Biomedical subjects

Suxing Liu

Publications and source records attributed to Suxing Liu.

12 recordsLinked to original sources

PubMed2006

In search of p53 target genes for the therapeutic manipulation of cancer.

As a tumor suppressor protein, p53 plays a crucial role in cancer development. Direct associations between p53, apoptosis and drug response suggest that targeting genes/gene products downstream of p53 may have clinical benefits. The completion of the human genome project and the availability of microarray technology have led to new ways in which to define the global regulatory network of p53 and to search for oncogenes in the p53 pathway. A crucial step toward antitumor drug discovery is the mapping of p53 transcriptomes onto cancer phenomes. In this review, recent developments in the genome-wide search of p53 target genes are discussed, along with current efforts in high-throughput antitumor target discovery in the p53 pathway and recent progress in the pharmacological modulation of targets downstream of p53 for effective cancer therapy.

Animals↗

PubMed2005

RNA interference targeting of A1 receptor-overexpressing breast carcinoma cells leads to diminished rates of cell proliferation and induction of apoptosis.

To determine if A1 adenosine receptors mediate breast tumorigenesis, we evaluated A1 receptor expression in human tumor cell lines and human primary breast tumor tissues using both quantitative RT-PCR and Western blot analysis. A1 receptor mRNA expression is upregulated in all breast tumor cell lines examined (n=7) compared to normal mammary epithelial cells/cell lines (n=3) as determined by quantitative RT-PCR analysis. Western blot analysis indicates that protein expression of A1 adenosine receptor is higher in 15 (62.5%) of 24 human primary breast tumor tissues than in matched normal breast tissue. To explore its cellular function, the A1 adenosine receptor was depleted by small interfering RNA (siRNA) in MDA-MB-468 human breast tumor cells. Depletion of A1 receptors in MDA-MB-468 breast tumor cells attenuated both cell growth and cell proliferation as measured by cell number counts and [(14)C]-thymidine incorporation, respectively. Cell cycle analysis indicated that depletion of A1 receptors by siRNA impairs G(1) checkpoint, leading to marked accumulation of cells in G(2)/M phase, in agreement with the inhibitory effect on cell proliferation. Further supporting this finding, synchronization studies of Hela cells in various cell cycle phases suggest that A1 receptor expression is suppressed in G(2)/M cells and depletion of A1 receptor expression by siRNA produced differential expression of several key cell cycle regulators, i.e., accumulation of the cyclin-dependent kinase inhibitor p27 with concomitant reduction of CDK4 and cyclin E proteins. In addition to the impact on cell cycle progression, depletion of A1 receptors by siRNA results in substantial cell death and apoptosis as determined by FACS analysis and annexin V staining method. Together these findings suggest that the A1 adenosine receptor may contribute to tumor cell growth and survival in breast tumor cells.

Apoptosis↗

PubMed2005

Integrative genomics revealed RAI3 is a cell growth-promoting gene and a novel P53 transcriptional target.

In this study, differential gene expression between normal human mammary epithelial cells and their malignant counterparts (eight well established breast cancer cell lines) was studied using Incyte GeneAlbum 1-6, which contains 65,873 cDNA clones representing 33,515 individual genes. 3,152 cDNAs showed a > or =3.0-fold expression level change in at least one of the human breast cancer cell lines as compared with normal human mammary epithelial cells. Integration of breast tumor gene expression data with the genes in the tumor suppressor p53 signaling pathway yielded 128 genes whose expression is altered in breast tumor cell lines and in response to p53 expression. A hierarchical cluster analysis of the 128 genes revealed that a significant portion of genes demonstrate an opposing expression pattern, i.e. p53-activated genes are down-regulated in the breast tumor lines, whereas p53-repressed genes are up-regulated. Most of these genes are involved in cell cycle regulation and/or apoptosis, consistent with the tumor suppressor function of p53. Follow-up studies on one gene, RAI3, suggested that p53 interacts with the promoter of RAI3 and repressed its expression at the onset of apoptosis. The expression of RAI3 is elevated in most tumor cell lines expressing mutant p53, whereas RAI3 mRNA is relatively repressed in the tumor cell lines expressing wild-type p53. Furthermore, ectopic expression of RAI3 in 293 cells promotes anchorage-independent growth and small interfering RNA-mediated depletion of RAI3 in AsPc-1 pancreatic tumor cells induces cell morphological change. Taken together, these data suggest a role for RAI3 in tumor growth and demonstrate the predictive power of integrative genomics.

Agar↗

PubMed2004

Generation of p53 target database via integration of microarray and global p53 DNA-binding site analysis.

The completion of the human genome sequence and availability of cDNA microarray technology provide new approaches to explore global cellular regulatory mechanisms. Here we present a strategy to identify genes regulated by specific transcription factors in the human genome, and apply it to p53. We first collected promoters or introns of all genes available using two methods: GenBank annotation and a computationally derived transcript map. The "FindPatterns" program is then used to search sequences in regulatory regions that match the p53 DNA-binding consensus sequence, resulting in the p53 Target Database. This database collects human genes that have at least one p53 DNA-binding sequence in their regulatory region. cDNA microarray was also used to identify genes that respond to p53 at a genomic scale. Integration of the microarray data and the p53 Target Database should greatly enrich direct p53 target genes. Taqman analysis and quantitative chromatin immunoprecipitation analysis are used to validate the in silico prediction and microarray data. Enrichment factor analysis is used to demonstrate that in silico prediction greatly enriches for genes that are transcriptionally regulated by p53 and assists us to identify other signaling pathways that are potentially connected to p53. The approaches can be extended to other transcription factors. The methods shown here illustrate a novel approach to the analysis of global gene regulatory networks through the integration of human genomic sequence information and genome-wide gene expression analysis.

Binding Sites↗

PubMed2003

Global transcriptional program of p53 target genes during the process of apoptosis and cell cycle progression.

The temporal gene expression profile during the entire process of apoptosis and cell cycle progression in response to p53 in human ovarian cancer cells was explored with cDNA microarrays representing 33 615 individual human genes. A total of 1501 genes (4.4%) were found to respond to p53 (approximately 80% of these were repressed by p53) using 2.5-fold change as a cutoff. It was anticipated that most of p53 responsive genes resulted from the secondary effect of p53 expression at late stage of apoptosis. To delineate potential p53 direct and indirect target genes during the process of apoptosis and cell cycle progression, microarray data were combined with global p53 DNA-binding site analysis. Here we showed that 361 out of 1501 p53 responsive genes contained p53 consensus DNA-binding sequence(s) in their regulatory region, approximately 80% of which were repressed by p53. This is the first time that a large number of p53-repressed genes have been identified to contain p53 consensus DNA-binding sequence(s) in their regulatory region. Hierarchical cluster analysis of these genes revealed distinct temporal expression patterns of transcriptional activation and repression by p53. More genes were activated at early time points, while more repressed genes were found after the onset of apoptosis. A small-scale quantitative chromatin immunoprecipitation analysis indicated that in vivo p53-DNA interaction was detected in eight out of 10 genes, most of which were repressed by p53 at the early onset of apoptosis, suggesting that a portion of p53 target genes in the human genome could be negatively regulated by p53 via sequence-specific DNA binding. The approaches and genes described here should aid the understanding of global gene regulatory network of p53.

Adenoviridae↗

PubMed2003

Genomic targets of the human c-Myc protein.

The transcription factor Myc is induced by mitogenic signals and regulates downstream cellular responses. If overexpressed, Myc promotes malignant transformation. Myc modulates expression of diverse genes in experimental systems, but few are proven direct targets. Here, we present a large-scale screen for genomic Myc-binding sites in live human cells. We used bioinformatics to select consensus DNA elements (CACGTG or E-boxes) situated in the 5' regulatory region of genes and measured Myc binding to those sequences in vivo by quantitative chromatin immunoprecipitation. Strikingly, most promoter-associated E-boxes showed selective recovery with Myc, unlike non-E-box promoters or E-boxes in bulk genomic DNA. Promoter E-boxes were distributed in two groups bound by Myc at distinct frequencies. The high-affinity group included an estimated 11% of all cellular loci, was highly conserved among different cells, and was bound independently of Myc expression levels. Overexpressed Myc associated at increased frequency with low-affinity targets and, at extreme levels, also with other sequences, suggesting that some binding was not sequence-specific. The strongest DNA-sequence parameter defining high-affinity targets was the location of E-boxes within CpG islands, correlating with an open, preacetylated state of chromatin. Myc further enhanced histone acetylation, with or without accompanying induction of mRNA expression. Our findings point to a high regulatory and biological diversity among Myc-target genes.

Cell Line↗

PubMed2003

Differential effects of cell cycle regulatory protein p21(WAF1/Cip1) on apoptosis and sensitivity to cancer chemotherapy.

p21(WAF1/Cip1) was initially identified as a cell cycle regulatory protein that can cause cell cycle arrest. It is induced by both p53-dependent and p53-independent mechanisms. This mini-review briefly discusses its currently known functions in apoptosis and drug sensitivity. As an inhibitor of cell proliferation, p21(WAF1/Cip1) plays an important role in drug-induced tumor suppression. Nevertheless, a number of recent studies have shown that p21(WAF1/Cip1) can assume both pro- or anti-apoptotic functions in response to anti-tumor agents depending on cell type and cellular context. This dual role of p21(WAF1/Cip1) in cancer cells complicates using p21(WAF1/Cip1) status to predict response to anti-tumor agents. However, it is possible to develop p21(WAF1/Cip1)-targeted reagents or p21(WAF1/Cip1) gene transfer techniques to have a beneficial effect within a well-defined therapeutic context. Better understanding of the roles of p21(WAF1/Cip1) in tumors should enable a more rational approach to anti-tumor drug design and therapy.

Antineoplastic Agents↗

PubMed2002

A reference database for tumor-related genes co-expressed with interleukin-8 using genome-scale in silico analysis.

BACKGROUND: The EST database provides a rich resource for gene discovery and in silico expression analysis. We report a novel computational approach to identify co-expressed genes using EST database, and its application to IL-8. RESULTS: IL-8 is represented in 53 dbEST cDNA libraries. We calculated the frequency of occurrence of all the genes represented in these cDNA libraries, and ranked the candidates based on a Z-score. Additional analysis suggests that most IL-8 related genes are differentially expressed between non-tumor and tumor tissues. To focus on IL-8's function in tumor tissues, we further analyzed and ranked the genes in 16 IL-8 related tumor libraries. CONCLUSIONS: This method generated a reference database for genes co-expressed with IL-8 and could facilitate further characterization of functional association among genes.

Journal Article↗

PubMed2002

Transcriptional regulation during p21WAF1/CIP1-induced apoptosis in human ovarian cancer cells.

In this study we used adenovirus vector-mediated transduction of either the p53 gene (rAd-p53) or the p21(WAF1/CIP1) gene (rAd-p21) to mimic both p53-dependent and -independent up-regulation of p21(WAF1/CIP1) within a human ovarian cancer cell line, 2774, and the derivative cell lines, 2774qw1 and 2774qw2. We observed that rAd-p53 can induce apoptosis in both 2774 and 2774qw1 cells but not in 2774qw2 cells. Surprisingly, overexpression of p21(WAF1/CIP1) also triggered apoptosis within these two cell lines. Quantitative reverse transcription-PCR analysis revealed that the differential expression of BAX, BCL2, and caspase 3 genes, specific in rAd-p53-induced apoptotic cells, was not altered in rAd-p21-induced apoptotic cells, suggesting p21(WAF1/CIP1)-induced apoptosis through a pathway distinguishable from p53-induced apoptosis. Expression analysis of 2774qw1 cells infected with rAd-p21 on 60,000 cDNA microarrays identified 159 genes in response to p21(WAF1/CIP1) expression in at least one time point with 2.5-fold change as a cutoff. Integration of the data with the parallel microarray experiments with rAd-p53 infection allowed us to extract 66 genes downstream of both p53 and p21(WAF1/CIP1) and 93 genes in response to p21(WAF1/CIP1) expression in a p53-independent pathway. The genes in the former set may play a dual role in both p53-dependent and p53-independent pathways, and the genes in the latter set gave a mechanistic molecular explanation for p53-independent p21(WAF1/CIP1)-induced apoptosis. Furthermore, promoter sequence analysis suggested that transcription factor E2F family is partially responsible for the differential expression of genes following p21(WAF1/CIP1). This study has profound significance toward understanding the role of p21(WAF1/CIP1) in p53-independent apoptosis.

Adenoviridae↗

PubMed2002

Transforming growth factor-beta 2 is a transcriptional target for Akt/protein kinase B via forkhead transcription factor.

Tumors evade cell death by constitutively activating cell survival pathways and suppressing intrinsic death machinery. Activation of cell survival pathways leads to transcriptional repression of genes associated with cell death and activation of ones promoting anti-apoptosis. Akt/protein kinase B phosphorylates forkhead transcription factors and prevents their nuclear localization, leading to repression of genes involved in apoptosis, such as Fas ligand (FasL). Using bioinformatic approaches, we have identified three consensus sequences for forkhead transcription factor binding in transforming growth factor beta2 (TGF-beta2) promoter. TGF-beta inhibits cell proliferation and induces apoptosis in many cell types, and acquisition of TGF-beta resistance is linked to tumorigenesis. In this study, we show that activated Akt down-regulates TGF-beta2 promoter, and sequences within the promoter that are related to consensus forkhead binding sites are necessary for repression. Forkhead factor FKHRL1 binds in vitro to the three consensus sequences and can activate TGF-beta2 promoter in normal and Akt-transformed cell lines. In human breast and pancreatic tumors, activated Akt expression correlated with down-regulation of TGF-beta 2 mRNA levels. A number of tumor cells expressing activated Akt were responsive to TGF-beta addition, indicating the presence of an intact TGF-beta-signaling pathway. These results suggest that repression of TGF-beta 2 promoter activity in cells expressing activated Akt may play a role in promoting tumorigenesis and escape from the growth-inhibitory and/or apoptotic effects of TGF-beta.

Base Sequence↗

PubMed2002

Human survivin is negatively regulated by wild-type p53 and participates in p53-dependent apoptotic pathway.

Survivin is an inhibitor of apoptosis protein, which is over-expressed in most tumors. Aberrant expression of survivin and loss of wild-type p53 in many tumors prompted us to investigate a possible link between these two events. Here we show that wild-type p53 represses survivin expression at both mRNA and protein levels. Transient transfection analyses revealed that the expression of wild-type p53, but not mutant p53, was associated with strong repression of the survivin promoter in various cell types. The over-expression of exogenous survivin protein rescues cells from p53-induced apoptosis in a dose-dependent manner, suggesting that loss of survivin mediates, at least, in part the p53-dependent apoptotic pathway. In spite of the presence of two putative p53-binding sites in the survivin promoter, deletion and mutation analyses suggested that neither site is required for transcriptional repression of survivin expression. This was confirmed by chromatin immunoprecipitation assays. Further analyses suggested that the modification of chromatin within the survivin promoter could be a molecular explanation for silencing of survivin gene transcription by p53.

Adenoviridae↗

PubMed2002

Analysis of a human brain transcriptome map.

BACKGROUND: Genome wide transcriptome maps can provide tools to identify candidate genes that are over-expressed or silenced in certain disease tissue and increase our understanding of the structure and organization of the genome. Expressed Sequence Tags (ESTs) from the public dbEST and proprietary Incyte LifeSeq databases were used to derive a transcript map in conjunction with the working draft assembly of the human genome sequence. RESULTS: Examination of ESTs derived from brain tissues (excluding brain tumor tissues) suggests that these genes are distributed on chromosomes in a non-random fashion. Some regions on the genome are dense with brain-enriched genes while some regions lack brain-enriched genes, suggesting a significant correlation between distribution of genes along the chromosome and tissue type. ESTs from brain tumor tissues have also been mapped to the human genome working draft. We reveal that some regions enriched in brain genes show a significant decrease in gene expression in brain tumors, and, conversely that some regions lacking in brain genes show an increased level of gene expression in brain tumors. CONCLUSIONS: This report demonstrates a novel approach for tissue specific transcriptome mapping using EST-based quantitative assessment.

Journal Article↗