- Research article
- Open Access
- Open Peer Review
A transcriptome anatomy of human colorectal cancers
© Lü et al; licensee BioMed Central Ltd. 2006
- Received: 12 August 2005
- Accepted: 23 February 2006
- Published: 23 February 2006
Accumulating databases in human genome research have enabled integrated genome-wide study on complicated diseases such as cancers. A practical approach is to mine a global transcriptome profile of disease from public database. New concepts of these diseases might emerge by landscaping this profile.
In this study, we clustered human colorectal normal mucosa (N), inflammatory bowel disease (IBD), adenoma (A) and cancer (T) related expression sequence tags (EST) into UniGenes via an in-house GetUni software package and analyzed the transcriptome overview of these libraries by GOTree Machine (GOTM). Additionally, we downloaded UniGene based cDNA libraries of colon and analyzed them by Xprofiler to cross validate the efficiency of GetUni. Semi-quantitative RT-PCR was used to validate the expression of β-catenin and. 7 novel genes in colorectal cancers.
The efficiency of GetUni was successfully validated by Xprofiler and RT-PCR. Genes in library N, IBD and A were all found in library T. A total of 14,879 genes were identified with 2,355 of them having at least 2 transcripts. Differences in gene enrichment among these libraries were statistically significant in 50 signal transduction pathways and Pfam protein domains by GOTM analysis P < 0.01 Hypergeometric Test). Genes in two metabolic pathways, ribosome and glycolysis, were more enriched in the expression profiles of A and IBD than in N and T. Seven transmembrane receptor superfamily genes were typically abundant in cancers.
Colorectal cancers are genetically heterogeneous. Transcription variants are common in them. Aberrations of ribosome and glycolysis pathway might be early indicators of precursor lesions in colon cancers. The electronic gene expression profile could be used to highlight the integral molecular events in colorectal cancers.
- Colorectal Cancer
- Inflammatory Bowel Disease
- Normal Mucosa
- UniGene Database
Worldwide, the incidence of colorectal cancer has been rising nowadays. It is the second mortality caused by cancers in western countries and the third or fourth in China . Many tumor suppressor genes, oncogenes, and growth factor genes have been demonstrated to be involved in the carcinogenesis of colon and rectum, for example, k-ras, APC, p53 and TGFβ. A molecular genetic model of multiple genes and steps was proposed by Vogelstein in 1990 . Two paralleling molecular pathways, mutator pathway and chromosomal instability pathway, were accepted since the identification of microsatellite instability (MSI) in hereditary non-polyposis colorectal cancer (HNPCC) in 1993 . Four precursor lesions of colorectal cancers, adenoma, inflammatory bowel disease (ulcerous colitis and Crohn's disease), juvenile polyp and hyperplastic polyp, were mentioned in the latest edition of WHO tumour classification of digestive tract . However, molecular understanding of colorectal cancer remained in its infancy. An emerging principle is that malignant transformation of colonic epithelial cells does not merely rely on mutations of generic oncogenes or tumour suppressor genes. It seems that the altered interactions among multiple genes or regulatory pathways might specifically subvert the physiological regulators of the epithelium . The finished human genome was released last October in which only 20,000~25,000 genes in the human genome were estimated, far less than expected previously . This also suggests that the interactions among genes or transcription level of genes really matters in both physiological and pathological processes including carcinogenesis. Hence, an integrated study on the genome-wide gene expression profile is necessary to build the corresponding gene networks underlying complicated diseases, such as colorectal cancers .
Experimental and computational approaches are most commonly used strategies in large-scale gene expression studies . The former was represented by cDNA or serial analysis of gene expression (SAGE) library and recently developed gene expression microarray. The latter consists of various data mining methods from public database including digital differential display (DDD) in non-normalized cancer genome anatomy project (CGAP) libraries and digital Northern-blot in National Cancer Institute (NCI) SAGEMap [8, 9].
Expression sequence tags (ESTs) are single passed, fragments of complementary DNA (cDNA) clones from different libraries. They are efficient for discovering novel genes in the genome . It is estimated that at least 10,000 different genes are expressed in a cell with an average of about 30,000 mRNA molecules per cell. Hence, an EST library, even constructed by various modified methods such as suppression subtraction hybridization (SSH) and representational differential display (RDA), is no more than a snapshot of the mRNA composition of a certain tissue at a certain time. Particularly, genes in low-abundance might not be well represented. Fortunately, ESTs of one tissue from different libraries were available via three international nucleic acid databases, GenBank, EMBL and DDBJ. The total number of ESTs in these databases amounted to an unprecedented figure especially in the process of the initial and finished human genome sequences. Additionally, these ESTs are automatically partitioned into UniGene cluster, a non-redundant set of gene-oriented clusters . Each UniGene cluster might represent one gene or at least one gene transcript. Thus, UniGene was widely applied in gene mapping, large scale gene expression, and gene alternative splicing variants identification. Therefore, it is a practical approach to mine a global transcriptome profile for a specific tissue in a certain physiological or pathological state from public databases .
In this study, we scrutinized the ESTs of colorectal tissues under 4 different states including normal mucosa (N), colorectal cancers (T), and two most common precancerous lesions: adenoma (A) and inflammatory bowel disease (IBD, ulcerative colitis and Crohn Disease included). Transcriptome maps of these four tissues were constructed via an in-house GetUni software package. To our knowledge, the current study is the first transcriptome map of colorectal cancers mining from NCBI EST database (dbEST) up to now. Genes in the maps were pathway oriented and analyzed by WebGestalt (WEB-based GENE SeT AnaLysis Toolkit). Several novel conceptions in colorectal tumours were emerging including heterogeneity in colorectal cancers, potential role of metabolic alterations in ribosome and glycolysis pathway in cancer precursor lesions, frequent variant transcripts in colorectal cancer as well as several novel genes in colorectal tumourigenesis, thus facilitate the understanding of molecular mechanisms underlying colorectal cancer development.
Resources for databases and computer programs
Human colorectal normal (N), IBD, adenoma (A) and cancer (T) associated electronic EST libraries were downloaded from dbEST  using keywords "(homo sapiens OR human) AND (colon OR rectal OR colorectal OR large bowel) AND normal AND gbdiv_est [PROP]", "(homo sapiens OR human) AND (colon OR rectal OR colorectal OR large bowel) AND (inflammatory bowel disease OR Crohn's disease OR ulcerative colitis) AND gbdiv_est [PROP]", "(homo sapiens OR human) AND (colon OR rectal OR colorectal OR large bowel) AND adenoma AND gbdiv_est [PROP] AND gbdiv_est [PROP]" and "(homo sapiens OR human) AND (colon OR rectal OR colorectal OR large bowel) AND (cancer OR carcinoma OR adenocarcinoma) AND gbdiv_est [PROP]", respectively. Human UniGene database (hs.data, build#181) was also downloaded from NCBI UniGene repository .
GetUni software package (available upon request), an in-house potent computational approach for clustering non-redundant nucleotide into UniGenes, was written in Perl6.0 and run under Linux (Redhat 9.0) operating system. The basic analytic scheme is depicted below: firstly, extract accession number from the non-redundant sequence; secondly, export related UniGene information from the downloaded UniGene database via accession number; then remove the redundant UniGene information and automatically record the hits of identical UniGene; and finally, obtain the expression profile via gene symbol for each electronic EST library.
Additionally, the cDNA libraries of colon mucosa, inflammatory bowel disease, adenoma and cancer were also downloaded from UniGene based cDNA expression profiler and analyzed by the online tool Xprofiler . Genes in these libraries were applied as controls to cross validate the results from our in-house GetUni software package.
Analysis of the transcriptome in colorectal tissues
GOTM is a web-based platform for interpreting interesting gene sets including microarray data using Gene Ontology hierarchies [16, 17]. It provides classification and tissue distribution of genes as well as analytical tools (WEB-based GEne SeT AnaLysis Toolkit, WebGestalt) for comparison of the significantly enriched gene numbers in the catalogue of gene ontology in a pathway- or gene family- oriented way between an interesting and a reference gene set. A reference gene set might include all the genes in the human genome or another appropriate gene set. Hypergeometric test, appropriate for sampling without replacement, was adopted by GOTM to determine whether those enrichments are statistically significant. Since gene classification in GOTree is comprehensive and complex, we adopted genes at the default level 4 as the final export results.
Primers and amplification conditions of 8 selected putative genes
PCR Fragments (bp)
Transcriptome comparison among the gene expression profiles of N, IBD, A and T
Comparison of these dbEST profiles with those of UniGene cDNA Libraries
A total of 134 cDNA libraries of colon were identified in the UniGene cDNA based expression profiler. Nevertheless, we only found 32 with definite histology diagnosis including colon mucosa 4 (i.e. normal, N), IBD 2, adenoma (A) 1 and cancer or tumour (T) 25. Using the online tool Xprofiler, we obtained 5274, 2234, 588 and 13071 UniGnene transcripts, or 5032, 2111, 566 and 11162 known genes in these UniGene library N, IBD, A and T. More than 98% genes in the UniGene based expression profile IBD, A and T were included in our corresponding libraries, respectively, in support of the potency of our GentUni software package. The minor discrepancy might reflect the updated UniGene database. We have to admit that a relatively greater gap existed between the two N profiles of the UniGene based libraries and ours since only 70% genes in UniGene N profile was identified in ours. We noticed that the annotation of these so-called normal libraries in UniGene database were "colon mucosa", not "NORMAL". Considering the stringent keywords that we used in this study, it is not strange that all these libraries were not included in our N library downloaded from the dbEST. Actually, it is inevitable that missing data could occur in any data mining studies. Fortunately, genes in the UniGene based N profile were included in our T library.
Expression of 8 putative genes in colorectal cancers by RT-PCR
The release of the human genome sequences and accumulating databases as well as technological development for detecting large-scale gene expression profile have enabled integrated genome-wide study on complicated pathological states, such as cancers. Tissue or organ-specific gene expression patterns as well as genome mapping have been reported via database mining including dbEST and SAGEMap [12, 18]. These computational methods were proved to be effective for comparisons among tissues under different physiological or pathological states . We thus developed an integrated dbEST mining procedure, GetUni. In this study, we utilized GetUni for genome-wide transcriptome analysis on normal mucosa, cancers and related precancerous lesions of colon. The efficiency of this software package was cross validated by the profiles of UniGene cDNA based libraries using the Xprofile online tool. However, we did not focus on differential gene expression patterns among these states since ESTs from dbEST were made by various methods by contributors. To our knowledge, this is the first report on computational genome-wide transcriptome analysis.
In the initial analysis of these 4 sets of transcriptome, we noticed a prominent phenomenon that all genes or gene transcripts from N, IBD and A were found in cancers. Besides the fact that the total ESTs in T were much more than those in the other 3 libraries, one of the underlying paradoxical interpretations was the complicated heterogeneity of colorectal cancers with regard to histogenesis, morphology and molecular genetics, etc. ESTs were highly redundant cDNA fragments derived from either the 3'- or 5'- regions of human genes. For example, there were 20,370 and 279,163 ESTs, and finally 4,108 and 14,879 genes in N and T library, respectively. The average ESTs per gene between T and N (18.7622, 279,163/14,879 versus 4.9586, 20,370/4,108) was approximately 5 and amounted to 7 after normalization of EST clustering efficiency (51.34% in N versus 71.86% ESTs in T which could be clustered into UniGenes, respectively). Considering that there are about 13 times more ESTs in T than in N, it is reasonable to believe that at least 50% increased ESTs in T library could be ascribed to redundancy, suggesting that increased EST was not the unique answer for the broad pattern of gene expression in cancers. Multiple pathways contributing to colorectal cancers were well established including adenoma-carcinoma sequence, inflammatory bowel disease-dysplasia-cancer, hyperplastic polyposis-intraepithelial neoplasia (IEN)-cancer or juvenile polyposis-IEN-cancer as well as direct malignant transformation from normal mucosa (de novo) . As for morphological features, various histological subtypes with varied differentiation were fully accepted including tubular adenocarcinoma, mucinous carcinoma, signet-ring cell carcinoma, medullary carcinoma, undifferentiated carcinoma, etc. A long standing concept in cancer biology is that tumours arise and grow as a result of "tumour stem cells" or "stem cells" (multipotent progenitor cells with the capacity for self-renewal) with multiple additional mutations . Consistent with this idea, a defined minority of these cells might be able to proliferate, differentiate, dedifferentiate and transdifferentiate, resulting in heterogenous gene expression patterns in cancers.
This study also found that transcript variants were quite common since 2,355 out of 14,879 genes had at least 2 transcripts. And, we believe that with the ever increasing ESTs in dbEST, more transcript variants would be discovered in these colonic tissues. In the finished human genome, a big surprise is that there are not more than 25,000 genes in the human genome, barely more than the worm Caenorhabditis elegans . Considering the myriad cellular processes that keep our body functioning, a clear and reinforcing realization is that many genes encode more than one protein, a theory replacing the old notion of one gene one protein. One way that human genome performs such complex functions with so few genes is alternative splicing, which plays important roles in development, physiology, and disease. A genome survey of human alternative pre-mRNA splicing indicated that at least 74% of human multi-exon genes are alternatively spliced . Furthermore, another intriguing phenomenon in this preliminary study is that the average transcripts of individual gene in T are higher than those in the other profiles, indicating that increased alternative splicing might be an optimal option for colorectal cancer considering their more complicated biological behaviours and functions than those of normal or benign lesions in colon tissue.
Uexpectedly, the enriched genes of ribosome in KEGG pathway were highest in 2 precancerous lesions, A and IBD, and lowest in cancer as suggested by GOTM analysis when we compared among these 4 libraries. Ribosome proteins, the major components of ribosome which is the protein synthesis center in a cell, play critical roles in physiological and pathological situations. The fundamental physiological function of colonocytes is secretion, which involves many ribosomes, as evidenced by electronic microscopy. In addition, there is highly active renewal and proliferation in crypt cells. But in cancer, this secretary capability was lost or or impaired due to dedifferentiation, resulting in the limited enrichment of ribosome genes in cancers despite that other oncogenic proteins might be actively synthesized with the absolute number of ribosome genes remaining high. This hypothesis was supported by a recent immunohistochemical study, in which 10 of 12 ribosome proteins were stained stronger in normal mucosa than in colon cancers . As in adenoma and IBD, 2 intermediate states between normal mucosa and cancers, we hypothesized that the ability of secretion largely remained and that there was additional new protein synthesis to maintain the transformed phenotype in IEN or dysplasia. In our previous analysis on differentially expressed genes between colonic adenoma-normal mucosa, 6 out of 62 differentially expressed genes were ribosome proteins . Ribosome protein S11 and L7 were upregulated in colonic adenomas rather than in normal mucosa or cancers as indicated by microarray . An early study also demonstrated that increased mRNA levels of several ribosomal proteins were present in colorectal tumors and polyps . All these findings implicated that increased synthesis of ribosomes might be an important indicator of precursor lesions of colorectal cancers.
Other findings in this study were also intriguing. Genes in the process of the KEGG Glycolysis/Gluconeogenesis pathway were significantly more enriched in adenomas and IBD than in cancers. This is consistent with a recent report on ApcMin/+ mouse model of colon tumours (26). Aberrant glucose metabolism might be emerged in the precancerous stage, earlier than before expected. Five thioredoxin family members were present in library A. These enriched genes might play important roles in anti-oxidative injury, inhibition of apoptosis, cell proliferation and differentiation [27, 28]. Totally, 111 7-transmembrane receptor (rhodopsin family) superfamily members were found in cancers. Small GTP-binding protein-coupled receptors, endocrinal or neuroendocrinal receptors, and cytokine receptors were included in this catalogue. Their role in colon cancer was well documented recently [29, 30].
Finally, we analyzed the expression of 8 putative genes in colorectal cancers. The preliminary data suggested that all these genes were variably expressed in cancer tissues and cell lines. Particularly, SOX9 was upregulated in most colorectal cancers. It is in consistent with our latest immunostaining results (unpublished data), indicating that SOX9 may play oncogenic roles and serve as an independent adverse prognosticator in colorectal cancers. A recent study revealed that SOX9 was an intestinal crypt specific transcription factor and downstream target of β-catenin . SOX9 may thus be a potential target gene for prognostic assessment and therapeutic intervention in colorectal cancers.
In this study, genome-wide transcriptome overview of colorectal cancers and their precursors were mined from dbEST using an in-house GetUni software. Landscaping the terrain of the transcriptome, new scopes in the initiation and development of colon cancers were implicated. We confirmed that colorectal cancers are genetically heterogeneous. The interactive network among these genes in colorectal cancers became more complicated due to frequent alternative splicing. Aberrations of the ribosome and glycolysis pathway might be early indicators of precursor lesions in colon cancers. Thus, the electronic gene expression profile could be used to highlight the integral molecular events in colorectal cancers. However, more effort should be put into elucidating the regulatory network among these genes via a strategy of system biology, integrating colorectal specific gene expression microarray, microfluidic card Q-PCR and proteomics study.
This study was supported by the National Natural Science Foundation of China (30371605, 30370636) and the Key Project Foundation of Zhejiang Bureau of Science and Technology (171170), PR China. We thank Dr Lina Shaw, Department of Epidemiology, University of Texas M. D. Anderson Cancer Center, Houston, TX 77030, USA, for her expertise in language revision.
- Hamilton SR, Altonin LA: Pathology and Genetics: tumours of the Digestive System. WHO classifications Third Series. 2001, RIAS, Ryon, FranceGoogle Scholar
- Fearon ER, Vogelstein B: A genetic model for colorectal tumorigenesis. Cell. 1990, 61: 759-767. 10.1016/0092-8674(90)90186-I.View ArticlePubMedGoogle Scholar
- Thibodeau SN, Bren G, Schaid D: Microsatellite instability in cancer of the proximal colon. Science. 1993, 260: 816-819.View ArticlePubMedGoogle Scholar
- Radtke F, Clevers H: Self-renewal and cancer of the gut: two sides of a coin. Science. 2005, 307: 1904-1909. 10.1126/science.1104815.View ArticlePubMedGoogle Scholar
- International Human Genome Sequencing Consortium: Finishing the euchromatic sequence of the human genome. Nature. 2004, 431: 931-945. 10.1038/nature03001.View ArticleGoogle Scholar
- Hanash S: Integrated global profiling of cancer. Nat Rev Cancer. 2004, 4: 638-644. 10.1038/nrc1414.View ArticlePubMedGoogle Scholar
- Dennis JL, Vass JK, Wit EC, Keith WN, Oien KA: Identification from public data of molecular markers of adenocarcinoma characteristic of the site of origin. Cancer Res. 2002, 62: 5999-6005.PubMedGoogle Scholar
- Scheurle D, DeYoung MP, Binninger DM, Page H, Jahanzeb M, Narayanan R: Cancer gene discovery using digital differential display. Cancer Res. 2000, 60: 4037-4043.PubMedGoogle Scholar
- Lal A, Lash AE, Altschul SF, Velculescu V, Zhang L, McLendon RE, Marra MA, Prange C, Morin PJ, Polyak K, Papadopoulos N, Vogelstein B, Kinzler KW, Strausberg RL, Riggins GJ: A public database for gene expression in human cancers. Cancer Res. 1999, 59: 5403-5407.PubMedGoogle Scholar
- Adams MD, Kelley JM, Gocayne JD, Dubnick M, Polymeropoulos MH, Xiao H, Merril CR, Wu A, Olde B, Moreno RF, Kerlavage AR, McCombie WR, Venter JC: Complementary DNA sequencing: expressed sequence tags and human genome project. Science. 1991, 252: 1651-1656.View ArticlePubMedGoogle Scholar
- Zhuo D, Zhao WD, Wright FA, Yang HY, Wang JP, Sears R, Baer T, Kwon DH, Gordon D, Gibbs S, Dai D, Yang Q, Spitzner J, Krahe R, Stredney D, Stutz A, Yuan B: Assembly, annotation, and integration of UNIGENE clusters into the human genome draft. Genome Res. 2001, 11: 904-918. 10.1101/gr.GR-1645R.View ArticlePubMedPubMed CentralGoogle Scholar
- Qiu P, Benbow L, Liu S, Greene JR, Wang L: Analysis of a human brain transcriptome map. BMC Genomics. 2002, 3: 10-10.1186/1471-2164-3-10.View ArticlePubMedPubMed CentralGoogle Scholar
- NCBI EST database. [http://0-www.ncbi.nlm.nih.gov.brum.beds.ac.uk/projects/dbEST/]
- UniGene database. [ftp://ftp.ncbi.nih.gov/repository/UniGene/]
- NCI cDNA Expression Profile Tool. [http://nciarray.nci.nih.gov/cgi-bin/UGlib_profiler_form.cgi?org=Hs&focus=All&minseq=200]
- GOTree Machine (GOTM). [http://genereg.ornl.gov/gotm/]
- The Gene Ontology Consortium: Gene ontology: tool for the unification of biology. Nat Genet. 2000, 25: 25-29. 10.1038/75556.View ArticlePubMed CentralGoogle Scholar
- Yamashita T, Honda M, Takatori H, Nishino R, Hoshino N, Kaneko S: Genome-wide transcriptome mapping analysis identifies organ-specific gene expression patterns along human chromosomes. Genomics. 2004, 84: 867-875. 10.1016/j.ygeno.2004.08.008.View ArticlePubMedGoogle Scholar
- Schmitt AO, Specht T, Beckmann G, Dahl E, Pilarsky CP, Hinzmann B, Rosenthal A: Exhaustive mining of EST libraries for genes differentially expressed in normal and tumour tissues. Nucleic Acids Res. 1999, 27: 4251-4260. 10.1093/nar/27.21.4251.View ArticlePubMedPubMed CentralGoogle Scholar
- Beachy PA, Karhadkar SS, Berman DM: Tissue repair and stem cell renewal in carcinogenesis. Nature. 2004, 432: 324-31. 10.1038/nature03100.View ArticlePubMedGoogle Scholar
- Johnson JM, Castle J, Garrett-Engele P, Kan Z, Loerch PM, Armour CD, Santos R, Schadt EE, Stoughton R, Shoemaker DD: Genome-wide survey of human alternative pre-mRNA splicing with exon junction microarrays. Science. 2003, 302: 2141-2144. 10.1126/science.1090100.View ArticlePubMedGoogle Scholar
- Kasai H, Nadano D, Hidaka E, Higuchi K, Kawakubo M, Sato TA, Nakayama J: Differential expression of ribosomal proteins in human normal and neoplastic colorectum. J Histochem Cytochem. 2003, 51: 567-574.View ArticlePubMedGoogle Scholar
- Luo MJ, Lai M: Identification of differentially expressed genes in normal mucosa, adenoma and adenocarcinoma of colon by SSH. World J Gastroenterol. 2001, 7: 726-731.PubMedPubMed CentralGoogle Scholar
- Notterman DA, Alon U, Sierk AJ, Levine AJ: Transcriptional Gene Expression Profiles of Colorectal Adenoma, Adenocarcinoma, and Normal Tissue Examined by Oligonucleotide Arrays. Cancer Res. 2001, 61: 3124-3130.PubMedGoogle Scholar
- Pogue-Geile K, Geiser JR, Shu M, Miller C, Wool IG, Meisler AI, Pipas JM: Ribosomal protein genes are overexpressed in colorectal cancer: isolation of a cDNA clone encoding the human S3 ribosomal protein. Mol Cell Biol. 1991, 11: 3842-3849.View ArticlePubMedPubMed CentralGoogle Scholar
- Leclerc D, Deng L, Trasler J, Rozen R: ApcMin/+ mouse model of colon cancer: gene expression profiling in tumors. J Cell Biochem. 2004, 93: 1242-1254. 10.1002/jcb.20236.View ArticlePubMedGoogle Scholar
- Sullivan DC, Huminiecki L, Moore JW, Boyle JJ, Poulsom R, Creamer D, Barker J, Bicknell R: EndoPDI, a novel protein-disulfide isomerase-like protein that is preferentially expressed in endothelial cells acts as a stress survival factor. J Biol Chem. 2003, 278: 47079-47088. 10.1074/jbc.M308124200.View ArticlePubMedGoogle Scholar
- Coppock DL, Kopman C, Scandalis S, Gilleran S: Preferential gene expression in quiescent human lung fibroblasts. Cell Growth Differ. 1993, 4: 483-493.PubMedGoogle Scholar
- Yang M, Zhong WW, Srivastava N, Slavin A, Yang J, Hoey T, An S: G protein-coupled lysophosphatidic acid receptors stimulate proliferation of colon cancer cells through the β-catenin pathway. Proc Natl Acad Sci U S A. 2005, 102: 6027-6032. 10.1073/pnas.0501535102.View ArticlePubMedPubMed CentralGoogle Scholar
- Li A, Varney ML, Singh RK: Expression of interleukin 8 and its receptors in human colon carcinoma cells with different metastatic potentials. Clin Cancer Res. 2001, 7: 3298-3304.PubMedGoogle Scholar
- Blache P, van de Wetering M, Duluc I, Domon C, Berta P, Freund JN, Clevers H, Jay P: SOX9 is an intestine crypt transcription factor, is regulated by the Wnt pathway, and represses the CDX2 and MUC2 genes. J Cell Biol. 2004, 166: 37-47. 10.1083/jcb.200311021.View ArticlePubMedPubMed CentralGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://0-www.biomedcentral.com.brum.beds.ac.uk/1471-2407/6/40/prepub
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