Background. Acute pancreatitis (AP) is a life-threatening disease caused by a variety of factors, and once it progresses to severe acute pancreatitis, the prognosis is poor. The purpose of this study was to investigate the diagnostic value of the neutrophil-lymphocyte ratio (NLR) for predicting the severity of acute pancreatitis. Materials and Methods. We searched the databases of PubMed, EMBASE, Web of Science, and Cochrane Library to identify eligible studies using the NLR to predict the severity of AP. The sensitivity (SEN), specificity (SPE), negative likelihood ratio (NLR), positive likelihood ratio (PLR), diagnostic odds ratio (DOR), and area under the receiver operating characteristic curve (AUC) were combined using a bivariate mixed model. Results. A total of 10 articles containing 394 cases and 1319 controls were included in the study. The combined SEN, SPE, NLR, PLR, DOR, and AUC are 79% (73%-84%), 71% (59%-80%), 0.30 (0.21-0.41), 2.7 (1.8-4.0), 9 (5-18), and 0.82 (0.78-0.85), respectively. Conclusions. NLR has a moderately high diagnostic value in predicting the severity of acute pancreatitis.

Purpose: To unravel the oncogenic role of CDCA4 in different cancers from the perspective of tumor immunity.Methods: Raw data on CDCA4 expression in tumor samples and paracancerous samples were obtained from TCGA and GTEX databases. In addition, we investigated pathological stages and the survival analysis of CDCA4 in pan-cancer across Gene Expression Profiling Interactive Analysis (GEPIA) database. Cox Proportional Hazards Model shows that high CDCA4 levels are associated with several vital indicators in oncology. On the one hand, we explored the correlation between CADA4 expression and tumor immune infiltration by the TIMER tool; On the other hand, we utilized the methods of CIBERSORT and ESTIMATE computational to evaluate the proportion of tumor infiltrating immune cells (TIIC) and the amounts of stromal and immune components based on TCGA database. The use of antineoplastic drugs and the expression of CDCA4 also showed a high correlation via linear regression. Protein–Protein Interaction analysis was performed in the GeneMANIA database, and enrichment analysis was performed and predicted signaling pathways were identified by using Gene Ontology and Kyoto Encyclopedia of Genes. The correlation between CDCA4 expression with Copy number variations (CNV) and methylation is detailed, respectively. Molecular biology experiments including Western blotting, flow cytometry, EDU staining, Transwell and Wound Healing assay to validate the cancer promoting role of CDCA4 in hepatocellular carcinoma (HCC).Results: Most tumors highly expressed CDCA4. Elevated CDCA4 expression was associated with poor OS and DFS. There was a significant correlation between CDCA4 expression and TITCs. Moreover, markers of TIICs exhibited distinct patterns of CDCA4 associated immune infiltration. In addition, we pay attention to the association between the expression of CDCA4 and the use of the anti-tumor drugs. CDCA4 is related to biological progress (BP), cellular component (CC) and molecular function (MF). Dopaminergic Synapse, AMPK, Sphingolipid, Chagas Disease, mRNA Surveillance were significantly enriched pathways in positive and negative correlation genes with CDCA4. CNV is thought to be a positive correlation with CDCA4 expression. Conversely, methylation is negative correlation with CDCA4 expression. Molecular biology experiments confirm a cancer promoting role for CDCA4 in HCCConclusion: CDCA4 may serve as a biomarker for cancer immunologic infiltration and poor prognosis, providing a new way of thinking for cancer treatment.

Corticotropin-releasing hormone-binding protein (CRHBP) is involved in many physiological processes. However, it is still unclear what role CRHBP has in tumor immunity and prognosis prediction. Using databases such as the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Tumor Protein Database, Timer Database, and Gene Expression Profiling Interactive Analysis (GEPIA), we evaluated the potential role of CRHBP in diverse cancers. Further research looked into the relationships between CRHBP and tumor survival prognosis, immune infiltration, immune checkpoint (ICP) indicators, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), DNA methylation, tumor microenvironment (TME), and drug responsiveness. The anticancer effect of CRHBP in liver hepatocellular carcinoma (LIHC) was shown by Western blotting, EdU staining, JC-1 staining, transwell test, and wound healing assays. CRHBP expression is significantly low in the majority of tumor types and is associated with survival prognosis, ICP markers, TMB, and microsatellite instability (MSI). The expression of CRHBP was found to be substantially related to the quantity of six immune cell types, as well as the interstitial and immunological scores, showing that CRHBP has a substantial impact in the TME. We also noticed a link between the IC50 of a number of anticancer medicines and the degree of CRHBP expression. CRHBP-related signaling pathways were discovered using functional enrichment. Cox regression analysis showed that CRHBP expression was an independent prognostic factor for LIHC. CRHBP has a tumor suppressor function in LIHC, according to cell and molecular biology trials. CRHBP has a significant impact on tumor immunity, treatment, and prognosis, and has the potential as a cancer treatment target and prognostic indicator.

Objective: The purpose of this study was to establish an N6-methylandenosine (m6A)-related long non-coding RNA (lncRNA) signature to predict the prognosis of hepatocellular carcinoma (HCC).Methods: Pearson correlation analysis was used to identify m6A-related lncRNAs. We then performed univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct an m6A-related lncRNA signature. Based on the cutoff value of the risk score determined by the X-title software, we divided the HCC patients into high -and low-risk groups. A time-dependent ROC curve was used to evaluate the predictive value of the model. Finally, we constructed a nomogram based on the m6A-related lncRNA signature.Results: ZEB1-AS1, MIR210HG, BACE1-AS, and SNHG3 were identified to comprise an m6A-related lncRNA signature. These four lncRNAs were upregulated in HCC tissues compared to normal tissues. The prognosis of patients with HCC in the low-risk group was significantly longer than that in the high-risk group. The M6A-related lncRNA signature was significantly associated with clinicopathological features and was established as a risk factor for the prognosis of patients with HCC. The nomogram based on the m6A-related lncRNA signature had a good distinguishing ability and consistency.Conclusion: We identified an m6A-related lncRNA signature and constructed a nomogram model to evaluate the prognosis of patients with HCC.

Purpose. Autophagy is a lysosomal degradation pathway that is essential for maintaining the homeostasis of the intracellular environment. Mounting evidence indicates that autophagy plays an essential role in the occurrence and development of hepatocellular cancer (HCC). This research is aimed at exploring the prognostic value of autophagy‐related genes (ARGs) in HCC patients. Methods. The Wilcoxon test was used to identify differentially expressed ARGs in The Cancer Genome Atlas (TCGA) HCC cohort. Then, the TCGA cohort was randomly divided into training and testing groups. Cox and LASSO regression models were used to screen for autophagy‐related genes that affect overall survival (OS) in the TCGA training group. Based on the coefficient of risk genes, we constructed an autophagy‐related gene signature for predicting the prognosis of HCC patients. Finally, we validated the prognostic significance of autophagy‐related gene signature using the TCGA testing group and three external datasets. Results. ATG10, BIRC5, GAPDH, and TMEM74 are risk genes for OS. According to the optimal cutoff value of risk score in each HCC dataset, HCC patients can divide into high‐ and low‐risk groups. ARG risk score can significantly distinguish HCC patients with different survival outcomes. Meanwhile, the ARG risk score is independently correlated with OS in multiple HCC cohorts. Conclusions. The autophagy‐related risk score can effectively screen high‐risk HCC patients and provide guidance for clinical prevention and treatment of HCC.

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, and its prognosis remains unsatisfactory. The identification of new and effective markers is helpful for better predicting the prognosis of patients with HCC and for conducting individualized management. The oncogene Aurora kinase A (AURKA) is involved in a variety of tumors; however, its role in liver cancer is poorly understood. The aim of this study was to establish AURKA-related gene signatures for predicting the prognosis of patients with HCC.Methods: We first analyzed the expression of AURKA in liver cancer and its prognostic significance in different data sets. Subsequently, we selected genes with prognostic value related to AURKA and constructed a gene signature based on them. The predictive ability of the gene signature was tested using the HCC cohort development and verification data sets. A nomogram was constructed by integrating the risk score and clinicopathological characteristics. Finally, the influence of the gene signature on the immune microenvironment in HCC was comprehensively analyzed.Results: We found that AURKA was highly expressed in HCC, and it exhibited prognostic value. We selected eight AURKA-related genes with prognostic value through the protein-protein interaction network and successfully constructed a gene signature. The nine-gene signature could effectively stratify the risk of patients with HCC and demonstrated a good ability in predicting survival. The nomogram showed good discrimination and consistency of risk scores. In addition, the high-risk group showed a higher percentage of immune cell infiltration (i.e., macrophages, myeloid dendritic cells, neutrophils, and CD4+T cells). Moreover, the immune checkpoints SIGLEC15, TIGIT, CD274, HAVCR2, and PDCD1LG2 were also higher in the high-risk group versus the low-risk group.Conclusions: This gene signature may be useful prognostic markers and therapeutic targets in patients with HCC.