Analysis of global changes in gene expression induced by human polynucleotide phosphorylase (hPNPase(old-35))

Abstract

As a strategy to identify gene expression changes affected by human polynucleotide phosphorylase (hPNPase(old-35)), we performed gene expression analysis of HeLa cells in which hPNPase(old-35) was overexpressed. The observed changes were then compared to those of HO-1 melanoma cells in which hPNPase(old-35) was stably knocked down. Through this analysis, 90 transcripts, which positively or negatively correlated with hPNPase(old-35) expression, were identified. The majority of these genes were associated with cell communication, cell cycle, and chromosomal organization gene ontology categories. For a number of these genes, the positive or negative correlations with hPNPase(old-35) expression were consistent with transcriptional data extracted from the TCGA (The Cancer Genome Atlas) expression datasets for colon adenocarcinoma (COAD), skin cutaneous melanoma (SKCM), ovarian serous cyst adenocarcinoma (OV), and prostate adenocarcinoma (PRAD). Further analysis comparing the gene expression changes between Ad.hPNPase(old-35) infected HO-1 melanoma cells and HeLa cells overexpressing hPNPase(old-35) under the control of a doxycycline-inducible promoter, revealed global changes in genes involved in cell cycle and mitosis. Overall, this study provides further evidence that hPNPase(old-35) is associated with global changes in cell cycle-associated genes and identifies potential gene targets for future investigation.

Figure 1. Comparison of hPNPase^old-35-induced changes in gene expression in HO-1 and HeLa cells

Hierarchical clustering of hPNPase^old-35 positively (A) and negatively (B) correlating genes as identified by microarray analysis. Each column represents a single biological replicate and each row corresponds to a gene, with red and green representing high and low expression levels, respectively.

Figure 2. Gene Ontology (GO) terms for PNPase responsive genes

GO analysis corresponding to Biological process (A), Molecular function (B) and PANTHER Protein class (C) represented as pie charts generated by PANTHER classification system (http://www.pantherdb.org/).

Figure 3. Real-time PCR validation of genes identified by microarray analysis

(A) hPNPase^old-35–stable knockdown HO-1cells, (B) hPNPase^old-35–stable knockdown WM35 cells, (C) HeLa cells transiently transfected with siRNA against hPNPase^old-35 and (D) HO-1 cells transfected with pcDNA3.1-hPNPase^old-35. Error bars represent mean ± S.E. of three independent experiments done in triplicate. Statistical significance was determined by a one-way analysis of variance followed by Dunnett’s multiple comparison test and a two-tailed student’s t-test, *P<0.05, **P<0.01, ***P<0.001.

Figure 4. Real-time PCR validation of genes identified by microarray analysis following Ad.hPNPase^old-35 –mediated overexpression

Error bars represent mean ± S.E. of three (4A, B, C) or two (4D) independent experiments done in triplicate. Statistical significance was determined by two-tailed student’s t-test, *P<0.05, **P<0.01.

Figure 5. Heat maps representing correlations of hPNPase^old-35 responsive genes with hPNPase^old-35 in different tumor types identified using TCGA datasets

Shown are the hPNPase^old-35 positively (A) and negatively (B) correlating genes in (i) colon adenocarcinoma (COAD), (ii) ovarian serous cyst adenocarcinoma (OV), (iii) prostate adenocarcinoma (PRAD), and (iv) skin cutaneous melanoma (SKCM), respectively. The samples are subdivided into solid normal (N) and primary tumor (T) groups, and arranged (top to bottom) in order of increasing (low=green to high=red) expression of PNPT1.

Figure 6

Genes differentially regulated in response to hPNPase^old-35 overexpression as identified by microarray analysis in HO-1 melanoma and HeLa cells.