Hepatocellular carcinoma (HCC) is a malignancy with a poor prognosis. Some E3 ubiquitin-protein ligases play essential roles in HCC development. We aimed to explore a hub E3 ubiquitin-protein ligase gene and verify its association with prognosis and immune cell in ltration in HCC. We identi ed cell division cycle 20 (CDC20) as a hub E3 ubiquitin-protein ligase in HCC by determining the intersecting genes in a protein-protein interaction (PPI) network of differentially expressed genes (DEGs) in HCC data from the International Cancer Genome Consortium (ICGC) and 919 E3 ubiquitin-protein ligase genes from the Integrated annotations for Ubiquitin and Ubiquitin-like Conjugation Database (IUUCD). DEGs and their correlations with clinicopathological features were explored in The Cancer Genome Atlas (TCGA), ICGC, and Gene Expression Omnibus (GEO) databases via the Wilcoxon signed-rank test. The prognostic value of CDC20 was illustrated by Kaplan-Meier (K-M) curves and Cox regression analyses. Subsequently, the correlation between CDC20 and immune in ltration was demonstrated via the Tumor Immune Estimation Resource (TIMER) and Gene Expression Pro ling Interactive Analysis (GEPIA). CDC20 expression was signi cantly higher in HCC than in normal tissues (all P < 0.05). K-M curves and Cox regression analyses showed that high CDC20 expression predicted a poor prognosis and might be an independent risk factor for HCC prognosis (P < 0.05). Additionally, the TIMER and GEPIA results indicated that CDC20 is correlated with the immune in ltration of CD8 + T cells, T cells (general), monocytes, and exhausted T cells. This research revealed the potential prognostic value of CDC20 in HCC and demonstrated that CDC20 might be an immune-associated therapeutic target in HCC because of its correlation with immune in ltration.

Cell division cycle-associated protein-3 (CDCA3) contributes to the regulation of the cell cycle. CDCA3 plays an important role in the carcinogenesis of various cancers; however, the association between CDCA3 expression, prognosis of patients, and immune infiltration in the tumor microenvironment is still unknown. Here, we demonstrated that CDCA3 was differentially expressed between the tumor tissues and corresponding normal tissues using in silico analysis in the ONCOMINE and Tumor Immune Estimation Resource (TIMER) databases. We analyzed the relationship between the expression of CDCA3 and prognosis of patients with hepatocellular carcinoma (HCC) using the Kaplan–Meier plotter database and Gene Expression Profiling Interactive Analysis (GEPIA). Furthermore, we determined the prognostic value of CDCA3 expression using univariate and multivariate analyses. We observed that CDCA3 expression closely correlated with immune infiltration and gene markers of infiltrating immune cells in the TIMER database. CDCA3 was highly expressed in the tumor tissues than in the adjacent normal tissues in various cancers, including HCC. Increased expression of CDCA3 was accompanied by poorer overall survival (OS), relapse-free survival (RFS), progression-free survival (PFS), and disease-specific survival (DSS). The correlation between CDCA3 expression and OS and disease-free survival (DFS) was also studied using GEPIA. CDCA3 expression was associated with the levels of immune cell infiltration and was positively correlated with tumor purity. Moreover, CDCA3 expression was associated with gene markers such as PD-1, CTLA4, LAG3, and TIM-3 from exhausted T cells, CD3D, CD3E, and CD2 from T cells, and TGFB1 and CCR8 located on the surface of Tregs. Thus, we demonstrated that CDCA3 may be a potential target and biomarker for the management and diagnosis of HCC.

Pancreatic cancer (PC) is a life-threatening cancer with increasing incidence in developed countries. Reports indicate that tRNA-derived fragments (tRFs) are possible therapeutic targets and biomarkers for cancer treatment. Nonetheless, the effect of tRF-Leu-AAG on PC is unclear. This study aims to explore the role of tRF-Leu-AAG and upstream frameshift mutant 1 (UPF1) in the development of PC and its potential underlying mechanisms. High-throughput second-generation sequencing techniques were used to detect the expression of tRFs in cancerous and adjacent normal tissues from PC patients. The role of tRF-Leu-AAG proliferation in PC cells was investigated via the Cell Counting Kit-8 (CCK8) assay. The effect of tRF-Leu-AAG on the invasion and migration ability of PC cells was also determined by the transwell assay. Thereafter, the downstream target genes of tRF-Leu-AAG were comprehensively predicted using bioinformatics analysis databases. We also used the Dual-Luciferase Reporter assay to assess the nexus between tRF-Leu-AAG and UPF1. Eventually, Western Blot was used to validate the expression of UPF1 in PC cells. A total of 33 tRF expressions significantly varied from PC patients. RT-qPCR confirmed that the expression of tRF-Leu-AAG was observably up-regulated in PC cells as compared to the control cells. Importantly, knockdown of tRF-Leu-AAG observably inhibited cell proliferation, migration, and invasion. Furthermore, according to the predicted frameshift database results, the UPF1 acted as downstream target genes for tRF-Leu-AAG and significantly down-regulated UPF1 expression.

Background. Docking protein 5 (DOK5) is a member of the docking protein group of membrane proteins and is an adapter protein involved in signal transduction. Nevertheless, the role of DOK5 expression in the prognosis of gastric cancer (GC) remains unclear. Methods. In this study, clinical prognostic parameters and survival data related to DOK5, in patients with GC, were analyzed using bioinformatics analysis comprising Oncomine and TIMER, UALCAN database, Kaplan-Meier plotter, GEPIA, GSEA, DAVID, and cBioPortal websites. Results. In our study, GC contained various DOK5 expressions, which forecasted poor survival outcomes. Moreover, our research showed that high DOK5 could predict high-level infiltration of several GC immune cells, as evidenced by M1, TAM, M2, B cell, and T cell failure. Hence, DOK5 might become a new gastric cancer biomarker and therapeutic target. In the following analysis, in order to explore the prognostic value of DOK5 in GC, more clinical trials are needed to validate our results. Conclusions. Through multiple database verifications, DOK5 was found to be part of the pathogenic genes for GC. Thus, it can change the formation and progression of tumors by acting on human immunity.

Background. The dysregulated PI3K/AKT/mTOR pathway acts as the main regulator of tumorigenesis in hepatocellular carcinoma (HCC). Aim. Here, we identify the prognostic significance of PI3K/AKT/mTOR pathway-associated genes (PAGs) as well as their putative signature based on PAGs in an HCC patient’s cohort. Methods. The transcriptomic data and clinical feature sets were queried to extract the putative prognostic signature. Results. We identified nine PAGs with different expressions. GO and KEGG indicated that these differentially expressed genes were associated with various carcinogenic pathways. Based on the signature-computed median risk score, we categorized the patients into groups of low risk and high risk. The survival time for the low-risk group is longer than that of the high-risk group in Kaplan-Meier (KM) curves. The prognostic value of risk score ( ROC = 0.736 ) of receiver operating characteristic (ROC) curves performed better in comparison to that of other clinicopathological features. In both the GEO database and ICGC database, these outcomes were verified. The predictions of the overall survival rates in HCC patients of 1 year, 3 years, and 5 years can be obtained separately from the nomogram. The risk score was associated with the immune infiltrations of CD8 T cells, activated CD4 memory T cells, and follicular helper T cells, and the expression of immune checkpoints (PD-1, TIGIT, TIM-3, BTLA, LAG-3, and CTLA4) was positively relevant to the risk score. The sensitivity to several chemotherapeutic drugs can also be revealed by the signature. CDK1, PITX2, PRKAA2, and SFN were all upregulated in the tumor tissue of clinical samples. Conclusion. A putative and differential dataset-validated prognostic signature on the basis of integrated bioinformatic analysis was established in our study, providing the immunotherapeutic targets as well as the personalized treatment in HCC with neoteric insight.

BackgroundHepatocellular carcinoma (HCC) is one of the most frequent malignancies. Alpha-fetoprotein (AFP) has some limitations in diagnosing early HCC. Recently, long noncoding RNAs (lncRNAs) showed great potential as tumor diagnostic biomarkers, and lnc-MyD88 was previously identified as a carcinogen in HCC. Here, we explored its diagnostic value as a plasma biomarker.Materials and methodsQuantitative real-time PCR was adopted to detect lnc-MyD88 expression in plasma samples of 98 HCC patients, 52 liver cirrhosis (LC) patients, and 105 healthy people. The correlation between lnc-MyD88 and clinicopathological factors was analyzed through chi-square test. The receiver operating characteristic (ROC) curve was used to analyze the sensitivity, specificity, Youden index, and area under the curve (AUC) of lnc-MyD88 and AFP alone and in combination for the diagnosis of HCC. The relationship between MyD88 and immune infiltration was analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm.ResultsLnc-MyD88 was highly expressed in plasma samples of HCC and hepatitis B virus (HBV)-associated HCC patients. Lnc-MyD88 had better diagnostic value than AFP in HCC patients using healthy people or LC patients as control (healthy people, AUC: 0.776 vs. 0.725; LC patients, AUC: 0.753 vs. 0.727). The multivariate analysis showed that lnc-MyD88 had great diagnostic value for distinguishing HCC from LC and healthy people. Lnc-MyD88 had no correlation with AFP. Lnc-MyD88 and AFP were independent diagnostic factors for HBV-associated HCC. The AUC, sensitivity, and Youden index of the combined diagnosis of lnc-MyD88 and AFP combined were higher than those of lnc-MyD88 and AFP alone. The ROC curve of lnc-MyD88 for the diagnosis of AFP-negative HCC was plotted with a sensitivity of 80.95%, a specificity of 79.59%, and an AUC value of 0.812 using healthy people as control. The ROC curve also presented its great diagnostic value using LC patients as control (sensitivity: 76.19%, specificity: 69.05%, AUC value: 0.769). Lnc-MyD88 expression was correlated with microvascular invasion in HBV-associated HCC patients. MyD88 was positively correlated with infiltrating immune cells and immune-related genes.ConclusionThe high expression of plasma lnc-MyD88 in HCC is distinct and could be utilized as a promising diagnostic biomarker. Lnc-MyD88 had great diagnostic value for HBV-associated HCC and AFP-negative HCC, and it had higher efficacy in combination with AFP.

Hepatocellular carcinoma (HCC) is a malignancy with a poor prognosis. Some E3 ubiquitin-protein ligases play essential roles in HCC development. We aimed to explore a hub E3 ubiquitin-protein ligase gene and verify its association with prognosis and immune cell infiltration in HCC. We identified cell division cycle 20 (CDC20) as a hub E3 ubiquitin-protein ligase in HCC by determining the intersecting genes in a protein-protein interaction (PPI) network of differentially expressed genes (DEGs) in HCC data from the International Cancer Genome Consortium (ICGC) and 919 E3 ubiquitin-protein ligase genes from the Integrated annotations for Ubiquitin and Ubiquitin-like Conjugation Database (IUUCD). DEGs and their correlations with clinicopathological features were explored in The Cancer Genome Atlas (TCGA), ICGC, and Gene Expression Omnibus (GEO) databases via the Wilcoxon signed-rank test. The prognostic value of CDC20 was illustrated by Kaplan-Meier (K-M) curves and Cox regression analyses. Subsequently, the correlation between CDC20 and immune infiltration was demonstrated via the Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA). CDC20 expression was significantly higher in HCC than in normal tissues (all P < 0.05). K-M curves and Cox regression analyses showed that high CDC20 expression predicted a poor prognosis and might be an independent risk factor for HCC prognosis (P < 0.05). Additionally, the TIMER and GEPIA results indicated that CDC20 is correlated with the immune infiltration of CD8 + T cells, T cells (general), monocytes, and exhausted T cells. This research revealed the potential prognostic value of CDC20 in HCC and demonstrated that CDC20 might be an immune-associated therapeutic target in HCC because of its correlation with immune infiltration.

Background: Hepatocellular carcinoma (HCC) has become the third leading cause of death from cancer worldwide, and PI3K/AKT signaling pathway acts as the most common carcinogenic pathway in HCC. But few studies have reported the prognostic value of PI3K/AKT associated genes (PAGs) and their association with immune infiltration in HCC.Methods: The mRNA sequencing data and clinical information were gained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC) database. The 105 PAGs gene sets were from the Gene set enrichment analysis (GSEA) website. The biological processes of differently expressed PAGs were explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. A four-gene prognostic signature (SFN, PRKAA2, PITX2 and CDK1) was built based on the multivariate analyses results. Its prognostic value was trained in TCGA database and tested in GEO database and ICGC database. The association between risk score and immune infiltration were explored by CIBERSORT method.Results: a total of nine differently expressed PAGs were identified. GO and KEGG revealed these genes were correlated with different carcinogenic pathways. The patients were divided into high-risk group and low-risk group according to the median risk score. The high-risk group had shorter survival time compared with the low-risk group in Kaplan-Meier (KM) curves. Receiver operating characteristic (ROC) curves showed the better prognostic value of risk score (ROC=0.736) compared with other clinicopathological characteristics (AUC ≤ 0.511). The consistent results were obtained in the GEO database and ICGC database. The nomogram predicted the 1-year, 3-year, and 5-year overall survival rates in HCC. The risk score was correlated with immune infiltration of monocytes and M0 macrophages, and the expression of immune checkpoints (PDCD1, CTLA4, TIM3 and TIGIT) were related to risk score. Conclusion: Our study established a novel four-gene prognostic signature by integrated bioinformatic analysis. It provided new insight into the immunotherapy targets and may direct the individualized treatment in HCC.