Cancer/testis (CT) genes are excellent candidates for cancer immunotherapies because of their restrict expression in normal tissues and the capacity to elicit an immune response when expressed in tumor cells. In this study, we provide a genome-wide screen for CT genes with the identification of 745 putative CT genes. Comparison with a set of known CT genes shows that 201 new CT genes were identified. Integration of gene expression and clinical data led us to identify dozens of CT genes associated with either good or poor prognosis. For the CT genes related to good prognosis, we show that there is a direct relationship between CT gene expression and a signal for CD8+ cells infiltration for some tumor types, especially melanoma.

Oxidative stress generated during inflammation is associated with a wide range of pathologies. Resveratrol (RESV) displays anti-inflammatory and antioxidant activities, being a candidate for the development of adjuvant therapies for several inflammatory diseases. Despite this potential, the cellular responses induced by RESV are not well known. In this work, transcriptomic analysis was performed following lipopolysaccharide (LPS) stimulation of monocyte cultures in the presence of RESV. Induction of an inflammatory response was observed after LPS treatment and the addition of RESV led to decreases in expression of the inflammatory mediators, tumor necrosis factor-alpha (TNF-α), interleukin-8 (IL-8), and monocyte chemoattractant protein-1 (MCP-1), without cytotoxicity. RNA sequencing revealed 823 upregulated and 2098 downregulated genes (cutoff ≥2.0 or ≤−2.0) after RESV treatment. Gene ontology analysis showed that the upregulated genes were associated with metabolic processes and the cell cycle, consistent with normal cell growth and differentiation under an inflammatory stimulus. The downregulated genes were associated with inflammatory responses, gene expression, and protein modification. The prediction of master regulators using the iRegulon tool showed nuclear respiratory factor 1 (NRF1) and GA-binding protein alpha subunit (GABPA) as the main regulators of the downregulated genes. Using immunoprecipitation and protein expression assays, we observed that RESV was able to decrease protein acetylation patterns, such as acetylated apurinic/apyrimidinic endonuclease-1/reduction-oxidation factor 1 (APE1/Ref-1), and increase histone methylation. In addition, reductions in p65 (nuclear factor-kappa B (NF-κB) subunit) and lysine-specific histone demethylase-1 (LSD1) expression were observed. In conclusion, our data indicate that treatment with RESV caused significant changes in protein acetylation and methylation patterns, suggesting the induction of deacetylase and reduction of demethylase activities that mainly affect regulatory cascades mediated by NF-кB and Janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling. NRF1 and GABPA seem to be the main regulators of the transcriptional profile observed after RESV treatment.

The presence of oxidized DNA lesions, such as 7,8-dihydro-8-oxoguanine (8-oxoG) and apurinic/apyrimidinic sites (AP sites), has been described as epigenetic signals that are involved in gene expression control. In mammals, Apurinic-apyrimidinic endonuclease 1/Redox factor-1 (APE1/Ref-1) is the main AP endonuclease of the base excision repair (BER) pathway and is involved in active demethylation processes. In addition, APE1/Ref-1, through its redox function, regulates several transcriptional factors. However, the transcriptional control targets of each APE1 function are not completely known. In this study, a transcriptomic approach was used to investigate the effects of chemical inhibition of APE1/Ref-1 redox or DNA repair functions by E3330 or methoxyamine (MX) in an inflammatory cellular model. Under lipopolysaccharide (LPS) stimulation, both E3330 and MX reduced the expression of some cytokines and chemokines. Interestingly, E3330 treatment reduced cell viability after 48 h of the treatment. Genes related to inflammatory response and mitochondrial processes were downregulated in both treatments. In the E3330 treatment, RNA processing and ribosome biogenesis genes were downregulated, while they were upregulated in the MX treatment. Furthermore, in the E3330 treatment, the cellular stress response was the main upregulated process, while the cellular macromolecule metabolic process was observed in MX-upregulated genes. Nuclear respiratory factor 1 (NRF1) was predicted to be a master regulator of the downregulated genes in both treatments, while the ETS transcription factor ELK1 (ELK1) was predicted to be a master regulator only for E3330 treatment. Decreased expression of ELK1 and its target genes and a reduced 28S/18S ratio were observed, suggesting impaired rRNA processing. In addition, both redox and repair functions can affect the expression of NRF1 and GABPA target genes. The master regulators predicted for upregulated genes were YY1 and FLI1 for the E3330 and MX treatments, respectively. In summary, the chemical inhibition of APE1/Ref-1 affects gene expression regulated mainly by transcriptional factors of the ETS family, showing partial overlap of APE1 redox and DNA repair functions, suggesting that these activities are not entirely independent. This work provides a new perspective on the interaction between APE1 redox and DNA repair activity in inflammatory response modulation and transcription.

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In this manuscript we describe Proteogenomics Viewer, a web-based tool that collects MS peptide identification, indexes to genomic sequence and structure, assigns exon usage, reports the identified protein isoforms with genomic alignments and, most importantly, allows the inspection of MS2 information for proper peptide identification. It also provides all performed indexing to facilitate global analysis of the data. The relevance of such tool is that there has been an increase in the number of proteogenomic efforts to improve the annotation of both genomics and proteomics data, culminating with the release of the two human proteome drafts. It is now clear that mass spectrometry-based peptide identification of uncharacterized sequences, such as those resulting from unpredicted exon joints or non-coding regions, is still prone to a higher than expected false discovery rate. Therefore, proper visualization of the raw data and the corresponding genome alignments are fundamental for further data validation and interpretation. Also see the video abstract here: http://youtu.be/5NzyRvuk4Ac.

The gain of transcription factor binding sites (TFBS) is believed to represent one of the major causes of biological innovation.Here we used strategies based on comparative genomics to identify 21,822 TFBS specific to the human lineage (TFBS-HS), when compared to chimpanzee and gorilla genomes. More than 40% (9,206) of these TFBS-HS are in the vicinity of 1,283 genes. A comparison of the expression pattern of these genes and the corresponding orthologs in chimpanzee and gorilla identified genes differentially expressed in human tissues. These genes show a more divergent expression pattern in the human testis and brain, suggesting a role for positive selection in the fixation of TFBS gains. Genes associated with TFBS-HS were enriched in gene ontology categories related to transcriptional regulation, signaling, differentiation/development and nervous system. Furthermore, genes associated with TFBS-HS present a higher expression breadth when compared to genes in general. This biased distribution is due to a preferential gain of TFBS in genes with higher expression breadth rather than a shift in the expression pattern after the gain of TFBS.

Data science is historically a complex field, not only because of the huge amount of data and its variety of formats, but also because the necessity of collaboration between several specialists to retrieve valuable information. In this context, we created Bio-DIA, an online software to build data science workflow process focused in the integration of data and algorithms. Bio-DIA also facilitates the reusability of information/results obtained in previous process without the need of specific skills from the computer science field. The software was created with Angular at the front-end, Django at the back-end together with Spark to handle and process a variety of big data formats. The workflow/project is specified through XML file. Bio-DIA application facilitated the collaboration among users, allowing researcher ś groups to share data, scripts and information.Availability: https://ucrania.imd.ufrn.br/biodia-app/. Login: bioguest, password: welcome123.

No abstract