Yanlin Huang

Background: Non-significant dengue season trends are difficult to interpret without knowing which changes surveillance records can detect. We assessed season-window trends and detection capacity across a globally assembled database.Methods: We analysed monthly aggregate surveillance from 3,289 administrative units in 132 countries and territories. Calendar-year windows were defined by the 5th and 95th cumulative-case percentiles. We pooled unit trends, examined country dependence and circular windows, and estimated minimum detectable slopes at 80% power (MDS80) under independent Gaussian noise. China provided a source-audited comparison.Finding: Among 91 units with at least 20 complete window years, pooled length increased by 0·043 months/year (95% CI 0·035–0·052); 72 units were Thai. Circular length increased by 0·039 months/year (country-cluster 95% CI 0·013–0·065). Among 367 estimable length series with at least ten years, none achieved modelled 80% power for 0·2 months/decade, whereas 12·8% (47/367) achieved it for 1·0 month/decade. At the smaller reference rate, 58·3% (214/367) failed to reach 80% power within 60 additional years; among those reaching it, median additional monitoring was 47 years (IQR 40–54). Suitable-temperature-month trends were not significantly associated with case-window trends.Interpretation: Long records support season lengthening in the represented regions, while modelled detection limits constrain interpretation of short-record nulls. These findings establish neither a globally representative trend rate nor climatic causation. Broader geographical coverage and consistent monthly reporting are needed.

Objective: Kruppel-associated box (KRAB) proteins reportedly play a dual role in neoplastic transformation. At present, little is known about the function of the proteins encoded by the human pogo transposable element derived with KRAB domain (POGK) gene. Herein, we evaluated the prognostic significance of POGK expression in patients with hepatocellular carcinoma (HCC). Methods: The data of HCC patients was downloaded from The Cancer Genome Atlas (TCGA) database. To determine the relationship between POGK and clinical features, logistic regression was applied. Cox regression and Kaplan-Meier analyses were used to evaluate the correlation between POGK and survival rates. Gene ontology (GO) analysis and Gene set enrichment analysis (GSEA) were conducted to identify the enriched pathways and functions associated with POGK. Results: A total of 374 HCC patients were identified in TCGA. POGK was significantly upregulated in HCC and correlated with tumor status (p = 0.036), race (p = 0.025), weight (p = 0.002), body mass index (p = 0.033), histologic grade (p < 0.001), and alpha-fetoprotein (p < 0.001). High POGK expression in HCC patients correlated with a poor outcome in terms of overall survival (p = 0.0018), progression-free survival (p = 0.0087), relapse-free survival (p = 0.045), and disease-specific survival (p = 0.014), according to Kaplan-Meier analysis. Receiver operating characteristic curve analysis showed that the area under the curve of POGK expression for HCC diagnosis was 0.891. GSEA showed that high POGK expression might activate mitotic prometaphase, kinesins, homologous DNA pairing and strand exchange, MET activates PTK2 signaling pathway, G1 to S cell cycle control, Aurora B pathway, ncRNAs involved in WNT signaling pathway, hepatitis C, and ncRNAs involved in the STAT3 signaling pathway. POGK expression correlated with the abundance of adaptive and innate immunocytes in HCC. Conclusion: High expression of POGK has high diagnostic and prognostic values in patients with HCC. Moreover, POGK expression is correlated with immune infiltration in HCC.

Background. Our study aims to develop a lncRNA-based classifier and a nomogram incorporating the genomic signature and clinicopathologic factors to help to improve the accuracy of recurrence prediction for hepatocellular carcinoma (HCC) patients. Methods. The lncRNA profiling data of 374 HCC patients and 50 normal healthy controls were downloaded from The Cancer Genome Atlas (TCGA). Using univariable Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, we developed a 15-lncRNA-based classifier and compared our classifier to the existing six-lncRNA signature. Besides, a nomogram incorporating the genomic classifier and clinicopathologic factors was also developed. The predictive accuracy and discriminative ability of the genomic-clinicopathologic nomogram were determined by a concordance index (C-index) and calibration curve and were compared with the TNM staging system by the C-index and receiver operating characteristic (ROC) analysis. Decision curve analysis (DCA) was performed to estimate the clinical value of our nomogram. Results. Fifteen relapse-free survival (RFS-) related lncRNAs were identified, and the classifier, consisting of the identified 15 lncRNAs, could effectively classify patients into the high-risk and low-risk subgroups. The prediction accuracy of the 15-lncRNA-based classifier for predicting 2-year and 5-year RFS was 0.791 and 0.834 in the training set and 0.684 and 0.747 in the validation set, respectively, which was better than the existing six-lncRNA signature. Moreover, the AUC of genomic-clinicopathologic nomogram in predicting RFS were 0.837 in the training set and 0.753 in the validation set, and the C-index of the genomic-clinicopathologic nomogram was 0.78 (0.72-0.83) in the training set and 0.71 (0.65-0.76) in the validation set, which was better than the traditional TNM stage and 15-lncRNA-based classifier. The decision curve analysis further demonstrated that our nomogram had a larger net benefit than the TNM stage and 15-lncRNA-based classifier. The results were confirmed externally. Conclusion. Compared to the TNM stage, the 15-lncRNAs-based classifier-clinicopathologic nomogram is a more effective and valuable tool to identify HCC recurrence and may aid in clinical decision-making.

C-C motif chemokine ligand 14 (CCL14) is a chemokine promoting the activation of immune cells. However, the relationship between CCL14 expression, tumor immunity, and prognosis in Hepatocellular Carcinoma (HCC) remain unclear. CCL14 expression and its influence on tumor prognosis were analyzed by the ONCOMINE, Tumor Immune Estimation Resource (TIMER) and Kaplan-Meier plotter. The relationship between CCL14 expression and tumor immunity were analyzed by TIMER and Gene Expression Profiling Interactive Analysis (GEPIA). CCL14 expression was significantly lower in several human cancers, including HCC, than in corresponding normal tissues. CCL14 expression in HCC tissues correlated with prognosis. Low CCL14 expression associated with poorer overall survival, disease-specific survival, progression-free survival, and relapse-free survival in multiple cohorts of HCC patients, particularly at early disease stages (stage 1+2 or grade 2). CCL14 showed strong correlation with tumor-infiltrating B cells, CD4+ and CD8+ T cells, macrophages, neutrophils, and dendritic cells. CCL14 expression in HCC negatively correlated with expression of several immune cell markers, including exhausted T cell markers, PD-1, TIM-3 and CTLA-4, suggesting its role in regulating tumor immunity. These findings demonstrate that CCL14 is a potential prognostic biomarker that determines cancer progression and correlated with tumor immune cells infiltration in HCC.

Background. Single nucleotide polymorphism (SNP) of complement component 2 (C2) has been found to be significantly associated with hepatocellular carcinoma (HCC). However, little is known about the role and mechanism of C2 in HCC. In the present study, we aimed to explore the prognostic value of C2 and its correlation with tumor‐infiltrating immune cells in HCC. Materials and Methods. mRNA expression was downloaded from TCGA (365 HCC patients and 50 healthy controls), GSE14520 (220 HCC patients and 220 adjacent normal tissues), and ICGC HCC (232 HCC patients) cohorts. Unpaired Student’s t‐tests or ANOVA tests were used to evaluate differences of C2 expression. Univariate and multivariate analyses were used to analyze the prognostic value of C2. CIBERSORT was used to calculate the proportion of 22 kinds of tumor‐infiltrating immune cells. Results. Significantly lower C2 expression was found at HCC compared to healthy controls, and C2 was associated with TNM stages. Higher C2 expression was significantly associated with better prognosis, and multivariate analysis showed that C2 was also an independent factor for the prognosis of HCC. Moreover, elevated CD4 T cells were found at HCC patients with higher C2 expression while the higher proportion of macrophage M0 cells was found in HCC patients with lower C2 expression. KEGG analysis showed that “cell cycle,” “AMPK signaling pathway,” and “PPAR signaling pathway” were enriched in HCC patients with higher C2 expression. Conclusion. C2 is a prognostic factor for HCC and may be used as a therapeutic target for future treatment of HCC.

Aims: A large number of studies have suggested that exportins (XPOs) play a pivotal role in human cancers. In the present study, we analyzed XPO mRNA expression in cancer tissues and explored their prognostic value in hepatocellular carcinoma (HCC). Methods: Transcriptional and survival data related to XPO expression in HCC patients were obtained through the ONCOMINE and UALCAN databases. Survival analysis plots were drawn with Gene Expression Profiling Interactive Analysis (GEPIA). Sequence alteration data for XPOs were obtained from The Cancer Genome Atlas (TCGA) database and c-BioPortal. Gene functional enrichment analyses were performed with Database for Annotation, Visualization and Integrated Discovery (DAVID). Results: Compared with normal liver tissues, significant XPO mRNA overexpression was observed in HCC cancer tissues. There was a trend of higher XPO expression in more advanced clinical stages and lower differentiated pathological grades of HCC. In HCC patients, high expression of XPO1, CSE1L, XPOT, XPO4/5/6 was related to poor overall survival (OS), and XPO1, CSE1L and XPO5/6 were correlated with poor disease-free survival (DFS). The main genetic alterations in XPOs involved mRNA up-regulation, DNA amplification and deletion. General XPO mutations were remarkably associated with worse OS and mostly affected the pathways of RNA transport and oocyte meiosis. Conclusion: High expression of XPOs was associated with a poor prognosis in HCC patients. XPOs may be exploited as good prognostic biomarkers for survival in HCC patients.

Hepatitis B virus (HBV) replicates non-cytopathically in the hepatocytes and HBV-related diseases are caused by immune-mediated inflammatory events. This study aimed to identify the relationship between clinical-virological characteristics and immunity in untreated chronic hepatitis B (CHB) patients. A total of 209 CHB patients were categorized into immune tolerant (IT, n = 17), inactive carrier (IC, n = 20), immune active (IA, n = 120), and gray zone (GZ, n = 72) phases. The quantitative hepatitis B surface antigen (qHBsAg), hepatitis B e antigen (HBeAg), anti-HBeAg (HBeAb), HBV genotype, viral mutant and frequencies of interleukin (IL)-4, IL-17, IL-10 and interferon-gamma (IFN-γ) produced by CD4+ and CD8+ T cells were tested. We also correlated these cytokines with clinical-virological characteristics using a linear regression model. CD8+ T cells frequency were significantly decreased in IT patients. Levels of CD4+ T cells IL-4+ or IL-10+ were strongly negatively associated with qHBsAg titers. The frequency of IFN-γ produced by CD4+ and CD8+ T cells showed significant positive association with age and alanine aminotransferase (ALT) level, while that had negative association with qHBsAg titers. Additionally, the ratios of mutations in the HBV precore (PC) stop codon and basal core promoter (BCP) and the combined mutations were 32.5, 27.2, and 11.3%, respectively. The frequency of CD4+ T cells IL-17+ was higher in patients with a PC mutation than that in patients carrying a wild-type sequence. Finally, little associations among T cell derived IL-4, IL-10, IL-17, and IFN-γ was observed in the current untreated CHB cohort. Several components of the immune system were correlated with HBV factors that influence an inflammatory process during CHB. Of particular relevance are the significant associations of between CD4+ T cells IL-4+ and qHBsAg level, and between CD4+ T cells IL-17+ and the presence of a mutation in PC.