are few studies investigating the relationship of serum markers and retinal structural changes with cognitive function in PD. To investigate the relationship between retinal structural changes, serum high mobility group box-1 (HMGB1) levels and cognitive function and motor symptoms in PD patients. Eighty-nine participants, including 47 PD patients and 42 healthy subjects, were enrolled. PD patients were divided into Parkinson's disease with normal cognitive (PD-NC), Parkinson's disease with mild cognitive impairment (PD-MCI), and Parkinson's disease with dementia (PDD) groups. The motor and nonmotor symptoms of PD patients were evaluated with clinical scale. Serum HMGB1 levels were detected by enzyme-linked immunosorbent assay (ELISA), and ganglion cell-inner plexiform layer complex (GCIPL) thickness changes in the macula were quantitatively analyzed by swept source optical coherence tomography (SS-OCT) in all patients. Compared with the control group, the macular GCIPL (t = −2.308, P = 0.023) was thinner and serum HMGB1 (z = −2.285, P = 0.022) was increased in PD patients. Macular GCIPL thickness in patients with PD-MCI and PDD were significantly lower than that in PD-NC patients, but there were no significant difference between the PD-MCI and PDD groups. Serum HMGB1 levels in patients with PD-MCI and PDD were significantly higher than those in PD-NC patients, and serum HMGB1 levels in PDD patients were higher than those in PD-MCI patients. Correlation analysis showed that serum HMGB1 levels in PD patients were positively correlated with disease duration, H Y stage, UPDRS-I score, UPDRS-III score, and UPDRS total score and negatively correlated with MOCA score. Macular GCIPL thickness was negatively correlated with H Y stage and positively correlated with MOCA score, and macular GCIPL thickness was negatively correlated with serum HMGB1 level. Logistic regression analysis showed that elevated serum HMGB1 level, thinner macular GCIPL thickness, and higher H Y stage were independent risk factors for Parkinson's disease with cognitive impairment (PD-CI). The areas under the receiver operating characteristic curve (AUC) for the serum HMGB1 level and macular GCIPL thickness-based diagnosis of PD-MCI, PDD and PD-CI based on in patients with PD were 0.786 and 0.825, 0.915 and 0.856, 0.852 and 0.841, respectively. The AUC for the diagnosis of PD-MCI, PDD and PD-CI with serum HMGB1 level and GCIPL thickness combined were 0.869, 0.967 and 0.916, respectively. The macular GCIPL thickness and serum HMGB1 level are potential markers of cognitive impairment in PD patients, and their combination can significantly improve the accuracy of the diagnosis of cognitive impairment in PD. • The serum HMGB1 level of PD patients were higher than that of the controls, and the GCIPL in the macular area was thinner than that of the control group. • Serum HMGB1 levels were negatively correlated with the GCIPL thickness in the macula. • Elevated serum HMGB1 levels and thinning of the macular GCIPL correlated with the severity of cognitive dysfunction in PD patients. • Serum HMGB1 level and GCIPL thickness can accurately predict different degrees of cognitive function status in PD patients, and their combination can improve the accuracy of predicting PD-related cognitive impairments. [ABSTRACT FROM AUTHOR]