WO2008107725A1 - A method for the construction of cancer-specific promoters using functional genomics - Google Patents

Abstract

The present invention relates to a method of producing a promoter element capable of regulating gene expression in a cell or tissue type of interest, said method comprising: (g) providing a plurality of transcription factor regulatory elements that are associated with genes that are expressed in said cell or tissue type; (h) constructing a library of expression vectors, wherein each vector comprises two or more of said transcription factor regulatory elements of (a) and a minimal promoter operably linked to an antibiotic resistance gene; (i) transfecting cells of the cell or tissue type of interest with vectors from said library (b); (j) culturing said cells under conditions suitable for gene expression and screening said cells for antibiotic resistance; and (k) identifying vectors in which the antibiotic resistance gene is expressed, thereby identifying a promoter element capable of regulating gene expression in the cell or tissue type of interest.

Description

A METHOD FOR THE CONSTRUCTION OF CANCER-SPECIFIC PROMOTERS USING FUNCTIONAL GENOMICS

Background of the Invention; Cancer is a complex biological phenomenon that is thought to arise out of a multi- step process of genetic and epi-genetic alterations in the cellular DNA, ultimately resulting in the transformation of the cell and its uncontrolled growth, division and migration. Identifying the aberrant molecular pathways that mediate cellular transformation has been a major challenge in understanding how malignancy develops. The advent of functional genomics has given scientists the prospect of examining global changes in gene expression, providing molecular phenotypes that could potentially help in establishing more effective techniques of diagnosis and prognosis in a variety of cancers^1"3.

Utilising microarrays to decipher the molecular events that result in tumour progression has proven a more difficult task, particularly since microarray data only provides a snapshot into a cell's transcriptome at a specific point in time. As many cancers contain multiple genetic alterations, it is difficult to ascribe specific changes in gene expression profiles to particular alterations in the genome of the transformed cell. However, progress in the past few years has revealed that microarray data can have wider applications in the study of cancer, particularly with the advent of comparative genomic microarray analysis⁴. In this type of analysis, gene expression data can be mapped to chromosomes, revealing potential sites of chromosomal aberrations, e.g. amplifications or deletions, which may predominate in particular types of cancer. There is also now a growing trend for researchers to analyse microarray data in terms of 'gene modules' instead of the presentation of differentially regulated gene lists⁵. By grouping genes into functionally related modules it is possible to identify subtle changes in gene expression that may be biologically (if not statistically significantly) important, to more easily interpret molecular pathways that mediate a particular response and to compare many different microarray experiments from different tumour types in an effort to uncover the commonalities and differences in multiple clinical conditions. Therefore, we are moving into a new era of functional genomics, where the large datasets generated by the evaluation of global gene expression studies can be more fully interpreted by improvements in computational methods. It is important in the study of cancer that these improved bioinformatics tools be applied to this complex disease in an effort to unravel the molecular processes that mediate the malignant phenotype. so that ultimately improved targeted therapeutics can be effectively designed.

Summary of the Invention:

The present invention provides a method of producing a promoter element capable of regulating gene expression in a cell or tissue type of interest, said method comprising:

(a) providing a plurality of transcription factor regulatory elements that are associated with genes that are expressed in said cell or tissue type;

(b) constructing a library of expression vectors, wherein each vector comprises two or more of said transcription factor regulatory elements of (a) and a minimal promoter operably linked to an antibiotic resistance gene;

(c) transfecting cells of the cell or tissue type of interest with vectors from said library (b);

(d) culturing said cells under conditions suitable for gene expression and screening said cells for antibiotic resistance; and (e) identifying vectors in which the antibiotic resistance gene is expressed, thereby identifying a promoter element capable of regulating gene expression in the cell or tissue type of interest.

The invention also provides vectors capable of gene expression and promoter elements capable of regulating gene expression in a cell or tissue of interest, wherein said vector or promoter element is identified by a method of the invention. Also provided is the use of such a vector or promoter element for targeting expression of a gene to a cell or tissue of interest.

For example, the invention provides a method of expressing a gene in a cell or tissue of interest, comprising (a) identifying a promoter element capable of directing gene expression in said cell or tissue using a method of the invention; (b) generating an expression vector comprising said promoter element operably linked to said gene; and (c) transfecting said cell or tissue of interest with said vector and allowing gene expression to occur.

Brief Description of the Figure:

Figure 1 shows a schematic diagram of one way in which the method of the invention may be carried out.

Microarray analysis of cancer tissue/cells compared to normal tissue/cells is conducted in order to identify differentially expressed genes, from the whole genome, which are specifically upregulated in cancer cells.

Using publicly available databases, the cis-regulatory elements driving the expression of upregulated genes are identified and synthesised as double stranded DNA oligonucleotides . The DNA oligonucleotides are randomly ligated together and cloned into a minimal promoter expression cassette driving the transcription of an antibiotic selection marker. A library of clones with randomly ligated cis regulatory elements is thus created. The library of clones is either transfected in the context of a retroviral vector into recipient cancer cells, or the plasmids comprising the expression cassette are first isolated from individual clones and transfected into recipient cancer cells.

Retro virally transduced or plasmid-transfected recipient cancer cells are subjected to high concentrations of the relevant antibiotic and synthetic promoter sequences are rescued from highly-expressing recipient cancer cells by PCR.

Detailed Description of the Invention:

The advances in functional genomics made in recent years have resulted in the identification of many more czs-regulatory elements that can be directly related to the increased transcription of specific genes. Indeed, the ability to use bioinformatics to unravel complex transcriptional pathways active in diseased cells can actually serve to facilitate the process of choosing suitable czs-elements that can be used to design synthetic promoters in complex pathologies such as cancer. In cancer the changes in the gene expression profile are often the result of alterations in the cell's transcription machinery induced by aberrant activation of signalling pathways that control growth, proliferation and migration. Such changes result in the activation of transcription regulatory networks that are not found in normal cells and provide us with an opportunity to design synthetic promoters that should only be active in cancerous cells.

If microarray technology is to truly result in the design of tailored therapies to individual cancers or even patients, as has been heralded, it is important that the functional genomics methodology that was designed for the identification of signalling and transcription networks be applied to the design of cancer-specific promoters so that effective gene therapeutic strategies can be formulated.

The development of bioinformatics algorithms for the analysis of microarray datasets has largely been applied in order to unravel the transcription networks operative under different disease and environmental conditions. To this date there has been no effort to use this type of approach to design synthetic promoters that are operative only under these certain disease or environmental conditions.

Described herein are methods whereby data obtained from functional genomics experiments, such as microarray analysis, are analysed using widely available bioinformatics software tools, which function to find over-represented cis promoter elements, in order to design synthetic promoters that are only active in cancer cells. This represents a major leap forward in the design of cancer-specific promoters that can subsequently be used in the study of cancer, or in the design of safe and effective genetic therapy of human malignancies.

The regulation of gene expression in eukaryotes is highly complex and often occurs through the coordinated action of multiple transcription factors. The use of trans- factor combinations in the control of gene expression allows a cell to employ a relatively small number of transcription factors in the regulation of disparate biological processes.

As discussed herein, a number of tools have been developed that allow us to utilise microarray data to identify novel czs-regulatory elements. It is also possible to use this information to decipher the transcriptional networks that are active in cells under different environmental conditions. La yeast, the importance of the combinatorial nature of transcriptional regulation was established by specifically examining clusters of upregulated genes for the presence of combinations of czs-elements⁶. By examining microarray data from yeast exposed to a variety of conditions the authors were able to construct a network of transcription revealing the functional associations between different regulatory elements. This approach resulted in the identification of key motifs with many interactions, suggesting that some factors serve as facilitator proteins assisting their gene-specific partners in their function.

The idea that a core number of transcription factors mediate such a vast array of biological responses by adopting multiple configurations implies that it may be possible to hijack the transcriptional programs that have gone awry in multifactorial diseases, such as cancer, in an effort to develop disease-specific regulatory elements. This is possible as the methods of interpreting cancer microarray data are continually evolving so that a more global picture of transcriptional regulation in transformed cells can now be painted. Meta-analyses of cancer datasets has permitted the identification of gene modules, allowing for the reduction of complex cancer signatures to small numbers of activated transcription programs and even to the identification of common programs that are active in most types of cancer⁷. This type of analysis can also help to identify specific transcription factors whose deregulation plays a key role in tumour development. For instance, in one study, the importance of aberrant E2F activity in cancer was reaffirmed during a search for the regulatory programs linking transcription factors to the target genes found upregulated in specific cancer types⁸. It was shown that E2F target genes were disproportionately upregulated in more than half of the gene expression profiles examined, which were obtained from a multitude of different cancer types. It was thus proposed that integrative bioinformatics analyses have the potential to generate new hypotheses about cancer progression.

The present invention is based on the premise that the elucidation of disease- specific transcriptional programs will afford us the opportunity to construct synthetic conditional promoter elements that can be used in gene therapy to drive restricted gene expression in pathologic sites of interest. Integrative computational approaches may be used to identify transcriptional programs active in specific cancer indications, and will consequently allow for the rational design of synthetic promoter elements designed to drive highly cytotoxic genes for an effective anti-cancer therapeutic approach.

Thus, according to the present invention, microarray data obtained by experimentation, or taken from publicly available resources such as Oncomine⁸, may be used in order to identify the regulatory sequences overrepresented in clusters of genes found to be upregulated in cancer stem cells.

Different bioinformatics tools, examples of which are given in table 1, may be used to screen for cw-regulatory elements. In general, such tools function by comparing gene expression profiles between differentially regulated genes and examining upstream sequences, available through genome sequence resources. For the phylogenetic footprinting tools, the untranslated regions of specific genes are compared between species and the most highly conserved sequences are returned and proposed to be potential czs-elements. A combination of all available approaches may employed in order to identify regulatory sequences that predominate in the profile of specific cell or tissue types, for example in cancer stem cells. The most common sequences identified are then used as the building blocks employed in the design of synthetic promoters.

Cells or Tissues of Interest

The invention relates to assays carried out on a cell or tissue type of interest. This may be any type of cell, or plurality of cells such as a tissue. This may be a prokaryotic cell or cells or a eukaryotic cell, cells or tissue. A suitable eukaryotic cell may be derived from an organism, such as an animal, such as a mammal and preferably a human. Such a cell or tissue may have been taken directly from such an organism or may be derived therefrom. For example, the cell or tissue may be from a primary, secondary or immortalised cell line or culture that is derived from such an organism.

The cell or tissue may be a naturally occurring cell or tissue or may have been artificially manipulated. For example, a cell or tissue may be manipulated by exposure to altered environmental or disease-specific conditions. For example, a cell or tissue may be manipulated by exposing it to an agent, such as a biological ligand or chemical agent. The biological ligand may be any biological molecule that is capable of having an effect on the cell, particularly an effect on gene transcription. A biological ligand may be a molecule that is capable of binding to the cell or acting within the cell. A biological ligand may, for example, be a polypeptide, protein, nucleic acid or carbohydrate molecule. Suitable biological ligands include hormones, growth factors and neurotransmitters. The chemical agent may be any agent capable of acting on the cell, preferably leading to a change in gene transcription within the cell. The chemical agent may, for example, be a chemotherapeutic drug or a therapeutic small molecular drug.

The cell or tissue may from an abnormal or disease source. For example, the cell or tissue may be taken from, or derive from, an organism suffering from a disease. Preferably the cell or tissue is from a tissue or organ that is affected by the disease. For example, where the disease is cancer, the cell or tissue may be taken from a tumour. The cell may be from, or derived from, a tumour cell line in vitro.

Transcription Factor Regulatory Elements The methods of the invention require the identification of transcription factor regulatory elements (TFREs) that are active in the cell or tissue of interest.

A suitable TFRE is a nucleic acid molecule that is recognised by a transcription factor. For example, a TFRE may comprise a sequence to which a transcription factor can bind. A TFRE may comprise a cis-acting region. By transcription factor is meant any factor, such as a protein, that can bind to such a cis-acting region and regulate either positively or negatively the expression of a gene. For example, a transcription factor may bind upstream of the coding sequence of a gene to either enhance or repress transcription of the gene by assisting or blocking RNA polymerase binding. Many transcription factors are well known in the art and include STAT, E2F, Oct-4, Nanog, Brachury, Pax genes, Sox2 and MCEF.

A TFRE comprises a nucleic acid sequence preferably, a double stranded DNA sequence. A TFRE may comprise a cis-acting region and may also comprise additional nucleic acids. The core six to eight nucleotides of promoter and enhancer elements may be sufficient for the binding of their corresponding frvms-activating factors. Indeed, in some cases this short oligonucleotide element is sufficient to drive gene expression alone⁹. Thus, a transcription factor binding site may consist of 6 to 8 nucleic acids. A TFRE comprising that site will be at least 6 to 8 nucleic acids in length. A TFRE of the invention is preferably 6 or more, 8 or more, 10 or more, 15 or more, 20 or more, 25 or more, or 30 or more nucleic acids in length. A TFRE of the invention may be 100 or less,

75 or less, 50 or less, 30 or less, 25 or less, 20 or less or 15 or less nucleic acids in length.

Identification of TFREs

A suitable TFRE is one that is active in the cell or tissue of interest. Such a TFRE may be identified as being associated with a gene that is expressed in the cell or tissue of interest. For example, a TFRE may be associated with a gene that is differentially expressed in that cell or tissue, when compared with another cell or tissue. For example, differential expression of a gene may be seen by comparing the expression of the gene in two different cells or tissues, or in the same cells or tissues under different conditions. Expression in one cell or tissue type may be compared with that in a different, but related, tissue type. For example, where the cell or tissue of interest is a disease cell or tissue or has been artificially manipulated as described herein, the expression of genes in that cell or tissue may be compared with the expression of the same genes in an equivalent normal or untreated cell or tissue. This may allow the identification of genes that are differentially regulated between the two cell or tissue types. A TFRE that is associated with such a gene is generally located close to the coding sequence of the gene within the genome of the cell. For example, such a TFRE may be located in the region immediately upstream or downstream of that coding sequence. Such a TFRE may be located close to a promoter or other regulatory sequence that regulates expression of the gene. The location of a TFRE may be determined by the skilled person using his knowledge of this field and the methods described herein.

Suitable TFREs may thus be identified by analysis of the cell or tissue of interest. Genes that are differentially expressed in the cell or tissue of interest may be identified by routine methods. For example, routine methods may be used to compare the expression profile of genes in the cell or tissue of interest with that in other cell or tissue types which may act as a control. Genes that are up-regulated or down-regulated in the cell or tissue of interest may thus be identified. Such an analysis may make use of, for example, microarray analysis or serial analysis of gene expression (SAGE).

Such an analysis may be carried out using a sample of expressed molecules from the cell or tissue of interest or using all the expressed molecules from the cell or tissue of interest. For example, in one embodiment, such an analysis may be carried out using the total RNA content of the cell or tissue of interest. The methods of the invention may thus be used to analyse expression from the entire genome of the cell or tissue of interest.

Such an analysis may be used to assess the expression of a wide variety of genes, or a subgroup of genes. Thus, in accordance with the present invention, a selection of genes may be used that is known to be regulated by a wide variety of different transcription factors, or each gene by only one or two transcription factors.

The ability to use gene expression data to identify gene modules, which mediate specific responses to environmental stimuli (or to a diseased state) and to correlate their regulation to the c/s-regulatory elements present upstream of the genes in each module, has transformed the way in which we interpret microarray data¹⁰. For instance, by using the modular approach it is possible to examine whether particular gene modules are active in a variety of different cancers, or whether individual cancers require the function of unique gene modules. This has allowed us to look for transcriptional commonalities between different cancers, which should aid in the design of widely applicable anti- cancer therapeutic strategies. In one earlier study, gene expression data from 1,975 microarrays, spanning 22 different cancers was used to identify gene modules that were activated or deactivated in specific types of cancer¹¹. Using this approach the authors found that a bone osteoblastic module was active in a number of cancers whose primary metastatic site is known to be the bone. Thus, a common mechanism of bone metastasis between varieties of different cancers was identified, which could be targeted in the development of novel anticancer therapies.

It is also possible to identify the higher-level regulator that controls the expression of the genes in each module¹⁰. Examination of the upstream regulatory sequences of each gene in a module may reveal the presence of common czs-regulatory elements that are known to be the target of the module's regulator. Therefore, by identifying specific regulatory proteins that control the activation of gene modules in different cancers, it should be possible to extrapolate the important cw-elements that mediate transcription in the transformed cell. Thereby, allowing us to design and construct novel tumour-specific promoters based on the most active czs-regulatory elements in a number of tumour- specific gene modules. Thus, once the differential expression of genes in a cell or tissue of interest has been established, the sequences upstream of the differentially expressed genes may be screened for cis-regulatory elements. Those cis-regulatory elements which control expression of differentially expressed genes are considered to be active in the cell or tissue of interest. Thus, for those cis-elements to be active, the transcription factor(s) which control their activity must be present in that cell type. This therefore allows the identification of TFREs that are active in the cell or tissue of interest.

TFREs and cis-elements may be identified using known methods, for example by screening using known bioinformatics techniques.

The ability to identify specific transcriptional elements in the human genome that control the expression of functionally related genes is transforming the application of functional genomics. Until recently the interpretation of data from microarray analysis has been limited to the identification of genes whose function may be important in a single pathway or response. How this related to global changes in the cellular phenotype had been largely ignored, as the necessary tools to examine this simply did not exist. With the advancement of bioinformatics we are now in a position to utilize all the data that is obtained from large-scale gene expression analysis and combine it with knowledge of the completed sequence of the human genome and with transcription factor, gene ontology and molecular function databases, thereby more fully utilizing the large datasets that are generated by global gene expression studies. For nearly two decades scientists have been compiling databases that catalogue the trans-factors and czs-elements that are responsible for gene regulation¹². This has resulted in the emergence of useful tools, such as TRANSCompel¹³, ABS¹⁴, JASPAR¹⁵, HTPSELEX¹⁶ and TRANSFAC¹⁷ that index transcription factors and their target sequences based on experimental data, and TRED¹⁸, which indexes based on both experimental and automated data. Databases of known transcription factor binding sites can be used to detect the presence of protein-recognition elements in a given promoter, but only when the binding site of the relevant DNA-binding protein and its tolerance to mismatches in vivo is already known. Because this knowledge is currently limited to a small subset of transcription factors, much effort has been devoted to the discovery of regulatory motifs by comparative analysis of the DNA sequences of promoters. By finding conserved regions between multiple promoters, motifs can be identified with no prior knowledge of transcription factor binding sites.

A number of models have emerged that achieve this by statistical overrepresentation. These algorithms function by aligning multiple untranslated regions from the entire genome and identifying sequences that are statistically significantly overrepresented in comparison to what it expected by random, e.g. YMF¹⁹'²⁰ and SCORE²¹. At present these tools are mainly applied in the study of lower eukaryotes where the genome is less complex and regulatory elements are easier to identify, extending these algorithms to the human genome has proven somewhat more difficult.

In order to redress this issue a number of groups have shown that it is possible to mine the genome of higher eukaryotes by searching for conserved regulatory elements adjacent to transcription start site motifs such as TATA and CAAT boxes, e.g. as catalogued in the DBTSS resource²²'²³, or one can search for putative czs-elements in CpG rich regions that are present in higher proportions in promoter sequences²⁴.

Alternatively, with the co-emergence of microarray technology and the complete sequence of the human genome, it is now possible to search for potential transcription factor binding sites by comparing the upstream non-coding regions of multiple genes that show similar expression profiles under certain conditions. Gene sets for comparative analysis can be chosen based on clustering, e.g. hierarchical and k-means²⁵, from simple expression ratio²⁶ or functional analysis of gene products²⁷. This provides scientists with the opportunity to identify promoter elements that are responsive to certain environmental conditions, or those that play a key role in mediating the differentiation of certain tissues or those that may be particularly active in mediating pathologic phenotypes. Phylogenetic footprinting, or comparative genomics, is now being applied to identify novel promoter elements by comparing the evolutionary conserved untranslated elements proximal to known genes from a variety of organisms²⁸. The availability of genome sequences between species has notably advanced comparative genomics and the understanding of evolutionary biology in general. The neutral theory of molecular evolution provides a framework for the identification of DNA sequences in genomes of different species.

Its central hypothesis is that the vast majority of mutations in the genome are neutral with respect to the fitness of an organism. Whilst deleterious mutations are rapidly removed by selection, neutral mutations persist and follow a stochastic process of genetic drift through a population. Therefore, non-neutral DNA sequences (functional DNA sequences) must be conserved during evolution, whereas neutral mutations accumulate. Initial studies sufficiently demonstrated that the human genome could be adequately compared to the genomes of other organisms allowing for the efficient identification of homologous regions in functional DNA sequences^29'31.

Subsequently, a number of bioinformatics tools have emerged that operate by comparing non-coding regulatory sequences between the genomes of various organisms to enable the identification of conserved transcription factor binding sites that are significantly enriched in promoters of candidate genes or from clusters identified by microarray analysis.

Examples of these software suites include TRAFAC³², CORG³³, CONSITE³⁴, CONFAC³⁵, VAMP³⁶ and CisMoIs Analyser³⁷. Typically these tools work by aligning the upstream sequences of target genes between species thus identifying conserved regions that could potentially function as cw-regulatory elements and have consequently been applied in the elucidation of transcription regulatory networks in a variety of models.

A significant amount of effort has been dedicated to the cataloguing of transcription factors and their corresponding cλs-elements. More recently, these databases have been compiled with the aim to utilise them to unravel regulatory networks active in response to diverse stimuli. Some examples of these resources include PreMod ' , CisView⁴⁰, BEARR⁴¹, VISTA⁴², PromAn⁴³, CRSD⁴⁴ and MPromDb⁴⁵. Table 1 lists some of the currently available databases that can be used when searching for potential regulatory sequences. This table provides an example of the type of resource utilised when identifying potential cis-acting sequences.

Table 1: Databases employed in the identification of m-elements Thus, any of the databases listed in Table 1, or any equivalent publicly available resource, may be used to identify TFREs, such as cis-regulatory elements, that are associated with genes that are expressed in the cell or tissue of interest, preferably genes that are differentially expressed in the cell or tissue of interest.

Construction of Synthetic Promoters

In recent years some efforts have been made to construct synthetic promoters for tissue specific transcription based on the linking of short oligonucleotide promoter and enhancer elements in a random fashion^{4 "} .

In one approach, which aimed to identify synthetic promoters for muscle-specific expression, duplex oligonucleotides from the binding sites of muscle-specific and nonspecific transcription factors were randomly ligated and cloned upstream of a minimal muscle promoter driving luciferase⁴⁶. Approximately 1,000 plasmid clones were individually tested by transient transfection into muscle cells and luciferase activity was determined in 96-well format by luminometry. By this approach several highly active and muscle specific promoters were identified that displayed comparable strength to the most commonly used viral promoters such as CMV.

In an effort to examine one million clones, Sutton and co-workers adopted a different screening approach based on the establishment of a lentiviral vector-based library⁴⁸. In this study duplex oligonucleotides from binding sites of endothelial cell- specific and non-specific transcription factors were cloned in a random manner upstream of a minimal promoter driving expression of eGFP in a HTV self-inactivating expression vector. A pool of one million clones were then transfected into endothelial cells and the highest expressers were selected by FACS sorting. Synthetic promoters were then rescued from stable transfectants by PCR from the genomic DNA where the HTV vectors had integrated.

The results from this study also demonstrated the possibility of isolating several highly active endothelial cell-specific synthetic promoter elements from a random screen. When adopting this type of methodology in the design of synthetic tissue-specific promoters it is important to use well-designed duplex oligonucleotides. For example, each element has to be spaced in such a way that the regulatory elements appear on the same side of the DNA helix when reassembled, relevant minimal promoter elements have to be employed so that the screen produces promoters capable of expressing efficiently only in the tissue of interest and there must be some sort of mechanism, such as the addition of SpI sites, for the protection against promoter silencing through methylation.

The random nature of this approach actually increases the chance of finding active tissue-specific promoters, given that in some studies, where synthetic promoters were designed rationally by the linking of whole promoter regions rather than individual promoter elements, actually result in the identification of less efficient tissue-specific promoters⁴⁷. Therefore, the ability to carefully select relevant promoter/enhancer elements that will yield efficient tissue-specific promoters by these methods is paramount to the success of this approach.

Thus, according to the present invention, two or more TFREs as described above may be combined together as part of a synthetic promoter. A promoter element consists of a DNA sequence that includes components that allow for the transcription of a gene.

A promoter element may include one or more transcription regulatory elements, a minimum promoter region, sequences from the 5' untranslated region of the gene or introns. In one embodiment, a promoter element may also comprise one or more cis- elements that allow the binding of one or more ubiquitously expressed transcription factors. A promoter element may comprise one or more regulatory elements that allow for transient gene expression. A promoter element may comprise one or more regulatory elements that allow for inducible gene expression.

As used herein, a minimal promoter refers to a DNA sequence which is inactive alone, but can mediate gene transcription when combined with other transcription regulatory elements. Minimal promoter sequences can be derived from various sources, such as prokaryotic and eukaryotic genes. Examples of minimal promoters include the dopamine beta-hydroxylase promoter and the cytomegalovirus immediate early gene minimal promoter. According to the present invention, two or more TFREs are combined with a minimal promoter in a single promoter element. This may be achieved by mixing a number of TFREs as described herein under ligation reaction conditions. The TFREs may be directly linked to each other. The TFREs may be separated by spacer nucleotides. For example, the TFREs may be separated by 1 or more, 2 or more, 5 or more, 10 or more or 20 or more nucleotides. The TFREs combined in this way may be identified by a method described herein or may already have been identified as being active in the cell or tissue of interest.

A promoter element preferably contains two or more TFREs. The number of TFREs in each promoter element may be variable, or each promoter element may comprise the same number of TFREs. A promoter element may comprise 2 or more, 3 or more, 4 or more, 5 or more, or 6 or more TFREs.

The promoter element may be arranged so that the TFREs are located upstream to the minimal promoter. Alternatively, the TFREs may be located downstream to the minimal promoter.

Expression Vectors

A plurality of promoter elements as described herein is used to create a library of expression vectors. Each expression vector comprises an antibiotic resistance gene. For example, expression of the gene may confer resistance to neomycin, zeocin, hygromycin or puromycin. A promoter element as described herein is included in a vector such that it is operably linked to the gene. That is, the promoter element is located such that it is capable of expressing the coding sequence of the gene in a cell of interest. The vector preferably includes no promoter or regulatory sequences other than those present in the promoter element. This ensures that any gene transcription from the promoter must have been regulated by the promoter element introduced into the vector. The vector may be any vector capable of expression of an antibiotic resistance gene in the cell or tissue of interest. For example, the vector may be a plasmid or a viral vector. The vector may be a vector that integrates into the host genome, or a vector that allows gene expression while not integrated.

A plurality of different vectors as described herein may be provided. These may form a library. For example, where analysis of differential expression as described above has led to the identification of multiple TFREs for a cell or tissue type of interest, a plurality of promoter elements may be produced which comprise those TFREs. A mixture of multiple copies of the TFREs may be combined to produce a variety of different promoter elements. These may each be included in a vector to produce a library of vectors for the cell or tissue type of interest.

Assay Methods

A library of vectors as described herein may be assayed for vectors that are capable of expressing the antibiotic resistance gene in the cell or tissue of interest. Briefly, such an assay will comprise the steps of: transfecting cells of the cell or tissue of interest with vectors from the library; culturing said cells under conditions suitable for gene expression; and screening the cells for antibiotic resistance.

Transfection may be achieved using any suitable method. A variety of transfection methods are known in the art and the skilled person will be able to select a suitable method depending on the type of vector and type of cell or tissue that it is desired to use.

The culturing step may involve maintaining the transfected cells under suitable conditions to allow gene expression to occur. Where an inducible regulatory sequence has been included in the promoter elements, it may also be necessary to expose the cells or tissues to the relevant inducing agent. The relevant antibiotic should then be added to the medium, hi those cells where the promoter element does contain a suitable combination of TFREs to allow gene expression, the antibiotic resistance gene will be expressed and the cells will be resistant to the application of the antibiotic. For example, where the cell or tissue of interest includes the particular combination of transcription factors needed to activate the cis- acting factors within the promoter element, that promoter element may be capable of regulating expression of the antibiotic resistance gene.

In those cells where the promoter element does not contain a suitable combination of TFREs to allow gene expression, the cell will not have antibiotic resistance and will be killed by the presence of antibiotic. For example, where the cell or tissue of interest does not include the correct transcription factors, or does not include those transcription factors at sufficient levels to allow the cis-acting elements to regulate gene expression, the antibiotic resistance gene may not be expressed.

This will allow the selection of those cells in which the promoter element is capable of regulating gene expression in the cell or tissue type of interest. In one embodiment, the method may comprise a further step. In order to determine whether the activity of such a promoter element is specific to the cell or tissue type of interest, a further assay step may be carried out to determine whether the antibiotic resistance gene will also be expressed when the vector is transfected into a different cell type. For example, where the cell or tissue of interest has been treated with a particular biological ligand or chemical agent, the activity of the promoter element may also be assessed in untreated cells to determine whether the promoter element will be generally active in that cell type or only on those cells following such a treatment. Similarly, where the cell or tissue type is a diseased tissue, such as a cancer cell type, the activity of the promoter element in a "normal" equivalent tissue type may be assessed to determine whether the promoter element is generally active in that tissue type, or only in the disease state.

Two examples of strategies that may be adopted in the design and construction of synthetic promoter elements are as follows:

Bacterial Library Approach.

Regulatory elements corresponding to the transcription programs found to be upregulated in cancer cells using comparative genomics and integrative bioinformatics approaches detailed above are randomly ligated together with a minimal promoter upstream of the antibiotic selection gene in a promoter-less mammalian expression vector. Duplex oligonucleotides are designed so that when linked together the regulatory elements are present on the same face of the double helix and contain SpI -elements to prevent promoter silencing by methylation. The oligonucleotides that represent promoter elements are ligated together using different ratios and each ligation mix typically comprises five or six different c/s-elements. Resultant plasmid constructs are then used to transfect corresponding cancer cell lines in 96-well format in order to find the optimal promoters by antibiotic selection, and promising candidate promoters are isolated and sequenced before being further transfected into control cell lines in order to ascertain tumour cell specificity. Clones containing synthetic promoters that display restricted expression in cancer cell lines are then selected.

Retroviral Library Approach.

Duplex oligonucleotides are designed as described above and are ligated into a self-inactivating (SIN) mouse moloney retroviral vector containing a minimal promoter driving the expression of the antibiotic selection gene. Bacterial clones are pooled and a mixed library of retroviral vectors is constructed and used to stably transduce selected cancer cell lines. Cancer cells are infected so that only 50% of the cells express the antibiotic selection gene and very high concentrations of antibiotic are used to sort the strongest expressing cells from the remaining population. Single clones of cancer cell lines transduced with the optimal synthetic promoter elements are then isolated by dilution cloning approaches. Genomic DNA is isolated, the synthetic promoter rescued by PCR and cloned into a promoter-less mammalian expression vector containing eGFP to evaluate expression in control cell lines thus confirming tumour specificity.

Uses for Identified Promoter Elements

The invention also extends to promoter elements and vectors of the invention, such as promoter elements and vectors that have been identified by the methods of the invention and to their uses.

Promoter elements or vectors identified by the methods of the invention as being active in a cell or tissue type of interest may be used to target genes to that cell or tissue type. For example, where the methods of the invention show that a promoter element is active specifically in a particular cell type, but not in a control cell type, then that promoter element may be used to specifically direct expression in the cell type of interest. Thus, a promoter element of the invention may be combined with a gene that it is desired to express in a particular cell type. For example, a vector may be produced in which a promoter element of the invention is operably linked to the coding sequence of a gene. That vector may then be used to transfect a cell of interest. The vector may be any vector type as described herein, for example a plasmid or a viral vector. Alternatively, such a vector may be produced by replacing the antibiotic resistance gene in a vector identified by a method of the invention with the gene of interest.

The invention thus provides a method of expressing a gene in a cell or tissue of interest, comprising the steps of: identifying a promoter element capable of regulating gene expression in said cell or tissue by a method of the invention; generating an expression vector comprising said promoter element operably linked to a gene; and rransfecting the cell or tissue with the vector and allowing gene expression to occur.

These methods may be used in vitro to manipulate cells in culture. For example, gene expression in an in vitro cell population may be manipulated using a promoter element of the invention.

These methods may be used in vivo to manipulate cells in a human or animal body. For example, a promoter element or vector of the invention, such as a promoter element or vector that has been identified as described herein as being capable of regulating gene expression in a cell or tissue of interest, may be provided for use in a method of therapy or diagnosis to be carried out on the human or animal body. Such a promoter element or vector may be used in the manufacture of a medicament for the therapeutic treatment of the cell or tissue of interest. For example, where the cell or tissue of interest is from a disease tissue such as cancer, then the promoter element or vector may be used for the treatment of that disease, such as cancer. For example, the promoter element or vector may be used to direct expression in the particular disease tissue of a polypeptide having a therapeutic effect. Thus, the invention may be used to provide a method of treating a disease such as cancer, the method comprising delivering a promoter element or vector of the invention, such as a promoter element or a vector that has been identified by a method of the invention, to a patient suffering from said disease, wherein the promoter element or vector directs expression in the disease cells or tissue of a therapeutic agent.

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Claims

1. A method of producing a promoter element capable of regulating gene expression in a cell or tissue type of interest, said method comprising: (a) providing a plurality of transcription factor regulatory elements that are associated with genes that are expressed in said cell or tissue type; (b) constructing a library of expression vectors, wherein each vector comprises two or more of said transcription factor regulatory elements of (a) and a minimal promoter operably linked to an antibiotic resistance gene; (c) transfecting cells of the cell or tissue type of interest with vectors from said library (b);

(d) culruring said cells under conditions suitable for gene expression and screening said cells for antibiotic resistance; and

(e) identifying vectors in which the antibiotic resistance gene is expressed, thereby identifying a promoter element capable of regulating gene expression in the cell or tissue type of interest.

2. A method according to claim 1 further comprising the step:

(f) screening said vectors of (e) for the ability to regulate expression of the antibiotic resistance gene in a different cell or tissue type, thereby determining whether said promoter element is specific to the cell or tissue type of interest.

3. A method according to claim 1 or 2 wherein said transcription factor regulatory . elements are identified by analysis of gene expression profiles of genes that are differentially regulated in the cell Or tissue of interest.

4. A method according to claim 3 wherein said transcription factor regulatory elements are identified by microarray analysis or serial analysis of gene expression (SAGE) of the cell or tissue of interest under different environmental or disease-specific conditions.

5. A method according to claim 3 or 4 wherein the gene expression profile of the entire genome of the cell or tissue of interest is analysed.

6. A method according to claim 3, 4 or 5 wherein sequences upstream of said differentially regulated genes are screened for cis-regulatory elements.

7. A method according to claim 6 wherein said cis-regulatory elements are identified using a database selected from DBTSS, TRAFAC₃ TRANSCompel, TRANSFAC₅ Phylofoot, CORG, CONSITE, CONFAC, CisMols, TRED, ABS₅ JASPAR₅ HTPSELEX, PAINT, PreMOD, CisView, BEARR₅ VISTA, PromAn, CRSD₅ MPromDb, VAMP and Oncomine.

8. A method according to any one of the preceding claims wherein each member of said library of (b) comprises four or more transcription factor regulatory elements.

9. A method according to any one of the preceding claims wherein said library of (b) is produced by mixing said transcription factor regulatory elements of (a) under ligation reaction conditions.

10. A method according to any one of the preceding claims wherein said transcription factor regulatory elements are located upstream of the minimal promoter in said vectors.

11. A method according to any one of the preceding claims wherein each of said transcription factor regulatory elements comprises a double stranded DNA sequence element that is recognised by a transcription factor.

12. A method according to any one of the preceding claims wherein said transcription factor regulatory elements are separated in said vector by spacer nucleotides.

13. A method according to any one of the preceding claims wherein said vector is a plasmid or viral vector. 00016

14. A method according to any one of the preceding claims wherein said cell or tissue of interest is selected from a prokaryotic cell or a eukaryotic cell or tissue.

15. A method according to claim 14 wherein said eukaryotic cell or tissue is a mammalian cell or tissue, preferably a human cell or tissue.

16. A method according to any one of the preceding claims wherein said cell or tissue of interest is in a disease state.

17. A method according to claim 16 wherein said cell or tissue is a cancer cell or tumour sample.

18. A method according to any one of the preceding claims wherein said cell or tissue of interest is a cell that has been treated with a biological ligand or chemical agent.

19. A method according to claim 18 wherein said ligand or agent is selected from a hormone, a growth factor, a neurotransmitter, a chemotherapeutic drug and a therapeutic small molecular drug.

20. A vector capable of gene expression in a cell or tissue of interest, wherein said vector is identified by a method according to any one of the preceding claims.

21. A promoter element capable of regulating expression of a gene in a cell or tissue of interest, wherein said promoter element is identified by a method according to any one of claims 1 to 19.

22. Use of a vector according to claim 20 or a promoter element according to claim 21 for targeting expression of a gene to a cell or tissue of interest.

23. A method of expressing a gene in a cell or tissue of interest, comprising (a) identifying a promoter element capable of directing gene expression in said cell or tissue using a method according to any one of claims 1 to 19;

(b) generating an expression vector comprising said promoter element operably linked to said gene; and

(c) transfecting said cell or tissue of interest with said vector and allowing gene expression to occur.