1.Effects of downregulated ATP citrate lyase on the growth and apoptosis of prostate cancer cells
Hairui KONG ; Shen GENG ; Jie YANG ; Fangyin ZENG
Journal of Medical Postgraduates 2017;30(1):26-30
Objective Tumor cells are able to support their malignant proliferation by changing metabolic models .Prostate cells rely much on lipid metabolism in which ATP-citrate lyase ( ACLY) plays a very important role .The aim of this research was to study the effects of downregulated ACLY on the cell proliferation , cycle distribution and apoptosis of androgen-independent prostate cancer cells DUl45. Methods DU145 cells were divided into two groups:the cells in experiment group were transfected with the small interfering RNA-mediated knockdown of ACLY , while the cells in control group were transfected with meaningless small interfering RNA.Cell counting Kit test ( CCK-8 ) was applied to detect the effects of the downregulation of ATP citrate lyase on the proliferation of DU145.Flow cytometry instrument was used to analyze the variation of cell cycle distribution and apoptosis rate between groups .Western blot was used to detect the change of intracellular Caspase-3 protein content. Results Western blot showed favorable effects of ACLY interference .Compared with control group , ACLY protein content significantly decreased in experiment group ( P<0.05) ;the acetyl coenzyme A content and the percentage of early apoptosis cells and late apoptosis cells increased significantly [(0.42±1.99) vs (0.79±2.38), (37.10±3.28) vs (6.20±2.88), P<0.05].As to the selec-tive ACLY knockdown in DU145 cells, the proliferation ability in experiment group weakened in comparison with control group , which became more and more apparent as time went on .At 48h and 72h time points, the cell absorbance between two groups at the same time point was of significant difference (P<0.05).As to the interfering ACLY expression in DU145 cells, the percentage of G1 cells in-creased without any statistical significance (P>0.05), while the percentage of G2 cells decreased and the percentage of S cells in-creased with most cell cycle blocking at G 0/G1 stage, which were of significant difference .Meanwhile the expression of apoptosis pro-tein Caspase-3 upregulated significantly . Conclusion ACLY is of vital significance to maintain the malignant proliferation of prostate cancer cells and its downregulation results in the inhibition of cell proliferation and the promotion of cell apoptosis .
2.Urinary metabolomics study of renal cell carcinoma based on gas chromatography-mass spectrometry.
Lin ZHANG ; Ling LI ; Hairui KONG ; Fangyin ZENG
Journal of Southern Medical University 2015;35(5):763-766
OBJECTIVETo identify the biomarkers of renal cell cancer (RCC) through urine metabolic analysis.
METHODSUrine samples of 27 RCC patients, 26 patients with other urinary cancers and 26 healthy volunteers were examined with gas chromatography-mass spectrometry (GC-MS). SIMCA-P+12.0.1.0 software was used for principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) to screen for the differential metabolites.
RESULTSPCA (R2X=0.846, Q2=0.575) and OPLS-DA (R2X=0.736, R2Y=0.974, Q2Y=0.897) model were established for the RCC patients and control subjects. Fourteen metabolites were selected as the characteristic metabolites, including pentanoic acid, malonic acid, glutaric acid, adipic acid, amino quinoline, quinoline, indole acetic acid, and tryptophan, whose levels in the urine were significantly higher in the RCC patients than in the normal subjects (P<0.01); the RCC patients showed significantly higher urine contents of pentanoic acid, phenylalanine, and 6-methoxy-nitro quinoline than those with other urinary tumors (P<0.01).
CONCLUSIONThe urine metabolites identified based on GC-MS analysis can distinguish RCC patients from patients with other urinary cancers and healthy subjects, suggesting their potential as diagnostic markers for RCC.
Biomarkers ; urine ; Carcinoma, Renal Cell ; urine ; Discriminant Analysis ; Gas Chromatography-Mass Spectrometry ; Humans ; Least-Squares Analysis ; Metabolome ; Metabolomics ; Principal Component Analysis ; Software