Alpha-fetoprotein (AFP) is the primary marker for detecting hepatocellular carcinoma (HCC) and has been used widely in the clinic, but AFP is a biomarker characterized by poor sensitivity and specificity. Alpha-L-fucosidase (AFU) has been proposed as a tumor marker for diagnosis of HCC in many studies. However, conclusions of its diagnostic value are inconsistent. The current review aimed to evaluate the diagnostic value of AFU for HCC. After systematic review of 12 related studies, sensitivity, specificity, and diagnostic odds ratio (DOR) were pooled using random-effect models. Summary receiver operating characteristic (sROC) curve analysis was used to summarize the overall test performance. The pooled sensitivity for AFU was 0.72 (95% confidence interval (CI) 0.69-0.76), while the pooled specificity was 0.78 (95% CI 0.74-0.81). DOR was 10.26 (95% CI 5.99-17.59), and the area under the curve (AUC) was 0.8125. AFU had great value for the diagnosis of HCC as a serum marker.

The differentially expressed proteins of spinal cord tissues after ASCI will provide scientific foundation for further study to explore the secondary injury mechanism of ASCI.

Gastric cancer (GC) is one of the most common malignancies worldwide. Despite rapid advances in systemic therapy, GC remains the third leading cause of cancer-related deaths. We aimed to identify a novel prognostic signature associated with FAT2 mutations in GC. We analyzed the expression levels of FAT2-mutant and FAT2-wildtype GC samples obtained from The Cancer Genome Atlas (TCGA). The Kaplan-Meier survival curve showed that patients with FAT2 mutations showed better prognosis than those without the mutation. Sixteen long non-coding RNAs (lncRNAs) and 62 messenger RNAs (mRNAs) associated with FAT2 mutations were correlated with the prognosis of GC. We then constructed a 4-mRNA signature and a 5-lncRNA signature for GC. Finally, we identified the most relevant RP11-21 C4.1/SVEP1 gene pair as a prognostic signature of GC that exhibited superior predictive performance in comparison with the 4-mRNA or 5-lncRNA signature by weighted gene correlation network analysis (WGCNA) and Cox proportional hazards regression analysis. In this study, we constructed a prognostic signature of GC by integrative genomics analysis, which also provided insights into the molecular mechanisms linked to FAT2 mutations in GC.

Background: In recent years, a variety of long noncoding RNA (lncRNA) has been confirmed to be involved in the initiation and progression of osteosarcoma. Taurine-up regulated gene 1 (TUG1) plays an important role in the formation, invasion, and metastasis of osteosarcoma. Therefore, perhaps TUG1 is a potential biomarker for the prognosis of patients suffering from osteosarcoma. In this study, meta-analysis and bioinformatics were adopted to further explore the effects of TUG1 on the prognosis of patients with osteosarcoma and its potential molecular mechanism. Methods: Embase, PubMed, Sinomed, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Wanfang database, and Vip Journal Integration Platform were searched from inception to May 2021. The relationship between TUG1 expression and survival outcome was estimated by hazard ratio (HRs) and 95% confidence interval (CIs). Meta-analysis was conducted on the Stata 16.0. The differential expression of TUG1 in osteosarcoma was analyzed by using UALCAN database, and the survival of TUG1 was analyzed as well. The target genes of TUG1 were predicted by RegRNA2.0 biology software, HMDD, targetscan and microTCDS, and TUG1-micoRNAs-mRNAs regulatory network was constructed. The predicted target genes obtained GeneOntology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal transduction pathway enrichment analysis using FunRich platform. Results: The results of this meta-analysis would be submitted to peer-reviewed journals for publication. Conclusion: This study will provide evidence-based medical evidence for the relationship between TUG1 and the prognosis of osteosarcoma. Furthermore, bioinformatics analysis will provide ideas for the exploration on osteosarcoma mechanism. Ethics and dissemination: The private information from individuals will not be published. This systematic review also should not damage participants’ rights. Ethical approval is not available. The results will be published in a peer-reviewed journal or disseminated in relevant conferences. OSF registration number: DOI 10.17605/OSF.IO/CW4BF.

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