Thyroid cancer is a common endocrine malignancy with a rapidly increasing incidence worldwide. Although its mortality is steady or declining because of earlier diagnoses, its survival rate varies because of different tumour types. Thus, the aim of this study was to identify key biomarkers and novel therapeutic targets in thyroid cancer. The expression profiles of GSE3467, GSE5364, GSE29265 and GSE53157 were downloaded from the Gene Expression Omnibus database, which included a total of 97 thyroid cancer and 48 normal samples. After screening significant differentially expressed genes (DEGs) in each data set, we used the robust rank aggregation method to identify 358 robust DEGs, including 135 upregulated and 224 downregulated genes, in four datasets. Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analyses of DEGs were performed by DAVID and the KOBAS online database, respectively. The results showed that these DEGs were significantly enriched in various cancer-related functions and pathways. Then, the STRING database was used to construct the protein-protein interaction network, and modules analysis was performed. Finally, we filtered out five hub genes, including LPAR5, NMU, FN1, NPY1R, and CXCL12, from the whole network. Expression validation and survival analysis of these hub genes based on the The Cancer Genome Atlas database suggested the robustness of the above results. In conclusion, these results provided novel and reliable biomarkers for thyroid cancer, which will be useful for further clinical applications in thyroid cancer diagnosis, prognosis and targeted therapy. K E Y W O R D Sbioinformatics, differentially expressed genes, GEO, robust rank aggregation, thyroid cancer

To demonstrate in vivo tumor growth inhibition, the liver cancer cell lines HepG2, BEL7402, and SMMC7721 were independently inoculated into the livers of 45 6-week-old nude mice. After 24 h, mice were randomly divided into celecoxib (intragastric celecoxib suspension, 300 mg/kg), negative control (equal volume intragastric saline), and positive control (intraperitoneal injection of 6 mg/kg doxorubicin) and treated once per day for 3 days. Body weights, tumor diameters, and tumor expressions of proliferating cell nuclear antigen (PCNA) and c-Met were determined at 23 days posttreatments. Significant increases in body weight were observed in celecoxib- or doxorubicin-treated mice compared to saline-treated animals and tumor growth was significantly attenuated, accompanied by downregulation of tumor PCNA expression (p < 0.01). Weight gain, attenuated tumor growth, and reduced PCNA expression were similar following celecoxib or doxorubicin treatment. Celecoxib also significantly reduced c-Met expression in HepG2- and BEL7402-induced tumors, but not SMMC7721-induced tumors (p < 0.05). In conclusion, celecoxib effectively suppressed the in vivo growth of liver cancer in an orthotopic tumor model. Celecoxib also inhibited tumor cell PCNA expression independent of changes in c-Met expression, with some variability between different implanted cell lines. This preclinical demonstration of celecoxib efficacy and safety provides a foundation for future clinical investigations involving use of this agent alone or as a component of chemotherapeutic regimens for treatment of HCC.

Xenotransplantation is an attractive solution to the problem of allograft shortage. However, transplants across discordant species barriers are subject to vigorous immunologic and pathobiologic hurdles, some of which might be overcome with the induction of immunologic tolerance. Several strategies have been designed to induce tolerance to a xenograft at both the central (including induction of mixed chimerism and thymic transplantation) and peripheral (including adoptive transfer of regulatory cells and blocking T cell costimulation) levels. Currently, xenograft tolerance has been well-established in rodent models, but these protocols have not yet achieved similar success in nonhuman primates. This review will discuss the major barriers that impede the establishment of immunological tolerance across xenogeneic barriers and the potential solution to these challenges, and provide a perspective on the future of the development of novel tolerance-inducing strategies.

Background Linked colour imaging (LCI) is a novel new image-enhanced endoscopy (IEE) technology that produces bright and vivid images. The aim of this study was to assess the ability of LCI to improve the diagnostic accuracy of early gastric cancer (EGC) relative to white light imaging (WLI). Materials and methods We performed this study on patients undergoing screening endoscopy from 12 medical institutions in China. Patients were randomly assigned to receive WLI followed by LCI or LCI followed by WLI. The primary outcome was to compared the diagnostic accuracy between LCI and WLI for EGC/high-grade intraepithelial neoplasms. Secondary outcomes included the numbers of suspicious lesions, neoplastic lesions and examination time by using LCI detected versus using WLI. Results A total of 1924 patients were randomly selected, and 1828 were included in the analysis. The diagnostic accuracy for EGC, which was 78.8% by using LCI and 68.4% by using WLI ( p < .0001). More suspicious lesions were detected by LCI than by WLI ( n = 1235 vs. 1036, p = .031), especially among differentiated EGC ( p = .013). LCI greatly shortened the examination time compared with WLI ( p = .019). Conclusions LCI has better accuracy and shorter examination time in diagnosing EGC than WLI (Clinical trial registration: NCT03092414). Key messages Compared with white light imaging (WLI), the diagnostic accuracy, sensitivity and specificity increased by using LCI. More lesions were detected by LCI alone than by WLI alone, especially among differentiated EGC. LCI may be used as a screening tool for routine clinical observation.

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