Identification of STRBP as a Novel JAK2 Fusion Partner Gene in a Young Adult With Philadelphia Chromosome-Like B-Lymphoblastic Leukemia

The hsa-miR-3613-5p, a potential oncogene correlated with diagnostic and prognostic merits in kidney renal clear cell carcinoma

MicroRNA-3613 (hsa-miR-3613-5p), a biomarker with a dual role as an oncogenic or tumor suppressor, is associated with different types of cancer. This study aimed to determine the correlation between the hsa-miR-3613-5p gene expression and Kidney renal clear cell carcinoma (KIRC). Utilizing several bioinformatics tools, we examined the expression level and clinicopathological value of hsa-miR-3613-5p in patients with KIRC compared to normal tissues. Other bioinformatic measures, including survival analysis, diagnostic merit of hsa-miR-3613-5p, downstream target prediction, potential upstream lncRNAs, network construction, and functional enrichment analysis of hsa-miR-3613-5p, were performed. We observed that overexpression of hsa-miR-3613-5p in KIRC tissues had valuable diagnostic merit and was significantly correlated with the poor overall survival of KIRC patients. We also realized a correlation between abnormal expression of hsa-miR-3613-5p and several clinical parameters such as pathological stage, race, age, and histological grades in patients with KIRC. Moreover, we constructed the most potential regulatory network of hsa-miR-3613-5p in KIRC with 17 different axes, including four pseudogenes, two lncRNAs, and three mRNAs. Besides, we uncovered six variants in the mature form of hsa-miR-3613-5p. Finally, pathway enrichment analysis demonstrated that the top-ranked pathways for hsa-miR-3613-5p are cell cycle, cell adhesion molecules (CAMs), and hepatocellular carcinoma pathways. The present report suggests that the higher expression of hsa-miR-3613-5p is associated with the progression of KIRC. Therefore, it may be considered a valuable indicator for the early detection, risk stratification, and targeted treatment of patients with KIRC.

Development and validation of a genomic nomogram based on a ceRNA network for comprehensive analysis of obstructive sleep apnea

Objectives: Some ceRNA associated with lncRNA have been considered as possible diagnostic and therapeutic biomarkers for obstructive sleep apnea (OSA). We intend to identify the potential hub genes for the development of OSA, which will provide a foundation for the study of the molecular mechanism underlying OSA and for the diagnosis and treatment of OSA.

Methods: We collected plasma samples from OSA patients and healthy controls for the detection of ceRNA using a chip. Based on the differential expression of lncRNA, we identified the target genes of miRNA that bind to lncRNAs. We then constructed lncRNA-related ceRNA networks, performed functional enrichment analysis and protein-protein interaction analysis, and performed internal and external validation of the expression levels of stable hub genes. Then, we conducted LASSO regression analysis on the stable hub genes, selected relatively significant genes to construct a simple and easy-to-use nomogram, validated the nomogram, and constructed the core ceRNA sub-network of key genes.

Results: We successfully identified 282 DElncRNAs and 380 DEmRNAs through differential analysis, and we constructed an OSA-related ceRNA network consisting of 292 miRNA-lncRNAs and 41 miRNA-mRNAs. Through PPI and hub gene selection, we obtained 7 additional robust hub genes, CCND2, WT1, E2F2, IRF1, BAZ2A, LAMC1, and DAB2. Using LASSO regression analysis, we created a nomogram with four predictors (CCND2, WT1, E2F2, and IRF1), and its area under the curve (AUC) is 1. Finally, we constructed a core ceRNA sub-network composed of 74 miRNA-lncRNA and 7 miRNA-mRNA nodes.

Conclusion: Our study provides a new foundation for elucidating the molecular mechanism of lncRNA in OSA and for diagnosing and treating OSA.