Exploring the biological function of immune cell-related genes in human immunodeficiency virus (HIV)-1 infection based on weighted gene co-expression network analysis (WGCNA).

BACKGROUND: Acquired immunodeficiency syndrome (AIDS) is a chronic infectious disease characterized by consistent immune dysfunction. The objective of this study is to determine whether immune cell-related genes can be used as biomarkers for the occurrence of AIDS and potential molecular mechanisms. METHODS: A weighted gene co-expression network analysis was performed using the GSE6740 dataset from the Gene Expression Synthesis Database to identify the Hub gene, which contained microarray data from HIV-1 positive (HIV-1+) and HIV-1 negative (HIV-1-) individuals. The HIV-1+-related differentially expressed genes were then identified using the limma package. Subsequently, the characteristic immune cell-related genes were identified as diagnostic biomarkers for HIV-1+ using the random forest model (RF), support vector machine model, and generalized linear model. RESULTS: MEdarkgreen exhibited the strongest correlation with HIV clinical features of any of these modules. As the best model for diagnosing HIV-1±, RF was used to select four critical immune cell-related genes, namely, ARRB1, DPEP2, LTBP3, and RGCC, and a nomogram model was created to predict the occurrence of HIV-1 infection based on four key immune cell-related genes. Diagnostic genes were shown to be engaged in immune-related pathways, suggesting that immunological molecules, immune cells, and immune pathways all have a role in HIV-1 infection. The CTD database was explored for prospective medications or molecular compounds that might be utilized to treat HIV-1+ patients. = Moreover, in HIV-1+ individuals, the ceRNA network revealed that ARRB1, DPEP2, LTBP3, and RGCC could be regulated by lncRNAs through the corresponding miRNAs. Ultimately, RT-PCR results from clinical blood samples demonstrated that the four diagnostic genes were significantly downregulated in HIV-1+ patients. CONCLUSION: We screened four immune cell-related genes, ARRB1, DPEP2, LTBP3, and RGCC, which may be considered as the diagnostic markers for HIV-1/AIDS. Our findings reveal that immune related genes and pathways involved in HIV-1 pathogenesis were regulated on both genetic and epigenetic levels by constructing a ceRNA network associated with lncRNA.

Long-Term Kinetics of Immunologic Components and Neurological Deficits in Rats Following Repetitive Mild Traumatic Brain Injury.

BACKGROUND Despite growing awareness of repetitive mild traumatic brain injury (rmTBI), understanding of the involvement of long-term kinetics of immunologic components in the central and peripheral immune system took part remains incomplete. The present study aimed to provide a quantitative assay for certain immune system parameters in rmTBI rats. MATERIAL AND METHODS Neurological functions were assessed by modified Neurological Severity Score (mNSS) and Morris Water Maze (MWM), immunologic components from brain and peripheral blood were analyzed by flow cytometry (FCM), and concentrations of inflammatory cytokines, including tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-10 were measure by enzyme-linked immunosorbent assay (ELISA). RESULTS Neurological functions of rmTBI rats were seriously impaired. In the brain, T cells were up-regulated and peaked at week 1. The percentage of CD4+ T cells decreased from week 1 to week 4, while CD8+ T cells notably decreased at week 1, then increased until week 4. The infiltration proportion of Treg cells was reduced at week 1 and peaked at week 2. CD86+/CD11b+ M1 peaked at week 4 and CD206+/CD11b+ M2 rose at week 1. IL-6/IL-10 showed a similar pattern, whose rise corresponded to the decrease in TNF-α at week 2 after rmTBI. FCM demonstrated peripheral immune dysfunction after rmTBI. CONCLUSIONS mNSS and MWM demonstrated neuronal deficits in rmTBI rats, and central and peripheral immune systems were implicated in the pathophysiological processes of rmTBI. Long-term immune response may play dual roles in injury and repair of rmTBI.

The accumulation of brain injury leads to severe neuropathological and neurobehavioral changes after repetitive mild traumatic brain injury.

Traumatic brain injury (TBI) is a major public health problem with long-term neurobehavioral sequela. The evidences have revealed that TBI is a risk factor for later development of neurodegenerative disease and both the single and repetitive brain injury can lead to the neurodegeneration. But whether the effects of accumulation play an important role in the neurodegenerative disease is still unknown. We utilized the Sprague Dawley (SD) rats to develop the animal models of repetitive mild TBI and single mild TBI in order to detect the neurobehavioral changes. The results of neurobehavioral test revealed that the repetitive mild TBI led to more severe behavioral injuries than the single TBI. There were more activated microglia cells and astrocytes in the repetitive mild TBI group than the single TBI group. In consistent with this, the levels of TNF-α and IL-6 were higher and the expression of IL-10 was lower in the repetitive mild TBI group compared with the single TBI group. The expression of amyloid precursor protein (APP) increased in the repetitive TBI group detected by ELISA and western blot. But the levels of total tau (Tau-5) and P-tau (ser202) seem no different between the two groups in most time point. In conclusion, repetitive mild TBI could lead to more severe neurobehavioral impairments and the effects of accumulation may be associated with the increased inflammation in the brain.

Volume-based predictive biomarkers of sequential FDG-PET/CT for sunitinib in cancer of unknown primary: identification of the best benefited patients.

PURPOSE: To test the performance of sequential 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) in predicting survival after sunitinib therapies in patients with cancer of unknown primary (CUP). METHODS: CUP patients were enrolled for sequential PET/CT scanning for sunitinib and a control group. Univariate and multivariate analysis were applied to test the efficacy of sunitinib therapy in CUP patients. Next, sequential analyses involving PET/CT parameters were performed to identify and validate sensitive PET/CT biomarkers for sunitinib therapy. Finally, time-dependent receiver operating characteristic (TDROC) analyses were performed to compare the predictive accuracy. RESULTS: Multivariate analysis proved that sunitinib group had significantly improved survival (p < 0.01) as compared to control group. After cycle 2 of therapy, multivariate analysis identified volume-based PET/CT parameters as sensitive biomarkers for sunitinib (p < 0.01). TDROC curves demonstrated whole-body total lesion glycolysis reduction (Δ WTLG) and follow-up WTLG to have good accuracy for efficacy prediction. This evidence was validated after cycle 4 of therapy with the same method. CONCLUSION: Sunitinib therapy proved effective in treatment of CUP. PET/CT volume-based parameters may help predict outcome of sunitinib therapy, in which Δ WTLG and follow-up WTLG seem to be sensitive biomarkers for sunitinib efficacy. Patients with greater reduction and lower WTLG at follow-up seem to have better survival outcome.