Knockdown of ARL4C inhibits osteogenic differentiation of human adipose-derived stem cells through disruption of the Wnt signaling pathway

Cross-Tissue Analysis Using Machine Learning to Identify Novel Biomarkers for Knee Osteoarthritis

Background

Knee osteoarthritis (KOA) is a common degenerative joint disease. In this study, we aimed to identify new biomarkers of KOA to improve the accuracy of diagnosis and treatment.

Methods

GSE98918 and GSE51588 were downloaded from the Gene Expression Omnibus database as training sets, with a total of 74 samples. Gene differences were analyzed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, and Disease Ontology enrichment analyses for the differentially expressed genes (DEGs), and GSEA enrichment analysis was carried out for the training gene set. Through least absolute shrinkage and selection operator regression analysis, the support vector machine recursive feature elimination algorithm, and gene expression screening, the range of DEGs was further reduced. Immune infiltration analysis was carried out, and the prediction results of the combined biomarker logistic regression model were verified with GSE55457.

Results

In total, 84 DEGs were identified through differential gene expression analysis. The five biomarkers that were screened further showed significant differences in cartilage, subchondral bone, and synovial tissue. The diagnostic accuracy of the model synthesized using five biomarkers through logistic regression was better than that of a single biomarker and significantly better than that of a single clinical trait.

Conclusions

CX3CR1, SLC7A5, ARL4C, TLR7, and MTHFD2 might be used as novel biomarkers to improve the accuracy of KOA disease diagnosis, monitor disease progression, and improve the efficacy of clinical treatment.

Impact of Different Proportions of 2D and 3D Scaffolds on the Proliferation and Differentiation of Human Adipose-Derived Stem Cells

PURPOSE

To observe the proliferation and differentiation of human adipose-derived stem cells (hADSCs) on 2D and 3D scaffolds, the sodium alginate and collagen interpenetrating network hydrogel were developed to determine optimal properties for bone tissue engineering.

METHODS

Three groups of scaffold materials were prepared according to the ratio of sodium alginate to collagen: A (4:1), B (2:1), and C (1:1), respectively. For each group, gel beads (3D surfaces) and freeze-dried films (2D surfaces) were respectively prepared. For gel beads, hADSCs were mixed during the preparation of the beads, and then stem cells were applied to the surface of each film after freeze-drying and sterilization during the preparation of the freeze-dried films. Cell proliferation and osteogenic differentiation potential were detected by cell counting kit, viable/dead cell staining kit, quantitative reverse transcription polymerase chain reaction, and immunofluorescent staining, respectively.

RESULTS

Results showed that cell proliferation rate progressively increased with the increase of collagen ratio, with group C of 3D surfaces of gel beads achieving the highest rate. In particular, highest cell viability on the 2D surfaces was achieved in group B. Differences in BGLAP and RUNX2 expression in hADSCs on 2D or 3D surfaces of the 3 groups were statistically significant. Particularly, BGLAP and RUNX2 gene expression levels were highest in group C of freeze-dried films and were highest in group B of gel beads. Furthermore, the trend of immunofluorescence expression of RUNX2 and osteocalcin expression were consistent with the genetic testing results.

CONCLUSIONS

All data indicated that sodium alginate-collagen scaffolding materials had no adverse impact on the proliferation and osteogenic differentiation of hADSCs. Cell differentiation and proliferation of bone tissue engineering can be promoted with the use of sodium alginate and collagen interpenetrating network hydrogel, and the appropriate ratio of sodium alginate and collagen is 2:1.

ARL4C is associated with initiation and progression of lung adenocarcinoma and represents a therapeutic target

Lung adenocarcinoma is the most common histological type of lung cancer and is classified into adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IA). Atypical adenomatous hyperplasia (AAH) lesions are possible precursors to adenocarcinoma. However, the mechanism underlying the stepwise continuum of lung adenocarcinoma is unclear. In this study, the involvement of ADP‐ribosylation factor (ARF)‐like (ARL) 4C (ARL4C), a member of the small GTP‐binding protein family, in the progression of lung adenocarcinoma and the possibility of ARL4C as a molecular target for lung cancer therapy were explored. ARL4C was frequently expressed in AAH and ARL4C expression in immortalized human small airway epithelial cells promoted cell proliferation and suppressed cell death. In addition, ARL4C was expressed with increased frequency in AIS, MIA and IA in a stage‐dependent manner, and the expression was correlated with histologic grade, fluorine‐18 fluorodeoxyglucose uptake and poor prognosis. An anti–sense oligonucleotide (ASO) against ARL4C (ARL4C ASO‐1316) inhibited RAS‐related C3 botulinum toxin substrate activity and nuclear import of Yes‐associated protein and transcriptional coactivator with PDZ‐binding motif, and suppressed in vitro proliferation and migration of lung cancer cells with KRAS or epidermal growth factor receptor (EGFR) mutations. In addition, transbronchial administration of ARL4C ASO‐1316 suppressed orthotopic tumor formation induced by these cancer cells. Thus, ARL4C is involved in the initiation of the premalignant stage and is associated with the stepwise continuum of lung adenocarcinoma. ARL4C ASO‐1316 would be useful for lung adenocarcinoma patients expressing ARL4C regardless of the KRAS or EGFR mutation.