A cell cycle-related lncRNA signature predicts the progression-free interval in papillary thyroid carcinoma.

The cell cycle plays a vital role in tumorigenesis and progression. Long non-coding RNAs (lncRNAs) are key regulators of cell cycle processes. Therefore, understanding cell cycle-related lncRNAs (CCR-lncRNAs) is crucial for determining the prognosis of papillary thyroid carcinoma (PTC). RNA-seq and clinical data of PTC were acquired from The Cancer Genome Atlas, and CCR-lncRNAs were selected based on Pearson's correlation coefficients. According to univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses, a five-CCR-lncRNA signature (FOXD2-AS1, LOC100507156, BSG-AS1, EGOT, and TMEM105) was established to predict the progression-free interval (PFI) in PTC. Kaplan-Meier survival, time-dependent receiver operating characteristic curve, and multivariate Cox regression analyses proved that the signature had a reliable prognostic capability. A nomogram consisting of the risk signature and clinical characteristics was constructed that effectively predicted the PFI in PTC. Functional enrichment analyses indicted that the signature was involved in cell cycle- and immune-related pathways. Furthermore, we also analyzed the correlation between the signature and immune cell infiltration. Finally, we verified the differential expression of CCR-lncRNAs in vitro using quantitative real-time polymerase chain reaction. Overall, the newly developed prognostic risk signature based on five CCR-lncRNAs may become a marker for predicting the PFI in PTC.

Multiplex-Heterogeneous Network-Based Capturing Potential SNP "Switches" of Pathways Associating With Diverse Disease Characteristics of Asthma.

Asthma is a complex heterogeneous respiratory disorder. In recent years nubbly regions of the role of genetic variants and transcriptome including mRNAs, microRNAs, and long non-coding RNAs in the pathogenesis of asthma have been separately excavated and reported. However, how to systematically integrate and decode this scattered information remains unclear. Further exploration would improve understanding of the internal communication of asthma. To excavate new insights into the pathogenesis of asthma, we ascertained three asthma characteristics according to reviews, airway inflammation, airway hyperresponsiveness, and airway remodeling. We manually created a contemporary catalog of corresponding risk transcriptome, including mRNAs, miRNAs, and lncRNAs. MIMP is a multiplex-heterogeneous networks-based approach, measuring the relevance of disease characteristics to the pathway by examining the similarity between the determined vectors of risk transcriptome and pathways in the same low-dimensional vector space. It was developed to enable a more concentrated and in-depth exploration of potential pathways. We integrated experimentally validated competing endogenous RNA regulatory information and the SNPs with significant pathways into the ceRNA-mediated SNP switching pathway network (CSSPN) to analyze ceRNA regulation of pathways and the role of SNP in these dysfunctions. We discovered 11 crucial ceRNA regulations concerning asthma disease feature pathway and propose a potential mechanism of ceRNA regulatory SNP → gene → pathway → disease feature effecting asthma pathogenesis, especially for MALAT1 (rs765499057/rs764699354/rs189435941) → hsa-miR-155 → IL13 (rs201185816/rs1000978586/rs202101165) → Interleukin-4 and Interleukin-13 signaling → inflammation/airway remodeling and MALAT1 (rs765499057/rs764699354/rs189435941) → hsa-miR-155 → IL17RB (rs948046241) → Interleukin-17 signaling (airway remodeling)/Cytokine-cytokine receptor interaction (inflammation). This study showed a systematic and propagable workflow for capturing the potential SNP "switch" of asthma through text and database mining and provides further information on the pathogenesis of asthma.

No association between IL-1RN VNTR and the risk of duodenal ulcer: a meta-analysis.

The aim of this study was to perform a meta-analysis to investigate a more authentic association between interleukin-1 RN variable number of tandem repeats (IL-1RN VNTR) and duodenal ulcer (DU). Systematic searches of electronic databases Embase, PubMed and Web of Science were performed. Statistical analyses were conducted using software Stata 11.0. The pooled odds ratios (ORs) with 95% confidence intervals (95% CIs) were applied. Publication bias was tested by Begg's funnel plot and Egger's regression test. A total of 16 studies including 2115 cases and 3622 controls were included in our final meta-analysis. There was no evidence of significant association between IL-1RN VNTR and DU (allelic model: OR = 1.04, 95% CI = 0.87-1.26; additive model: OR = 0.85, 95% CI = 0.62-1.16; dominant model: OR = 1.06, 95% CI = 0.92-1.23; and recessive model: OR = 0.83, 95% CI = 0.61-1.12). Significant protective associations were found in additive model (OR = 0.51, 95% CI = 0.31-0.83) and recessive model (OR = 0.45, 95% CI = 0.28-0.73) in Caucasian subgroup. In conclusion, our meta-analysis suggests that there is no evidence of significant association between IL-1RN VNTR and DU with or without Helicobacter pylori infection in overall population, whereas significant association is found by subgroup analyses which showed protective effect of IL-1RN allele 2 against DU risk in Caucasian population.