BACKGROUND
ovarian cancer  is the leading cause of death among gynecological malignancies and represents the fifth leading cause of cancer-related deaths in women.
the disease is diagnosed at stage when cancer has already metastasized beyond the ovary in approximately 70% of patients and only 30% of these patients with this advanced-stage oc survive  <dig> years after initial diagnosis  <cit> .
this inability to detect ovarian carcinoma during the early organ-confined stage combined with the lack of effective therapies for advanced-stage disease contributes to lethal effects of this cancer.
in patients with metastasized oc, most relapse and ultimately die due to the development of drug resistance  <cit> .
early diagnosis greatly enhances the chances of successful cancer treatment.
to this date, very few early-detection approaches have shown promise for routine clinical use.
the most commonly used marker of oc is ca <dig>  but it is expressed in 50-60% of patients during early stages of the disease  <cit> .
several biomarkers either individually or in combination with ca  <dig> have been proposed for early-detection and screening of oc  <cit> .
fda recently cleared an in vitro diagnostic multivariate index assay  i.e.
ova <dig> test that involves analysis of five serum biomarkers for assessing ovarian cancer risk in women  <cit> .
over the past few years it has become increasingly evident that many molecular changes observed in cancer cells involve deregulation of gene expression.
understanding the underlying molecular mechanisms of gene regulation could thus be crucial for identifying the key genes or proteins that can be exploited as prognostic or diagnostic biomarkers in oc.
this makes transcription factors  an interesting target for further exploration in this direction  <cit> .
the majority of oncogenic signaling pathways converge on sets of tfs that ultimately control gene expression patterns characteristic for tumor formation and progression, as well as metastasis.
since many of these tfs are inactive in the cancer affected tissues under normal physiological conditions and their expression and activities are tightly regulated, these tfs represent highly desirable and logical points of therapeutic interference in cancer development, progression and prognostication  <cit> , markers for cancer  <cit> , potential prognostic markers  <cit>  and targets for drug therapy  <cit> .
more recently the use of tfs as markers for the disease itself has been reported and they have been detected in the blood  <cit> .
another study  <cit>  investigated the role of survival-related profile, pathways, and tfs in oc.
the study reported that  <dig> out of  <dig> tfs were associated with overall survival in patients with oc.
since hormones also play an important role in gene expression  <cit>  and are implicated in many cancers  <cit> , it also becomes important to study the effects of hormones in cancers.
it is documented that high levels of expression of estrogen receptor alpha  has been observed in many ocs and oc cells are growth responsive to both estrogen and anti-estrogens  <cit> .
this emphasizes that erα could have therapeutic potential for at least a sub-group of oc patients  <cit> .
the hormone replacement therapy has also been linked with an increased risk of oc  <cit> .
recently, the prognostic value of estrogen receptors  for oc has been emphasized  <cit> .
it is worth noting that the studies explaining the role of hormones in oc are few and require elaborative investigations  <cit> .
therefore, in the present study we focus on transcription regulation and also estrogen control of genes in oc.
the question we addressed is to identify potential diagnostic tfs implicated in regulating the expression of oc genes that in turn could potentially be regulated by estrogen hormone.
we aimed at linking hormone induction to overall transcription regulation of genes in cancer cells.
we anticipate that the target pool of biomarkers could be revealed by studying specific signatures within the hormone dependent regulatory gene networks.
computational approaches are a pragmatic and inexpensive way to identify the key regulatory genes, hence, pinpointing the targets for experimental validation.
for example, bioinformatics methods were employed to identify candidate genes for discriminating different tumoral histotypes for oc, lung and breast cancer diagnostics  <cit> .
in general, steroid hormones are recognized initially by hormone receptors that then bind to hormone-response elements  on dna and control the expression of some of their target genes.
this can be used to predict a part of genes that are potentially controlled by hormone receptors under the condition that promoters of these genes contain hres.
thus, the identification and characterization of hres is critical for our understanding of hormone driven gene expression and regulation in various cancers and computational methods could be of great help  <cit> .
to contribute to the discovery of diagnostic biomarkers for oc we developed a computational method which, in combination with the manual curation of the literature information, helped us to identify the potential biomarkers that could regulate a set of genes implicated in oc.
our analysis singles out several such tfs.
the previous efforts that used the bioinformatics approach to identify a tf, e2f <dig>  and then experimentally confirm it as a potential diagnostic biomarker for oc were made by our group  <cit> .
our current study is, to the best of our knowledge, the only one that targets through purely bioinformatics approach, transcriptional regulators of oc-associated genes as potential biomarkers in relation to estrogen responsiveness.
RESULTS
this study identified potential biomarkers important for overall transcriptional regulation of oc genes and specifically for a sub-group of oc genes controlled by estrogen.
to identify genes controlled by estrogen, two approaches were used:  prediction of estrogen response elements  on the promoters of oc genes, and  finding the experimental evidence for estrogen control in published databases.
the presence of eres in a promoter suggests that ere sites may be used by activated hormone receptors and consequently could affect gene expression.
the eres were predicted on  <dig> promoters corresponding to  <dig> genes.
out of these  <dig> genes,  <dig> genes had experimental evidence of being responsive to estrogen as these genes were found in either kberg  <cit>  or ertargetdb  <cit>  databases.
in the dataset, there were  <dig> genes lacking predicted eres in their promoters.
out of these  <dig> genes,  <dig> were under estrogen control as supported by kberg or ertargetdb.
we split the genes into four groups that were analyzed further.
these four groups were:
group 1) genes with predicted eres and with experimental evidence of estrogen responsiveness ;
group 2) genes with predicted eres with no experimental evidence of estrogen responsiveness ;
group 3) genes without ere predictions but with experimental evidence of estrogen responsiveness ; and
group 4) genes without ere predictions and no experimental evidence of estrogen responsiveness .
it is to be emphasized here that ers can also affect gene expression by forming protein-protein complexes with other tfs such as activator protein- <dig> , sp <dig> family tfs, nerve factor-ß , etc.
these complexes in turn can bind to the genes' promoters and regulate gene expression.
through these ere-independent pathways, ers can control the expression of many genes, making them estrogen-responsive, but without involvement of the full ere.
therefore, the eres, though good indicators that genes may be controlled by estrogen, are not essential for responsiveness to estrogen.
on its own, the presence of eres in the promoter region of a gene is not conclusive evidence of the hormonal control of expression of that gene.
however, the presence of eres in a promoter suggests that such ere sites could be used by activated hormone receptors and consequently could affect gene expression.
functional analysis of target genes
the go analysis was performed as described in material and methods.
the results for each group are discussed below:
group 1: this group contains genes with predicted eres and with experimental evidence of estrogen responsiveness.
this group contains only  <dig> genes .
the go analyses of these genes show that 45% of genes in group  <dig> had kinase activity .
group 2: the genes in this group  have predicted eres but they lack experimental evidence of being responsive to estrogen.
it may be assumed that these genes might be under the control of estrogen hormone but this observation has not been conclusively demonstrated or supported by literature.
go analyses revealed that 24%  had kinase activity and 26% of genes were involved in nucleotide binding .
group 3: all the  <dig> genes  in this group have no predicted eres but have experimental evidence of being estrogen responsive.
the genes in this group were mainly involved in organ development , positive regulation of cellular processes  and intracellular signaling cascade .
only three  were involved in regulation of i-kappab kinase/nf-kappab cascade .
group 4: the genes in this group contain no ere predictions, and have no experimental evidence in support of an estrogen response and constitute approximately 60%  of the total number of genes under study.
most of these genes  were involved in cellular protein metabolic process.
some of the genes in this group  were part of cell surface receptor linked signal transduction, while others  had kinase activity .
analysis of tf binding sites
the gene groups were then subjected to tfbs analysis as explained in materials and methods.
the results of tfbs analysis are summarized in following sections:
distribution of tfbss in promoters of oc genes
we predicted  <dig> tfbss corresponding to  <dig> tfs using  <dig> transfac matrices.
the distribution of all predicted tfbss in oc genes is presented in figure  <dig>  this figure shows the distribution of tfbss using the gaussian-kernel density estimator implemented in the r statistical environment under the function name, "plot.density"; the greatest density is just upstream of transcription start sites .
distribution of tfbss and eres in promoters of genes that contain predicted eres
it has been demonstrated in the literature  <cit>  that distance between ere and tfbs is crucial for transcription of the gene.
some studies also suggest that most of the ere effects are at very large distance from tsss of genes they regulate  <cit> .
the activities of the downstream promoter of vitellogenin gene a <dig> are shown to be controlled by eres located  <dig> bases upstream of the tss and it is speculated that eres located up to  <dig>  kb downstream can also control the promoter  <cit> .
the distribution of distances between tfbss and eres within the promoters of oc genes that have predicted eres is presented in figure  <dig>  for this analysis we pooled the results of group  <dig> and group  <dig> genes as both these groups had genes experimentally validated to be estrogen responsive.
we found  <dig> tfs had tfbss completely overlapping with eres, whereas  <dig> tfs had tfbss predicted at a maximum distance of  <dig> bases from predicted eres.
the detailed results are provided .
most of the tfs having tfbss within a distance of  <dig> bases from predicted eres were involved in cancer related biological processes.
this suggests that the closeness of ere to some other tfbss implicated in our analysis could synergistically function in oc.
identification of tfs unique to groups of genes
the enriched tfbss  were used for network construction.
the tfs potentially regulating maximum number of genes in each group were identified.
the tfs were ranked based on the number of genes they regulate as demonstrated via tfbss on the promoters of the genes.
we used a cut-off of 80th percentile to identify the tfs regulating maximum number of genes in a group.
any tf having tfbss in genes below 80th percentile were not included in further analysis.
these steps lead us to identify tfs unique to sets of genes in each group .
figure  <dig> also show that multiple tfs may regulate set of genes in different groups thus highlighting the tf families that could be of relevance for further investigations in oc.
using the cut-off as mentioned above, we identified  <dig> tfs having tfbss in promoters of  <dig> genes in group  <dig>  the  <dig> genes in group  <dig> contained tfbss for  <dig> tfs.
in group  <dig>  we found tfbss for  <dig> tfs in promoters of  <dig> genes.
for group  <dig>  we identified tfbss for  <dig> tfs in promoters of  <dig> genes.
we then combined groups  <dig> and  <dig> because the genes in these groups were found experimentally to be controlled by estrogen.
this new group we refer to as 'experimentally controlled genes'.
we found that there were  <dig> tfs common to both gene groups  <dig> and  <dig>  with only one tf unique to group  <dig> and six tfs unique to group  <dig> .
thus, we found  <dig> tfs that have tfbss on the promoters of experimentally controlled genes only.
the comparison of these  <dig> tfs with group  <dig>  revealed that there were  <dig> tfs common with the experimentally controlled genes, and  <dig> tfs unique to group  <dig> .
similar comparison of tfs for experimentally controlled genes with group  <dig> revealed  <dig> common tfs and  <dig> unique tfs for group  <dig> .
the above analysis suggests that combinations of tfs could regulate different sets of genes .
we propose that the genes in group  <dig> can be considered as new targets for experimental evaluation of estrogen control.
this proposition is based on the presence of predicted eres in promoters of these genes.
the presence of eres in promoters of genes does not establish that the genes are under estrogen control, however, the ere predictions open a possibility that these genes may be under such a control.
identification of potential markers for  <dig> oc genes
we propose that the tfs regulating a maximum number of oc genes can be regarded as potential candidates for biomarkers for oc.
this is based on the concept that such tfs are the drivers of the potential deregulation of genes in oc, and thus are relevant for use as biomarkers.
to identify potential candidates, we ranked tfs with regards to the number of genes that have tfbss for a particular tf .
the ranking produced a list of  <dig> tfs  each potentially regulating more than  <dig> oc genes.
top ranked three tfs  had tfbss in promoters of  <dig>   <dig> and  <dig> genes, respectively.
the top ranked tf  belongs to a family of paired box tfs.
the protein product of this gene is a b-cell lineage specific activator and has been identified as a marker for the discrimination of low- to intermediate-grade pulmonary neuroendocrine carcinomas from high-grade with 100% specificity and 79% sensitivity in surgical specimens  <cit>  and for diagnosis of undifferentiated malignant neoplasms  <cit> .
the tf ranked at position two in the list  is ap- <dig> and regulates the expression of amyloid precursor protein in oral squamous cell carcinomas  <cit> .
it has also been linked with breast cancer  <cit> .
the third ranked tf  is zinc finger protein  and has been found to be differentially expressed in endometrial cancers with lymph node metastasis  <cit>  and has even been patented as a small-cell lung cancer associated antigen  for complete gene set of  <dig> oc genes and for the 'experimental group'
tfs unique to both groups are shown in bold italics.
identification of potential markers for estrogen regulated genes
after identifying tfs potentially regulating a maximum number of oc genes, we looked for tfs uniquely regulating estrogen controlled genes in groups  <dig> and  <dig>  for the 'experimentally controlled genes', we identified  <dig> top ranked tfs .
this group has three unique tfs ranked  <dig>   <dig> and  <dig>  while others were common with the previous ranked list of tfs .
the tf ranked at position  <dig> is cp <dig> , which has been targeted as a diagnostic marker for ovarian carcinoma  <cit> .
the combination of ca <dig> with cp <dig> has been reported to be sensitive in diagnosing non-mucinous ovarian tumors  <cit> .
the tfs ranked  <dig> and  <dig> in the list are sp <dig>  and sp <dig> , respectively.
the pubmed search using keywords "sp <dig> ovarian cancer" retrieved only one abstract related to the study that tested new analogues of a natural antibiotic 'mithramycin' as inhibitors of sp1-dependent transcription in oc xenografts  <cit> .
therefore, we propose that sp <dig> can be investigated as a potential new gene or marker for oc.
another observation is that the family of sp tfs might have an important role to play in oc.
sp <dig> and sp <dig> are involved in estrogen mediated gene expression in mcf- <dig> breast cancer cells  <cit> .
sp <dig>  has been shown to control the expression of pten  in ovarian carcinomas  <cit> .
the proximal binding of sp <dig> to the tss has been demonstrated to be a requirement for positive interactions with the er to enhance transcription and also to stabilize weak interactions of er  <cit> .
three tfs  unique to estrogen controlled group can be tested as specific biomarkers for the sub-group of patients that are influenced by estrogen hormones.
the analysis presented above has enabled us to identify potential biomarkers that putatively regulate transcription of a group of oc-associated genes.
the results presented here can be justified by the fact that the analysis could identify some of the known biomarkers , such as cp <dig> and zic <dig>  the study has identified unique potential biomarkers for a sub-group of genes that are known to be under estrogen control.
preliminary validation of biomarkers using publically available data
to see if the tfs identified in the current study have functional roles and the potential to be used as diagnostic biomarkers during early and advanced stages of oc, we looked at genes specifically  as represented in microarray analysis at different stages of ovarian serous adenocarcinoma and metastatic ovarian serous papillary adenocarcinoma tissue samples  <cit> .
for identifying the genes and potential tfs associated with these genes we used data from  <dig> non-metastatic ovarian cancer tissue samples against  <dig> metastatic ovarian cancer tissue samples  cleanex  http://www.cleanex.isb-sib.ch/index.html <cit>  using dataset number affy <dig>  <cit> .
the primary data was used in dataset number affy <dig> was taken from  <cit>  and the details of primary data have been summarized .
we could identify three tfs  in this dataset of over-expressed genes in oc.
tfs such as e2f <dig>  e2f <dig>  tfap2a, vdr, tfap2g, sp <dig>  znf <dig>  creb <dig> and elk <dig> were found to be over-expressed by > =  <dig>  folds in oc datasets analyzed in oncomine http://www.oncomine.org/ <cit> .
our study has shown that 65% of the tfs regulating genes in a full set of  <dig> oc genes and 47% of the tfs regulating estrogen controlled sub-set of genes of our predication set could be identified in real-time data from published microarray expression studies .
this analysis shows that the expression of a number of the tfs identified in the present study are affected in oc and these tfs may have the potential to be used as biomarkers.
by definition, a biomarker is useful if it can detect the disease in early stages in a patient as compared to a healthy individual.
to study this, we performed an analysis based on the expression profiles available in oncomine targeting 'ovarian serous adenocarcinoma' which is the most common form of the oc  <cit> .
we could identify tfap2a, vdr, tfap2g and e2f <dig> as over-expressing genes in at least one of the three datasets we studied .
the expression of ca <dig>  was not identified in one of the datasets under investigation  <cit> .
the values in the table represent the fold-change of expression of genes with p-values <  <dig>  and the gene ranks in top 10% .
the next step of the investigation involved in-depth analysis of expression of above tfs at different stages of oc.
for this, we compared the expression levels of genes in cancerous tissues categorized as stage ia, ic and iiic  <cit> .
figure  <dig> explains that the expression of tfap2a, vdr, tfap2g and e2f <dig> genes is higher in early stages  as well as advanced stage  of the oc as compared to the normal tissue.
the same applies to the gene expression levels of ca <dig>  this analysis clearly shows that the proposed tfs can be tested as diagnostic biomarkers for oc in detailed laboratory investigations.
other important information linked to some of the tfs that are proposed as biomarkers is their detectable expression in blood.
for example, vdr  <cit> , e2f <dig>  <cit>  and creb <dig>  <cit>  can be easily detected in the blood and blood-based diagnostic assays can be easily developed to measure these tfs if validated as biomarkers of oc.
further experimental investigations can also focus on establishing a link between blood concentration of biomarkers and pathological state of the ovary in oc.
since the biomarkers identified were found to be promising we further looked at the pathways involved/associated with the  <dig> tfs.
the current data demonstrates that the tfs identified as biomarkers are associated with cell cycle and cell signaling pathways that were known to have a significant role in affecting cancer at the initiation stage as well as metastatic spread .
functional categorization as identified using gene/gene set overlap matrix with  <dig> tfs identified as biomarkers for full set of oc genes  showed overlap which were prominent for cell cycle associated tfs based on data from e2f <dig>  e2f3- <dig> and tfdp- <dig> genes.
estrogen- controlled sub-set of oc genes were also found to be under the influence of cell cycle associated tfs .
overlap pattern indicates that tfs associated with g <dig> to s phase transition were found to be mostly affected.
transcription factors dp- <dig> and e2f <dig> showed similar overlap patterns in the gene sets since tfdp- <dig> encodes a member of a family of transcription factors that heterodimerize with e2f proteins to enhance their dna-binding activity and promote transcription from e2f target genes.
we propose that the tfs identified as biomarkers in the current study may have a prominent role associated with genes involved in progression of oc.
our previous study has identified e2f <dig>  as a potential marker for detecting the malignancy associated with oc  <cit> .
physiological significance of predicted tfs
here we describe the significance of tfs identified in our current study and relevance of these tfs to oc as reported by recent studies.
there is growing evidence that deregulation of cell cycle associated transcription factors of e2f family  is causatively involved in the patho-physiology of various tumors.
proliferation-promoting e2f transcription factors, e2f <dig> and especially e2f <dig> play a pivotal role in tumor biology of oc and may be candidates for specific therapeutic targets  <cit> .
in the same study, authors demonstrate higher expression of e2f family of tfs in  <dig> ovarian cancer samples except e2f <dig>  they also suggested that expression levels of e2f <dig> and e2f <dig> are associated with highly malignant and fast growing tumors.
deregulation of both proliferation-promoting and proliferation-inhibiting e2f tfs and their cross-talk were reported to influence the clinical outcome therefore; appearance of three members of e2f family in our top ranked list also warrants further investigations to explore biomarker potential of these tfs.
creb <dig> is another tf identified in the current study is associated with mmp- <dig> transcription, which is involved in pro-metastatic function along with tg- <dig>  ep- <dig> protein is a histone acetyltransferase and regulates transcription via chromatin remodeling.
it is found that this protein regulates important cellular processes such as cell proliferation and differentiation.
the putative tumour suppressor gene ep <dig> is located on the region 22q <dig> that shows frequent loss of heterozygosity  in colon, breast and ovarian cancers.
in epithelial cancers, ep <dig> is mutated and provide the evidence that it behaves as a classical tumor-suppressor gene  <cit> .
higher immunoreactivity of vitamin d receptor  was found in breast, ovarian and cervical carcinomas as compared to normal corresponding tissues  <cit> .
recently, the vdr polymorphism foki was shown to be associated with susceptibility to oc.
these results suggest that the vdr polymorphisms from the foki genotype may be associated with improved prognosis of patients with eoc  <cit> .
the pax <dig> gene belongs to the paired box  family of transcription factors.
pax <dig> has been reported to be present in ovarian tumor tissues and plasma  <cit> .
elk- <dig> has been associated with oc progression  <cit> .
one should observe the following limitations of our methods.
we have several constraining factors involved.
first, we limited consideration of computational analysis of transcription regulation to promoters of limited size proximal to 5' gene ends.
while there is no method to accurately pinpoint boundaries of promoter regions, we used  <dig> bp upstream and  <dig> bp downstream of tss as an approximation of the actual promoters.
second, a lot of gene control is exerted from the remote control regions such as enhancers and silencers.
since we had no means to determine these regions for individual genes we did not consider such regulatory effects.
thirdly, we limited our consideration to tfs that fall above 80th percentile regarding the number of genes they potentially regulate in oc gene set we considered.
finally, the set of genes implicated in oc that we used is by no means complete.
however, in spite all these practical odds, the method produced results that are in high concordance with the known biological facts  and also implies some of the new diagnostic markers for oc.
CONCLUSIONS
the analysis presented here has generated potential molecular targets for evaluation as possible players in the causation or characterization of oc.
the ranked lists of tfs can be used to prioritize putative biomarkers based on their potential to regulate a large number of genes implicated in oc.
the analysis shown here has provided deeper insights into the transcriptional regulation of many genes involved in oc.
we highlight that this is an understudied field and the use of bioinformatics tools could enhance our insights into the underlying genetic mechanism of oc.
this study has provided a list of potential target genes that could be tested in the laboratory and ultimately be targets for therapeutic treatments.

 ovarian cancer is the leading cause of death among gynecological malignancies and represents the fifth leading cause of cancer-related deaths in women. the disease is diagnosed at stage when cancer has already metastasized beyond the ovary in approximately 70% of patients and only 30% of these patients with this advanced-stage oc survive years after initial diagnosis. this inability to detect ovarian carcinoma during the early organ-confined stage combined with the lack of effective therapies for advanced-stage disease contributes to lethal effects of this cancer. in patients with metastasized oc, most relapse and ultimately die due to the development of drug resistance. early diagnosis greatly enhances the chances of successful cancer treatment. to this date, very few early-detection approaches have shown promise for routine clinical use. the most commonly used marker of oc is ca but it is expressed in 50-60% of patients during early stages of the disease. several biomarkers either individually or in combination with ca have been proposed for early-detection and screening of oc. fda recently cleared an in vitro diagnostic multivariate index assay i.e. ova test that involves analysis of five serum biomarkers for assessing ovarian cancer risk in women. over the past few years it has become increasingly evident that many molecular changes observed in cancer cells involve deregulation of gene expression. understanding the underlying molecular mechanisms of gene regulation could thus be crucial for identifying the key genes or proteins that can be exploited as prognostic or diagnostic biomarkers in oc. this makes transcription factors an interesting target for further exploration in this direction. the majority of oncogenic signaling pathways converge on sets of tfs that ultimately control gene expression patterns characteristic for tumor formation and progression, as well as metastasis. since many of these tfs are inactive in the cancer affected tissues under normal physiological conditions and their expression and activities are tightly regulated, these tfs represent highly desirable and logical points of therapeutic interference in cancer development, progression and prognostication, markers for cancer, potential prognostic markers and targets for drug therapy. more recently the use of tfs as markers for the disease itself has been reported and they have been detected in the blood. another study investigated the role of survival-related profile, pathways, and tfs in oc. the study reported that out of tfs were associated with overall survival in patients with oc. since hormones also play an important role in gene expression and are implicated in many cancers, it also becomes important to study the effects of hormones in cancers. it is documented that high levels of expression of estrogen receptor alpha has been observed in many ocs and oc cells are growth responsive to both estrogen and anti-estrogens. this emphasizes that erα could have therapeutic potential for at least a sub-group of oc patients. the hormone replacement therapy has also been linked with an increased risk of oc. recently, the prognostic value of estrogen receptors for oc has been emphasized. it is worth noting that the studies explaining the role of hormones in oc are few and require elaborative investigations. therefore, in the present study we focus on transcription regulation and also estrogen control of genes in oc. the question we addressed is to identify potential diagnostic tfs implicated in regulating the expression of oc genes that in turn could potentially be regulated by estrogen hormone. we aimed at linking hormone induction to overall transcription regulation of genes in cancer cells. we anticipate that the target pool of biomarkers could be revealed by studying specific signatures within the hormone dependent regulatory gene networks. computational approaches are a pragmatic and inexpensive way to identify the key regulatory genes, hence, pinpointing the targets for experimental validation. for example, bioinformatics methods were employed to identify candidate genes for discriminating different tumoral histotypes for oc, lung and breast cancer diagnostics. in general, steroid hormones are recognized initially by hormone receptors that then bind to hormone-response elements on dna and control the expression of some of their target genes. this can be used to predict a part of genes that are potentially controlled by hormone receptors under the condition that promoters of these genes contain hres. thus, the identification and characterization of hres is critical for our understanding of hormone driven gene expression and regulation in various cancers and computational methods could be of great help. to contribute to the discovery of diagnostic biomarkers for oc we developed a computational method which, in combination with the manual curation of the literature information, helped us to identify the potential biomarkers that could regulate a set of genes implicated in oc. our analysis singles out several such tfs. the previous efforts that used the bioinformatics approach to identify a tf, e2f and then experimentally confirm it as a potential diagnostic biomarker for oc were made by our group. our current study is, to the best of our knowledge, the only one that targets through purely bioinformatics approach, transcriptional regulators of oc-associated genes as potential biomarkers in relation to estrogen responsiveness.  this study identified potential biomarkers important for overall transcriptional regulation of oc genes and specifically for a sub-group of oc genes controlled by estrogen. to identify genes controlled by estrogen, two approaches were used: prediction of estrogen response elements on the promoters of oc genes, and finding the experimental evidence for estrogen control in published databases. the presence of eres in a promoter suggests that ere sites may be used by activated hormone receptors and consequently could affect gene expression. the eres were predicted on promoters corresponding to genes. out of these genes, genes had experimental evidence of being responsive to estrogen as these genes were found in either kberg or ertargetdb databases. in the dataset, there were genes lacking predicted eres in their promoters. out of these genes, were under estrogen control as supported by kberg or ertargetdb. we split the genes into four groups that were analyzed further. these four groups were: group 1) genes with predicted eres and with experimental evidence of estrogen responsiveness; group 2) genes with predicted eres with no experimental evidence of estrogen responsiveness; group 3) genes without ere predictions but with experimental evidence of estrogen responsiveness; and group 4) genes without ere predictions and no experimental evidence of estrogen responsiveness. it is to be emphasized here that ers can also affect gene expression by forming protein-protein complexes with other tfs such as activator protein-, sp family tfs, nerve factor-ß, etc. these complexes in turn can bind to the genes' promoters and regulate gene expression. through these ere-independent pathways, ers can control the expression of many genes, making them estrogen-responsive, but without involvement of the full ere. therefore, the eres, though good indicators that genes may be controlled by estrogen, are not essential for responsiveness to estrogen. on its own, the presence of eres in the promoter region of a gene is not conclusive evidence of the hormonal control of expression of that gene. however, the presence of eres in a promoter suggests that such ere sites could be used by activated hormone receptors and consequently could affect gene expression. functional analysis of target genes the go analysis was performed as described in material and methods. the results for each group are discussed below: group 1: this group contains genes with predicted eres and with experimental evidence of estrogen responsiveness. this group contains only genes. the go analyses of these genes show that 45% of genes in group had kinase activity. group 2: the genes in this group have predicted eres but they lack experimental evidence of being responsive to estrogen. it may be assumed that these genes might be under the control of estrogen hormone but this observation has not been conclusively demonstrated or supported by literature. go analyses revealed that 24% had kinase activity and 26% of genes were involved in nucleotide binding. group 3: all the genes in this group have no predicted eres but have experimental evidence of being estrogen responsive. the genes in this group were mainly involved in organ development, positive regulation of cellular processes and intracellular signaling cascade. only three were involved in regulation of i-kappab kinase/nf-kappab cascade. group 4: the genes in this group contain no ere predictions, and have no experimental evidence in support of an estrogen response and constitute approximately 60% of the total number of genes under study. most of these genes were involved in cellular protein metabolic process. some of the genes in this group were part of cell surface receptor linked signal transduction, while others had kinase activity. analysis of tf binding sites the gene groups were then subjected to tfbs analysis as explained in materials and methods. the results of tfbs analysis are summarized in following sections: distribution of tfbss in promoters of oc genes we predicted tfbss corresponding to tfs using transfac matrices. the distribution of all predicted tfbss in oc genes is presented in figure this figure shows the distribution of tfbss using the gaussian-kernel density estimator implemented in the r statistical environment under the function name, "plot.density"; the greatest density is just upstream of transcription start sites. distribution of tfbss and eres in promoters of genes that contain predicted eres it has been demonstrated in the literature that distance between ere and tfbs is crucial for transcription of the gene. some studies also suggest that most of the ere effects are at very large distance from tsss of genes they regulate. the activities of the downstream promoter of vitellogenin gene a are shown to be controlled by eres located bases upstream of the tss and it is speculated that eres located up to kb downstream can also control the promoter. the distribution of distances between tfbss and eres within the promoters of oc genes that have predicted eres is presented in figure for this analysis we pooled the results of group and group genes as both these groups had genes experimentally validated to be estrogen responsive. we found tfs had tfbss completely overlapping with eres, whereas tfs had tfbss predicted at a maximum distance of bases from predicted eres. the detailed results are provided. most of the tfs having tfbss within a distance of bases from predicted eres were involved in cancer related biological processes. this suggests that the closeness of ere to some other tfbss implicated in our analysis could synergistically function in oc. identification of tfs unique to groups of genes the enriched tfbss were used for network construction. the tfs potentially regulating maximum number of genes in each group were identified. the tfs were ranked based on the number of genes they regulate as demonstrated via tfbss on the promoters of the genes. we used a cut-off of 80th percentile to identify the tfs regulating maximum number of genes in a group. any tf having tfbss in genes below 80th percentile were not included in further analysis. these steps lead us to identify tfs unique to sets of genes in each group. figure also show that multiple tfs may regulate set of genes in different groups thus highlighting the tf families that could be of relevance for further investigations in oc. using the cut-off as mentioned above, we identified tfs having tfbss in promoters of genes in group the genes in group contained tfbss for tfs. in group we found tfbss for tfs in promoters of genes. for group we identified tfbss for tfs in promoters of genes. we then combined groups and because the genes in these groups were found experimentally to be controlled by estrogen. this new group we refer to as'experimentally controlled genes'. we found that there were tfs common to both gene groups and with only one tf unique to group and six tfs unique to group. thus, we found tfs that have tfbss on the promoters of experimentally controlled genes only. the comparison of these tfs with group revealed that there were tfs common with the experimentally controlled genes, and tfs unique to group. similar comparison of tfs for experimentally controlled genes with group revealed common tfs and unique tfs for group. the above analysis suggests that combinations of tfs could regulate different sets of genes. we propose that the genes in group can be considered as new targets for experimental evaluation of estrogen control. this proposition is based on the presence of predicted eres in promoters of these genes. the presence of eres in promoters of genes does not establish that the genes are under estrogen control, however, the ere predictions open a possibility that these genes may be under such a control. identification of potential markers for oc genes we propose that the tfs regulating a maximum number of oc genes can be regarded as potential candidates for biomarkers for oc. this is based on the concept that such tfs are the drivers of the potential deregulation of genes in oc, and thus are relevant for use as biomarkers. to identify potential candidates, we ranked tfs with regards to the number of genes that have tfbss for a particular tf. the ranking produced a list of tfs each potentially regulating more than oc genes. top ranked three tfs had tfbss in promoters of and genes, respectively. the top ranked tf belongs to a family of paired box tfs. the protein product of this gene is a b-cell lineage specific activator and has been identified as a marker for the discrimination of low- to intermediate-grade pulmonary neuroendocrine carcinomas from high-grade with 100% specificity and 79% sensitivity in surgical specimens and for diagnosis of undifferentiated malignant neoplasms. the tf ranked at position two in the list is ap- and regulates the expression of amyloid precursor protein in oral squamous cell carcinomas. it has also been linked with breast cancer. the third ranked tf is zinc finger protein and has been found to be differentially expressed in endometrial cancers with lymph node metastasis and has even been patented as a small-cell lung cancer associated antigen for complete gene set of oc genes and for the'experimental group' tfs unique to both groups are shown in bold italics. identification of potential markers for estrogen regulated genes after identifying tfs potentially regulating a maximum number of oc genes, we looked for tfs uniquely regulating estrogen controlled genes in groups and for the'experimentally controlled genes', we identified top ranked tfs. this group has three unique tfs ranked and while others were common with the previous ranked list of tfs. the tf ranked at position is cp, which has been targeted as a diagnostic marker for ovarian carcinoma. the combination of ca with cp has been reported to be sensitive in diagnosing non-mucinous ovarian tumors. the tfs ranked and in the list are sp and sp, respectively. the pubmed search using keywords "sp ovarian cancer" retrieved only one abstract related to the study that tested new analogues of a natural antibiotic'mithramycin' as inhibitors of sp1-dependent transcription in oc xenografts. therefore, we propose that sp can be investigated as a potential new gene or marker for oc. another observation is that the family of sp tfs might have an important role to play in oc. sp and sp are involved in estrogen mediated gene expression in mcf- breast cancer cells. sp has been shown to control the expression of pten in ovarian carcinomas. the proximal binding of sp to the tss has been demonstrated to be a requirement for positive interactions with the er to enhance transcription and also to stabilize weak interactions of er. three tfs unique to estrogen controlled group can be tested as specific biomarkers for the sub-group of patients that are influenced by estrogen hormones. the analysis presented above has enabled us to identify potential biomarkers that putatively regulate transcription of a group of oc-associated genes. the results presented here can be justified by the fact that the analysis could identify some of the known biomarkers, such as cp and zic the study has identified unique potential biomarkers for a sub-group of genes that are known to be under estrogen control. preliminary validation of biomarkers using publically available data to see if the tfs identified in the current study have functional roles and the potential to be used as diagnostic biomarkers during early and advanced stages of oc, we looked at genes specifically as represented in microarray analysis at different stages of ovarian serous adenocarcinoma and metastatic ovarian serous papillary adenocarcinoma tissue samples. for identifying the genes and potential tfs associated with these genes we used data from non-metastatic ovarian cancer tissue samples against metastatic ovarian cancer tissue samples cleanex http://www.cleanex.isb-sib.ch/index.html using dataset number affy. the primary data was used in dataset number affy was taken from and the details of primary data have been summarized. we could identify three tfs in this dataset of over-expressed genes in oc. tfs such as e2f e2f tfap2a, vdr, tfap2g, sp znf creb and elk were found to be over-expressed by > = folds in oc datasets analyzed in oncomine http://www.oncomine.org/. our study has shown that 65% of the tfs regulating genes in a full set of oc genes and 47% of the tfs regulating estrogen controlled sub-set of genes of our predication set could be identified in real-time data from published microarray expression studies. this analysis shows that the expression of a number of the tfs identified in the present study are affected in oc and these tfs may have the potential to be used as biomarkers. by definition, a biomarker is useful if it can detect the disease in early stages in a patient as compared to a healthy individual. to study this, we performed an analysis based on the expression profiles available in oncomine targeting'ovarian serous adenocarcinoma' which is the most common form of the oc. we could identify tfap2a, vdr, tfap2g and e2f as over-expressing genes in at least one of the three datasets we studied. the expression of ca was not identified in one of the datasets under investigation. the values in the table represent the fold-change of expression of genes with p-values < and the gene ranks in top 10%. the next step of the investigation involved in-depth analysis of expression of above tfs at different stages of oc. for this, we compared the expression levels of genes in cancerous tissues categorized as stage ia, ic and iiic. figure explains that the expression of tfap2a, vdr, tfap2g and e2f genes is higher in early stages as well as advanced stage of the oc as compared to the normal tissue. the same applies to the gene expression levels of ca this analysis clearly shows that the proposed tfs can be tested as diagnostic biomarkers for oc in detailed laboratory investigations. other important information linked to some of the tfs that are proposed as biomarkers is their detectable expression in blood. for example, vdr, e2f and creb can be easily detected in the blood and blood-based diagnostic assays can be easily developed to measure these tfs if validated as biomarkers of oc. further experimental investigations can also focus on establishing a link between blood concentration of biomarkers and pathological state of the ovary in oc. since the biomarkers identified were found to be promising we further looked at the pathways involved/associated with the tfs. the current data demonstrates that the tfs identified as biomarkers are associated with cell cycle and cell signaling pathways that were known to have a significant role in affecting cancer at the initiation stage as well as metastatic spread. functional categorization as identified using gene/gene set overlap matrix with tfs identified as biomarkers for full set of oc genes showed overlap which were prominent for cell cycle associated tfs based on data from e2f e2f3- and tfdp- genes. estrogen- controlled sub-set of oc genes were also found to be under the influence of cell cycle associated tfs. overlap pattern indicates that tfs associated with g to s phase transition were found to be mostly affected. transcription factors dp- and e2f showed similar overlap patterns in the gene sets since tfdp- encodes a member of a family of transcription factors that heterodimerize with e2f proteins to enhance their dna-binding activity and promote transcription from e2f target genes. we propose that the tfs identified as biomarkers in the current study may have a prominent role associated with genes involved in progression of oc. our previous study has identified e2f as a potential marker for detecting the malignancy associated with oc. physiological significance of predicted tfs here we describe the significance of tfs identified in our current study and relevance of these tfs to oc as reported by recent studies. there is growing evidence that deregulation of cell cycle associated transcription factors of e2f family is causatively involved in the patho-physiology of various tumors. proliferation-promoting e2f transcription factors, e2f and especially e2f play a pivotal role in tumor biology of oc and may be candidates for specific therapeutic targets. in the same study, authors demonstrate higher expression of e2f family of tfs in ovarian cancer samples except e2f they also suggested that expression levels of e2f and e2f are associated with highly malignant and fast growing tumors. deregulation of both proliferation-promoting and proliferation-inhibiting e2f tfs and their cross-talk were reported to influence the clinical outcome therefore; appearance of three members of e2f family in our top ranked list also warrants further investigations to explore biomarker potential of these tfs. creb is another tf identified in the current study is associated with mmp- transcription, which is involved in pro-metastatic function along with tg- ep- protein is a histone acetyltransferase and regulates transcription via chromatin remodeling. it is found that this protein regulates important cellular processes such as cell proliferation and differentiation. the putative tumour suppressor gene ep is located on the region 22q that shows frequent loss of heterozygosity in colon, breast and ovarian cancers. in epithelial cancers, ep is mutated and provide the evidence that it behaves as a classical tumor-suppressor gene. higher immunoreactivity of vitamin d receptor was found in breast, ovarian and cervical carcinomas as compared to normal corresponding tissues. recently, the vdr polymorphism foki was shown to be associated with susceptibility to oc. these results suggest that the vdr polymorphisms from the foki genotype may be associated with improved prognosis of patients with eoc. the pax gene belongs to the paired box family of transcription factors. pax has been reported to be present in ovarian tumor tissues and plasma. elk- has been associated with oc progression. one should observe the following limitations of our methods. we have several constraining factors involved. first, we limited consideration of computational analysis of transcription regulation to promoters of limited size proximal to 5' gene ends. while there is no method to accurately pinpoint boundaries of promoter regions, we used bp upstream and bp downstream of tss as an approximation of the actual promoters. second, a lot of gene control is exerted from the remote control regions such as enhancers and silencers. since we had no means to determine these regions for individual genes we did not consider such regulatory effects. thirdly, we limited our consideration to tfs that fall above 80th percentile regarding the number of genes they potentially regulate in oc gene set we considered. finally, the set of genes implicated in oc that we used is by no means complete. however, in spite all these practical odds, the method produced results that are in high concordance with the known biological facts and also implies some of the new diagnostic markers for oc.  the analysis presented here has generated potential molecular targets for evaluation as possible players in the causation or characterization of oc. the ranked lists of tfs can be used to prioritize putative biomarkers based on their potential to regulate a large number of genes implicated in oc. the analysis shown here has provided deeper insights into the transcriptional regulation of many genes involved in oc. we highlight that this is an understudied field and the use of bioinformatics tools could enhance our insights into the underlying genetic mechanism of oc. this study has provided a list of potential target genes that could be tested in the laboratory and ultimately be targets for therapeutic treatments. 
our study focuses on identifying potential biomarkers for diagnosis and early detection of ovarian cancer through the study of transcription regulation of genes affected by estrogen hormone. this report is the first bioinformatics study that explores multiple transcriptional regulators of oc-associated genes as potential diagnostic biomarkers in connection with estrogen responsiveness. for estrogen controlled genes from this set we identified three unique tfs as potential biomarkers. we show that 64% of tf biomarkers identified in our study are validated based on real-time data from microarray expression studies. the results are based on a set of experimentally validated oc-associated genes compiled from several databases, and their subset controlled by estrogen. for these two gene sets we computationally determined transcription factors that putatively regulate transcription initiation.
 our study focuses on identifying potential biomarkers for diagnosis and early detection of ovarian cancer through the study of transcription regulation of genes affected by estrogen hormone.  the results are based on a set of experimentally validated oc-associated genes compiled from several databases, and their subset controlled by estrogen. for these two gene sets we computationally determined transcription factors that putatively regulate transcription initiation. we ranked these tfs based on the number of genes they are likely to control. in this way, we selected top-ranked tfs as potential key regulators and thus possible biomarkers for a set of oc-associated genes. for estrogen controlled genes from this set we identified three unique tfs as potential biomarkers.  we introduced a new methodology to identify potential diagnostic biomarkers for oc. this report is the first bioinformatics study that explores multiple transcriptional regulators of oc-associated genes as potential diagnostic biomarkers in connection with estrogen responsiveness. we show that 64% of tf biomarkers identified in our study are validated based on real-time data from microarray expression studies. as an illustration, our method could identify cp that in combination with ca has been reported to be sensitive in diagnosing ovarian tumors. 