The Prognostic Signature and Therapeutic Value of Phagocytic Regulatory Factors in Prostate Adenocarcinoma (PRAD)

There is growing evidence that phagocytosis regulatory factors (PRFs) play important roles in tumor progression, and therefore, identifying and characterizing these factors is crucial for understanding the mechanisms of cellular phagocytosis in tumorigenesis. Our research aimed to comprehensively characterize PRFs in prostate adenocarcinoma (PRAD) and to screen and determine important PRFs in PRAD which may help to inform tumor prognostic and therapeutic signatures based on these key PRFs. Here, we first systematically described the expression of PRFs in PRAD and evaluated their expression patterns and their prognostic value. We then analyzed prognostic phagocytic factors by Cox and Lasso analysis and constructed a phagocytic factor-mediated risk score. We then divided the samples into two groups with significant differences in overall survival (OS) based on the risk score. Then, we performed correlation analysis between the risk score and clinical features, immune infiltration levels, immune characteristics, immune checkpoint expression, IC50 of several classical sensitive drugs, and immunotherapy efficacy. Finally, the Human Protein Atlas (HPA) database was used to determine the protein expression of 18 PRF characteristic genes. The aforementioned results confirmed that multilayer alterations of PRFs were associated with the prognosis of patients with PRAD and the degree of macrophage infiltration. These findings may provide us with potential new therapies for PRAD.

Screening a novel six critical gene-based system of diagnostic and prognostic biomarkers in prostate adenocarcinoma patients with different clinical variables

The mechanisms behind prostate adenocarcinoma (PRAD) pathogenicity remain to be understood due to tumor heterogeneity. In the current study, we identified by microarray technology six eligible real hub genes from already identified hub genes through a systematic in silico approach that could be useful to lower the heterogenetic-specific barriers in PRAD patients for diagnosis, prognosis, and treatment. For this purpose, microarray technology-based, already-identified PRAD-associated hub genes were initially explored through extensive literature mining; then, a protein-protein interaction (PPI) network construction of those hub genes and its analysis helped us to identify six most critical genes (real hub genes). Various online available expression databases were then used to explore the tumor driving, diagnostic, and prognostic roles of real hub genes in PRAD patients with different clinicopathologic variables. In total, 124 hub genes were extracted from the literature, and among those genes, six, including CDC20, HMMR, AURKA, CDK1, ASF1B, and CCNB1 were identified as real hub genes by the degree method. Further expression analysis revealed the significant up-regulation of real hub genes in PRAD patients of different races, age groups, and nodal metastasis status relative to controls. Moreover, through correlational analyses, different valuable correlations between treal hub genes expression and different other data (promoter methylation status, genetic alterations, overall survival (OS), tumor purity, CD4+ T, CD8+ T immune cells infiltration, and different other mutant genes and a few more) across PRAD samples were also documented. Ultimately, from this study, a few important transcription factors (TFS), miRNAs, and chemotherapeutic drugs showing a great therapeutic potential were also identified. In conclusion, we have discovered a set of six real hub genes that might be utilized as new biomarkers for lowering heterogenetic-specific barriers in PRAD patients for diagnosis, prognosis, and treatment.

2-kupl: mapping-free variant detection from DNA-seq data of matched samples

BACKGROUND

The detection of genome variants, including point mutations, indels and structural variants, is a fundamental and challenging computational problem. We address here the problem of variant detection between two deep-sequencing (DNA-seq) samples, such as two human samples from an individual patient, or two samples from distinct bacterial strains. The preferred strategy in such a case is to align each sample to a common reference genome, collect all variants and compare these variants between samples. Such mapping-based protocols have several limitations. DNA sequences with large indels, aggregated mutations and structural variants are hard to map to the reference. Furthermore, DNA sequences cannot be mapped reliably to genomic low complexity regions and repeats.

RESULTS

We introduce 2-kupl, a k-mer based, mapping-free protocol to detect variants between two DNA-seq samples. On simulated and actual data, 2-kupl achieves higher accuracy than other mapping-free protocols. Applying 2-kupl to prostate cancer whole exome sequencing data, we identify a number of candidate variants in hard-to-map regions and propose potential novel recurrent variants in this disease.

CONCLUSIONS

We developed a mapping-free protocol for variant calling between matched DNA-seq samples. Our protocol is suitable for variant detection in unmappable genome regions or in the absence of a reference genome.

Gene Expression Changes and Associated Pathways Involved in the Progression of Prostate Cancer Advanced Stages

Prostate cancer (PC) is one of the most common cancers among men worldwide, and advanced PCs, such as locally advanced PC (LAPC) and castration-resistant PC (CRPC), present the greatest challenges in clinical management. Current indicators have limited capacity to predict the disease course; therefore, better prognostic markers are greatly needed. In this study, we performed a bioinformatic analysis of The Cancer Genome Atlas (TCGA) datasets, including RNA-Seq data from the prostate adenocarcinoma (PRAD; n = 55) and West Coast Dream Team – metastatic CRPC (WCDT-MCRPC; n = 84) projects, to evaluate the transcriptome changes associated with progression-free survival (PFS) for LAPC and CRPC, respectively. We identified the genes whose expression was positively/negatively correlated with PFS. In LAPC, the genes with the most significant negative correlations were ZC2HC1A, SQLE, and KIF11, and the genes with the most significant positive correlations were SOD3, LRRC26, MIR22HG, MEG3, and MIR29B2CHG. In CRPC, the most significant positive correlations were found for BET1, CTAGE5, IFNGR1, and GIMAP6, and the most significant negative correlations were found for CLPB, PRPF19, ZNF610, MPST, and LINC02001. In addition, we performed a gene network interaction analysis using STRINGdb, which revealed a significant relationship between genes predominantly involved in the cell cycle and characterized by upregulated expression in early recurrence. Based on the results, we propose several genes that can be used as potential prognostic markers.

Expression patterns and a prognostic model of m6A-associated regulators in prostate adenocarcinoma

Aim: To study the expression patterns and prognostic value of the m⁶A-associated regulators in prostate adenocarcinoma (PRAD). Materials & methods: The mRNA expression and clinical data were downloaded from 'The Cancer Genome Atlas database'. The m⁶A-associated variants were downloaded from m⁶AVar database, and combined with 14 common m⁶A regulators for subsequent analysis. One-way analysis of variance, univariate Cox regression analysis and least absolute shrinkage and selection operator algorithm were successively applied to obtain the ultimate regulators and prognostic model. Finally, consensus clustering, protein-protein interaction (PPI) and enrichment analysis were performed. Result: Nine regulators were obtained. PRAD patients could be classified into two risk groups and subclasses with significant survival differences by the prognostic model and consensus clustering, respectively. Conclusion: All these nine regulators were related to prognosis in PRAD, and could be used as clinical biomarkers.

vtRNA2-1/nc886 Produces a Small RNA That Contributes to Its Tumor Suppression Action through the microRNA Pathway in Prostate Cancer

vtRNA2-1 is a vault RNA initially classified as microRNA precursor hsa-mir-886 and recently proposed as "nc886", a new type of non-coding RNA involved in cancer progression acting as an oncogene and tumor suppressor gene in different tissues. We have shown that vtRNA2-1/nc886 is epigenetically repressed in neoplastic cells, increasing cell proliferation and invasion in prostate tissue. Here we investigate the ability of vtRNA2-1/nc886 to produce small-RNAs and their biological effect in prostate cells. The interrogation of public small-RNA transcriptomes of prostate and other tissues uncovered two small RNAs, snc886-3p and snc886-5p, derived from vtRNA2-1/nc886 (previously hsa-miR-886-3p and hsa-miR-886-5p). Re-analysis of PAR-CLIP and knockout of microRNA biogenesis enzymes data showed that these small RNAs are products of DICER, independent of DROSHA, and associate with Argonaute proteins, satisfying microRNA attributes. In addition, the overexpression of snc886-3p provokes the downregulation of mRNAs bearing sequences complementary to its "seed" in their 3'-UTRs. Microarray and in vitro functional assays in DU145, LNCaP and PC3 cell lines revealed that snc886-3p reduced cell cycle progression and increases apoptosis, like its precursor vtRNA2-1/nc886. Finally, we found a list of direct candidate targets genes of snc886-3p upregulated and associated with disease condition and progression in PRAD-TCGA data. Overall, our findings suggest that vtRNA2-1/nc886 and its processed product snc886-3p are synthesized in prostate cells, exerting a tumor suppressor action.

High-throughput validation of ceRNA regulatory networks

Background

MicroRNAs (miRNAs) play multiple roles in tumor biology. Interestingly, reports from multiple groups suggest that miRNA targets may be coupled through competitive stoichiometric sequestration. Specifically, computational models predicted and experimental assays confirmed that miRNA activity is dependent on miRNA target abundance, and consequently, changes in the abundance of some miRNA targets lead to changes to the regulation and abundance of their other targets. The resulting indirect regulatory influence between miRNA targets resembles competition and has been dubbed competitive endogenous RNA (ceRNA). Recent studies have questioned the physiological relevance of ceRNA interactions, our ability to accurately predict these interactions, and the number of genes that are impacted by ceRNA interactions in specific cellular contexts.

Results

To address these concerns, we reverse engineered ceRNA networks (ceRNETs) in breast and prostate adenocarcinomas using context-specific TCGA profiles, and tested whether ceRNA interactions can predict the effects of RNAi-mediated gene silencing perturbations in PC3 and MCF7 cells._ENREF_22 Our results, based on tests of thousands of inferred ceRNA interactions that are predicted to alter hundreds of cancer genes in each of the two tumor contexts, confirmed statistically significant effects for half of the predicted targets.

Conclusions

Our results suggest that the expression of a significant fraction of cancer genes may be regulated by ceRNA interactions in each of the two tumor contexts.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3790-7) contains supplementary material, which is available to authorized users.

Progress in the development of enzyme-based nerve agent bioscavengers

Acetylcholinesterase is the physiological target for acute toxicity of nerve agents. Attempts to protect acetylcholinesterase from phosphylation by nerve agents, is currently achieved by reversible inhibitors that transiently mask the enzyme active site. This approach either protects only peripheral acetylcholinesterase or may cause side effects. Thus, an alternative strategy consists in scavenging nerve agents in the bloodstream before they can reach acetylcholinesterase. Pre- or post-exposure administration of bioscavengers, enzymes that neutralize and detoxify organophosphorus molecules, is one of the major developments of new medical counter-measures. These enzymes act either as stoichiometric or catalytic bioscavengers. Human butyrylcholinesterase is the leading stoichiometric bioscavenger. Current efforts are devoted to its mass production with care to pharmacokinetic properties of the final product for extended lifetime. Development of specific reactivators of phosphylated butyrylcholinesterase, or variants with spontaneous reactivation activity is also envisioned for rapid in situ regeneration of the scavenger. Human paraoxonase 1 is the leading catalytic bioscavenger under development. Research efforts focus on improving its catalytic efficiency toward the most toxic isomers of nerve agents, by means of directed evolution-based strategies. Human prolidase appears to be another promising human enzyme. Other non-human efficient enzymes like bacterial phosphotriesterases or squid diisopropylfluorophosphatase are also considered though their intrinsic immunogenic properties remain challenging for use in humans. Encapsulation, PEGylation and other modifications are possible solutions to address this problem as well as that of their limited lifetime. Finally, gene therapy for in situ generation and delivery of bioscavengers is for the far future, but its proof of concept has been established.