Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood

Background Gene expression studies require appropriate normalization methods. One such method uses stably expressed reference genes. Since suitable reference genes appear to be unique for each tissue, we have identified an optimal set of the most stably expressed genes in human blood that can be used for normalization. Methods Whole-genome Affymetrix Human 2.0 Plus arrays were examined from 526 samples of males and females ages 2 to 78, including control subjects and patients with Tourette syndrome, stroke, migraine, muscular dystrophy, and autism. The top 100 most stably expressed genes with a broad range of expression levels were identified. To validate the best candidate genes, we performed quantitative RT-PCR on a subset of 10 genes (TRAP1, DECR1, FPGS, FARP1, MAPRE2, PEX16, GINS2, CRY2, CSNK1G2 and A4GALT), 4 commonly employed reference genes (GAPDH, ACTB, B2M and HMBS) and PPIB, previously reported to be stably expressed in blood. Expression stability and ranking analysis were performed using GeNorm and NormFinder algorithms. Results Reference genes were ranked based on their expression stability and the minimum number of genes needed for nomalization as calculated using GeNorm showed that the fewest, most stably expressed genes needed for acurate normalization in RNA expression studies of human whole blood is a combination of TRAP1, FPGS, DECR1 and PPIB. We confirmed the ranking of the best candidate control genes by using an alternative algorithm (NormFinder). Conclusion The reference genes identified in this study are stably expressed in whole blood of humans of both genders with multiple disease conditions and ages 2 to 78. Importantly, they also have different functions within cells and thus should be expressed independently of each other. These genes should be useful as normalization genes for microarray and RT-PCR whole blood studies of human physiology, metabolism and disease.Boryana S Stamova, Michelle Apperson, Wynn L Walker, Yingfang Tian, Huichun Xu, Peter Adamczy, Xinhua Zhan, Da-Zhi Liu, Bradley P Ander, Isaac H Liao, Jeffrey P Gregg, Renee J Turner, Glen Jickling, Lisa Lit and Frank R Shar

A lack of association between elevated serum levels of S100B protein and autoimmunity in autistic children

<p>Abstract</p> <p>Background</p> <p>S100B is a calcium-binding protein that is produced primarily by astrocytes. Increased serum S100B protein levels reflect neurological damage. Autoimmunity may have a role in the pathogenesis of autism in some patients. Autoantibodies may cross the blood-brain barrier and combine with brain tissue antigens, forming immune complexes and resulting in neurological damage. We are the first to investigate the relationship between serum levels of S100B protein, a marker of neuronal damage, and antiribosomal P protein antibodies in autistic children.</p> <p>Methods</p> <p>Serum S100B protein and antiribosomal P antibodies were measured in 64 autistic children in comparison to 46 matched healthy children.</p> <p>Results</p> <p>Autistic children had significantly higher serum S100B protein levels than healthy controls (<it>P </it>< 0.001). Children with severe autism had significantly higher serum S100B protein than patients with mild to moderate autism (<it>P </it>= 0.01). Increased serum levels of antiribosomal P antibodies were found in 40.6% of autistic children. There were no significant correlations between serum levels of S100B protein and antiribosomal P antibodies (<it>P </it>= 0.29).</p> <p>Conclusions</p> <p>S100B protein levels were elevated in autistic children and significantly correlated to autistic severity. This may indicate the presence of an underlying neuropathological condition in autistic patients. Antiribosomal P antibodies may not be a possible contributing factor to the elevated serum levels of S100B protein in some autistic children. However, further research is warranted to investigate the possible link between serum S100B protein levels and other autoantibodies, which are possible indicators of autoimmunity to central nervous system in autism.</p

Atypical miRNA expression in temporal cortex associated with dysregulation of immune, cell cycle, and other pathways in autism spectrum disorders

BACKGROUND: Autism spectrum disorders (ASDs) likely involve dysregulation of multiple genes related to brain function and development. Abnormalities in individual regulatory small non-coding RNA (sncRNA), including microRNA (miRNA), could have profound effects upon multiple functional pathways. We assessed whether a brain region associated with core social impairments in ASD, the superior temporal sulcus (STS), would evidence greater transcriptional dysregulation of sncRNA than adjacent, yet functionally distinct, primary auditory cortex (PAC). METHODS: We measured sncRNA expression levels in 34 samples of postmortem brain from STS and PAC to find differentially expressed sncRNA in ASD compared with control cases. For differentially expressed miRNA, we further analyzed their predicted mRNA targets and carried out functional over-representation analysis of KEGG pathways to examine their functional significance and to compare our findings to reported alterations in ASD gene expression. RESULTS: Two mature miRNAs (miR-4753-5p and miR-1) were differentially expressed in ASD relative to control in STS and four (miR-664-3p, miR-4709-3p, miR-4742-3p, and miR-297) in PAC. In both regions, miRNA were functionally related to various nervous system, cell cycle, and canonical signaling pathways, including PI3K-Akt signaling, previously implicated in ASD. Immune pathways were only disrupted in STS. snoRNA and pre-miRNA were also differentially expressed in ASD brain. CONCLUSIONS: Alterations in sncRNA may underlie dysregulation of molecular pathways implicated in autism. sncRNA transcriptional abnormalities in ASD were apparent in STS and in PAC, a brain region not directly associated with core behavioral impairments. Disruption of miRNA in immune pathways, frequently implicated in ASD, was unique to STS. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13229-015-0029-9) contains supplementary material, which is available to authorized users

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Consequences of EU Biofuel Policies on Agricultural Production and Land Use

Some recent discussions of adverse human health effects of active and passive smoking have suggested that low levels of exposure are disproportionately dangerous, so that “The effects of even brief (minutes to hours) passive smoking are often nearly as large (averaging 80% to 90%) as chronic active smoking” (Barnoya and Glantz, 2005). Recent epidemiological evidence (Teo et al., 2006) suggests a more linear relation. This paper reexamines the empirical relation between self-reported low levels of active smoking and risk of coronary heart disease (CHD) in public-domain data from the National Health and Nutrition Examination Survey (NHANES). Consistent with biological evidence on J-shaped and U-shaped relations between smoking-associated risk factors and CHD risks, we find that low levels of active smoking do not appear to be associated with increased CHD risk. Several methodological challenges in epidemiology may explain how model-derived estimates can predict low-dose linear or concave dose-response estimates, even if the empirical (i.e., data-based) relation does not show a clear increased risk at the lowest doses