1.Influence of hepatocyte cell adhesion molecule on gene expression profile of human bladder transitional cell carcinoma cell line.
Qiu-ju WANG ; Chang-kun LV ; Jia TAO ; Hong-fei DU ; Yan-ru FAN ; Xue-dong SONG ; Chun-li LUO
Acta Academiae Medicinae Sinicae 2013;35(2):190-198
OBJECTIVETo investigate the changes of gene expression file in transitional cell carcinoma of bladder after hepatocyte cell adhesion molecule(hepaCAM) overexpression.
METHODSAffymetrix Human Genome U133 Plus 2.0 Array was used to investigate the changes of gene expression profile between adenovirus-green fluorescent protein(GFP) -hepaCAM group and GFP group in transitional cell carcinoma of bladder EJ cells.Significant Analysis of Microarray(SAM) was used to screen the differentially expressed genes, DAVID software was used to conduct gene ontology analysis and wikiPathway analysis based on the differentially expressed genes. Reverse transcription-polymerase chain reaction and Western blot were applied to verify microarray data.
RESULTSCompared with the GFP group, a total of 2469 genes were up-regulated or down-regulated by more than 2 times in the GFP-hepaCAM group. Among these genes, 1602 genes were up-regulated and 867 were down-regulated.Most of the differentially expressed genes were involved in the function of cell proliferation and cell cycle regulation. The mRNA expressions of nibrin, liver kinase B1, and cyclin D1 detected by reverse transcription-polymerase chain reaction in three different bladder cancer cell lines were consistent with the microarray data.The protein expressions of nibrin and liver kinase B1 in these three cell lines measured by Western blot were consistent with the mRNA expression.
CONCLUSIONSHepaCAM can alter the gene expression profile of bladder cancer EJ cells. The well-known anti-tumor effect of hepaCAM may be mediated by regulating the gene expression via multiple pathways.
Carcinoma, Transitional Cell ; genetics ; pathology ; Cell Cycle Proteins ; metabolism ; Cell Line, Tumor ; Cyclin D1 ; metabolism ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Genes, Tumor Suppressor ; physiology ; Humans ; Nuclear Proteins ; metabolism ; Protein-Serine-Threonine Kinases ; metabolism ; Proteins ; genetics ; physiology ; Urinary Bladder Neoplasms ; genetics ; pathology
2.Investigation of PRAM1 Expression Features and Their Clinical Significance in AML via Gene Expression Microarray Database.
Na LV ; Kun QIAN ; Jing LIU ; Li-Li WANG ; Yong-Hui LI ; Li YU
Journal of Experimental Hematology 2018;26(2):368-374
OBJECTIVETo study the clinical phenotype and its prognostic value of PRAM1 in patients with acute myeloid leukemia(AML).
METHODSBased on the gene expression microarray platform of 486 AML cases, the PRAM1 expression phenotypes were summarized in all of AML subtypes. The PRAM1 expression features were explored in every differentiation stage of hematocytes through normal human stem cell chips and bone marrow gene expression microarray. The clinical drugs which could up-regulate PRAM1 expression in AML cell lines should be found out.
RESULTSThe PRAM1 expression was the richest in the inv(16) AML and the lowest in the t(15;17)M3, almost the same in the other subtypes of AML. By the classification of molecular abnormalities, PRAM1 expression was more in the panel of CN-AML with CEBPAdm than the other two panels. Interestingly, high/low expression of PRAM1 could be re-classified in the CN-AML, and the EFS is statistically significant. It was proven again that PRAM1 is more expressed in the mature granulocytes. Finally, it was confirmed that decitabine and the chidamide could up-regulate PRAM1 expression in AML cell lines, and chidamide effect is better.
CONCLUSIONPRAM1 expression is the lowest in t(15;17) M3 and the highest in inv(16) AML. The high expression of PRAM1 is a sign for favorable prognosis in the CN-AML. PRAM1 is more expressed in mature granulocytes, chidamide can up-regulate PRAM1 expression in AML cell lines.
Adaptor Proteins, Signal Transducing ; Bone Marrow ; Gene Expression ; Humans ; Leukemia, Myeloid, Acute ; Microarray Analysis ; Prognosis