Additional file 1: of Effects of automated smartphone mobile recovery support and telephone continuing care in the treatment of alcohol use disorder: study protocol for a randomized controlled trial

SPIRIT 2013 Checklist: Recommended items to address in a clinical trial protocol and related documents*. (DOC 122 kb

Epstein - Barr Virus Transforming Protein LMP-1 Alters B Cells Gene Expression by Promoting Accumulation of the Oncoprotein ΔNp73α

<div><p>Many studies have proved that oncogenic viruses develop redundant mechanisms to alter the functions of the tumor suppressor p53. Here we show that Epstein-Barr virus (EBV), via the oncoprotein LMP-1, induces the expression of ΔNp73α, a strong antagonist of p53. This phenomenon is mediated by the LMP-1 dependent activation of c-Jun NH2-terminal kinase 1 (JNK-1) which in turn favours the recruitment of p73 to ΔNp73α promoter. A specific chemical inhibitor of JNK-1 or silencing JNK-1 expression strongly down-regulated ΔNp73α mRNA levels in LMP-1-containing cells. Accordingly, LMP-1 mutants deficient to activate JNK-1 did not induce ΔNp73α accumulation. The recruitment of p73 to the ΔNp73α promoter correlated with the displacement of the histone-lysine N-methyltransferase EZH2 which is part of the transcriptional repressive polycomb 2 complex. Inhibition of ΔNp73α expression in lymphoblastoid cells (LCLs) led to the stimulation of apoptosis and up-regulation of a large number of cellular genes as determined by whole transcriptome shotgun sequencing (RNA-seq). In particular, the expression of genes encoding products known to play anti-proliferative/pro-apoptotic functions, as well as genes known to be deregulated in different B cells malignancy, was altered by ΔNp73α down-regulation. Together, these findings reveal a novel EBV mechanism that appears to play an important role in the transformation of primary B cells.</p> </div

Association between selected SNPs and risk of cervical cancer, overall and by country.

<p>Association between selected SNPs and risk of cervical cancer, overall and by country.</p

Results of single RV-based association analysis in the genes <i>CTSL</i> and <i>APOE</i> using UK Biobank data.

Results of single RV-based association analysis in the genes CTSL and APOE using UK Biobank data.</p

QQ plot of ILCCO WES study.

The departure of the right tail from the 45 degree line represents the association signals from the study. (A) illustrates results using BF with KS prior. Under the null hypothesis (no association between genes and phenotype), 2logBFks~χ2(3). (B) shows results using BF with SKAT prior. Similarly, 2logBFSKAT ~ χ2(3) under the null hypothesis.</p

Results of gene-based analyses using BF_KS test^a in the discovery and replication studies.

Results of gene-based analyses using BFKS testa in the discovery and replication studies.</p

JNK-1 is involved in LMP-1-mediated activation of ΔNp73α expression.

<p>(<b>A</b>) BJAB cells were transfected with JNK-1 expression vector or empty pcDNA3 construct as control. After 36 hours cells were collected and processed for RNA extraction. The levels of ΔNp73, JNK-1 and GAPDH transcripts were determined by quantitative RT-PCR. The data are the mean of three independent experiments. The difference of ΔNp73α mRNA levels in mock cells (BJAB) and BJAB expressing JNK-1 is statistically significant (p value = 0.022). (<b>B</b>) LCLs were treated with JNK-1 inhibitor (SP600125) at 20 µM. After the indicated times cells were collected and processed for RNA extraction. ΔNp73 mRNA levels were determined by quantitative RT-PCR. The data are the mean of three independent experiments. The difference of ΔNp73α mRNA levels in LCLs cultured in presence (7 hours) or absence (DMSO) of JNK-1 inhibitor is statistically significant ((p value = 0.015). (<b>C and D</b>) Scrambled siRNA and siRNA for JNK-1 (siJNK-1) was transfected in LCLs. Thirty-six hours after transfection, cells were collected and processed for RNA or total cells proteins extraction. (C) ΔNp73 and JNK-1 transcript levels were determined by quantitative RT-PCR. The data are the mean of three independent experiments. The difference of JNK-1 or ΔNp73α mRNA levels in LCLs transfected with scramble siRNA or siJNK-1 is statistically significant (p value = 0.008 and p value = 0.0002, respectively). (D) Forty µg of whole cell lysate was analyzed by immunoblotting for the levels of ΔNp73α, JNK-1 or β-actin proteins (left panel). ΔNp73α and JNK-1 protein signal was quantified by Quantity one (Biorad), normalized on the levels of β-actin, and the values obtained were reported in the histogram (right panel). The data are the mean of three independent experiments. The difference of ΔNp73α mRNA levels in LCLs transfected with scramble siRNA or siJNK-1 is statistically significant (p value = 0.01). (<b>E and F</b>) SaOS-2 cells were transfected with different pcDNA3 constructs in the indicated combinations. After 36 hours, cells were collected and fixed for ChIP experiments performed with a HA antibody and followed by quatitative PCR (E) or analysed by immunoblot for the indicated proteins (F). (<b>G</b>) RPMI- EBVΔLMP-1 cells were transduced with pLXSN, pLXSN-LMP-1 wild-type or 378/Stop mutant retroviruses. Cells were selected for neomycin resistance, and then collected for RNA extraction. The levels of ΔNp73α, LMP-1 and EBER2 transcript were determined by RT-PCR.</p

Method Supplement.

Common genetic variants associated with lung cancer have been well studied in the past decade. However, only 12.3% heritability has been explained by these variants. In this study, we investigate the contribution of rare variants (RVs) (minor allele frequency CTSL and APOE, significantly associated with lung cancer in both studies. Single variant tests in UK Biobank identified 4 RVs (3 missense variants) in CTSL and 2 RVs (1 missense variant) in APOE stongly associated with lung cancer (OR between 2.0 and 139.0). The role of these genetic variants in the regulation of CTSL or APOE expression remains unclear. If such a role is established, this could have important therapeutic implications for lung cancer patients.</div

Population Structure shown in top 3 principal components.

Population Structure shown in top 3 principal components.</p

Results of gene-based analyses using BF_SKAT^a in the discovery and replication studies.

Results of gene-based analyses using BFSKATa in the discovery and replication studies.</p