Correction: An epistatic interaction between the PAX8 and STK17B genes in papillary thyroid cancer susceptibility

El artículo original ha sido publicado: Landa I, Boullosa C, Inglada-Pe´rez L, Sastre-Perona A, Pastor S, et al. (2013) An Epistatic Interaction between the PAX8 and STK17B Genes in Papillary Thyroid Cancer Susceptibility. PLoS ONE 8(9): e74765. doi:10.1371/journal.pone.0074765

Transcriptomic and genetic associations between Alzheimer’s disease, Parkinson’s disease, and cancer

Alzheimer’s (AD) and Parkinson’s diseases (PD) are the two most prevalent neurodegenerative disorders in human populations. Epidemiological studies have shown that patients suffering from either condition present a reduced overall risk of cancer than controls (i.e., inverse comorbidity), suggesting that neurodegeneration provides a protective effect against cancer. Reduced risks of several site-specific tumors, including colorectal, lung, and prostate cancers, have also been observed in AD and PD. By contrast, an increased risk of melanoma has been described in PD patients (i.e., direct comorbidity). Therefore, a fundamental question to address is whether these associations are due to shared genetic and molecular factors or are explained by other phenomena, such as flaws in epidemiological studies, exposure to shared risk factors, or the effect of medications. To this end, we first evaluated the transcriptomes of AD and PD post-mortem brain tissues derived from the hippocampus and the substantia nigra and analyzed their similarities to those of a large panel of 22 site-specific cancers, which were obtained through differential gene expression meta-analyses of array-based studies available in public repositories. Genes and pathways that were deregulated in both disorders in each analyzed pair were examined. Second, we assessed potential genetic links between AD, PD, and the selected cancers by establishing interactome-based overlaps of genes previously linked to each disorder. Then, their genetic correlations were computed using cross-trait LD score regression and GWAS summary statistics data. Finally, the potential role of medications in the reported comorbidities was assessed by comparing disease-specific differential gene expression profiles to an extensive collection of differential gene expression signatures generated by exposing cell lines to drugs indicated for AD, PD, and cancer treatment (LINCS L1000). We identified significant inverse associations of transcriptomic deregulation between AD hippocampal tissues and breast, lung, liver, and prostate cancers, and between PD substantia nigra tissues and breast, lung, and prostate cancers. Moreover, significant direct (same direction) associations of deregulation were observed between AD and PD and brain and thyroid cancers, as well as between PD and kidney cancer. Several biological processes, including the immune system, oxidative phosphorylation, PI3K/AKT/mTOR signaling, and the cell cycle, were found to be deregulated in both cancer and neurodegenerative disorders. Significant genetic correlations were found between PD and melanoma and prostate cancers. Several drugs indicated for the treatment of neurodegenerative disorders and cancer, such as galantamine, selegiline, exemestane, and estradiol, were identified as potential modulators of the comorbidities observed between neurodegeneration and cancer.The research was supported by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER.Peer Reviewed"Article signat per 11 autors/es: Jaume Forés-Martos, Cesar Boullosa, David Rodrigo-Domínguez, Jon Sánchez-Valle, Beatriz Suay-García, Joan Climent, Antonio Falcó, Alfonso Valencia, Joan Anton Puig-Butillé, Susana Puig and Rafael Tabarés-Seisdedos"Postprint (published version

ChiTaRS: a database of human, mouse and fruit fly chimeric transcripts and RNA-sequencing data.

International audienceChimeric RNAs that comprise two or more different transcripts have been identified in many cancers and among the Expressed Sequence Tags (ESTs) isolated from different organisms; they might represent functional proteins and produce different disease phenotypes. The ChiTaRS database of Chimeric Transcripts and RNA-Sequencing data (http://chitars.bioinfo.cnio.es/) collects more than 16 000 chimeric RNAs from humans, mice and fruit flies, 233 chimeras confirmed by RNA-seq reads and ∼2000 cancer breakpoints. The database indicates the expression and tissue specificity of these chimeras, as confirmed by RNA-seq data, and it includes mass spectrometry results for some human entries at their junctions. Moreover, the database has advanced features to analyze junction consistency and to rank chimeras based on the evidence of repeated junction sites. Finally, 'Junction Search' screens through the RNA-seq reads found at the chimeras' junction sites to identify putative junctions in novel sequences entered by users. Thus, ChiTaRS is an extensive catalog of human, mouse and fruit fly chimeras that will extend our understanding of the evolution of chimeric transcripts in eukaryotes and can be advantageous in the analysis of human cancer breakpoints

Effects of drop jumps on 1000-m performance time and pacing in elite male and female endurance runners

Purpose: To evaluate the effect of drop jumps (DJs) on performance time and pacing in a field test (ie, 1000 m) commonly used to evaluate endurance runners and to evaluate running and jumping performance in male and female athletes separately. Methods: Twenty elite endurance runners (male, n = 10. 27.8 [7.0] y. 62.3 [5.2] kg; female, n = 10, 25.9 [5.3] y, 51.7 [4.1] kg) competing in middle- and long-distance events participated in this study. After determination of the box height associated with the best reactive strength index, athletes randomly performed a warm-up with or without the inclusion of 5 DJs with the highest reactive strength index prior to a 1000-m track test. Performance time and pacing (250-m splits) were determined. Countermovement jump heights at different time points and blood lactate concentration after running tests were also recorded. Results: A "possible" faster 1000-m time (162.4 vs 165.3 s) with a "very likely" faster first split (38.8 vs 40.3 s) was observed in male athletes in the DJ condition. In contrast, female athletes showed a "possible" slower running time (186.8 vs 184.8 s) and a "likely" greater blood lactate concentration after the 1000-m test in the DJ condition. Male and female athletes presented greater countermovement-jump performances after warm-up and running tests in both conditions. Conclusions: The inclusion of 5 DJs with the height associated with the best reactive strength index induced a "possible" improvement in 1000-m performance time in elite male endurance runners. The current protocol should be avoided in female athletes

An epistatic interaction between the PAX8 and STK17B genes in papillary thyroid cancer susceptibility.

Papillary Thyroid Cancer (PTC) is a heterogeneous and complex disease; susceptibility to PTC is influenced by the joint effects of multiple common, low-penetrance genes, although relatively few have been identified to date. Here we applied a rigorous combined approach to assess both the individual and epistatic contributions of genetic factors to PTC susceptibility, based on one of the largest series of thyroid cancer cases described to date. In addition to identifying the involvement of TSHR variation in classic PTC, our pioneer study of epistasis revealed a significant interaction between variants in STK17B and PAX8. The interaction was detected by MD-MBR (p = 0.00010) and confirmed by other methods, and then replicated in a second independent series of patients (MD-MBR p = 0.017). Furthermore, we demonstrated an inverse correlation between expression of PAX8 and STK17B in a set of cell lines derived from human thyroid carcinomas. Overall, our work sheds additional light on the genetic basis of thyroid cancer susceptibility, and suggests a new direction for the exploration of the inherited genetic contribution to disease using association studies

An Epistatic Interaction between the PAX8 and STK17B Genes in Papillary Thyroid Cancer Susceptibility

Papillary Thyroid Cancer (PTC) is a heterogeneous and complex disease; susceptibility to PTC is influenced by the joint effects of multiple common, low-penetrance genes, although relatively few have been identified to date. Here we applied a rigorous combined approach to assess both the individual and epistatic contributions of genetic factors to PTC susceptibility, based on one of the largest series of thyroid cancer cases described to date. In addition to identifying the involvement of TSHR variation in classic PTC, our pioneer study of epistasis revealed a significant interaction between variants in STK17B and PAX8. The interaction was detected by MD-MBR (p = 0.00010) and confirmed by other methods, and then replicated in a second independent series of patients (MD-MBR p = 0.017). Furthermore, we demonstrated an inverse correlation between expression of PAX8 and STK17B in a set of cell lines derived from human thyroid carcinomas. Overall, our work sheds additional light on the genetic basis of thyroid cancer susceptibility, and suggests a new direction for the exploration of the inherited genetic contribution to disease using association studies

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

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