No abstract

Aims Ageing-related incompetence becomes a major hurdle for the clinical translation of adult stem cells in the treatment of osteoarthritis (OA). This study aims to investigate the effect of stepwise preconditioning on cellular behaviours in human mesenchymal stem cells (hMSCs) from ageing patients, and to verify their therapeutic effect in an OA animal model. Methods Mesenchymal stem cells (MSCs) were isolated from ageing patients and preconditioned with chondrogenic differentiation medium, followed by normal growth medium. Cellular assays including Bromodeoxyuridine / 5-bromo-2'-deoxyuridine (BrdU), quantitative polymerase chain reaction (q-PCR), β-Gal, Rosette forming, and histological staining were compared in the manipulated human mesenchymal stem cells (hM-MSCs) and their controls. The anterior cruciate ligament transection (ACLT) rabbit models were locally injected with two millions, four millions, or eight millions of hM-MSCs or phosphate-buffered saline (PBS). Osteoarthritis Research Society International (OARSI) scoring was performed to measure the pathological changes in the affected joints after staining. Micro-CT analysis was conducted to determine the microstructural changes in subchondral bone. Results Stepwise preconditioning approach significantly enhanced the proliferation and chondrogenic potential of ageing hMSCs at early passage. Interestingly, remarkably lower immunogenicity and senescence was also found in hM-MSCs. Data from animal studies showed cartilage damage was retarded and subchondral bone remodelling was prevented by the treatment of preconditioned MSCs. The therapeutic effect depended on the number of cells applied to animals, with the best effect observed when treated with eight millions of hM-MSCs. Conclusion This study demonstrated a reliable and feasible stepwise preconditioning strategy to improve the safety and efficacy of ageing MSCs for the prevention of OA development. Cite this article: Bone Joint Res 2021;10(1):10–21.

Hepatocellular carcinoma (HCC), a highly aggressive tumor, has high incidence and mortality rates. Recently, immunotherapies have been shown to be a promising treatment in HCC. The results of either the CheckMate-040 or IMbrave 150 trials demonstrate the importance of immunotherapy in the systemic treatment of liver cancer. Thus, in this study, we tried to establish a reliable prognostic model for liver cancer based on immune-related genes (IRGs) and to provide a new insight for immunotherapy of HCC. In this study, we used four datasets that incorporated 851 HCC samples, including 340 samples with complete clinical information from the cancer genome atlas (TCGA) database, to establish an effective model for predicting the prognosis of HCC patients based on the differential expression of IRGs and validated the prognostic model using the data from International Cancer Genome Consortium (ICGC). The top 6 characteristic IRGs identified by protein-protein interaction (PPI) network analysis, MMP9, FOS, CAT, ESR1, ANGPTL3, and KLKB1, were selected for further study. In addition, we assessed the correlations of the six characteristic IRGs with the tumor immune microenvironment, clinical stage, and sensitivity to anti-cancer drugs. We also explored whether the differential expression of the characteristic IRGs was specific to HCC or present in pan-cancer. The expression levels of the six characteristic IRGs were significantly different between most tumor tissues and adjacent normal tissues. In addition, these characteristic IRGs showed a strong association with immune cell infiltration in HCC patients. We found that MMP9 and ESR1 were independent prognostic factors for HCC, while CAT, ESR1, and KLKB1 were associated with the clinical stage. We collected HCC paraffin sections from 24 patients from Xijing hospital to identify the differential expression of the five genes (MMP9, ESR1, CAT, FOS, and KLKB1). Finally, the results of decision curve analysis (DCA) and nomogram revealed that our models provided a prognostic benefit for most HCC patients and the predicted overall survival (OS) was consistent with the actual OS. In conclusion, we systemically constructed a novel prognostic model that provides new insights into HCC.

No abstract

Hepatocellular carcinoma (HCC) is one of the deadliest tumors in the world and is notorious for poor prognosis. There is mounting evidence that pseudouridine performs key functions in the initiation and progression of several cancers. A previous study demonstrated that Pseudouridine 5’-phosphatase (PUDP) may be a novel prognostic biomarker in colorectal cancer. However, in the past, we have paid little attention to PUDP and we are still not clear about its function and role in cancer. In this study, a pan-cancer analysis of PUDP expression and prognosis was performed firstly using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) data and we found that PUDP may be a potential oncogene for HCC. Then the most potential upstream microRNA contributing to PUDP was identified as let-7c-5p through expression analysis, correlation analysis, and survival analysis. Subsequently, the result of single cell RNA sequencing (scRNA-seq) demonstrated that PUDP was significantly highly expressed on malignant cells. In addition, there are significantly positive correlations between PUDP and tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression, especially with tumor-promoting immune cells such as T cell regulatory (Treg), Myeloid-derived suppressor cell (MDSC), cancer-associated fibroblast (CAF). Moreover, we found the methylation level of three loci was positively correlated with PUDP expression and four loci were negatively correlated. 15 pairs of HCC and normal adjacent tissues from HCC patients who were treated at our center were used to verify the results of the bioinformatics analysis and the results of experiments are similar to the bioinformatics analysis. Our study demonstrated that HCC patients with high PUDP expression are less likely to benefit from immunotherapy, and in addition, we explored the relationship between PUDP and anticancer drugs. Finally, we explored the clinical relevance of PUDP, identified PUDP as an independent risk factor for HCC patients and constructed a prognostic model, used International Cancer Genome Consortium (ICGC) data to do external validation. Collectively, our study demonstrated that high expression of PUDP suggested a poor prognosis and low response to immunotherapy, providing new insight into the treatment and prognosis of HCC.

Background: Neuromyelitis optica spectrum disorder (NMOSD), an autoimmune inflammatory disorder of the central nervous system, often leads to vision loss or paralysis. This meta-analysis focused on the assessment of the monoclonal antibody therapy in NMOSD and compared different targets of monoclonal antibodies with each other in terms of efficacy and safety outcomes.Method: We searched through the databases of MEDLINE, EMBASE, Central Register of Controlled Trials (CENTRAL), and clinicaltrials.gov for randomized controlled trials (RCTs) evaluating monoclonal antibody therapy in NMOSD up to April 2020.Results: We identified seven randomized controlled trials (RCTs), including 775 patients (monoclonal antibody group, n = 485 and placebo group, n = 290). Monoclonal antibody therapy decreased relapse risk (RR 0.33, 95% CI 0.21–0.52, P < 0.00001), annualized relapse rate (ARR) (mean −0.28, 95% CI −0.35−0.20, P < 0.00001), expanded disability status scale score (EDSS) (mean −0.19, 95% CI −0.32−0.07, P = 0.002) and serious adverse events (RR 0.78, 95% CI 0.61–1.00, P = 0.05). However, we did not observe any significant difference in terms of adverse events or mortality. Further, the subgroup analysis demonstrated that the anti-complement protein C5 monoclonal antibody (eculizumab) might have a lower relapse risk (RR 0.07, 95% CI 0.02–0.23, P < 0.0001) in the AQP4 seropositive patients, and anti-interleukin-6 receptor monoclonal antibodies (satralizumab and tocilizumab) showed decreased EDSS score (mean −0.17, 95% CI −0.31−0.02, P = 0.02) more effectively than other monoclonal antibodies.Conclusions: Monoclonal antibodies were effective and safe in NMOSD. Different targets of monoclonal antibodies might have their own advantages.

Background Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Costimulatory molecules have been proven to be the foundation of immunotherapy. However, the potential roles of costimulatory molecule genes (CMGs) in HCC remain unclear. Our study is aimed to develop a costimulatory molecule-related gene signature that could evaluate the prognosis of HCC patients. Methods Based on The Cancer Gene Atlas (TCGA) database, univariate Cox regression analysis was applied in CMGs to identify prognosis-related CMGs. Consensus clustering analysis was performed to stratify HCC patients into different subtypes and compared them in OS. Subsequently, the LASSO Cox regression analysis was performed to construct the CMGs-related prognostic signature and Kaplan–Meier survival curves as well as ROC curve were used to validate the predictive capability. Then we explored the correlations of the risk signature with tumor-infiltrating immune cells, tumor mutation burden (TMB) and response to immunotherapy. The expression levels of prognosis-related CMGs were validated based on qRT-PCR and Human Protein Atlas (HPA) databases. Results All HCC patients were classified into two clusters based on 11 CMGs with prognosis values and cluster 2 correlated with a poorer prognosis. Next, a prognostic signature of six CMGs was constructed, which was an independent risk factor for HCC patients. Patients with low-risk score were associated with better prognosis. The correlation analysis showed that the risk signature could predict the infiltration of immune cells and immune status of the immune microenvironment in HCC. The qRT-PCR and immunohistochemical results indicated six CMGs with differential expression in HCC tissues and normal tissues. Conclusion In conclusion, our CMGs-related risk signature could be used as a prediction tool in survival assessment and immunotherapy for HCC patients.

BackgroundEvidence from prevailing studies show that hepatocellular carcinoma (HCC) is among the top cancers with high mortality globally. Gene regulation at post-transcriptional level orchestrated by RNA-binding proteins (RBPs) is an important mechanism that modifies various biological behaviors of HCC. Currently, it is not fully understood how RBPs affects the prognosis of HCC. In this study, we aimed to construct and validate an RBP-related model to predict the prognosis of HCC patients.MethodsDifferently expressed RBPs were identified in HCC patients based on the GSE54236 dataset from the Gene Expression Omnibus (GEO) database. Integrative bioinformatics analyses were performed to select hub genes. Gene expression patterns were validated in The Cancer Genome Atlas (TCGA) database, after which univariate and multivariate Cox regression analyses, as well as Kaplan-Meier analysis were performed to develop a prognostic model. Then, the performance of the prognostic model was assessed using receiver operating characteristic (ROC) curves and clinicopathological correlation analysis. Moreover, data from the International Cancer Genome Consortium (ICGC) database were used for external validation. Finally, a nomogram combining clinicopathological parameters and prognostic model was established for the individual prediction of survival probability.ResultsThe prognostic risk model was finally constructed based on two RBPs (BOP1 and EZH2), facilitating risk-stratification of HCC patients. Survival was markedly higher in the low-risk group relative to the high-risk group. Moreover, higher risk score was associated with advanced pathological grade and late clinical stage. Besides, the risk score was found to be an independent prognosis factor based on multivariate analysis. Nomogram including the risk score and clinical stage proved to perform better in predicting patient prognosis.ConclusionsThe RBP-related prognostic model established in this study may function as a prognostic indicator for HCC, which could provide evidence for clinical decision making.