Effect of NDRG2 expression on Bax and Bcl-2 after OGD.

<p>The C6-originated astrocytes were transfected with pEGFP-C1 constructs expressing NDRG2 (NDRG2 vector), empty pEGFP-C1 (vector), NDRG2-specific siRNA (NDRG2 siRNA) or scramble siRNA before OGD. The levels of Bax and Bcl-2 were measured by Western-blotting at the time of 24 h after OGD exposure. (<b>A</b>) OGD induced a higher Bax expression, which could be further improved by NDRG2 over-expression. Neither NDRG2 over-expression nor OGD stimuli had effect on the Bcl-2 expression. (<b>B</b>) NDRG2 silencing with NDRG2-specific siRNA greatly suppressed the OGD-induced Bax uprising, and had no impact on the Bcl-2 expression. All data were presented as the mean ± SD of three independent experiments. ANOVA, *<i>P<0.05 vs</i>. normal.</p

The role of p53 in OGD-induced NDRG2 up-regulation.

<p>In differently transfected astrocytes, the NDRG2 expression was detected at the time of 24 h after OGD exposure by Western-blotting. (<b>A</b>) Compared to normal cells after OGD, the astrocytes transfected with either scramble siRNA of p53 or empty vector presented a similar uprising of NDRG2. Without an OGD stimulus, the NDRG2 up-regulation would not happen. (<b>B</b>) The p53 silencing obviously suppressed the up-regulation of NDRG2 after OGD, and its over-expression did not further improve the NDRG2 increase. All data were presented as the mean ± SD of three independent experiments. ANOVA, *<i>P</i><0.05 <i>vs</i>. normal.</p

NDRG2 expression in C6 glioma cells after OGD.

<p>(<b>A</b>) The C6 glioma cells were subjected to RPMI 1640 medium in the absence or presence of 100 ng/ml IL-6 for 24 hours to induce an astrocyte-like differentiation. The upper (Scale bar = 20 µm) and lower row (Scale bar = 10 µm) showed different magnifications. (<b>B</b>) The IL-6-differentiated cells were verified by GFAP and OX42 in Western-blotting analysis. GFAP expression sharply increased in the differentiated cells, while OX42 expression maintained hardly detected. So it was astrocytes that we employed in the following experiments. (<b>C, D</b>) Both NDRG2 mRNA (C) and protein (D) were up-regulated after OGD exposure in a time-dependent way. NDRG2 mRNA and protein began to increase at 2 h after OGD, then reached a peak at 24 h. All data were presented as the mean ± SD of three independent experiments. Student’s <i>t</i> test, *<i>P</i><0.05 <i>vs</i>. normal.</p

NDRG2 nuclear translocation after OGD exposure.

<p>(<b>A</b>) Immunofluorescent double-labeling staining of NDRG2 and GFAP showed the localization of NDRG2. NDRG2 is indicated in green, GFAP to mark the astroglial cytoplasm is indicated in red, and DAPI to mark the nucleus is indicated in blue. In normal astrocytes (upper row), NDRG2 expression overlapped with GFAP, but not with DAPI. In OGD-treated cells (lower row), NDRG2 expression overlapped with GFAP and DAPI simultaneously. Scale bar = 10 µm. (<b>B</b>) The NDRG2 expression in nucleus and cytoplasm extraction was measured with Western-blotting analysis. In normal astrocytes, NDRG2 could hardly be detected in nucleus. At the time of 24 h after OGD exposure, the NDRG2 expression both in the nucleus and in the cytoplasm sharply increased.</p

p53 down-regulation suppressed the OGD-induced cellular apoptosis.

<p>(<b>A</b>) In C6-originated astrocytes, p53 appeared a time-dependent uprising after OGD exposure, which started at the time of 2 h and then peaked at the time of 24 h after OGD. Student’s <i>t</i> test. (<b>B</b>) The over-expression and silencing systems of p53 were constructed and verified by Western-blotting. From left to right, the C6-originated astrocytes were kept normal (Normal), or transfected with the empty pEGFP-C1 vector (vector), the pEGFP-C1 vector expressing p53 (p53 vector), scramble siRNA (Scramble siRNA), and p53-specific siRNA (p53 siRNA) in order. (<b>C</b>) The effect of p53 on the OGD-induced apoptosis in astrocytes was evaluated by flow cytometry analysis. As presented in histogram, p53 silencing with p53 siRNA greatly reduced the percentage of apoptotic cells at the time of 24 h after OGD. All data were presented as the mean ± SD of three independent experiments. ANOVA, *<i>P</i><0.0<i>5 vs</i>. normal.</p

Effect of NDRG2 expression on cellular proliferation and apoptosis after OGD exposure.

<p>(<b>A</b>) TUNEL (green) and DAPI (blue) double-staining was used to test the apoptosis of C6-originated astrocytes at the time of 24 h after OGD. NDRG2 down-regulation with NDRG2-specfic siRNA greatly reduced the enhancement of TUNEL and DAPI signals after OGD. Scale bar = 10 µm. (<b>B</b>) The over-expression and silencing systems of NDRG2 were constructed and verified by Western-blotting. From left to right, the C6-originated astrocytes were kept normal (Normal), or transfected with the empty pEGFP-C1 vector (vector), the pEGFP-C1 vector expressing NDRG2 (NDRG2 vector), scramble siRNA (Scramble siRNA), and NDRG2-specific siRNA (NDRG2 siRNA) in order. (<b>C</b>) At the day 3, 4, 5, 6, 7 after OGD exposure, the astrocytes transfected with NDRG2-specific siRNA presented improved proliferation, compared with normal cells and those transfected with scramble siRNA. (<b>D</b>) At the day 3, 4, 5, 6, 7 after OGD exposure, the astrocytes with over-expressed NDRG2 presented restrained proliferation, compared with normal cells and those transfected with empty pEGFP-C1 vector. All data were presented as the mean ± SD of three independent experiments. ANOVA, *<i>P</i><0.05 <i>vs</i>. normal.</p

Presentation_1_Pan-Cancer Analysis Reveals the Functional Importance of Protein Lysine Modification in Cancer Development.PDF

<p>Large-scale tumor genome sequencing projects have revealed a complex landscape of genomic mutations in multiple cancer types. A major goal of these projects is to characterize somatic mutations and discover cancer drivers, thereby providing important clues to uncover diagnostic or therapeutic targets for clinical treatment. However, distinguishing only a few somatic mutations from the majority of passenger mutations is still a major challenge facing the biological community. Fortunately, combining other functional features with mutations to predict cancer driver genes is an effective approach to solve the above problem. Protein lysine modifications are an important functional feature that regulates the development of cancer. Therefore, in this work, we have systematically analyzed somatic mutations on seven protein lysine modifications and identified several important drivers that are responsible for tumorigenesis. From published literature, we first collected more than 100,000 lysine modification sites for analysis. Another 1 million non-synonymous single nucleotide variants (SNVs) were then downloaded from TCGA and mapped to our collected lysine modification sites. To identify driver proteins that significantly altered lysine modifications, we further developed a hierarchical Bayesian model and applied the Markov Chain Monte Carlo (MCMC) method for testing. Strikingly, the coding sequences of 473 proteins were found to carry a higher mutation rate in lysine modification sites compared to other background regions. Hypergeometric tests also revealed that these gene products were enriched in known cancer drivers. Functional analysis suggested that mutations within the lysine modification regions possessed higher evolutionary conservation and deleteriousness. Furthermore, pathway enrichment showed that mutations on lysine modification sites mainly affected cancer related processes, such as cell cycle and RNA transport. Moreover, clinical studies also suggested that the driver proteins were significantly associated with patient survival, implying an opportunity to use lysine modifications as molecular markers in cancer diagnosis or treatment. By searching within protein-protein interaction networks using a random walk with restart (RWR) algorithm, we further identified a series of potential treatment agents and therapeutic targets for cancer related to lysine modifications. Collectively, this study reveals the functional importance of lysine modifications in cancer development and may benefit the discovery of novel mechanisms for cancer treatment.</p

Table_3_Pan-Cancer Analysis Reveals the Functional Importance of Protein Lysine Modification in Cancer Development.XLSX

<p>Large-scale tumor genome sequencing projects have revealed a complex landscape of genomic mutations in multiple cancer types. A major goal of these projects is to characterize somatic mutations and discover cancer drivers, thereby providing important clues to uncover diagnostic or therapeutic targets for clinical treatment. However, distinguishing only a few somatic mutations from the majority of passenger mutations is still a major challenge facing the biological community. Fortunately, combining other functional features with mutations to predict cancer driver genes is an effective approach to solve the above problem. Protein lysine modifications are an important functional feature that regulates the development of cancer. Therefore, in this work, we have systematically analyzed somatic mutations on seven protein lysine modifications and identified several important drivers that are responsible for tumorigenesis. From published literature, we first collected more than 100,000 lysine modification sites for analysis. Another 1 million non-synonymous single nucleotide variants (SNVs) were then downloaded from TCGA and mapped to our collected lysine modification sites. To identify driver proteins that significantly altered lysine modifications, we further developed a hierarchical Bayesian model and applied the Markov Chain Monte Carlo (MCMC) method for testing. Strikingly, the coding sequences of 473 proteins were found to carry a higher mutation rate in lysine modification sites compared to other background regions. Hypergeometric tests also revealed that these gene products were enriched in known cancer drivers. Functional analysis suggested that mutations within the lysine modification regions possessed higher evolutionary conservation and deleteriousness. Furthermore, pathway enrichment showed that mutations on lysine modification sites mainly affected cancer related processes, such as cell cycle and RNA transport. Moreover, clinical studies also suggested that the driver proteins were significantly associated with patient survival, implying an opportunity to use lysine modifications as molecular markers in cancer diagnosis or treatment. By searching within protein-protein interaction networks using a random walk with restart (RWR) algorithm, we further identified a series of potential treatment agents and therapeutic targets for cancer related to lysine modifications. Collectively, this study reveals the functional importance of lysine modifications in cancer development and may benefit the discovery of novel mechanisms for cancer treatment.</p

Table_1_Pan-Cancer Analysis Reveals the Functional Importance of Protein Lysine Modification in Cancer Development.XLSX

<p>Large-scale tumor genome sequencing projects have revealed a complex landscape of genomic mutations in multiple cancer types. A major goal of these projects is to characterize somatic mutations and discover cancer drivers, thereby providing important clues to uncover diagnostic or therapeutic targets for clinical treatment. However, distinguishing only a few somatic mutations from the majority of passenger mutations is still a major challenge facing the biological community. Fortunately, combining other functional features with mutations to predict cancer driver genes is an effective approach to solve the above problem. Protein lysine modifications are an important functional feature that regulates the development of cancer. Therefore, in this work, we have systematically analyzed somatic mutations on seven protein lysine modifications and identified several important drivers that are responsible for tumorigenesis. From published literature, we first collected more than 100,000 lysine modification sites for analysis. Another 1 million non-synonymous single nucleotide variants (SNVs) were then downloaded from TCGA and mapped to our collected lysine modification sites. To identify driver proteins that significantly altered lysine modifications, we further developed a hierarchical Bayesian model and applied the Markov Chain Monte Carlo (MCMC) method for testing. Strikingly, the coding sequences of 473 proteins were found to carry a higher mutation rate in lysine modification sites compared to other background regions. Hypergeometric tests also revealed that these gene products were enriched in known cancer drivers. Functional analysis suggested that mutations within the lysine modification regions possessed higher evolutionary conservation and deleteriousness. Furthermore, pathway enrichment showed that mutations on lysine modification sites mainly affected cancer related processes, such as cell cycle and RNA transport. Moreover, clinical studies also suggested that the driver proteins were significantly associated with patient survival, implying an opportunity to use lysine modifications as molecular markers in cancer diagnosis or treatment. By searching within protein-protein interaction networks using a random walk with restart (RWR) algorithm, we further identified a series of potential treatment agents and therapeutic targets for cancer related to lysine modifications. Collectively, this study reveals the functional importance of lysine modifications in cancer development and may benefit the discovery of novel mechanisms for cancer treatment.</p

Table_2_Pan-Cancer Analysis Reveals the Functional Importance of Protein Lysine Modification in Cancer Development.XLSX

<p>Large-scale tumor genome sequencing projects have revealed a complex landscape of genomic mutations in multiple cancer types. A major goal of these projects is to characterize somatic mutations and discover cancer drivers, thereby providing important clues to uncover diagnostic or therapeutic targets for clinical treatment. However, distinguishing only a few somatic mutations from the majority of passenger mutations is still a major challenge facing the biological community. Fortunately, combining other functional features with mutations to predict cancer driver genes is an effective approach to solve the above problem. Protein lysine modifications are an important functional feature that regulates the development of cancer. Therefore, in this work, we have systematically analyzed somatic mutations on seven protein lysine modifications and identified several important drivers that are responsible for tumorigenesis. From published literature, we first collected more than 100,000 lysine modification sites for analysis. Another 1 million non-synonymous single nucleotide variants (SNVs) were then downloaded from TCGA and mapped to our collected lysine modification sites. To identify driver proteins that significantly altered lysine modifications, we further developed a hierarchical Bayesian model and applied the Markov Chain Monte Carlo (MCMC) method for testing. Strikingly, the coding sequences of 473 proteins were found to carry a higher mutation rate in lysine modification sites compared to other background regions. Hypergeometric tests also revealed that these gene products were enriched in known cancer drivers. Functional analysis suggested that mutations within the lysine modification regions possessed higher evolutionary conservation and deleteriousness. Furthermore, pathway enrichment showed that mutations on lysine modification sites mainly affected cancer related processes, such as cell cycle and RNA transport. Moreover, clinical studies also suggested that the driver proteins were significantly associated with patient survival, implying an opportunity to use lysine modifications as molecular markers in cancer diagnosis or treatment. By searching within protein-protein interaction networks using a random walk with restart (RWR) algorithm, we further identified a series of potential treatment agents and therapeutic targets for cancer related to lysine modifications. Collectively, this study reveals the functional importance of lysine modifications in cancer development and may benefit the discovery of novel mechanisms for cancer treatment.</p