MOESM1 of CREBBP/EP300 bromodomains are critical to sustain the GATA1/MYC regulatory axis in proliferation

Additional file 1: Table S1. gRNAs used for gene editing. Fig. S1. Statistical analysis of the CRISPR-Cas9 growth competition experiments. Tukey Kramer analysis of the adjusted percentages of growth inhibition caused by gRNAs targeting different regions of CREBBP (A) or EP300 (B). 5′ coding region (5′), non-conserved aminoacids of the bromodomain (ncBD), conserved aminoacids of the bromodomain (cBD) and non-target (NT). Fig. S2. Enrichment of gene expression changes after treatment with CBP30 and I-CBP112. (A) p-values for enrichment of SE-associated genes (SE) and genes with top levels of EP300 (EP300) in genes upregulated and downregulated by CBP30 and I-CBP112 treatments. (B) GSEA analysis of changes in gene expression caused by the indicated treatments and gene sets. Fig. S3. GATA1 mRNA expression in cancer cell lines and patients. (A) mRNA levels of GATA1 determined by microarray in CCLE lines grouped by cancer type. (B) GATA1 mRNA levels determined by RNAseq in cancer patients according to TCGA. Fig. S4. Expression of GATA1 splicing variants in K562 (A) Three variants are expressed in K562 according to the analysis of the RNA-seq experiment (B) Graph shows the levels of expression of the different variants in K562 cells treated with vehicle or two concentrations of CBP30. P-values for significant changes (p ≤ 0.05) are shown. Fig. S5. Human myeloma cell lines with MYC amplifications or translocations are sensitive to CBP30. (A) IC50s of growth inhibition in KMS11 or MM1S cells treated with JQ1, C646 and CBP30 for 7 days. (B) mRNA (upper panel) and protein (lower panel) levels of MYC in KMS11 or MM1S cells treated with 2 µM CBP30, 10 µM C646 and 150 nM JQ1 for 48 hours

Gene-gene interaction results for susceptibility to classic Papillary Thyroid Carcinoma.

<p>SH- SNPHarvester; MSH- MegaSNPHunter; Light grey shading indicates interactions selected by each of the algorithms; dark grey green shading indicates the interaction fulfilling the established criteria to pass to stage 2 (replication) (SNP pair selected by at least three methods);</p>*<p>associated P-value; NA- not available (all genotypes combinations classified as neutral).</p

Association with risk of follicular cell-derived thyroid cancer for 9 candidate variants in the discovery and replication stages.

<p>Abbreviations: MAF = minor allele frequency; OR = odds ratio; CI = confidence interval; ESE = Exonic Splicing Enhancers; PTC = Papillary Thyroid Carcinoma; cPTC = classic PTC; fvPTC = follicular variant of PTC; FTC = Follicular Thyroid Carcinoma. The table is sorted by disease subtype and, within each group, by <i>P</i>-value.</p>a<p>Major/minor allele (in controls);</p>b<p>OR and CI were obtained using homozygotes for the most frequent allele in controls as the reference group;</p>c<p><i>P</i>-values are derived from Wald statistics;</p>d<p>Results adjusted for age and gender;</p>e<p>Results adjusted for age, gender and country.</p

Relative expression levels of STK17B in Pax8-silenced cells.

<p>PCCl3 cells were transiently (A) or stably (B) silenced for the transcription factor Pax8 (siPax8). As a control, wild type or siScramble transfected cells were used. The expression levels were assessed by means of qRT-PCR (A, upper panel) or western blot (A, lower panel, and B).</p

Epistatic model for SNPs in <i>PAX8</i> and <i>STK17B</i> and genotype frequencies for cPTC-cases and controls.

<p>Relative frequencies of the nine genotype combinations of the replicated interaction (<i>PAX8</i>-<i>STK17B</i>) are shown for cases and controls (red and blue columns, respectively). The cell containing the high-risk genotype combination is highlighted in light red, those with low-risk combinations in light blue, and those with neutral combinations are uncoloured. Figure1a - based on the discovery stage (series I); <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074765#pone-0074765-g001" target="_blank">Figure 1b</a> - based on the replication stage (series II and III); <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074765#pone-0074765-g001" target="_blank">Figure 1c</a> – based on both stages combined (series I, II and III).</p

STK17B and PAX8 mRNA levels in thyroid tumoral cell lines.

<p>The mRNA expression levels of both genes were determined by qRT-PCR and are represented as relative units. The name of the cell line and its origin (follicular, papillary or anaplastic) is indicated.</p

DataSheet_1_Randomized phase II clinical trial of ruxolitinib plus simvastatin in COVID19 clinical outcome and cytokine evolution.pdf

BackgroundManaging the inflammatory response to SARS-Cov-2 could prevent respiratory insufficiency. Cytokine profiles could identify cases at risk of severe disease.MethodsWe designed a randomized phase II clinical trial to determine whether the combination of ruxolitinib (5 mg twice a day for 7 days followed by 10 mg BID for 7 days) plus simvastatin (40 mg once a day for 14 days), could reduce the incidence of respiratory insufficiency in COVID-19. 48 cytokines were correlated with clinical outcome.ParticipantsPatients admitted due to COVID-19 infection with mild disease.ResultsUp to 92 were included. Mean age was 64 ± 17, and 28 (30%) were female. 11 (22%) patients in the control arm and 6 (12%) in the experimental arm reached an OSCI grade of 5 or higher (p = 0.29). Unsupervised analysis of cytokines detected two clusters (CL-1 and CL-2). CL-1 presented a higher risk of clinical deterioration vs CL-2 (13 [33%] vs 2 [6%] cases, p = 0.009) and death (5 [11%] vs 0 cases, p = 0.059). Supervised Machine Learning (ML) analysis led to a model that predicted patient deterioration 48h before occurrence with a 85% accuracy.ConclusionsRuxolitinib plus simvastatin did not impact the outcome of COVID-19. Cytokine profiling identified patients at risk of severe COVID-19 and predicted clinical deterioration.Trial registrationhttps://clinicaltrials.gov/, identifier NCT04348695.</p

Table_1_Randomized phase II clinical trial of ruxolitinib plus simvastatin in COVID19 clinical outcome and cytokine evolution.xlsx

BackgroundManaging the inflammatory response to SARS-Cov-2 could prevent respiratory insufficiency. Cytokine profiles could identify cases at risk of severe disease.MethodsWe designed a randomized phase II clinical trial to determine whether the combination of ruxolitinib (5 mg twice a day for 7 days followed by 10 mg BID for 7 days) plus simvastatin (40 mg once a day for 14 days), could reduce the incidence of respiratory insufficiency in COVID-19. 48 cytokines were correlated with clinical outcome.ParticipantsPatients admitted due to COVID-19 infection with mild disease.ResultsUp to 92 were included. Mean age was 64 ± 17, and 28 (30%) were female. 11 (22%) patients in the control arm and 6 (12%) in the experimental arm reached an OSCI grade of 5 or higher (p = 0.29). Unsupervised analysis of cytokines detected two clusters (CL-1 and CL-2). CL-1 presented a higher risk of clinical deterioration vs CL-2 (13 [33%] vs 2 [6%] cases, p = 0.009) and death (5 [11%] vs 0 cases, p = 0.059). Supervised Machine Learning (ML) analysis led to a model that predicted patient deterioration 48h before occurrence with a 85% accuracy.ConclusionsRuxolitinib plus simvastatin did not impact the outcome of COVID-19. Cytokine profiling identified patients at risk of severe COVID-19 and predicted clinical deterioration.Trial registrationhttps://clinicaltrials.gov/, identifier NCT04348695.</p