Synovial macrophage polarization is essential for osteoarthritis (OA) development. Our study aims to investigate the underlying function and the molecular mechanisms of hsa_circ_0005567 in macrophage polarization. Circular RNA (CircRNA), microRNA (miRNA), and mRNA expression levels were detected by quantitative reverse transcription polymerase chain reaction (RT-qPCR). RNA pull down, luciferase reporter were employed to test the interaction between miR-492 and hsa_circ_0005567/suppressors of cytokine signaling 2 (SOCS2). Ectopic overexpression was used to evaluate the function of hsa_circ_0005567. The supernatant of THP-1 cells was used to incubate chondrocytes. Cell Counting Kit-8 (CCK-8) and flow cytometry were conducted to determine cell viability, proportion of M1 or M2 macrophages and apoptotic rate. The results showed that the hsa_circ_0005567 expression level was downregulated in the synovial tissues of osteoarthritis patients. Overexpression of hsa_circ_0005567 inhibited M1 macrophage polarization, and promoted M2 macrophage polarization. Hsa_circ_0005567 was proved to be a molecular sponge for miR-492, and SOCS2 was verified as the target of miR-492. MiR-492 mimic could reverse the effect of hsa_circ_0005567 overexpression on macrophage polarization. Besides, the supernatant from LPS-treated THP-1 macrophage significantly decreased chondrocytes cell viability and increased cell apoptosis ratio, which was reversed by hsa_circ_0005567 overexpression. In conclusion, hsa_circ_0005567 overexpression promoted M2 macrophage polarization through miR-492/SOCS2 axis to reduced chondrocyte apoptosis, which could inhibit osteoarthritis progression.

Excessive chondrocyte apoptosis is mostly responsible for the progression of osteoarthritis (OA). It has been shown that circular RNAs (circRNAs) are differentially expressed in OA cartilage and participate in various pathological processes during OA. Here, this study was designed to explore the effect and molecular mechanism of hsa_circ_0005567 on IL-1β-induced chondrocyte apoptosis. The results showed that hsa_circ_0005567 knockdown aggravated the IL-1β-induced chondrocyte apoptosis. In contrast, hsa_circ_0005567 overexpression attenuated the IL-1β-induced chondrocyte apoptosis, but this effect could be abrogated by 3-methyladenine (an inhibitor of autophagy), suggesting that hsa_circ_0005567 overexpression inhibited chondrocyte apoptosis by inducing autophagy. Furthermore, hsa_circ_0005567 competitively bound to miR-495 and derepressed the expression of ATG14, an early autophagy marker that was a direct target of miR-495. Moreover, both miR-495 mimic and ATG14 knockdown counteracted the autophagy-promoting and anti-apoptotic effects of hsa_circ_0005567 overexpression in IL-1β-treated chondrocytes. Taken together, hsa_circ_0005567 activates autophagy by regulating the miR-495/ATG14 axis and thereby suppresses IL-1β-induced chondrocyte apoptosis. These findings suggest that hsa_circ_0005567 may serve as a therapeutic target for the treatment of OA.

Osteosarcomas (OSs) represent a huge challenge to improve the overall survival, especially in metastatic patients. Increasing evidence indicates that both tumor-associated elements but also on host-associated elements are under a remarkable effect on the prognosis of cancer patients, especially systemic inflammatory response. By analyzing a series prognosis of factors, including age, gender, primary tumor size, tumor location, tumor grade, and histological classification, monocyte ratio, and NLR ratio, a clinical predictive model was established by using stepwise logistic regression involved circulating leukocyte to compute the estimated probabilities of metastases for OS patients. The clinical predictive model was described by the following equations: probability of developing metastases = ex/(1 + ex), x = −2.150 +  (1.680 × monocyte ratio) + (1.533 × NLR ratio), where is the base of the natural logarithm, the assignment to each of the 2 variables is 1 if the ratio >1 (otherwise 0). The calculated AUC of the receiver-operating characteristic curve as 0.793 revealed well accuracy of this model (95% CI, 0.740–0.845). The predicted probabilities that we generated with the cross-validation procedure had a similar AUC (0.743; 95% CI, 0.684–0.803). The present model could be used to improve the outcomes of the metastases by developing a predictive model considering circulating leukocyte influence to estimate the pretest probability of developing metastases in patients with OS.

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