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Comprehensive profiling of Epstein-Barr virus-encoded miRNA species associated with specific latency types in tumor cells.

Yang HJ, Huang TJ, Yang CF, Peng LX, Liu RY, Yang GD, Chu QQ, Huang JL, Liu N, Huang HB, Zhu ZY, Qian CN, Huang BJ - Virol. J. (2013)

Bottom Line: EBV expresses different genes that are associated with three latency types.Specifically, in nasopharyngeal carcinoma (NPC) tissues and the EBV-positive cell line C666-1, the miR-BART family accounted for more than 10% of all detected miRNAs, suggesting that these miRNAs have important roles in maintaining latent EBV infections and in driving NPC tumorigenesis.In addition, EBV miRNA-based clustering analysis clearly distinguished between the three distinct EBV latency types, and our results suggested that a switch from type I to type III latency might occur in the Daudi BL cell line.

View Article: PubMed Central - HTML - PubMed

Affiliation: State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China. qianchn@sysucc.org.cn.

ABSTRACT

Background: Epstein-Barr virus (EBV) is an etiological cause of many human lymphocytic and epithelial malignancies. EBV expresses different genes that are associated with three latency types. To date, as many as 44 EBV-encoded miRNA species have been found, but their comprehensive profiles in the three types of latent infection that are associated with various types of tumors are not well documented.

Methods: In the present study, we utilized poly (A)-tailed quantitative real-time RT-PCR in combination with microarray analysis to measure the relative abundances of viral miRNA species in a subset of representative lymphoid and epithelial tumor cells with various EBV latency types.

Results: Our findings showed that the miR-BHRF1 and miR-BART families were expressed differentially in a tissue- and latency type-dependent manner. Specifically, in nasopharyngeal carcinoma (NPC) tissues and the EBV-positive cell line C666-1, the miR-BART family accounted for more than 10% of all detected miRNAs, suggesting that these miRNAs have important roles in maintaining latent EBV infections and in driving NPC tumorigenesis. In addition, EBV miRNA-based clustering analysis clearly distinguished between the three distinct EBV latency types, and our results suggested that a switch from type I to type III latency might occur in the Daudi BL cell line.

Conclusions: Our data provide a comprehensive profiling of the EBV miRNA transcriptome that is associated with specific tumor cells in the three types of latent EBV infection states. EBV miRNA species represent a cluster of non-encoding latency biomarkers that are differentially expressed in tumor cells and may help to distinguish between the different latency types.

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Comprehensive and quantitative profiling of the EBV miRNA transcriptome in cells with the three latency types. (A) The comparable results from poly(A)-tailed, real-time RT-PCR analysis of the EBV-encoded miRNA transcriptome in the cell lines with latency I, II and III. The respective positions of the four clusters of EBV miRNAs (miR-BHRF1, miR-BART clusters I/II, miR-BART2 and the B95-8 deletion region) are marked below, and the numbers under the lines indicate the EBV genomic locations (nt). (B) Differential amplification curves of EBV miRNA species between epithelial and lymphoid tumor cells. The amplification curves of EBV miRNAs in C666-1 and Raji cells are separated distinctly into two parts: in epithelial C666-1 cells, the EBV BART family generally had lower Ct values than the BHRF1 family (left); and the opposite results were observed for the lymphoid Raji cells (right). (C) Verification of qPCR product specificity via DNA sequencing based on AT cloning. Representative DNA sequence results are shown for three, randomly selected qPCR products, the BHRF1 family member BHRF1-1 and two BART family members, Bart5 and Bart15. (D) An overview image from the microarray analysis of human miRNAs and EBV miRNAs in C666-1 cells (left). The right panel displays a subset of the hybridization signals for EBV miRNAs in the indicated region of the chips for tumor cell lines with various EBV latency types and including the EBV-negative cell line CNE2. (E) Correlation between the microarray read counts and the expression levels that were determined by real-time PCR of EBV miRNAs that were detected in cells with various latency types. The microarray and real-time PCR results were log2-transformed and analyzed using Person’s correlation analysis. Pearson’s correlation coefficients and p-values are shown in the inserts.
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Figure 3: Comprehensive and quantitative profiling of the EBV miRNA transcriptome in cells with the three latency types. (A) The comparable results from poly(A)-tailed, real-time RT-PCR analysis of the EBV-encoded miRNA transcriptome in the cell lines with latency I, II and III. The respective positions of the four clusters of EBV miRNAs (miR-BHRF1, miR-BART clusters I/II, miR-BART2 and the B95-8 deletion region) are marked below, and the numbers under the lines indicate the EBV genomic locations (nt). (B) Differential amplification curves of EBV miRNA species between epithelial and lymphoid tumor cells. The amplification curves of EBV miRNAs in C666-1 and Raji cells are separated distinctly into two parts: in epithelial C666-1 cells, the EBV BART family generally had lower Ct values than the BHRF1 family (left); and the opposite results were observed for the lymphoid Raji cells (right). (C) Verification of qPCR product specificity via DNA sequencing based on AT cloning. Representative DNA sequence results are shown for three, randomly selected qPCR products, the BHRF1 family member BHRF1-1 and two BART family members, Bart5 and Bart15. (D) An overview image from the microarray analysis of human miRNAs and EBV miRNAs in C666-1 cells (left). The right panel displays a subset of the hybridization signals for EBV miRNAs in the indicated region of the chips for tumor cell lines with various EBV latency types and including the EBV-negative cell line CNE2. (E) Correlation between the microarray read counts and the expression levels that were determined by real-time PCR of EBV miRNAs that were detected in cells with various latency types. The microarray and real-time PCR results were log2-transformed and analyzed using Person’s correlation analysis. Pearson’s correlation coefficients and p-values are shown in the inserts.

Mentions: In our investigation, we mainly used real-time RT-PCR to gain insight into the comparable profiles of the EBV miRNA transcriptomes of the three latency types. To confirm the specificity of the PCR products and verify the reliability of this poly(A)-tailed, real-time qPCR method, we randomly sequenced three qPCR products, submitted them to AT cloning procedures, and the results of DNA sequencing are shown in Figure 3C. Following qPCR analysis, we further evaluated the expression levels of EBV miRNAs using a microarray assay, and the scanning images are shown in Figure 3D. In addition, correlation analysis showed statistically significant correlations between the two methods for the latency I (Akata(+) cells; Pearson’s correlation coefficient = 0.51, p = 0.0004), latency II (C666-1 cells; Pearson’s correlation coefficient = 0.73, p < 0.0001) and latency III profiles (Raji cells; Pearson’s correlation coefficient = 0.47, p = 0.0024) (Figure 3E).


Comprehensive profiling of Epstein-Barr virus-encoded miRNA species associated with specific latency types in tumor cells.

Yang HJ, Huang TJ, Yang CF, Peng LX, Liu RY, Yang GD, Chu QQ, Huang JL, Liu N, Huang HB, Zhu ZY, Qian CN, Huang BJ - Virol. J. (2013)

Comprehensive and quantitative profiling of the EBV miRNA transcriptome in cells with the three latency types. (A) The comparable results from poly(A)-tailed, real-time RT-PCR analysis of the EBV-encoded miRNA transcriptome in the cell lines with latency I, II and III. The respective positions of the four clusters of EBV miRNAs (miR-BHRF1, miR-BART clusters I/II, miR-BART2 and the B95-8 deletion region) are marked below, and the numbers under the lines indicate the EBV genomic locations (nt). (B) Differential amplification curves of EBV miRNA species between epithelial and lymphoid tumor cells. The amplification curves of EBV miRNAs in C666-1 and Raji cells are separated distinctly into two parts: in epithelial C666-1 cells, the EBV BART family generally had lower Ct values than the BHRF1 family (left); and the opposite results were observed for the lymphoid Raji cells (right). (C) Verification of qPCR product specificity via DNA sequencing based on AT cloning. Representative DNA sequence results are shown for three, randomly selected qPCR products, the BHRF1 family member BHRF1-1 and two BART family members, Bart5 and Bart15. (D) An overview image from the microarray analysis of human miRNAs and EBV miRNAs in C666-1 cells (left). The right panel displays a subset of the hybridization signals for EBV miRNAs in the indicated region of the chips for tumor cell lines with various EBV latency types and including the EBV-negative cell line CNE2. (E) Correlation between the microarray read counts and the expression levels that were determined by real-time PCR of EBV miRNAs that were detected in cells with various latency types. The microarray and real-time PCR results were log2-transformed and analyzed using Person’s correlation analysis. Pearson’s correlation coefficients and p-values are shown in the inserts.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4231337&req=5

Figure 3: Comprehensive and quantitative profiling of the EBV miRNA transcriptome in cells with the three latency types. (A) The comparable results from poly(A)-tailed, real-time RT-PCR analysis of the EBV-encoded miRNA transcriptome in the cell lines with latency I, II and III. The respective positions of the four clusters of EBV miRNAs (miR-BHRF1, miR-BART clusters I/II, miR-BART2 and the B95-8 deletion region) are marked below, and the numbers under the lines indicate the EBV genomic locations (nt). (B) Differential amplification curves of EBV miRNA species between epithelial and lymphoid tumor cells. The amplification curves of EBV miRNAs in C666-1 and Raji cells are separated distinctly into two parts: in epithelial C666-1 cells, the EBV BART family generally had lower Ct values than the BHRF1 family (left); and the opposite results were observed for the lymphoid Raji cells (right). (C) Verification of qPCR product specificity via DNA sequencing based on AT cloning. Representative DNA sequence results are shown for three, randomly selected qPCR products, the BHRF1 family member BHRF1-1 and two BART family members, Bart5 and Bart15. (D) An overview image from the microarray analysis of human miRNAs and EBV miRNAs in C666-1 cells (left). The right panel displays a subset of the hybridization signals for EBV miRNAs in the indicated region of the chips for tumor cell lines with various EBV latency types and including the EBV-negative cell line CNE2. (E) Correlation between the microarray read counts and the expression levels that were determined by real-time PCR of EBV miRNAs that were detected in cells with various latency types. The microarray and real-time PCR results were log2-transformed and analyzed using Person’s correlation analysis. Pearson’s correlation coefficients and p-values are shown in the inserts.
Mentions: In our investigation, we mainly used real-time RT-PCR to gain insight into the comparable profiles of the EBV miRNA transcriptomes of the three latency types. To confirm the specificity of the PCR products and verify the reliability of this poly(A)-tailed, real-time qPCR method, we randomly sequenced three qPCR products, submitted them to AT cloning procedures, and the results of DNA sequencing are shown in Figure 3C. Following qPCR analysis, we further evaluated the expression levels of EBV miRNAs using a microarray assay, and the scanning images are shown in Figure 3D. In addition, correlation analysis showed statistically significant correlations between the two methods for the latency I (Akata(+) cells; Pearson’s correlation coefficient = 0.51, p = 0.0004), latency II (C666-1 cells; Pearson’s correlation coefficient = 0.73, p < 0.0001) and latency III profiles (Raji cells; Pearson’s correlation coefficient = 0.47, p = 0.0024) (Figure 3E).

Bottom Line: EBV expresses different genes that are associated with three latency types.Specifically, in nasopharyngeal carcinoma (NPC) tissues and the EBV-positive cell line C666-1, the miR-BART family accounted for more than 10% of all detected miRNAs, suggesting that these miRNAs have important roles in maintaining latent EBV infections and in driving NPC tumorigenesis.In addition, EBV miRNA-based clustering analysis clearly distinguished between the three distinct EBV latency types, and our results suggested that a switch from type I to type III latency might occur in the Daudi BL cell line.

View Article: PubMed Central - HTML - PubMed

Affiliation: State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China. qianchn@sysucc.org.cn.

ABSTRACT

Background: Epstein-Barr virus (EBV) is an etiological cause of many human lymphocytic and epithelial malignancies. EBV expresses different genes that are associated with three latency types. To date, as many as 44 EBV-encoded miRNA species have been found, but their comprehensive profiles in the three types of latent infection that are associated with various types of tumors are not well documented.

Methods: In the present study, we utilized poly (A)-tailed quantitative real-time RT-PCR in combination with microarray analysis to measure the relative abundances of viral miRNA species in a subset of representative lymphoid and epithelial tumor cells with various EBV latency types.

Results: Our findings showed that the miR-BHRF1 and miR-BART families were expressed differentially in a tissue- and latency type-dependent manner. Specifically, in nasopharyngeal carcinoma (NPC) tissues and the EBV-positive cell line C666-1, the miR-BART family accounted for more than 10% of all detected miRNAs, suggesting that these miRNAs have important roles in maintaining latent EBV infections and in driving NPC tumorigenesis. In addition, EBV miRNA-based clustering analysis clearly distinguished between the three distinct EBV latency types, and our results suggested that a switch from type I to type III latency might occur in the Daudi BL cell line.

Conclusions: Our data provide a comprehensive profiling of the EBV miRNA transcriptome that is associated with specific tumor cells in the three types of latent EBV infection states. EBV miRNA species represent a cluster of non-encoding latency biomarkers that are differentially expressed in tumor cells and may help to distinguish between the different latency types.

Show MeSH
Related in: MedlinePlus