Prognostic value of geriatric nutritional risk index and prognostic nutritional index in hepatocellular carcinoma.

BACKGROUND: The geriatric nutritional risk index (GNRI) and prognostic nutritional index (PNI) are considered prognostic factors for several cancers. This study aimed to investigate the relationship between the GNRI and PNI for survival outcomes in patients with hepatocellular carcinoma (HCC). METHODS: We retrospectively analyzed 1666 patients with HCC who underwent hepatectomy. Restricted cubic spline regression was used to analyze the relationship between the GNRI and PNI for recurrence and mortality. Cox proportional hazards regression analysis was used to evaluate the risk factors associated with overall survival (OS) and recurrence-free survival (RFS). Interaction analysis was performed to investigate the comprehensive effects of the GNRI, PNI, and subgroup parameters on the prognosis of patients with HCC. RESULTS: The risks of death and recurrence decreased rapidly and gradually stabilized as the GNRI and PNI scores increased. Patients with lower GNRI and PNI scores had significantly shorter OS and RFS rates than those with higher scores. Multivariate analysis showed that high GNRI [HR and 95%CI = 0.77 (0.70-0.85), P < 0.001] and PNI [HR and 95%CI = 0.77 (0.70-0.86), P < 0.001] scores were associated with decreased mortality risk. This trend was maintained by confounding variables in adjusted models despite partial interactions with clinical factors. The combined GNRI and PNI analysis showed that HCC patients with high GNRI and PNI had longer OS and RFS. CONCLUSIONS: The GNRI and PNI showed good survival predictions in patients with HCC. Combining the GNRI with PNI may help predict the prognosis of patients (age>18 years) with HCC after hepatectomy.

Diagnosis and prognostic value of C-X-C motif chemokine ligand 1 in colon adenocarcinoma based on The Cancer Genome Atlas and Guangxi cohort.

Objective: The objective was to identify and validate C-X-C motif chemokine ligand 1(CXCL1) for diagnosis and prognosis in colon adenocarcinoma (COAD). Methods: Our current study had enrolled one The Cancer Genome Atlas (TCGA) cohort and two Guangxi cohorts to identify and verify the diagnostic and prognostic values of CXCL1 in COAD. Functional enrichment was performed by gene set enrichment analysis (GSEA). Results: In TCGA cohort, the expression of CXCL1 was significantly up-regulated in tumor tissues and decreased as the tumor stage developed. The receiver operating characteristic (ROC) curve showed that CXCL1 had a high diagnostic value for COAD. The result of Kaplan-Meier survival analysis showed that CXCL1 gene expression (P=0.045) was significantly correlated with overall survival (OS) of COAD. Results of Guangxi cohort also verified the diagnostic value of CXCL1 in COAD, and sub-group survival analyses also suggested that patients with high CXCL1 expression were related to a favorable OS (Corrected P=0.005). GSEA revealed that CXCL1 high expression phenotype was related to cytokine activity, cell apoptosis, P53 regulation pathway, and regulation of autophagy in COAD. Conclusions: In this study, we found that CXCL1 gene might be a potential diagnostic biomarker for COAD, and might serve as a prognostic biomarker for specific subgroup of COAD.

SOX4 as biomarker in hepatitis B virus-associated hepatocellular carcinoma.

Background: Hepatitis B virus infection is associated with liver disease, including cancers. In this study, we assessed the power of sex-determining region Y (SRY)-related high-mobility group (HMG)-box 4(SOX4) gene to predict the clinical course of hepatocellular carcinoma (HCC). Methods: To evaluate the differential expression of SOX4 and its diagnostic and prognostic potential in HCC, we analyzed the GSE14520 dataset. Stratified analysis and joint-effect analysis were done using SOX4 and clinical factor. We then designed a nomogram for predicting the clinical course of HCC. Differential SOX4 expression and its correlation with tumor stage as well as its diagnostic and prognostic value were analyzed on the oncomine and GEPIA websites. Gene set enrichment analysis was explored as well as candidate gene ontology and metabolic pathways modulated by in SOX4 HCC. Results: Our analysis revealed that the level of SOX4 was significantly upregulated in tumor issue (P <0.001). This observation was validated through oncomine dataset and MERAV analysis (all P <0.05). Diagnostic receiver operating characteristic (ROC) analysis of SOX4 suggested it has diagnostic potential in HCC (GSE14520 dataset: P <0.001, area under curve (AUC) = 0.782; Oncomine: (Wurmbach dataset) P = 0.002, AUC = 0.831 and (Mas dataset) P <0.001, AUC = 0.947). In addition, SOX4 exhibited high correlation with overall survival of HBV-associated HCC (adjusted P = 0.004, hazard ratio (HR) (95% confidence interval (CI)) = 2.055 (1.261-3.349) and recurrence-free survival (adjusted P = 0.008, HR (95% CI) = 1.721 (1.151-2.574). These observations which were verified by GEPIA analysis for overall survival (P = 0.007) and recurrence-free survival (P= 0.096). Gene enrichment analysis revealed that affected processes included lymphocyte differentiation, pancreatic endocrine pathways, and insulin signaling pathway. SOX4 prognostic value was evaluated using nomogram analysis for HCC 1, 3, and 5-year, survival. Conclusion: Differential SOX4 expression presents an avenue of diagnosing and predicting clinical course of HCC. In HCC, SOX4 may affect TP53 metabolic processes, lymphocyte differentiation and the insulin signaling pathway.

Genome-wide RNA-sequencing dataset reveals the prognostic value and potential molecular mechanisms of lncRNA in non-homologous end joining pathway 1 in early stage Pancreatic Ductal Adenocarcinoma.

Objective: Our current study is to explore the prognostic value and molecular mechanisms underlying the role of lncRNA in non-homologous end joining pathway 1 (LINP1) in early stage pancreatic ductal adenocarcinoma (PDAC). Methods: Genome-wide RNA-seq datasets of 112 early stage PDAC patients were got from The Cancer Genome Atlas and analyzed using multiple online tools. Results: Overall survival in high LINP1 expression patients was shorter than those with low expression (high-LINP1 vs. low-LINP1=481 vs. 592 days, log-rank P=0.0432). The multivariate Cox proportional hazard regression model suggested that high-LINP1 patients had a markedly higher risk of death than low-LINP1 patients (adjusted P=0.004, hazard ratio=2.214, 95% confidence interval=1.283-3.820). Analysis of genome-wide co-expressed genes, screening of differentially expressed genes, and gene set enrichment analysis indicated that LINP1 may be involved in the regulation of cell proliferation-, cell adhesion- and cell cycle-related biological processes in PDAC. Six small-molecule compounds including STOCK1N-35874, fenofibrate, exisulind, NU-1025, vinburnine, and doxylamine were identified as potential LINP1-targeted drugs for the treatment of PDAC. Conclusions: Our study indicated that LINP1 may serve as a prognostic biomarker of early stage PDAC. Analysis of genome-wide datasets led to the elucidation of the underlying mechanisms and identified six potential targeted drugs for the treatment of early PDAC.

Comprehensive investigation of p53, p21, nm23, and VEGF expression in hepatitis B virus-related hepatocellular carcinoma overall survival after hepatectomy.

Objective: The goal of our current study is to assess the immunohistochemical of p53, p21, nm23, and VEGF expression in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) prognosis after hepatectomy, as well as the prospective molecular mechanisms of prognostic indicator. Methods: There were 419 HBV-related HCC patients who were from southern China of Guangxi province and were used to evaluate the immunohistochemical expression for these biomarkers in prognosis. A genome-wide expression microarray dataset of HBV-related HCC were obtained from GSE14520. Results: In our study, the expression of p53, p21, and nm23 in cancer tissues of patients with hepatitis B-related hepatocellular carcinoma did not affected the clinical outcome of 2 years, 5 years or overall. Patients with high expression of VEGF had a worse overall survival after 2 years of surgery than patients with low expression (adjusted P=0.040, adjusted HR = 1.652, 95% CI = 1.024-2.665). Survival analysis of VEGF in GSE14520 cohort also demonstrated that VEGF mRNA expression also significantly associated with HBV-related HCC OS (adjusted P=0.035, adjusted HR =1.651, 95% CI =1.035-2.634). The prospective molecular mechanisms by co-expression analysis suggested that VEGF might be correlated to regulation of cell proliferation, cell growth and apoptotic process, Rap1 signaling pathway, HIF-1 signaling pathway, PPAR signaling pathway, cell cycle. Whereas the GSEA suggested that VEGF might involve in the regulation of HIF and HIF1A pathway, and TP53 regulation pathway. Conclusion: Our findings suggested that VEGF might be a prognostic indicator of HBV-related HCC, and we also identified the VEGF prospective molecular mechanisms through the whole genome co-expression and GSEA approaches.

Diagnostic and prognostic biomarkers of Human Leukocyte Antigen complex for hepatitis B virus-related hepatocellular carcinoma.

Background: Hepatitis B virus infection had been identified its relationship with liver diseases, including liver tumors. We aimed to explore diagnostic and prognostic values between the Human Leukocyte Antigen (HLA) complex and hepatocellular carcinoma (HCC). Methods: We used the GSE14520 dataset to explore diagnostic and prognostic significance between HLA complex and HCC. A nomogram was constructed to predict survival probability of HCC prognosis. Gene set enrichment analysis was explored using gene ontologies and metabolic pathways. Validation of prognostic values of the HLA complex was performed in the Kaplan-Meier Plotter website. Results: We found that HLA-C showed the diagnostic value (P <0.0001, area under curve: 0.784, sensitivity: 93.14%, specificity: 62.26%). In addition, HLA-DQA1 and HLA-F showed prognostic values for overall survival, and HLA-A, HLA-C, HLA-DPA1 and HLA-DQA1 showed prognostic values for recurrence-free survival (all P ≤ 0.05, elevated 0.927, 0.992, 1.023, 0.918, 0.937 multiples compared to non-tumor tissues, respectively). Gene set enrichment analysis found that they were involved in antigen processing and toll like receptor signalling pathway, etc. The nomogram was evaluated for survival probability of HCC prognosis. Validation analysis indicated that HLA-C, HLA-DPA1, HLA-E, HLA-F and HLA-G were associated with HCC prognosis of overall survival (all P ≤ 0.05, elevated 0.988 and 0.997 multiples compared to non-tumor tissues, respectively). Conclusion: HLA-C might be a diagnostic and prognostic biomarker for HCC. HLA-DPA1 and HLA-F might be prognostic biomarkers for HCC.

Use of Genome-Scale Integrated Analysis to Identify Key Genes and Potential Molecular Mechanisms in Recurrence of Lower-Grade Brain Glioma.

BACKGROUND The aim of this study was to identify gene signals for lower-grade glioma (LGG) and to assess their potential as recurrence biomarkers. MATERIAL AND METHODS An LGG-related mRNA sequencing dataset was downloaded from The Cancer Genome Atlas (TCGA) Informix. Multiple bioinformatics analysis methods were used to identify key genes and potential molecular mechanisms in recurrence of LGG. RESULTS A total of 326 differentially-expressed genes (DEGs), were identified from 511 primary LGG tumor and 18 recurrent samples. Gene ontology (GO) analysis revealed that the DEGs were implicated in cell differentiation, neuron differentiation, negative regulation of neuron differentiation, and cell proliferation in the forebrain. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database suggests that DEGs are associated with proteoglycans in cancer, the Wnt signaling pathway, ECM-receptor interaction, the PI3K-Akt signaling pathway, transcriptional deregulation in cancer, and the Hippo signaling pathway. The hub DEGs in the protein-protein interaction network are apolipoprotein A2 (APOA2), collagen type III alpha 1 chain (COL3A1), collagen type I alpha 1 chain (COL1A1), tyrosinase (TYR), collagen type I alpha 2 chain (COL1A2), neurotensin (NTS), collagen type V alpha 1 chain (COL5A1), poly(A) polymerase beta (PAPOLB), insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), and anomalous homeobox (ANHX). GSEA revealed that the following biological processes may associated with LGG recurrence: cell cycle, DNA replication and repair, regulation of apoptosis, neuronal differentiation, and Wnt signaling pathway. CONCLUSIONS Our study demonstrated that hub DEGs may assist in the molecular understanding of LGG recurrence. These findings still need further molecular studies to identify the assignment of DEGs in LGG.

Aldehyde dehydrogenase 1 (ALDH1) isoform expression and potential clinical implications in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most prevalent and life-threatening malignancies worldwide. There are few diagnostic and prognostic biomarkers and druggable targets for HCC. Aldehyde dehydrogenase 1 (ALDH1) is a marker of stem cells in a variety of cancers, but the mRNA levels and prognostic value of ALDH1 isoforms in HCC patients remain unknown. In the present study, gene ontology annotation of the ALDH1 family was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID), and the gene pathway analsis was performed using GeneMANIA software. The initial prognostic value of ALDH1 expression in 360 HCC patients was assessed using the OncoLnc database. The expression levels of ALDH1 isoforms in normal liver tissues and clinical specimens of cancer vs. normal control datasets were determined using the GTEx and Oncomine databases, respectively. We then analyzed the prognostic value of ALDH1 expression in 212 hepatitis B virus (HBV)-related HCC patients using the GEO database. We found that the ALDH1 isoform showed high aldehyde dehydrogenase activity. The ALDH1A1, ALDH1B1, and ALDH1L1 genes encoded for the ALDH1 enzyme. High ALDH1B1 expression had protective qualities in HCC patients. Moreover, HBV-related HCC patients who showed high ALDH1L1 gene expression had a better clinical outcomes. In addition, high ALDH1A1 expression was associated with a 57-month recurrence-free survival in HBV-related HCC patients. High ALDH1B1 expression was protective for HCCs with multiple nodules and high serum alpha-fetoprotein (AFP) level. Furthermore, high serum AFP levels contributed to lower ALDH1L1. ALDH1A1, ALDH1B1, and ALDH1L1, all of which were considered promising diagnostic and prognostic markers as well as potential drug targets.

Genome-Wide Association Study of MKI67 Expression and its Clinical Implications in HBV-Related Hepatocellular Carcinoma in Southern China.

BACKGROUND/AIMS: Hepatocellular carcinoma (HCC) is a common malignant tumor with a high rate of recurrence. Immunohistochemical analysis of the marker of proliferation Ki-67 (MKI67) is used to assess proliferation activity of HCC The regulation of MKI67 expression remains unclear in HCC This study aims to explore the association between MKI67 expression and gene variants. METHODS: A total of 195 hepatitis B virus (HBV)-related HCC patients were genotyped using Illumina HumanExome BeadChip-12-1_A (242,901 markers). An independent cohort (97 subjects) validated the association of polymorphism determinants and candidate genes with MKI67 expression. The relationships between MKI67 with p53 and variants of candidate genes in the clinical outcomes of HCC patients were analyzed. RESULTS: We found that MKI67 combined with p53 was associated with a 3-year recurrence-free survival and five variants near TTN and CCDC8 were associated with MKI67 expression. TTN harboring rs2288563-TT and rs2562832-AA+CA indicated a favorable outcome for HCC patients. CONCLUSION: Variants near TTN and CCDC8 were associated with MKI67 expression, and rs2288563 and rs2562832 in TTN are potential biomarkers for the prediction of clinical outcomes in HBV-related HCC patients.