Downregulation of N-myc and STAT Interactor Protein Predicts Aggressive Tumor Behavior and Poor Prognosis in Invasive Ductal Carcinoma / 한국유방암학회지

PURPOSE: We investigated the expression of the N-myc and STAT interactor (NMI) protein in invasive ductal carcinoma tissue and estimated its clinicopathologic significance as a prognostic factor. The expression levels and prognostic significance of NMI were also analyzed according to the molecular subgroup of breast cancers.METHODS: Human NMI detection by immunohistochemistry was performed using tissue microarrays of 382 invasive ductal carcinomas. The correlation of NMI expression with patient clinicopathological parameters and prognostic significance was analyzed and further assessed according to the molecular subgroup of breast cancers. Moreover, in vitro experiments with 13 breast cancer cell lines were carried out. We also validated NMI expression significance in The Cancer Genome Atlas cohort using the Human Protein Atlas (HPA) database.RESULTS: Low NMI expression was observed in 190 cases (49.7%). Low NMI expression was significantly associated with the “triple-negative” molecular subtype (p < 0.001), high nuclear grade (p < 0.001), high histologic grade (p < 0.001), and advanced anatomic stage (p = 0.041). Patients with low NMI expression had poorer progression-free survival (p = 0.038) than patients with high NMI expression. Low NMI expression was not significantly associated with patient prognosis in the molecular subgroup analysis. In vitro, a reduction of NMI expression was observed in 8 breast cancer cell lines, especially in the estrogen receptor-positive and basal B type of triple-negative breast cancer molecular subgroups. The HPA database showed that low NMI expression levels were associated with a lower survival probability compared with that associated with high NMI expression (p = 0.053).CONCLUSION: NMI expression could be a useful prognostic biomarker and a potential novel therapeutic target in invasive ductal carcinoma.

Expression of TM6SF2 in hepatocellular carcinoma tissue and its bioinformatics functions / 临床肝胆病杂志

ObjectiveTo investigate the expression of TM6SF2 in hepatocellular carcinoma (HCC) tissue and its biological functions by data mining in tumor databases. MethodsThe GEPIA database was applied to measure the change in the mRNA expression level of TM6SF2 in HCC tissue, and OncoLnc was used to analyze the association of TM6SF2 expression with the survival time of HCC patients. The cBioPortal and LinkedOmics databases were used to analyze the genes associated with the expression of TM6SF2 in HCC tissue, and the DAVID6.8 and STRING databases were used to perform a bioinformatics analysis of TM6SF2 and the genes associated with its expression. The t-test was used to investigate the difference in the mRNA expression of TM6SF2 between HCC tissue and adjacent tissue. The Spearman correlation coefficient was used to analyze the correlation of gene expression. The Kaplan-Meier method was used to calculate survival percentage, and the log-rank test was used to analyze the difference in survival percentage. ResultsCompared with the normal liver tissue, the HCC tissue had low mRNA expression of TM6SF2 (｜log2FC｜cut-off = 0.5, P＜0.01). Compared with those with high expression of TM6SF2, the patients with low expression had a significant reduction in overall survival time (χ2=9.897，P＜0.01). Data analysis showed that a total of 49 genes were associated with the expression of TM6SF2 in HCC tissue, and the gene ontology analysis showed that these genes were enriched in the biological processes and functions including fatty acid synthesis, fatty acid ligase activation, and thrombin regulation (P＜0.05). The Kyoto Encyclopedia of Genes and Genome pathway analysis showed that these genes were mainly involved in the signaling pathways of alanine metabolism, peroxisome proliferator-activated receptor signaling pathway, and bile secretion (P＜0.05). The protein-protein interaction network analysis showed that the genes of SERPINC1, NR1I2, SERPINA10, and SLC10A1 had marked or potential interaction with TM6SF2 (P＜0.01). ConclusionTumor data mining can quickly obtain the information on the expression of TM6SF2 in HCC tissue and provide a bioinformatics basis for exploring the role of TM6SF2 in the development and progression of HCC.

Expression and significance of the ABAT gene in hepatocellular carcinoma: An analysis based on data mining / 临床肝胆病杂志

ObjectiveTo investigate the expression and significance of the ABAT gene in hepatocellular carcinoma (HCC) using related databases. MethodsThe Oncomine database and GEPIA were used to analyze the expression of ABAT in HCC tissue. GEPIA was used to investigate the correlation of ABAT mRNA with the survival time and pathological stage of HCC patients. The MethHC database was used to analyze the methylation level of ABAT promoter region. The String database was used to analyze the network of proteins interacting with ABAT protein. The Human Protein Atlas was used to analyze the expression of ABAT protein in HCC tissue and the influence of the protein expression of ABAT on prognosis. ResultsThe mRNA expression of ABAT in HCC tissue was significantly lower than that in normal liver tissue; patients with lower mRNA expression tended to have a poorer prognosis (log-rank, P=0.002 1) and a higher degree of malignancy (P=0.002 34). The protein expression of ABAT in HCC tissue was significantly lower than that in normal liver tissue, and patients with lower protein expression tended to have a poorer prognosis (log-rank, P=2.14×10-3). The methylation level of ABAT promoter region in HCC tissue was significantly higher than that in normal liver tissue (P＜0.005). The proteins interacting with ABAT included ALDH1A3, ALDH9A1, ALDH3A2, GAD1, and GAD2, which might be involved in cell functions such as cell apoptosis, redox, and neurotransmitter secretion. ConclusionData mining of tumor gene databases shows that there are low levels of mRNA and protein expression of ABAT in HCC tissue, which is associated with patient’s survival time. At present, database mining can provide a reference for the diagnosis and prognosis evaluation of HCC and a theoretical basis for tumor research in the future.

Expression and significance of the ABAT gene in hepatocellular carcinoma: An analysis based on data mining / 临床肝胆病杂志

ObjectiveTo investigate the expression and significance of the ABAT gene in hepatocellular carcinoma (HCC) using related databases. MethodsThe Oncomine database and GEPIA were used to analyze the expression of ABAT in HCC tissue. GEPIA was used to investigate the correlation of ABAT mRNA with the survival time and pathological stage of HCC patients. The MethHC database was used to analyze the methylation level of ABAT promoter region. The String database was used to analyze the network of proteins interacting with ABAT protein. The Human Protein Atlas was used to analyze the expression of ABAT protein in HCC tissue and the influence of the protein expression of ABAT on prognosis. ResultsThe mRNA expression of ABAT in HCC tissue was significantly lower than that in normal liver tissue; patients with lower mRNA expression tended to have a poorer prognosis (log-rank, P=0.002 1) and a higher degree of malignancy (P=0.002 34). The protein expression of ABAT in HCC tissue was significantly lower than that in normal liver tissue, and patients with lower protein expression tended to have a poorer prognosis (log-rank, P=2.14×10-3). The methylation level of ABAT promoter region in HCC tissue was significantly higher than that in normal liver tissue (P＜0.005). The proteins interacting with ABAT included ALDH1A3, ALDH9A1, ALDH3A2, GAD1, and GAD2, which might be involved in cell functions such as cell apoptosis, redox, and neurotransmitter secretion. ConclusionData mining of tumor gene databases shows that there are low levels of mRNA and protein expression of ABAT in HCC tissue, which is associated with patient’s survival time. At present, database mining can provide a reference for the diagnosis and prognosis evaluation of HCC and a theoretical basis for tumor research in the future.

Methodological research on the application of AFLP in complicated samples / 中国基层医药

Objective To explore the application probability of AFLP method (Amplified Fragment Length Polymorphism) for the genetic study of complicated samples and to make clear the analytical approach on polymorphic fragments.Methods An AFLP fragement sequence,resolved between murines with high and low metastatic hepatocarcinoma,was retrieved from a reference paper and was annotated on NCBI database by different BLAST programs. Results The retrieved information varied along with the different BLAST programs, nevertheless BLASTX program provided more comprehensive information and showed that the differentiated fragment exhibited high homology with terminase large subunits from Burkholderia phage Bups phil and Mycobacterium tuberculosis H37Ra. However, there is no detailed information for the latter,key words search returned the relationship between terminase and the formation and metastasis of tumors and provided the further research clues. Conclusions Whole genome screening in parallel of AFLP markers between genetically differentiated paired materials would readily produce informatic fragments. Further analysis of the sequenced fragments by informatic methods would facilitate the subsequent research.