Exploring the role of ubiquitin regulatory X domain family proteins in cancers: bioinformatics insights, mechanisms, and implications for therapy.

UBXD family (UBXDF), a group of proteins containing ubiquitin regulatory X (UBX) domains, play a crucial role in the imbalance of proliferation and apoptotic in cancer. In this study, we summarised bioinformatics proof on multi-omics databases and literature on UBXDF's effects on cancer. Bioinformatics analysis revealed that Fas-associated factor 1 (FAF1) has the largest number of gene alterations in the UBXD family and has been linked to survival and cancer progression in many cancers. UBXDF may affect tumour microenvironment (TME) and drugtherapy and should be investigated in the future. We also summarised the experimental evidence of the mechanism of UBXDF in cancer, both in vitro and in vivo, as well as its application in clinical and targeted drugs. We compared bioinformatics and literature to provide a multi-omics insight into UBXDF in cancers, review proof and mechanism of UBXDF effects on cancers, and prospect future research directions in-depth. We hope that this paper will be helpful for direct cancer-related UBXDF studies.

Biomarker of Pulmonary Inflammatory Response in LUAD: miR-584-5p Targets RAB23 to Suppress Inflammation Induced by LPS in A549 Cells.

BACKGROUND: Pulmonary inflammatory response (PIR) is one of the prognostic risk factors of lung adenocarcinoma (LUAD), with a high mortality rate. OBJECTIVES: This study aims to investigate prognostic microRNA (miRNA) to improve clinical prognosis prediction and postoperative inflammation treatment in LUAD patients. METHODS: About 201 differentially expressed microRNAs (DE-miRNAs) in LUAD were mined by differential analysis. Univariate/multivariate Cox analyses established and validated prognostic risk miRNAs in TCGA-LUAD. KEGG and GO were used to link risk signatures and biological functions. After 48 hours of exposure to 50 ng/mL LPS, the miR-584-5p/RAB23 regulatory network was verified in qRT-PCR, Western Blotting, and the Luciferase Reporter Assay in A549 cells. RESULTS: MiR-584-5p and miR-101-3p were validated as riskscore correlated with LUAD patients' 1-year survival (p < 0.001) and participate in multiple inflammation-related pathways. RAB23, a RAS oncogene, is involved in inflammatory MAPK signaling. Evidence suggests that miR-584-5p regulates inflammation in LUAD by targeting RAB23. A549 cells were transfected with the mimic and inhibitor of miR-584-5p, confirming the negative regulatory relationship between miR-584-5p and RAB23. In the A549 induced by LPS, either over-expression of miR-584-5p or knock-down of RAB23 expression decreased the expression of inflammatory factors and increased cell viability. CONCLUSION: Prognostic-related risk miR-584-5p can regulate the expression of RAB23 at both the mRNA and protein levels, thereby influencing the development of a PIR in LUAD. This will have significant implications for the clinical prognosis prediction and therapy decision-making of LUAD patients with PIR.

The Emerging Roles of circRNAs in Papillary Thyroid Carcinoma: Molecular Mechanisms and Biomarker Potential.

Papillary thyroid carcinoma (PTC) is a common endocrine malignant tumor. The incidence of PTC has increased in the past decades and presents a younger trend. Accumulating evidence indicates that circular RNAs (circRNAs), featured with non-linear, closed-loop structures, play pivotal roles in tumorigenesis and regulate cell biological processes, such as proliferation, migration, and invasion, by acting as microRNA (miRNA) sponges. Additionally, due to their unique stability, circRNAs hold promising potential as diagnostic biomarkers and effective therapeutic targets for PTC treatment. In this review, we systematically arrange the expression level of circRNAs, related clinical characteristics, circRNA-miRNA-mRNA regulatory network, and molecular mechanisms. Furthermore, related signaling pathways and their potential ability of diagnostic biomarkers and therapeutic targets are discussed, which might provide a new strategy for PTC diagnosis, monitoring, and prognosis.

Machine learning modeling and prognostic value analysis of invasion-related genes in cutaneous melanoma.

In this study, we aimed to develop an invasion-related risk signature and prognostic model for personalized treatment and prognosis prediction in skin cutaneous melanoma (SKCM), as invasion plays a crucial role in this disease. We identified 124 differentially expressed invasion-associated genes (DE-IAGs) and selected 20 prognostic genes (TTYH3, NME1, ORC1, PLK1, MYO10, SPINT1, NUPR1, SERPINE2, HLA-DQB2, METTL7B, TIMP1, NOX4, DBI, ARL15, APOBEC3G, ARRB2, DRAM1, RNF213, C14orf28, and CPEB3) using Cox and LASSO regression to establish a risk score. Gene expression was validated through single-cell sequencing, protein expression, and transcriptome analysis. Negative correlations were discovered between risk score, immune score, and stromal score using ESTIMATE and CIBERSORT algorithms. High- and low-risk groups exhibited significant differences in immune cell infiltration and checkpoint molecule expression. The 20 prognostic genes effectively differentiated between SKCM and normal samples (AUCs >0.7). We identified 234 drugs targeting 6 genes from the DGIdb database. Our study provides potential biomarkers and a risk signature for personalized treatment and prognosis prediction in SKCM patients. We developed a nomogram and machine-learning prognostic model to predict 1-, 3-, and 5-year overall survival (OS) using risk signature and clinical factors. The best model, Extra Trees Classifier (AUC = 0.88), was derived from pycaret's comparison of 15 classifiers. The pipeline and app are accessible at https://github.com/EnyuY/IAGs-in-SKCM.

A Versatile Luminescent Ga-Organic Framework with Multi-Emission Centers as a Blue LED and Fluorescent Probe for Low-Temperature Detection and Selective Fe3+ Sensing.

The development and utilization of 3p-block based MOFs as fluorescent materials has attracted significant attention in recent years. Herein, we have successfully constructed a versatile luminescent Ga-MOF (SNNU-63) with a 3d10 configuration and a large ligand twist configuration. Interestingly, the as-synthesized Ga-MOF exhibits excellent luminescence property and a good material for blue light-emitting diode (LED). At 80 K, this Ga-MOF shows multi-emission centers at 381, 462, and 494 nm. As a ratiometric thermometer, this Ga-MOF exhibits an excellent temperature sensing property with high relative sensitivity (Sm = 2.60 % K-1 at 110 K). The fluorescence intensity ratio I381/I494 shows a very good fit for the Boltzmann results (80-240 K). Moreover, the luminescent Ga-MOF exhibits an excellent selective detection of Fe3+ over other metal ions in aqueous an medium, and the limit of detection (LOD) towards Fe3+ ions is calculated to be 1.227 × 10-4 M. This work presents a versatile luminescent Ga-MOF material as a blue LED and fluorescent probe for low-temperature and selective Fe3+ sensing.