BACKGROUND
processes and pathways, whose deregulation may contribute to the development of cancers  <cit> , are often represented as cascades of proteins transmitting a signal from the cell surface to the nucleus.
however, the delineation of the canonical members of these cellular pathways is based on a multitude of experimental methods, and some inconsistencies exist across databases  <cit> .
indeed, the assignment of a protein to a pathway often relies on the experimental procedure and on a subjective assessment of the protein's importance for the process.
many closely associated regulators, effectors or targets of cellular pathways may therefore have been overlooked by these classical approaches.
additionally, recent functional genomics high-throughput initiatives have identified a large number of interaction partners for signalling proteins, suggesting more complex relationships between cellular pathways than in their traditional representations  <cit> .
in this context, the analysis of cancer mutated genes at the level of canonical cellular processes and pathways may previously have missed potentially interesting findings.
this paper introduces a new methodology to amalgamate the information from cellular process and pathway databases with large-scale protein-protein interaction data.
previous approaches for in-silico generation of cellular processes based on molecular interaction data have constructed pathways from scratch , and related approaches for disease candidate gene prioritisation also rely on interaction network data to identify molecules which are associated with a gene set  <cit> .
however, to the best of the authors' knowledge an extension approach which preserves existing process definitions has not yet been investigated.
here, we present a procedure for extending cellular pathways and processes by mapping them onto a protein-protein interaction network and identifying densely interconnected interaction partners.
briefly, we map proteins annotated for different cellular processes onto a large protein-protein interaction network, and extend each of these processes by adding their most densely interconnected network partners .
these added proteins display distinctive network topological features and molecular function annotations and can be proposed as putative new components of the corresponding cellular process, and/or as regulators of the communication between different cellular processes.
this is illustrated by the prediction of new alzheimer disease candidate genes and the identification of proteins with potential involvement in the crosstalk between several interleukin signalling pathways.
finally, we employ the extension procedure to investigate mutated genes from a large-scale resequencing study of pancreatic tumours.
we identified many pathways and processes enriched in mutated genes, as well as cancer mutated genes predicted to be involved in specific pathway deregulations.
implementation
all data processing and analysis steps were implemented in the programming language r. the web-based pathway visualisation on http://www.infobiotics.net/pathexpand was implemented in php.
interaction network construction
the human protein-protein interactions were combined from  <dig> public databases, as of july,  <dig>  these include mips  <cit> , dip  <cit> , mint  <cit> , hprd  <cit>  and intact  <cit> .
we considered only experimental methods dedicated to the identification of direct binary protein interactions .
the final protein interaction network contained  <dig> proteins  and  <dig> interactions .
process mapping
the gene/protein sets corresponding to cellular pathways/processes were extracted from the public databases kegg  <cit> , biocarta  <cit>  and reactome  <cit>  and were mapped onto the protein interaction network.
since the interaction data does not represent the entire proteome, on average about 60% of the pathway proteins could be mapped onto the network.
process extension procedure
original cellular pathways/processes containing at least  <dig> proteins were used as seeds and mapped onto the protein-protein interaction network.
the direct neighbours of these seed nodes were then considered as candidates for the extension procedure, and filtered according to multiple criteria to assess the strength of their association with the pathway nodes.
more specifically, in the first filtering step, a candidate-node v has to fulfill condition  below and at least one of the following conditions  to be added to a pathway p .
node degree:
degree> <dig>
direct pathway/process association:
process_linksoutside_links>t <dig>
process extension procedure:
triangle_linkspossible_triangles>t <dig>
pathway/process node coverage:
process_linksprocess_nodes>t <dig>
where degree is the number of direct links of node v, process_links is the number of direct links from v to a node in the process p and outside_links is the number of direct links from v to a node outside of process p. triangle_links is the number of triangles in which v occurs together with a node in p and another candidate-node, and possible_triangles is the number of these triangles which could potentially be formed, if all other candidate nodes would be part of a triangle formed together with v and p. t <dig>  t <dig> and t <dig> are defined here as t <dig> =  <dig> , t <dig> =  <dig>  and t <dig> =  <dig>  .
for t <dig> =  <dig> , equation  <dig> corresponds to a well-known condition in graph theory introduced to define "strong communities" in networks .
given that a candidate node can have connections with all the original pathway nodes, the threshold t <dig> always has to be smaller than  <dig> .
since we expected the extension procedure to be more meaningful if it results in a more compact pathway-representation in the network, we apply a second filter to the candidate nodes which passed the first fillter based on the above criteria.
a candidate node is only accepted if the following compactness-score, given by the mean of the shortest path lengths between all pairs of proteins belonging to a protein set p, is reduced after adding the candidate:
compact_score=∑i,j∈p;i<jdist|p|*/ <dig>
thus, the proteins that are added to a pathway by the procedure are both strongly associated with the original pathway members and provide an extended pathway with a compact network representation.
specifically, we expect that added proteins which increase the compactness by connecting disconnected proteins in the original pathway are more likely to be functionally similar to the pathway members.
the order in which proteins are added to extend a pathway is given by a greedy strategy, i.e.
the protein that increases the compactness the most is always added first.
topological network analysis
to quantify local and global topological properties of proteins in the network, we used the web-application topogsa  <cit>  to compute five topological descriptors: the number of connections to other nodes , the tendency of nodes to form clusters , their centrality in the network  and the distances between them .
for a detailed explanation of these topological characteristics, see  <cit> .
cross-validation
we applied the following cross-validation strategy to analyse the extent to which randomly deleted proteins in the original pathways/processes can be recovered by our extension procedure:
<dig>  10% of the proteins from each pathway were removed randomly among those proteins that are connected to at least one other protein in the pathway.
if the set of proteins that are connected to other pathway members covers less than 10% of the total number of proteins, we iteratively remove random proteins from this set and recompute the set until it is empty.
<dig>  to each reduced pathway the proposed extension procedure was applied as well as  <dig> alternative random extensions, computed by sampling randomly the same number of proteins from the candidate proteins of the reduced pathway .
<dig>  p-value significance scores are estimated as the relative frequency of cases where more proteins were correctly recovered by a random extension than by the proposed extension procedure across all pathways in a database.
semantic similarity analysis of gene ontology terms
we quantified pairwise similarities between protein annotations based on jiang and conrath's semantic similarity measure for go terms  <cit> .
using this similarity score, we computed the average go-term similarities between all pairwise combinations of go biological process  terms for the original proteins in the cellular pathway and the added proteins.
a random extension model was created by randomly sampling the same number of proteins from the candidate proteins of the pathway  as in the real extension, excluding the proteins from the extended cellular pathway under consideration.
the reader should note that it is not possible to compare the extensions of real pathways to extensions of random gene/protein sets with similar connectivity in the network, because in most cases these sets would largely overlap with other pathways.
enrichment analyses
• the enrichment of molecular functions among the proteins added to the cellular pathways/processes by the extension procedure was tested for all databases independently using the david functional annotation clustering tool  <cit>  , with the proteins from the interaction network.
functional annotation clusters with a more than 2-fold enrichment were selected and manually labelled.
• to estimate the probability of observing certain overlaps between extended or original protein sets representing pathways and other protein sets of interest, e.g.
cancer-related proteins, we used a classical over-representation analysis  based on the one-tailed fisher exact test.
to adjust for multiple testing, we employ the approach by benjamini  <cit> .
RESULTS
in the following we discuss the results obtained by applying our pathway extension approach to cellular pathway and process datasets from the databases kegg  <cit> , biocarta  <cit>  and reactome  <cit> .
across all databases,  <dig> different processes were considered  and mapped onto a network containing  <dig> interactions .
extension of cellular pathways/processes with protein interaction data predicts new putative components
our procedure has been able to extend  <dig> pathways from biocarta,  <dig> from kegg and  <dig> from reactome .
the pathway sizes increased on average from 113% to 126% of the original size.
statistics on the number of pathways that could be extended, the average extension size, the number of added  proteins and their molecular function categories.
network properties of the proteins added to the cellular pathways/processes
the added proteins in the interaction network had a more than one standard deviation higher node degree, betweenness and average local clustering coefficient  than  <dig> matched size random protein sets  <cit>  .
moreover, the shortest path lengths between the added proteins were smaller by several standard deviations .
this tendency of proteins added by the extension method to occur in more central and dense regions of the network is consistent with similar trends observed for the topological properties of proteins from the original cellular pathways and processes .
comparison of different numerical topological properties for the proteins added by the proposed extension method  or the random model , as well as a comparison of these properties for the nodes corresponding to the original cellular processes  and the entire protein-protein interaction network .
functional annotations of the proteins added to the cellular pathways/processes
a semantic similarity analysis of the go terms was used to compare the functional annotations of the original cellular process proteins with the annotations of the proteins added during the extension procedure .
for almost all cellular pathways, the go-terms of the added proteins are more similar to the go-terms of the original cellular pathway proteins than those of matched-size random protein sets .
these results confirm that the added proteins belong to similar functional categories as the proteins from the cellular processes they were assigned to.
furthermore, a functional enrichment analysis of the combined set of proteins added to all cellular processes  reveals an enrichment in proteins annotated for regulatory activity .
more interestingly, for the databases kegg and biocarta, the added proteins are enriched in phosphatases.
this result could indicate that phosphatases, which might correspond to negative regulators, have previously been overlooked in the definition of canonical pathways.
the extension procedure can recover known pathway proteins after deletion
a cross-validation procedure  showed that the cellular pathway extension recovers a significantly larger number of randomly deleted pathway- nodes in the network than a simplistic extension based on random selection among the candidate nodes .
specifically, the distribution of the number of recoveries across the  <dig> random model extensions never provided a higher number of recoveries than the proposed extension method.
prediction of new components
based on the observations that 1) the proteins added by our method are well connected and central in the protein interaction network, 2) the added proteins display gene ontology annotations matching better to the original cellular pathway/process annotations than random proteins, and are enriched in processes known to be related to cellular signalling, and 3) our method is able to recover known cellular pathway/process proteins in a cross-validation experiment, we propose to consider the proteins added by the extension procedure as new candidate components with a functional role in the corresponding cellular processes.
to illustrate the utility of our extension procedure for the prediction of new components, we analysed a cellular map modelling the process likely to be deregulated by the most penetrant alzheimer susceptibility genes .
our extension method added  <dig> different proteins to this cellular map http://www.infobiotics.net/pathexpand.
interestingly, three of them have previously been implied in alzheimer disease .
two other proteins, mettl2b and mmp <dig>  which are also added to the alzheimer cellular map by our method, have not been linked to the disease so far, to the best of our knowledge.
mmp <dig> is a member of the metallopeptidase protein family involved in the breakdown of the extracellular matrix.
according to the huge navigator  <cit> ,  <dig> other members of this protein family have been associated with the alzheimer disease.
the other candidate is a methyltransferase-like, mettl2b.
another member of this family, mmetl <dig> has been associated with alzheimer disease in a case-control study  <cit> .
thus, using the alzheimer disease pathway as a first test case of our method, we can propose mmp <dig> and mettl2b as new candidate disease genes.
the extension of cellular processes points to extensive communication
the involvement of some proteins in multiple processes suggests that extensive communication exists between different cellular processes.
indeed, before applying the extension procedure, about 50% of the cellular process proteins are annotated for more than one cellular process.
interestingly, after the extension procedure, the percentage of unique proteins among all proteins added to the cellular processes ranged from 30%  to 66% , revealing that many proteins are added to more than one cellular process.
in agreement with our observations for the original process proteins, again about 50% of the added proteins belong to more than one cellular process.
accordingly, many proteins in the protein interaction network are well connected with different cellular processes, and might therefore be expected to have a functional role in the communication between the cellular processes.
as an example for these type of connections, we consider the class of interleukins .
ils are secreted proteins mainly involved in the immune system to regulate the communication between immune cells.
they activate different signalling pathways, which can share intracellular signalling cascades , but which also display distinct properties .
in this context, some il-pathway proteins are annotated only for one il pathway , while other proteins occur in multiple pathways .
furthermore, all the il pathways share protein-protein interactions .
thus, the analysis of protein-protein interactions between the members of different il pathways highlights the complexity of this signalling system.
we applied our pathway extension method to extend the seven interleukin signalling pathways depicted in figure  <dig> .
the figure shows that some proteins were added to only a single il pathway.
for instance, the ctag1b  protein was added to the il5- signalling pathway .
interestingly, the added protein is an antigen expressed only in cancer cells and in normal testis cells, and could represent a regulatory member of this pathway in these two particular conditions.
moreover, four other proteins were added jointly to more than one il pathway.
three of them are added to the il <dig>  il <dig> and il <dig> pathways, which are all activating the stat and ras/mapk signalling cascades.
these proteins are known regulators of these cascades and can also participate in the regulation of the communication between the different interleukin signalling pathways.
functional enrichment of tumour mutated genes in extended cellular pathways reveals new putative regulators of cancer pathways
large-scale tumour resequencing projects have revealed a large number of genes mutated in different cancer types  <cit> .
to understand the biological significance of these mutated genes, those cellular processes containing more mutated genes than expected by chance have been identified .
we applied an enrichment analysis on cancer mutated genes extracted from a pancreatic large-scale resequencing study  <cit> , with extended cellular processes from biocarta, kegg and reactome, and identified significant associations between different cancer types and the extended pathways .
interestingly, we retrieve 8/ <dig> core signalling pathways that have previously been identified as significantly associated with this disease  <cit> .
an over-representation analysis  shows that some cellular pathways and processes are more significantly enriched in mutated genes in the extended versions than in the original versions .
these include signalling pathways, such as mapk, p <dig> mapk, p <dig>  wnt, pdgf, fc epsilon receptor i, erbb or functions such as apoptosis and cell cycle g1/s check point .
interestingly, some of the proteins added to these processes during the extension procedure are also pancreatic mutated genes .
these proteins include, for instance, the bcl2-related protein a <dig>  which is added by our method to the apoptosis reactome pathway .
a less obvious example is the dual specificity phosphatase  <dig> , a phosphatase added by the extension procedure to mapk pathways, the fc epsilon receptor i signalling pathway and to a pathway known to be activated in response to hiv nef protein .
this protein is highly expressed in the pancreas  <cit>  and displays a frameshift mutation in pancreatic tumours  <cit> .
the complete list of cellular processes that display a statistically significant enrichment in pancreatic cancer mutated genes after applying the proposed extension method  and improved significance scores in relation to the original pathways .
the significance scores for the overrepresentation analysis  and the pathway sizes are shown before and after the extension, and the total number of mutated genes in the extended pathways is provided, as well as the size and the annotations for the set of mutated genes among the genes that were added to these pathways.
finally, new insights can be gained when analysing the biocarta cell cycle g1/s check point process .
this process contains several proteins that were found mutated in large-scale pancreatic resequencing studies , as well as many other proteins known to be involved in cancerogenesis.
our extension procedure adds seven proteins to this process .
all of these proteins are either transcription factors, kinases or other signal transduction regulators, and six of them are known to be involved in cell cycle regulation , though not belonging to the biocarta canonical cell cycle g1/s check point proteins.
interestingly, the cancer resequencing study showed the tgif <dig> gene to be mutated in a pancreatic tumour .
this transcriptional repressor gene has also been reported to be amplified in some ovarian cancers, and can be recruited by tgf-β-activated smads  <cit> .
we predict both the involvement of the corresponding tgif <dig> protein in the cell cycle g1/s check point process, and its involvement in cancer through the deregulation of this process.
in conclusion, the extensions of the cell cycle g1/s and other processes provide useful explanatory information for the cancer association of these pathways/processes by adding new regulators that increase the connectivity between cancer mutated genes and other process members in the interaction network.
for instance, in the g1/s process, smad <dig> is connected to other process members by adding the proteins tgif <dig>  grb <dig> and plagl <dig>  and smad <dig> is connected to the process member cdk <dig> by adding uhrf <dig>  thus, the overall coherence of the processes is increased and an expanded view of the influence of different cancer genes in these processes is obtained.
CONCLUSIONS
the extension of known cellular pathways and processes with densely interconnected interaction partners in a protein-protein interaction network leads to the proposal of new putative components and to the identification of mediators of the communication between the processes.
thus, by taking into account canonical knowledge as well as large-scale interaction data, the extended pathways help to explain the functions of cancer mutated genes.
availability and requirements
the web-based pathway visualisation, details about the generation of the human protein-protein interaction network and the complete enrichment analysis results are freely available at http://www.infobiotics.net/pathexpand.
authors' contributions
ab and eg jointly drafted the manuscript.
eg participated in the design of the study, implemented the algorithm and web-based visualisation, and carried out the statistical analyses.
ab participated in the design of the study, collected the cancer mutated gene, cellular pathway and interaction data, and analysed the functional annotations of added proteins and the enrichment results.
av and nk took part in the design and coordination of the study, provided input into main ideas of the paper and obtained funding for the project.
all authors read, commented and approved the final version of the manuscript.

 processes and pathways, whose deregulation may contribute to the development of cancers, are often represented as cascades of proteins transmitting a signal from the cell surface to the nucleus. however, the delineation of the canonical members of these cellular pathways is based on a multitude of experimental methods, and some inconsistencies exist across databases. indeed, the assignment of a protein to a pathway often relies on the experimental procedure and on a subjective assessment of the protein's importance for the process. many closely associated regulators, effectors or targets of cellular pathways may therefore have been overlooked by these classical approaches. additionally, recent functional genomics high-throughput initiatives have identified a large number of interaction partners for signalling proteins, suggesting more complex relationships between cellular pathways than in their traditional representations. in this context, the analysis of cancer mutated genes at the level of canonical cellular processes and pathways may previously have missed potentially interesting findings. this paper introduces a new methodology to amalgamate the information from cellular process and pathway databases with large-scale protein-protein interaction data. previous approaches for in-silico generation of cellular processes based on molecular interaction data have constructed pathways from scratch, and related approaches for disease candidate gene prioritisation also rely on interaction network data to identify molecules which are associated with a gene set. however, to the best of the authors' knowledge an extension approach which preserves existing process definitions has not yet been investigated. here, we present a procedure for extending cellular pathways and processes by mapping them onto a protein-protein interaction network and identifying densely interconnected interaction partners. briefly, we map proteins annotated for different cellular processes onto a large protein-protein interaction network, and extend each of these processes by adding their most densely interconnected network partners. these added proteins display distinctive network topological features and molecular function annotations and can be proposed as putative new components of the corresponding cellular process, and/or as regulators of the communication between different cellular processes. this is illustrated by the prediction of new alzheimer disease candidate genes and the identification of proteins with potential involvement in the crosstalk between several interleukin signalling pathways. finally, we employ the extension procedure to investigate mutated genes from a large-scale resequencing study of pancreatic tumours. we identified many pathways and processes enriched in mutated genes, as well as cancer mutated genes predicted to be involved in specific pathway deregulations. implementation all data processing and analysis steps were implemented in the programming language r. the web-based pathway visualisation on http://www.infobiotics.net/pathexpand was implemented in php. interaction network construction the human protein-protein interactions were combined from public databases, as of july, these include mips, dip, mint, hprd and intact. we considered only experimental methods dedicated to the identification of direct binary protein interactions. the final protein interaction network contained proteins and interactions. process mapping the gene/protein sets corresponding to cellular pathways/processes were extracted from the public databases kegg, biocarta and reactome and were mapped onto the protein interaction network. since the interaction data does not represent the entire proteome, on average about 60% of the pathway proteins could be mapped onto the network. process extension procedure original cellular pathways/processes containing at least proteins were used as seeds and mapped onto the protein-protein interaction network. the direct neighbours of these seed nodes were then considered as candidates for the extension procedure, and filtered according to multiple criteria to assess the strength of their association with the pathway nodes. more specifically, in the first filtering step, a candidate-node v has to fulfill condition below and at least one of the following conditions to be added to a pathway p. node degree: degree> direct pathway/process association: process_linksoutside_links>t process extension procedure: triangle_linkspossible_triangles>t pathway/process node coverage: process_linksprocess_nodes>t where degree is the number of direct links of node v, process_links is the number of direct links from v to a node in the process p and outside_links is the number of direct links from v to a node outside of process p. triangle_links is the number of triangles in which v occurs together with a node in p and another candidate-node, and possible_triangles is the number of these triangles which could potentially be formed, if all other candidate nodes would be part of a triangle formed together with v and p. t t and t are defined here as t =, t = and t =. for t =, equation corresponds to a well-known condition in graph theory introduced to define "strong communities" in networks. given that a candidate node can have connections with all the original pathway nodes, the threshold t always has to be smaller than. since we expected the extension procedure to be more meaningful if it results in a more compact pathway-representation in the network, we apply a second filter to the candidate nodes which passed the first fillter based on the above criteria. a candidate node is only accepted if the following compactness-score, given by the mean of the shortest path lengths between all pairs of proteins belonging to a protein set p, is reduced after adding the candidate: compact_score=∑i,j∈p;i<jdist|p|*/ thus, the proteins that are added to a pathway by the procedure are both strongly associated with the original pathway members and provide an extended pathway with a compact network representation. specifically, we expect that added proteins which increase the compactness by connecting disconnected proteins in the original pathway are more likely to be functionally similar to the pathway members. the order in which proteins are added to extend a pathway is given by a greedy strategy, i.e. the protein that increases the compactness the most is always added first. topological network analysis to quantify local and global topological properties of proteins in the network, we used the web-application topogsa to compute five topological descriptors: the number of connections to other nodes, the tendency of nodes to form clusters, their centrality in the network and the distances between them. for a detailed explanation of these topological characteristics, see. cross-validation we applied the following cross-validation strategy to analyse the extent to which randomly deleted proteins in the original pathways/processes can be recovered by our extension procedure: 10% of the proteins from each pathway were removed randomly among those proteins that are connected to at least one other protein in the pathway. if the set of proteins that are connected to other pathway members covers less than 10% of the total number of proteins, we iteratively remove random proteins from this set and recompute the set until it is empty. to each reduced pathway the proposed extension procedure was applied as well as alternative random extensions, computed by sampling randomly the same number of proteins from the candidate proteins of the reduced pathway. p-value significance scores are estimated as the relative frequency of cases where more proteins were correctly recovered by a random extension than by the proposed extension procedure across all pathways in a database. semantic similarity analysis of gene ontology terms we quantified pairwise similarities between protein annotations based on jiang and conrath's semantic similarity measure for go terms. using this similarity score, we computed the average go-term similarities between all pairwise combinations of go biological process terms for the original proteins in the cellular pathway and the added proteins. a random extension model was created by randomly sampling the same number of proteins from the candidate proteins of the pathway as in the real extension, excluding the proteins from the extended cellular pathway under consideration. the reader should note that it is not possible to compare the extensions of real pathways to extensions of random gene/protein sets with similar connectivity in the network, because in most cases these sets would largely overlap with other pathways. enrichment analyses • the enrichment of molecular functions among the proteins added to the cellular pathways/processes by the extension procedure was tested for all databases independently using the david functional annotation clustering tool, with the proteins from the interaction network. functional annotation clusters with a more than 2-fold enrichment were selected and manually labelled. • to estimate the probability of observing certain overlaps between extended or original protein sets representing pathways and other protein sets of interest, e.g. cancer-related proteins, we used a classical over-representation analysis based on the one-tailed fisher exact test. to adjust for multiple testing, we employ the approach by benjamini.  in the following we discuss the results obtained by applying our pathway extension approach to cellular pathway and process datasets from the databases kegg, biocarta and reactome. across all databases, different processes were considered and mapped onto a network containing interactions. extension of cellular pathways/processes with protein interaction data predicts new putative components our procedure has been able to extend pathways from biocarta, from kegg and from reactome. the pathway sizes increased on average from 113% to 126% of the original size. statistics on the number of pathways that could be extended, the average extension size, the number of added proteins and their molecular function categories. network properties of the proteins added to the cellular pathways/processes the added proteins in the interaction network had a more than one standard deviation higher node degree, betweenness and average local clustering coefficient than matched size random protein sets. moreover, the shortest path lengths between the added proteins were smaller by several standard deviations. this tendency of proteins added by the extension method to occur in more central and dense regions of the network is consistent with similar trends observed for the topological properties of proteins from the original cellular pathways and processes. comparison of different numerical topological properties for the proteins added by the proposed extension method or the random model, as well as a comparison of these properties for the nodes corresponding to the original cellular processes and the entire protein-protein interaction network. functional annotations of the proteins added to the cellular pathways/processes a semantic similarity analysis of the go terms was used to compare the functional annotations of the original cellular process proteins with the annotations of the proteins added during the extension procedure. for almost all cellular pathways, the go-terms of the added proteins are more similar to the go-terms of the original cellular pathway proteins than those of matched-size random protein sets. these results confirm that the added proteins belong to similar functional categories as the proteins from the cellular processes they were assigned to. furthermore, a functional enrichment analysis of the combined set of proteins added to all cellular processes reveals an enrichment in proteins annotated for regulatory activity. more interestingly, for the databases kegg and biocarta, the added proteins are enriched in phosphatases. this result could indicate that phosphatases, which might correspond to negative regulators, have previously been overlooked in the definition of canonical pathways. the extension procedure can recover known pathway proteins after deletion a cross-validation procedure showed that the cellular pathway extension recovers a significantly larger number of randomly deleted pathway- nodes in the network than a simplistic extension based on random selection among the candidate nodes. specifically, the distribution of the number of recoveries across the random model extensions never provided a higher number of recoveries than the proposed extension method. prediction of new components based on the observations that 1) the proteins added by our method are well connected and central in the protein interaction network, 2) the added proteins display gene ontology annotations matching better to the original cellular pathway/process annotations than random proteins, and are enriched in processes known to be related to cellular signalling, and 3) our method is able to recover known cellular pathway/process proteins in a cross-validation experiment, we propose to consider the proteins added by the extension procedure as new candidate components with a functional role in the corresponding cellular processes. to illustrate the utility of our extension procedure for the prediction of new components, we analysed a cellular map modelling the process likely to be deregulated by the most penetrant alzheimer susceptibility genes. our extension method added different proteins to this cellular map http://www.infobiotics.net/pathexpand. interestingly, three of them have previously been implied in alzheimer disease. two other proteins, mettl2b and mmp which are also added to the alzheimer cellular map by our method, have not been linked to the disease so far, to the best of our knowledge. mmp is a member of the metallopeptidase protein family involved in the breakdown of the extracellular matrix. according to the huge navigator, other members of this protein family have been associated with the alzheimer disease. the other candidate is a methyltransferase-like, mettl2b. another member of this family, mmetl has been associated with alzheimer disease in a case-control study. thus, using the alzheimer disease pathway as a first test case of our method, we can propose mmp and mettl2b as new candidate disease genes. the extension of cellular processes points to extensive communication the involvement of some proteins in multiple processes suggests that extensive communication exists between different cellular processes. indeed, before applying the extension procedure, about 50% of the cellular process proteins are annotated for more than one cellular process. interestingly, after the extension procedure, the percentage of unique proteins among all proteins added to the cellular processes ranged from 30% to 66%, revealing that many proteins are added to more than one cellular process. in agreement with our observations for the original process proteins, again about 50% of the added proteins belong to more than one cellular process. accordingly, many proteins in the protein interaction network are well connected with different cellular processes, and might therefore be expected to have a functional role in the communication between the cellular processes. as an example for these type of connections, we consider the class of interleukins. ils are secreted proteins mainly involved in the immune system to regulate the communication between immune cells. they activate different signalling pathways, which can share intracellular signalling cascades, but which also display distinct properties. in this context, some il-pathway proteins are annotated only for one il pathway, while other proteins occur in multiple pathways. furthermore, all the il pathways share protein-protein interactions. thus, the analysis of protein-protein interactions between the members of different il pathways highlights the complexity of this signalling system. we applied our pathway extension method to extend the seven interleukin signalling pathways depicted in figure. the figure shows that some proteins were added to only a single il pathway. for instance, the ctag1b protein was added to the il5- signalling pathway. interestingly, the added protein is an antigen expressed only in cancer cells and in normal testis cells, and could represent a regulatory member of this pathway in these two particular conditions. moreover, four other proteins were added jointly to more than one il pathway. three of them are added to the il il and il pathways, which are all activating the stat and ras/mapk signalling cascades. these proteins are known regulators of these cascades and can also participate in the regulation of the communication between the different interleukin signalling pathways. functional enrichment of tumour mutated genes in extended cellular pathways reveals new putative regulators of cancer pathways large-scale tumour resequencing projects have revealed a large number of genes mutated in different cancer types. to understand the biological significance of these mutated genes, those cellular processes containing more mutated genes than expected by chance have been identified. we applied an enrichment analysis on cancer mutated genes extracted from a pancreatic large-scale resequencing study, with extended cellular processes from biocarta, kegg and reactome, and identified significant associations between different cancer types and the extended pathways. interestingly, we retrieve 8/ core signalling pathways that have previously been identified as significantly associated with this disease. an over-representation analysis shows that some cellular pathways and processes are more significantly enriched in mutated genes in the extended versions than in the original versions. these include signalling pathways, such as mapk, p mapk, p wnt, pdgf, fc epsilon receptor i, erbb or functions such as apoptosis and cell cycle g1/s check point. interestingly, some of the proteins added to these processes during the extension procedure are also pancreatic mutated genes. these proteins include, for instance, the bcl2-related protein a which is added by our method to the apoptosis reactome pathway. a less obvious example is the dual specificity phosphatase, a phosphatase added by the extension procedure to mapk pathways, the fc epsilon receptor i signalling pathway and to a pathway known to be activated in response to hiv nef protein. this protein is highly expressed in the pancreas and displays a frameshift mutation in pancreatic tumours. the complete list of cellular processes that display a statistically significant enrichment in pancreatic cancer mutated genes after applying the proposed extension method and improved significance scores in relation to the original pathways. the significance scores for the overrepresentation analysis and the pathway sizes are shown before and after the extension, and the total number of mutated genes in the extended pathways is provided, as well as the size and the annotations for the set of mutated genes among the genes that were added to these pathways. finally, new insights can be gained when analysing the biocarta cell cycle g1/s check point process. this process contains several proteins that were found mutated in large-scale pancreatic resequencing studies, as well as many other proteins known to be involved in cancerogenesis. our extension procedure adds seven proteins to this process. all of these proteins are either transcription factors, kinases or other signal transduction regulators, and six of them are known to be involved in cell cycle regulation, though not belonging to the biocarta canonical cell cycle g1/s check point proteins. interestingly, the cancer resequencing study showed the tgif gene to be mutated in a pancreatic tumour. this transcriptional repressor gene has also been reported to be amplified in some ovarian cancers, and can be recruited by tgf-β-activated smads. we predict both the involvement of the corresponding tgif protein in the cell cycle g1/s check point process, and its involvement in cancer through the deregulation of this process. in conclusion, the extensions of the cell cycle g1/s and other processes provide useful explanatory information for the cancer association of these pathways/processes by adding new regulators that increase the connectivity between cancer mutated genes and other process members in the interaction network. for instance, in the g1/s process, smad is connected to other process members by adding the proteins tgif grb and plagl and smad is connected to the process member cdk by adding uhrf thus, the overall coherence of the processes is increased and an expanded view of the influence of different cancer genes in these processes is obtained.  the extension of known cellular pathways and processes with densely interconnected interaction partners in a protein-protein interaction network leads to the proposal of new putative components and to the identification of mediators of the communication between the processes. thus, by taking into account canonical knowledge as well as large-scale interaction data, the extended pathways help to explain the functions of cancer mutated genes. availability and requirements the web-based pathway visualisation, details about the generation of the human protein-protein interaction network and the complete enrichment analysis results are freely available at http://www.infobiotics.net/pathexpand. authors' contributions ab and eg jointly drafted the manuscript. eg participated in the design of the study, implemented the algorithm and web-based visualisation, and carried out the statistical analyses. ab participated in the design of the study, collected the cancer mutated gene, cellular pathway and interaction data, and analysed the functional annotations of added proteins and the enrichment results. av and nk took part in the design and coordination of the study, provided input into main ideas of the paper and obtained funding for the project. all authors read, commented and approved the final version of the manuscript. 
cellular processes and pathways, whose deregulation may contribute to the development of cancers, are often represented as cascades of proteins transmitting a signal from the cell surface to the nucleus. the added proteins display distinctive network topological features and molecular function annotations, and can be proposed as putative new components, and/or as regulators of the communication between the different cellular processes. we present a methodology for extending pre-defined protein sets representing cellular pathways and processes by mapping them onto a protein-protein interaction network, and extending them to include densely interconnected interaction partners. the proposed method for extending cellular pathways helps to explain the functions of cancer mutated genes by exploiting the synergies of canonical knowledge and large-scale interaction data. combining information from pathway databases and interaction networks obtained from functional genomic experiments is therefore a promising strategy to obtain more robust pathway and process representations, facilitating the study of cancer-related pathways. significant associations between mutated genes and certain processes are identified, enabling an analysis of the influence of previously non-annotated cancer mutated genes.
 cellular processes and pathways, whose deregulation may contribute to the development of cancers, are often represented as cascades of proteins transmitting a signal from the cell surface to the nucleus. however, recent functional genomic experiments have identified thousands of interactions for the signalling canonical proteins, challenging the traditional view of pathways as independent functional entities. combining information from pathway databases and interaction networks obtained from functional genomic experiments is therefore a promising strategy to obtain more robust pathway and process representations, facilitating the study of cancer-related pathways.  we present a methodology for extending pre-defined protein sets representing cellular pathways and processes by mapping them onto a protein-protein interaction network, and extending them to include densely interconnected interaction partners. the added proteins display distinctive network topological features and molecular function annotations, and can be proposed as putative new components, and/or as regulators of the communication between the different cellular processes. finally, these extended pathways and processes are used to analyse their enrichment in pancreatic mutated genes. significant associations between mutated genes and certain processes are identified, enabling an analysis of the influence of previously non-annotated cancer mutated genes.  the proposed method for extending cellular pathways helps to explain the functions of cancer mutated genes by exploiting the synergies of canonical knowledge and large-scale interaction data. 