Human umbilical cord mesenchymal stem cells promote steroid-induced osteonecrosis of the femoral head repair by improving microvascular endothelial cell function.

Recently, there has been growing interest in using cell therapy through core decompression (CD) to treat osteonecrosis of the femoral head (ONFH). Our study aimed to investigate the effectiveness and mechanism of human umbilical cord mesenchymal stem cells (hUCMSCs) in treating steroid-induced ONFH. We constructed a steroid-induced ONFH rabbit model as well as dexamethasone (Dex)-treated bone microvascular endothelial cells (BMECs) model of human femoral head. We injected hUCMSCs into the rabbit femoral head via CD. The effects of hUCMSCs on steroid-induced ONFH rabbit model and Dex-treated BMECs were evaluated via micro-CT, microangiography, histology, immunohistochemistry, wound healing, tube formation, and western blotting assay. Furthermore, we conducted single-cell RNA sequencing (scRNA-seq) to examine the characteristics of endothelial cells, the activation of signaling pathways, and inter-cellular communication in ONFH. Our data reveal that hUCMSCs improved the femoral head microstructure and bone repair and promoted angiogenesis in the steroid-induced ONFH rabbit model. Importantly, hUCMSCs improved the migration ability and angioplasty of Dex-treated BMECs by secreting COL6A2 to activate FAK/PI3K/AKT signaling pathway via integrin α1ß1.

Circadian rhythm-associated lncRNA RP11-414H17.5 as a key therapeutic target in osteosarcoma affects the tumor immune microenvironment and enhances malignancy.

BACKGROUND: It has previously been proven that circadian rhythm disruption is associated with the incidence and deterioration of several tumors, which potentially leads to increased tumor susceptibility and a worse prognosis for tumor-bearing patients. However, their potential role in osteosarcoma has yet to be sufficiently investigated. METHODS: Transcriptomic and clinical data of 84 osteosarcoma samples and 70 normal bone tissue samples were obtained from the TARGET and GTEx databases, circadian rhythm-related genes were obtained from Genecards, and circadian rhythm-related lncRNAs (CRLs) were obtained by Pearson correlation analysis, differential expression analysis, and protein-protein interaction (PPI) analysis. COX regression and LASSO regression were performed on the CRLs in order to construct a circadian rhythm-related prognostic prediction signature (CRPS). CRPS reliability was verified by Kaplan-Meier (KM), principal component analysis (PCA), nomogram, and receiver operating characteristic (ROC) curve. CRPS effects on the immune microenvironment of osteosarcoma were explored by enrichment analysis and immune infiltration analysis, and the effect of critical gene RP11-414H17.5 on osteosarcoma was experimentally verified. RESULT: CRPS consisting of three CRLs was constructed and its area under the curve (AUC) values predicted that osteosarcoma prognosis reached 0.892 in the training group and 0.843 in the test group, with a p value of < 0.05 for the KM curve and stable performance across different clinical subgroups. PCA analysis found that CRPS could significantly distinguish between different risk subgroups, and exhibited excellent performance in the prediction of the immune microenvironment. The experiment verified that RP11-414H17.5 can promote metastasis and inhibit apoptosis of osteosarcoma cells. CONCLUSION: The study revealed that circadian rhythm plays a crucial role in osteosarcoma progression and identified the impact of the key gene RP11-414H17.5 on osteosarcoma, which provides novel insights into osteosarcoma diagnosis and therapy.

Dissecting the role of lactate metabolism LncRNAs in the progression and immune microenvironment of osteosarcoma.

BACKGROUND: The process of lactate metabolism has been proved to play a critical role in the progression of various cancers and to influence the immune microenvironment, but its potential role in osteosarcoma remains unclear. METHODS: We have acquired transcriptomic and clinical data from 84 osteosarcoma samples and 70 normal bone samples from the TARGET and GTEx databases. We identified differentially expressed lactate metabolism-related LncRNAs (LRLs) in osteosarcoma and performed Cox regression and LASSO regression to establish LRLs prognostic signature (LRPS). The reliability of LRPS performance was examined by separate prognostic analysis, viability curves and receiver operating characteristic (ROC) curves. Furthermore, the effects of LRPS on the immune microenvironment of osteosarcoma were investigated, and the functions of the focal genes were experimentally validated. RESULT: A total of 856 differentially expressed LRLs were identified and 5 of them were selected to construct LRPS, which was a better prognostic predictor for osteosarcoma compared with other published prognostic signatures (AUC up to 0.947 and 0.839 in the training and test groups, respectively, with adj-p<0.05 for KM curves). We found that LRPS significantly affected the immune infiltration of osteosarcoma, while RP11-472M19.2 significantly promoted the metastasis of osteosarcoma, which was well validated experimentally. Encouragingly, a number of sensitive drugs were identified for LRPS and RP11-472M19.2 high-risk groups. CONCLUSION: Our study shows that lactate metabolism plays a crucial role in the development of osteosarcoma and has been well validated experimentally, providing extremely important insights into the clinical treatment and in-depth research of osteosarcoma.

Identification and validation of long noncoding RNA AC083900.1 and RP11-283C24.1 for prediction of progression of osteosarcoma.

BACKGROUND: The role of cuproptosis, an emerging cell death pathway that makes a remarkable contribution to tumor progression, remains elusive in osteosarcoma (OS), in addition to its regulator, including long-no-coding RNAs (lncRNAs) that are also a critical factor for fueling OS. METHODS: Transcriptome and clinical data from 70 normal human bone tissue samples and 84 frozen clinical osteosarcoma samples were included in this study. Cuproptosis-associated lncRNAs (CRlncs) were identified through differential expression and co-expression analyses. Univariate Cox regression was performed to screen for prognostic lncRNAs, then we used least absolute shrinkage and selection operator regression to distinguish prognosis-related CRlncs (AC083900.1 and RP11-283C24.1) for modeling the CRlncs prognostic signature (CLPS) by multivariate Cox regression using the stepwise method. CLPS performance was tested by independent prognostic analyses, survival curve and receiver operating characteristic (ROC) curve. In addition, the molecular and immune mechanisms that underlie the unfavorable prognosis of CLPS-identified high-risk group were elucidated. RESULT: AC083900.1 and RP11-283C24.1 have been identified as the most important CRlncs for OS progression (hazard ratio: 3.498 and 2.724, respectively), and the derived CLPS demonstrated outstanding performance for the prediction of OS prognosis (AUC of 0.799 and 0.778 in the training and test sets, both adj-p < 0.05 in survival curve). As was anticipated, CLPS also outperformed a recent clinical prognostic approach that only achieved an AUC of 0.682 [metastasis]. It is notable that AC083900.1 progressed OS metastasis, evidenced by its high expression in metastatic OS, its high correlation to metastasis-related genes, and its high AUC of 0.683 for the prediction of metastasis. Mechanistically, AC083900.1 and RP11-283C24.1 dysregulated many critical biological processes regarding humoral immune response, immunoglobulin complex, etc.; while reducing the infiltration of many cytotoxic immune cells (B-cells, TIL, neutrophils, etc.). It is encouraging that BMS-509744 and KIN001-135 demonstrated high therapeutic implications for CLPS-identified high-risk OS, and the low-risk counterpart was sensitive to SB-216763. Quantitative RT-PCR analysis showed that both AC083900.1 and RP11-283C24.1 were significantly upregulated in different osteosarcoma cell lines. CONCLUSION: This study elucidated the roles and mechanisms of AC083900.1 and RP11-283C24.1 in the development of OS, fostering a reliable prognostic approach and treatment for OS patients.

Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma.

BACKGROUND: The defense response is a type of self-protective response of the body that protects it from damage by pathogenic factors. Although these reactions make important contributions to the occurrence and development of tumors, the role they play in osteosarcoma (OS), particularly in the immune microenvironment, remains unpredictable. METHODS: This study included the clinical information and transcriptomic data of 84 osteosarcoma samples and the microarray data of 12 mesenchymal stem cell samples and 84 osteosarcoma samples. We obtained 129 differentially expressed genes related to the defense response (DRGs) by taking the intersection of differentially expressed genes with genes involved in the defense response pathway, and prognostic genes were screened using univariate Cox regression. Least absolute shrinkage and selection operator (LASSO) penalized Cox regression and multivariate Cox regression were then used to establish a DRG prognostic signature (DGPS) via the stepwise method. DGPS performance was examined using independent prognostic analysis, survival curves, and receiver operating characteristic (ROC) curves. In addition, the molecular and immune mechanisms of adverse prognosis in high-risk populations identified by DGPS were elucidated. The results were well verified by experiments. RESULT: BNIP3, PTGIS, and ZYX were identified as the most important DRGs for OS progression (hazard ratios of 2.044, 1.485, and 0.189, respectively). DGPS demonstrated outstanding performance in the prediction of OS prognosis (area under the curve (AUC) values of 0.842 and 0.787 in the training and test sets, respectively, adj-p < 0.05 in the survival curve). DGPS also performed better than a recent clinical prognostic approach with an AUC value of only 0.674 [metastasis], which was certified in the subsequent experimental results. These three genes regulate several key biological processes, including immune receptor activity and T cell activation, and they also reduce the infiltration of some immune cells, such as B cells, CD8+ T cells, and macrophages. Encouragingly, we found that DGPS was associated with sensitivity to chemotherapeutic drugs including JNK Inhibitor VIII, TGX221, MP470, and SB52334. Finally, we verified the effect of BNIP3 on apoptosis, proliferation, and migration of osteosarcoma cells through experiments. CONCLUSIONS: This study elucidated the role and mechanism of BNIP3, PTGIS, and ZYX in OS progression and was well verified by the experimental results, enabling reliable prognostic means and treatment strategies to be proposed for OS patients.

Miniature Broadband NIR Spectrometer Based on FR4 Electromagnetic Scanning Micro-Grating.

This paper presents a miniaturized, broadband near-infrared (NIR) spectrometer with a flame-retardant 4 (FR4)-based scanning micrograte. A 90° off-axis parabolic mirror and a crossed Czerny-Turner structure were used for creating an astigmatism-free optical system design. The optical system of the spectrometer consists of a 90° off-axis parabolic mirror, an FR4-based scanning micrograte, and a two-color indium gallium arsenide (InGaAs) diode with a crossed Czerny-Turner structure optical design. We used a wide exit slit and an off-axis parabolic mirror with a short focal length to improve the signal-to-noise ratio (SNR) of the full spectrum. We enabled a miniaturized design for the spectrometer by utilizing a novel FR4 micrograte for spectral dispersion and spatial scanning. The spectrometer can detect the full near-infrared spectrum while only using a two-color InGaAs diode, and thus, the grating scanning angle of this spectrometer is small when compared to a dual-detector-based spectrometer. In addition, the angle signal can be obtained through an angle sensor, which is integrated into the scanning micrograte. The real-time angle signal is used to form a closed-loop control over the scanning micrograte and calibrate the spectral signal. Finally, a series of tests was performed. The experimental results showed that the spectrometer has a working wavelength range of 800-2500 nm. The resolution is 10 nm at a wavelength range of 800-1650 nm and 15 nm at a wavelength range of 1650-2500 nm. Similarly, the stability of these two wavelength ranges is better than ±1 nm and ±2 nm, respectively. The spectrometer's volume is 80 × 75 × 65 mm3 and its weight is 0.5 kg. The maximum spectral fluctuation does not exceed 1.5% and the signal-to-noise ratio is 284 after only one instance of averaging.

FR4-based electromagnetic scanning micro-grating integrated with an angle sensor for a low-cost NIR micro-spectrometer.

Aiming to implement a low-cost single-photodetector-based NIR micro-spectrometer, we present a novel flame retardant 4 (FR4)-driven micro-grating for spectral dispersion and spatial scanning. It consists of a silicon blazed grating directly bonded onto the FR4 actuator platform and an integrated differential electromagnetic angle sensor. Owing to the better shock and vibration reliability, larger aperture, shorter fabrication cycle, and much lower cost, it may be a potential alternative to conventional silicon microelectromechanical systems scanning micro-gratings. The micro-spectrometer prototype based on this device shows a spectral range of 800-1800 nm, a spectral accuracy of ±1.3 nm, and a 10 nm spectral resolution.