Backgrounds:A large number of studies have reported the relationships between serum lactate dehydrogenase (LDH) and prognosis of osteosarcoma. However, the result is still controversial and no consensus has been reached. Therefore, we performed a meta-analysis to evaluate the prognostic role of serum LDH in osteosarcoma patients.Methods:We performed the systematic computerized search for eligible articles from PubMed, Embase, and Cochrane databases until December 21, 2017. The pooled hazard ratio (HR) and 95% confidence intervals (CIs) of overall survival (OS) and event-free survival (EFS) were obtained to assess the prognostic value of serum LDH.Results:A total of 18 studies with 2543 osteosarcoma patients were included. Overall, 15 studies assessed the elevated serum LDH level on OS and the pooled HR was 1.87 (95% CI = 1.58–2.20). Meanwhile, the pooled HR to evaluate the relationship between serum LDH and EFS in 9 studies was 1.78 (95% CI = 1.51–2.10). The same results were acquired when these studies were stratified by Enneking stage, geographic region, and sample size. No heterogeneity existed between these subgroups (P > .05). Begg's funnel plot and Egger's test (OS: P = .04; EFS: P = .34) showed that possible publication bias might exist in OS studies. Sensitivity analysis suggested the pooled HR was robust.Conclusions:This meta-analysis demonstrates that elevated serum LDH level is apparently associated with lower EFS rate and serum LDH could be a prognostic biomarker for osteosarcoma patients.

Premature ovarian failure (POF) is one of the common disorders found in women leading to 1% female infertility. Clinical features of POF are hypoestrogenism or estrogen deficiency, increased gonadotropin level, and, most importantly, amenorrhea. With the development of regenerative medicine, human mesenchymal stem cell (hMSC) therapy brings new prospects for POF. This study aimed to describe the types of MSCs currently available for POF therapy, their biological characteristics, and their mechanism of action. It reviewed the latest findings on POF to provide the theoretical basis for further investigation and clinical therapy.

BackgroundIncreasing evidence has shown that hypoxia microenvironment relates to tumor initiation and progression. However, no studies focus on the application of hypoxia-associated genes in predicting osteosarcoma patients’ prognosis. This research aims to identify the hypoxia-associated genes related to osteosarcoma metastasis and construct a gene signature to predict osteosarcoma prognosis.MethodsThe differentially expressed messenger RNAs (DEmRNAs) related to osteosarcoma metastasis were identified from Therapeutically Applicable Research to Generate Effective Treatments (Target) database. Univariate and multivariate cox regression analyses were performed to develop the hypoxia-associated prognostic signature. The Kaplan–Meier (KM) survival analyses of patients with high and low hypoxia risk scores were conducted. The nomogram was constructed and the gene signature was validated in the external Gene Expression Omnibus (GEO) cohort. Single-sample gene set enrichment analysis (ssGSEA) was conducted to investigate the relationships between immune infiltration and gene signature.ResultsTwo genes, including decorin (DCN) and prolyl 4-hydroxylase subunit alpha 1 (P4HA1), were involved in the hypoxia-associated gene signature. In training and testing datasets, patients with high-risk scores showed lower survival rates and the gene signature was identified as the independent prognostic factor. Receiver operating characteristic (ROC) curves demonstrated the robustness of signature. Functional analyses of DEmRNAs among high- and low-risk groups revealed that immune-associated functions and pathways were significantly enriched. Furthermore, ssGSEA showed that five immune cells (DCs, macrophages, neutrophils, pDCs, and TIL) and three immune features (CCR, APC co inhibition, and Check-point) were down-regulated in the high-risk group.ConclusionThe current study established and validated a novel hypoxia-associated gene signature in osteosarcoma. It could act as a prognostic biomarker and serve as therapeutic guidance in clinical applications.

Immunotherapy has become the standard of care for non-small cell lung cancer (NSCLC), either in combination or monotherapy. However, there are still some patients who cannot benefit from it. Immunization strategies for NSCLC are based on the expression of PD-L1 on tumor cells and TMB, and although these indicators have a certain predictive effect, their predictive performance is not good. Therefore, clinicians must make adjustments to recognize markers. This is a review article that summarized immunotherapeutic biomarkers according to the “seed-soil-environment”, generalizes primary resistance to immunotherapy, and summarizes the integration of markers.

In this study, we identified the multifaceted effects of atezolizumab, a specific monoclonal antibody against PD-L1, in tumor suppression except for restoring antitumor immunity, and investigated the promising ways to improve its efficacy. Atezolizumab could inhibit the proliferation and induce immune-independent apoptosis of osteosarcoma cells. With further exploration, we found that atezolizumab could impair mitochondria of osteosarcoma cells, resulting in increased release of reactive oxygen species and cytochrome-c, eventually leading to mitochondrial-related apoptosis via activating JNK pathway. Nevertheless, the excessive release of reactive oxygen species also activated the protective autophagy of osteosarcoma cells. Therefore, when we combined atezolizumab with autophagy inhibitors, the cytotoxic effect of atezolizumab on osteosarcoma cells was significantly enhanced in vitro. Further in vivo experiments also confirmed that atezolizumab combined with chloroquine achieved the most significant antitumor effect. Taken together, our study indicates that atezolizumab can induce mitochondrial-related apoptosis and protective autophagy independently of the immune system, and targeting autophagy is a promising combinatorial approach to amplify its cytotoxicity.

Leptin, an adipocyte-derived hormone, promotes liver fibrogenesis and inhibits the expression of peroxisome-proliferator activated receptor γ (PPARγ), a key transcription factor in inhibition of hepatic stellate cell (HSC) activation, in HSCs. This research aimed to further investigate the mechanisms underlying leptin regulation of PPARγ1 in HSCs in vivo and in vitro. Results demonstrated that sex-determining region Y-box 9 (Sox9) could bind to a site around -2275 within leptin response region of PPARγ1 promoter and inhibited PPARγ1 expression. Sox9 upregulated the expressions of α1(I)collagen and alpha-smooth muscle actin in HSCs. Leptin stimulated Sox9 expression and Sox9 binding to PPARγ1 promoter. The signaling pathways of NADPH oxidase, β-catenin, and delta-like homolog1 (DLK1) mediated leptin upregulation of Sox9 expression. Moreover, there existed crosstalk between NADPH oxidase pathway and β-catenin or DLK1 signaling pathway. Human liver specimens of cirrhosis were shown to be of a large number of the positive HSCs for p47phox (playing a central role in NADPH oxidase activity), 4-hydroxynonenal (a lipid peroxidation product), Sox9, and α-smooth muscle actin whereas PPARγ-positive HSCs were rarely detected. These results might deepen understanding of the molecular mechanisms for leptin inhibition of PPARγ1 expression in HSCs and for the liver fibrosis associated with leptin.

The sperm quality of some males is in a critical state, making it hard for clinicians to choose the suitable fertilisation methods. This study aimed to develop an intelligent nomogram for predicting fertilisation rate of infertile males with borderline semen. 160 males underwent in vitro fertilisation (IVF), 58 of whom received rescue ICSI (R‐ICSI) due to fertilisation failure (fertilisation rate of IVF ≤30%). A least absolute shrinkage and selection operator (LASSO) regression analysis identified sperm concentration, progressively motile spermatozoa (PMS), seminal plasma anti‐Müllerian hormone (spAMH), seminal plasma inhibin (spINHB), serum AMH (serAMH) and serum INHB (serINHB) as significant predictors. The nomogram was plotted by multivariable logistic regression. This nomogram‐illustrated model showed good discrimination, calibration and clinical value. The area under the receiver operating characteristic curve (AUC) of the nomogram was 0.762 (p < .001). Calibration curve and Hosmer–Lemeshow test (p = .5261) showed good consistency between the predictions of the nomogram and the actual observations, and decision curve analysis showed that the nomogram was clinically useful. This nomogram may be useful in predicting fertilisation rate, mainly focused on new biomarkers, INHB and AMH. It could assist clinicians and laboratory technicians select appropriate fertilisation methods (IVF or ICSI) for male patients with borderline semen.

Background: Intervertebral disc degeneration (IDD) is widely known as the main contributor to low back pain which has a negative socioeconomic impact worldwide. However, the underlying mechanism remains unclear. This study aims to analyze the dataset GSE23130 using bioinformatics methods to identify the pivotal genes and pathways associated with IDD. Material/methods: The gene expression data of GSE23130 was downloaded, and differentially expressed genes (DEGs) were extracted from 8 samples and 15 controls. GO and KEGG pathway enrichment analyses were performed. Also, protein-protein interaction (PPI) network was constructed and visualized, followed by identification of hub genes and key module. Results: A total of 30 downregulated and 79 upregulated genes were identified. The DEGs were mainly enriched in the regulation of protein catabolic process, extracellular matrix organization, collagen fibril organization, and extracellular structure organization. Meanwhile, we found that most DEGs were primarily enriched in the PI3K-Akt signaling pathway. The top 10 hub genes were FN1, COL1A2, SPARC, COL3A1, CTGF, LUM, TIMP1, THBS2, COL5A2, and TGFB1. Conclusions: In summary, key candidate genes and pathways were identified by using integrated bioinformatics analysis, which may provide insights into the underlying mechanisms and offer potential target genes for the treatment of IDD.