Transcription profiling of lung adenocarcinomas of c-myc-transgenic mice: Identification of the c-myc regulatory gene network

1752-0509-2-46 1752-0509 Research article Transcription profiling of lung adenocarcinomas of c-myc-transgenic mice: Identification of the c-myc regulatory gene network Reymann Susanne reymann@item.fraunhofer.de Borlak Jürgen borlak@item.fraunhofer.de

Fraunhofer Institute of Toxicology and Experimental Medicine (Fh-ITEM), Center for Drug Research and Medical Biotechnology, Nikolai-Fuchs-Str. 1, 30625 Hannover, Germany

Center of Pharmacology and Toxicology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625 Hannover, Germany

BMC Systems Biology 1752-0509 2008 2 1 46 http://www.biomedcentral.com/1752-0509/2/46 18498649 10.1186/1752-0509-2-46 15 1 2008 22 5 2008 22 5 2008 2008 Reymann and Borlak; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

The transcriptional regulator c-Myc is the most frequently deregulated oncogene in human tumors. Targeted overexpression of this gene in mice results in distinct types of lung adenocarcinomas. By using microarray technology, alterations in the expression of genes were captured based on a female transgenic mouse model in which, indeed, c-Myc overexpression in alveolar epithelium results in the development of bronchiolo-alveolar carcinoma (BAC) and papillary adenocarcinoma (PLAC). In this study, we analyzed exclusively the promoters of induced genes by different in silico methods in order to elucidate the c-Myc transcriptional regulatory network.

Results

We analyzed the promoters of 361 transcriptionally induced genes with respect to c-Myc binding sites and found 110 putative binding sites in 94 promoters. Furthermore, we analyzed the flanking sequences (+/- 100 bp) around the 110 c-Myc binding sites and found Ap2, Zf5, Zic3, and E2f binding sites to be overrepresented in these regions. Then, we analyzed the promoters of 361 induced genes with respect to binding sites of other transcription factors (TFs) which were upregulated by c-Myc overexpression. We identified at least one binding site of at least one of these TFs in 220 promoters, thus elucidating a potential transcription factor network. The analysis correlated well with the significant overexpression of the TFs Atf2, Foxf1a, Smad4, Sox4, Sp3 and Stat5a. Finally, we analyzed promoters of regulated genes which where apparently not regulated by c-Myc or other c-Myc targeted TFs and identified overrepresented Oct1, Mzf1, Ppargamma, Plzf, Ets, and HmgIY binding sites when compared against control promoter background.

Conclusion

Our in silico data suggest a model of a transcriptional regulatory network in which different TFs act in concert upon c-Myc overexpression. We determined molecular rules for transcriptional regulation to explain, in part, the carcinogenic effect seen in mice overexpressing the c-Myc oncogene.

Background

The proto-oncogene c-Myc is highly expressed in many cancer types 123 and plays a critical role in regulating cell growth, proliferation, loss of differentiation, and apoptosis 4. In transgenic mice, targeted overexpression of Myc has been shown to be sufficient to induce cancer 567. In our department, a transgenic mouse model was created which overexpresses c-Myc. The c-Myc overexpression in alveolar epithelium of these mice results in the development of bronchiolo-alveolar carcinoma (BAC) and papillary adenocarcinoma (PLAC). Life expectancies of c-Myc transgenics range between 12–14 months.

The molecular mechanisms by which c-Myc functions to effect tumorigenesis have been the subject of extensive research in the past several decades. c-Myc is a transcription factor, a basic helix-loop-helix leucine zipper protein that dimerizes with Max to bind the DNA sequence 5'-CACGTG-3', known as an E box, and activates transcription 8. Myc also represses transcription through interaction with Miz-1 or through other elements at core promoters 9. Furthermore, Brenner et al. 10 suggested that c-Myc may also repress transcription by recruitment of a DNA methyl-transferase corepressor Dnmt3a. DNA methylation is the most important epigenetic modification in mammalian cells and is associated with transcriptional repression. Nevertheless, the mechanisms of transcriptional repression by c-Myc seem not to occur by direct binding of c-Myc to the DNA sequence 5'-CACGTG-3', known as an E box, and are not really well understood.

The pleiotropic effects of c-Myc on tumorigenesis are thought to be mediated by its target genes, because transcriptionally defective Myc alleles have diminished transforming potential 11. Furthermore, the domain that is required for c-Myc DNA binding, the basic helix-loop-helix zipper domain, is essential for its oncogenic transformation, and c-Myc possesses an N-terminal transactivation domain. Deletions or mutations in this domain result in loss of c-Myc transformation 12. The transcriptional activation potential of c-Myc, however, does not always correlate with its ability to transform rodent fibroblast cells 13. Several studies showed that mutations in the Myc box II domain within c-Myc can abrogate its transformation capacity without affecting c-Myc activation of reporter gene constructs 1415. These results emphasized the complex and interrelated nature of c-Myc-mediated transformation and highlighted the need to identify specific factors that interact with functionally important domains of the c-Myc oncoproteins.

Despite extensive research, the specific mechanisms by which tumorigenesis are achieved are not well understood. This is largely because a comprehensive list of biologically relevant Myc target genes has not yet been defined and such "transformation" associated genes remain elusive 16. In order to elucidate Myc targets many different techniques have been employed, such as microarray profiling, serial analysis of gene expression, and chromatin immunoprecipitation 171819202122232425. To date, > 1,600 genes have been found to be Myc-responsive and stored in the Myc target gene database 2627, but only a minority of the Myc-responsive genes have been implicated as direct target genes. C-Myc seems to induce a regulatory gene network, which consists of direct and indirect responses. The direct responses also seem to depend on different other transcription factors which either cooperate with or compete against c-Myc. Some of these transcription factors have already been described in the literature 2829.

In this study, we report a genetic and bioinformatic approach designed to identify regulatory gene networks induced by overexpression of c-Myc in alveolar epithelium of our female transgenic mouse model, resulting in the development of bronchiolo-alveolar carcinoma (BAC) and papillary adenocarcinoma (PLAC). Because the mechanisms of transcriptional repression by c-Myc do not occur by direct binding of c-Myc to E boxes, we restricted our analysis to promoter sequences of induced genes in which the potential c-Myc binding sites can be identified in silico. Thus, we have identified potential direct target genes of c-Myc and propose different transcription factors which either cooperate with or compete against c-Myc. Furthermore, we in silico describe different indirect mechanisms possibly participating in the Myc tumorigenic phenotype. Taken together, we suggest a model of a regulatory gene network in which different TFs act in concert upon overexpression of c-Myc in our transgenic mouse model.

Results

Analysis of high-density oligonucleotide microarray data

Global gene expression studies were done with lung tissue stemming from a female mouse transgenic line overexpressing the c-Myc proto-oncogene. The complete data have been deposited in NCBIs Gene Expression Omnibus (GEO) 30 and are accessible through GEO Series accession number GSE10954. The quantitative changes in significantly altered genes were investigated. For the definition of "significantly altered", see the Methods section. According to these criteria, transcription of 469 genes was induced and transcription of 8 genes was repressed in 5 months old animals (data shown in Additional file 1). At this time point the tumor burden was approximately 50%. It must be mentioned here that gene expression profiling by microarrays does not provide information about rates of transcription but measure mRNA abundance which might have been modified by processes such as reduced RNA degradation.

Additional file 1

Transcription profiling of lung adenocarcinomas of female c-Myc-transgenic mice: 477 significantly regulated genes. This table shows the ProbeSet IDs, RefSeq accession numbers, Unigene IDs, gene titles, gene symbols, fold changes, and t-test p-values of the significantly regulated genes.

Click here for file

Validation of microarray data by real time PCR

For the validation of microarray data, five different genes were selected: Met (met proto-oncogene), Myct1 (myc target 1), Myc (myelocytomatosis oncogene), Pnliprp1 (pancreatic lipase related protein 1) and Pbk (PDZ binding kinase). Expression of these genes was alternatively investigated with real time quantitative PCR using the LightCycler^®. Comparison of fold changes determined by microarray analysis and real time PCR are shown in Figure 1. Statistical significant changes in microarray analysis are indicated by a black diamond. Criteria for significance are described in the methods section. Statistical significant changes in real time PCR are marked with an asterisk, which is based on a paired two-tailed student t-Test. The results were considered significant when the p-value was less than 0.05. As shown in Figure 1 there was basic agreement between the two platforms. The fold changes of Met, however, differ strongly between microarray analysis and real time PCR. This phenomenon can be observed sometimes with the validation of microarray data by real time PCR: microarray analysis shows strong up regulation whereas PCR indicates a very low fold change like 1.5 or less. Here, the reason might be the low average intensity value of 40.01 combined with its high standard deviation of 67.12% for Met in the microarray experiments of non-transgenic animals. Notably, the average standard deviation of all significantly regulated genes of this study amounts 23.81%. Together with a high and stable average intensity value of 480 combined with its low standard deviation of 16.83% for Met in the microarray experiments of c-myc-transgenic animals the corresponding fold change appears higher than it might be in fact. Furthermore, we did not compare gene expression on identical sequences. Hence, we can not exclude the possibility that transcript expression differs on the basis of the different sequences (primers and amplification products) employed.

Figure 1

Validation of microarray data by real time PCR

Validation of microarray data by real time PCR. Comparison of gene expression of selected genes determined by microarray analysis (black bars) and real time PCR (grey bars; LC: LightCycler^®). Fold changes are shown on the y-axis. Significant changes of gene expression are indicated either with a diamond for array analysis or with an asterisk for real time PCR.

Promoter sequence analysis of genes induced by overexpression of c-Myc

A flowchart of our in silico strategy used to elucidate the c-Myc regulatory network is depicted in Figure 2.

Figure 2

Flow chart of our in silico strategy used to elucidate the c-Myc regulatory network

Flow chart of our in silico strategy used to elucidate the c-Myc regulatory network.

1) Analysis of promoters of 361 induced genes with respect to c-Myc binding sites

By using their RefSeq annotation, 361 promoter sequences could be extracted from the UCSC Genome Browser for the 469 upregulated genes. Furthermore, promoters of 100 genes which were not regulated at all were extracted (the list of non-regulated genes was prepared after applying criteria according to the Methods section and was included in Additional file 2). Both sequence sets were analyzed using TRANSFAC^®Professional rel. 8.3 integrated tool MATCH^®by using the matrices V$EBOX_Q6_01 (cut-off core similarity: 1.00, matrix similarity: 0.99), V$MYC_Q2 (cut-off core similarity: 1.00, matrix similarity: 0.99), and V$MYCMAX_B (cut-off core similarity: 0.75, matrix similarity: 0.96). The results of these analyses including positions and sequences of the corresponding binding sites are given in Additional file 3. Altogether, 110 different c-Myc binding sites were found in 94 different promoters, which partly were recognized by different matrices. Table 1 gives the 94 genes which are putatively directly regulated by c-Myc and the corresponding biological process they are involved in. In this table, the 15 targets stored already in the Myc Target Database are marked bold. Moreover, the number of c-Myc binding sites identified in the promoter set including promoters of induced genes was compared to the number of c-Myc binding sites identified in the control promoter set. The corresponding calculated fold occurrences of binding sites and the significance (p-value) of the occurrence values are given in Table 2. The fold occurrences describe the number of c-Myc binding sites detected as a ratio with regard to the number of gene promoters analyzed. Here, the fold occurrence of the non-regulated gene promoters is set to 1. For all matrices used the fold occurrences of the c-Myc binding sites of the analyzed promoters in total are increased in comparison to the fold occurrences of the c-Myc binding sites of the control gene promoters in total. Furthermore, the significance of the occurrence values is high. This result indicates direct regulation by c-Myc of many of the genes analyzed.

Additional file 2

RefSeq IDs of genes the promoters of which were used as control promoters in promoter analysis.

Click here for file

Additional file 3

Putative direct c-Myc targets: positions of c-Myc binding sites in the promoter. RefSeq accession numbers, gene symbols, and gene titles of the putative c-Myc targets are listed in this table. Moreover, the TRANSFAC identifier of the respective matrix, the position of the hit (1 = 1000 bp upstream of TSS; 1100 = 100 bp downstream of TSS), and the corresponding recognized sequence are included in the right column.

Click here for file

Table 1

Putative direct c-Myc targets: biological processes

Probe Set ID

Gene Symbol

Gene Title

Biological process

1420821_at

Sgpp1

sphingosine-1-phosphate phosphatase 1

apoptosis

1428480_at

Cdca8

cell division cycle associated 8

cell cycle

1435306_a_at

Kif11

kinesin family member 11

cell cycle

1423903_at

Pvr

poliovirus receptor

cell-cell adhesion

1422889_at

Pcdh18

protocadherin 18

cell-cell adhesion

1427489_at

Itga8

integrin alpha 8

cell-matrix adhesion

1419717_at

Sema3e

sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3E

development

1448595_a_at

Bex1

brain expressed gene 1

development

1422198_a_at

Shmt1

serine hydroxymethyltransferase 1 (soluble)

amino acid metabolism

1418483_a_at

Ggta1

glycoprotein galactosyltransferase alpha 1, 3

carbohydrate metabolism

1421879_at

Mtmr1

myotubularin related protein 1

lipid metabolism

1426575_at

Sgms1

sphingomyelin synthase 1

lipid metabolism

1445103_at

Tmem23

Transmembrane protein 23

lipid metabolism

1417300_at

Smpdl3b

sphingomyelin phosphodiesterase, acid-like 3B

lipid metabolism

1421957_a_at

Pcyt1a

phosphate cytidylyltransferase 1, choline, alpha isoform

lipid metabolism

1422702_at

Azin1

antizyme inhibitor 1

polyamine metabolism

1417190_at

Pbef1

pre-B-cell colony-enhancing factor 1

NAD biosynthetic process

1423088_at

Tmod3

tropomodulin 3

negative regulation of cell motility

1420847_a_at

Fgfr2

fibroblast growth factor receptor 2

proliferation

1415691_at

Dlg1

discs, large homolog 1 (Drosophila)

proliferation

1422966_a_at

Tfrc

transferrin receptor

proliferation

1420924_at

Timp2

tissue inhibitor of metalloproteinase 2

proliferation

1420020_at

Suz12

suppressor of zeste 12 homolog (Drosophila)

proliferation

1416657_at

Akt1

thymoma viral proto-oncogene 1

proliferation

1420852_a_at

B3gnt2

UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase 2

protein amino acid glycosylation

1426342_at

Stt3b

STT3, subunit of the oligosaccharyltransferase complex, homolog B (S. cerevisiae)

protein amino acid glycosylation

1425581_s_at

Galnt7

UDP-N-acetyl-alpha-D-galactosamine: polypeptide N-acetylgalactosaminyltransferase 7

protein amino acid glycosylation

1415692_s_at

Canx

calnexin

protein folding

1429502_at

Stch

stress 70 protein chaperone, microsome-associated, human homolog

protein folding

1427074_at

Pcmtd2

protein-L-isoaspartate (D-aspartate) O-methyltransferase domain containing 2

protein modification

1426721_s_at

Tiparp

TCDD-inducible poly(ADP-ribose) polymerase

protein modification

1439151_at

Msrb3

methionine sulfoxide reductase B3

protein repair

1431361_at

Prcp

prolylcarboxypeptidase (angiotensinase C)

proteolysis

1421857_at

Adam17

a disintegrin and metallopeptidase domain 17

proteolysis

1422528_a_at

Zfp36l1

zinc finger protein 36, C3H type-like 1

regulation of mRNA stability

1420975_at

Baz1b

bromodomain adjacent to zinc finger domain, 1B