Cancerin: A computational pipeline to infer cancer-associated ceRNA interaction networks
[['MicroRNAs ( miRNAs ) are a family of short non-coding RNA molecules involved in post-transcriptional gene regulation .', 'MiRNAs attach to Argonaute protein to form RNA-induced silencing complexes ( RISCs ) , which bind to miRNA-response-elements ( MREs ) located on the 3′UTR of messenger RNAs ( mRNAs ) .', 'This binding promotes mRNA degradation or inhibit their translation into proteins [1] .', 'A typical mRNA contains multiple MREs , which are binding sites for one or multiple miRNAs .', 'Thus , a mRNA can be targeted by multiple miRNAs , and a miRNA can target multiple mRNAs [2] .', 'As protein synthesis is impacted by miRNA-mRNA binding , gene regulation by miRNAs plays an important role in a wide range of biological processes such as cell growth , differentiation , and apoptosis [3–5] .', 'Anomaly in miRNA regulation have been implicated in multiple diseases including cancer [6] .', 'Aberrant changes in miRNA concentration in cells could lead to dysregulation of tumor suppressors or oncogenic genes , which could trigger cancer development and progression [7] .', 'Recent experimental studies suggest a new layer of miRNA-mediated regulation that involves indirect interactions between RNA molecules via their interactions with common miRNAs [8 , 9] .', 'Such RNAs are called competing endogenous RNAs ( ceRNAs ) , and their indirect interactions are referred as ceRNA interactions [8] .', 'The ceRNA hypothesis [10] posits that change of expression level in one ceRNA would alter its miRNA regulators’ abundance , which in turn alters the expression level of other target ceRNAs of these miRNAs .', 'For example , a highly expressed ceRNA can sequester many miRNA molecules , reducing the total miRNA abundance and leading to the derepression of other target ceRNAs of these miRNAs .', 'CeRNA interactions are not only among protein coding RNAs ( i . e . , mRNAs ) .', 'Recent studies have found that non-coding RNAs ( e . g . , long non-coding RNAs ( lncRNAs ) [11 , 12] and pseudogenes [13] ) also involve in ceRNA interactions .', 'For the rest of the paper , “RNAs” refers to candidate ceRNAs , which includes mRNAs and lncRNAs .', 'CeRNA interactions have been shown to regulate important biological processes such as muscle differentiation [9] , self-renewal capability of embryonic stem cells [3] , and inhibition of cancer cell differentiation [14] .', 'Disruption of ceRNA interactions has been implicated in multiple types of diseases including cancer [15 , 16] .', 'Disruption of ceRNA interactions can repress tumor-suppressor genes and lead to oncogenic activities [17 , 18] .', 'Comprehensive reviews of functions of ceRNA in cancer biology can be found in [19–21] .', 'The existence and strength of ceRNA interactions may vary significantly in different physiological and cellular settings ( i . e . , normal cells versus tumor cells ) .', 'As ceRNA interaction is considered as a new layer of gene regulation , identification and construction of genome-wide and condition-specific ceRNA interaction networks could facilitate better understanding of ceRNA regulatory mechanisms and their biological significance .', 'While experimental studies are of great importance to confirm ceRNA interactions , inference of ceRNA interaction networks by only experimental methods would be time- and cost-prohibitive .', 'Thus , computational tools are needed to infer ceRNA interaction networks and generate new hypotheses for further experimental validation .', 'Since ceRNA interactions are mediated via miRNAs , identifying interactions between miRNAs and their targets is a prerequisite to infer ceRNA interactions .', 'Sequence-based miRNA target prediction algorithms such as TargetScan [22] and miRanda [23] have been employed to search for MREs in 3′UTR of mRNAs , and miRNA-mRNA interaction databases such as starBase [24] and miRWalk [25] store computationally and experimentally verified miRNA-mRNA interactions .', 'Expression profiles of both mRNAs and miRNAs were also used to identify condition-specific miRNA-mRNA interactions .', 'As miRNAs were mostly known to repress the expression of its targets , expression levels of miRNAs and their targets were often required to be negatively correlated [26 , 27] .', 'After predicting miRNA-target gene interactions , existing ceRNA inference methods differed in how they related expression of miRNAs and their co-regulated genes to decide which genes can establish ceRNA interactions .', 'Pairwise gene expression correlation was often considered as the main criterion to select ceRNA interactions .', 'Two ceRNAs were required to have positively correlated expression , and the ceRNAs and their miRNA regulators were required to have negatively correlated expression [26 , 27] .', 'However , miRNA expression data were also used to directly model the mediating effect of miRNAs in regulating ceRNA interaction .', 'Partial Pearson correlation ( PPC ) [28] and conditional mutual information ( CMI ) [29 , 30] metrics have been used to measure linear or nonlinear dependence of candidate ceRNAs’ expression on their shared miRNAs’ expression .', 'Applying CMI to identify and construct a glioblastoma-specific ceRNA interaction network , Sumazin et al . found experimentally validated interactions between PTEN and their known ceRNAs in the ceRNA network [29] .', 'In [28] , a new metric called sensitivity partial correlation was proposed to quantify the expression correlation dependency between two ceRNAs conditioned on their shared miRNAs’ expression .', 'The researchers applied this metric to gene and miRNA expression of normal and tumor breast samples to construct normal-specific and tumor-specific ceRNA interaction networks .', 'They observed that multiple cancer hallmarks such as tumor inflammation were only enriched in the tumor-specific ceRNA network .', 'A detailed review on computational methods to infer ceRNA interactions can be found in [31] .', 'In existing ceRNA studies , most computational methods consider miRNAs as the only type of gene regulators , while overlooking other important types of gene regulators such as transcription factors , DNA methylation , and copy number alteration .', 'Not considering other types of regulators might lead to spurious miRNA-gene interactions , which would cause false positive predictions of ceRNA interactions .', 'Notably , lack of experimental studies to confirm ceRNA interactions posed a big challenge to validate the accuracy and significance of inferred ceRNA interactions .', 'This study presents a computational pipeline called Cancerin , which infers Cancer-associated ceRNA iteraction networks .', 'A cancer-associated ceRNA interaction is defined as an interaction between two differentially expressed RNAs ( between normal and cancer samples ) , and the interaction is mediated by some differentially expressed miRNAs that regulate both RNAs .', 'Besides mRNAs , non-coding RNAs such as long non-coding RNAs ( lncRNAs ) have been shown to actively participate in functionally important ceRNA interactions in both normal and cancer cells [19 , 21] .', 'Thus , our pipeline considers both mRNAs and lncRNAs as potential ceRNAs .', 'To infer interaction between miRNAs and their RNA targets ( i . e . , candidate ceRNAs ) , Cancerin employs knowledge from both putative miRNA-RNA interactions and miRNA/RNA expression profiles .', 'In addition , Cancerin incorporates other types of gene expression regulatory factors , namely copy number alteration , DNA methylation , and transcription factors to infer miRNA-RNA interactions , which distinguish Cancerin from existing ceRNA inference methods .', 'An easy-to-use R software for Cancerin is freely available at https://github . com/bozdaglab/Cancerin .', 'Cancerin was applied to three cancer datasets .', 'Our result indicated that the ceRNAs in the obtained ceRNA interaction networks were significantly enriched with cancer-related genes .', 'Additionally , we observed that closely connected ceRNAs in the ceRNA networks were associated with cancer cell formation and development processes .', 'Compared to non-ceRNA genes , we showed that expression change of predicted ceRNAs had higher association with cancer survival outcomes .', 'To validate the effect of ceRNA interactions to expression change on an external dataset , we used the LINCS perturbation dataset [32] and observed that knockdown of ceRNAs was associated with the expression change of their ceRNA partners .'], ['We used the R Bioconductor package TCGABiolinks [33] to download genomic and clinical data of normal and solid tumor tissues for three types of cancer from The Cancer Genome Atlas ( TCGA ) [34] .', 'Cancer types were breast invasive carcinoma ( BRCA ) , kidney renal clear cell carcinoma ( KIRC ) , and head and neck squamous cell carcinoma ( HNSC ) .', 'We retrieved level 3 data for raw count mRNA and miRNA expression ( Illumina HiSeq 2000 ) , copy number alteration ( Affymetrix SNP Array 6 . 0 ) , and DNA methylation level ( Infinium HumanMethylation450 Bead-Chip ) .', 'The expression of lncRNAs was retrieved from the TANRIC database [35] .', 'We only kept tissue samples for which all of these genomic data and clinical data were available .', 'In addition , 3′UTR sequences of 18 , 959 mRNAs and 13 , 870 lncRNAs were downloaded from the GENCODE Release 26 ( GRCh38 . p10 ) [36] , and sequences of 2 , 588 mature miRNAs were downloaded from miRBase release 21 [37] .', 'Putative miRNA-mRNA interactions were retrieved from starBase v2 . 0 [24] and TargetScan 7 . 1 [22] databases .', 'Putative miRNA-lncRNA interactions were retrieved from starBase v2 . 0 [24] , DIANA-LncBase v2 [38] , and LnCeDb [39] .', 'Putative TF-gene interactions were retrieved from the TRED [40] and TRRUST ( version 2 ) [41] databases .', 'Cancerin is a computational pipeline to identify genome-wide cancer-associated ceRNA interaction networks .', 'It consists of three main steps .', 'Using putative miRNA-mRNA and miRNA-lncRNA interactions , the first step aims to construct an interaction network between DE miRNAs and DE RNAs .', 'In the second step , only the miRNAs that are associated with their targeted RNAs’ expression change are kept .', 'In the final step , several filtering layers are applied to infer ceRNA interactions between RNAs that are targeted by common miRNAs .', 'The entire Cancerin pipeline is illustrated in Fig 1 .', 'The details in each step in Cancerin are described in the following .'], ['The first step in Cancerin involved aggregating the putative interactions between miRNAs and RNAs from various data sources .', 'The candidate miRNA-mRNA interactions were downloaded from the starBase and the TargetScan databases .', 'Using mRNAs’ and miRNAs’ FASTA sequences , we selected only the mRNAs whose 3′UTR sequences and the miRNAs whose mature sequences were specified .', 'To further refine those putative interactions , the miRanda algorithm was used to check for the existence of MRE ( s ) on the mRNAs’ 3′UTR and to estimate the thermodynamic folding energy between the miRNAs and their predicted mRNA targets .', 'The lower the energy , the higher chance that an interaction will actually occur [56] .', 'A miRNA-mRNA interaction was kept if there existed at least one MRE on the mRNA as miRNA’s binding site and the miRNA-mRNA interaction’s folding energy was lower than 140 kcal/mol ( default value ) .', 'After applying miRanda , there remained 465 , 049 interactions between 473 miRNAs and 13 , 932 mRNAs .', 'Putative miRNA-lncRNA interactions were aggregated from starBase v2 . 0 , DIANA-LncBase v2 , and and LnCeDb , resulting in 3 , 961 , 135 interactions between 2 , 695 miRNAs and 24 , 215 lncRNAs .', 'Given all the putative miRNA-RNA interactions , we only kept the interactions between DE miRNAs and DE RNAs .', 'Table 1 summarizes the number of DE miRNA—DE RNA interactions in each cancer type .', 'To identify cancer-associated ceRNA interactions , Cancerin employed the putative miRNA-RNA interactions and the RNA expression as input data for the next two steps , which included applying a LASSO-based variable selection procedure to select cancer-specific miRNA-RNA interactions and using that information to identify ceRNA interactions .', 'The LASSO-based variable selection procedure ( see Materials and methods ) was applied to identify cancer-specific miRNA-RNA interactions while also taking into account the other types of gene regulators including TF , DNA methylation , and CNA .', 'Table 2 summarizes the number of miRNA-RNA interactions selected by the variable selection procedure in each cancer type .', 'Details of the selected miRNA-RNA interactions could be found in S1 File .', 'In Cancerin ( step 3 ) , given all the miRNA-RNA interactions obtained after applying the LASSO-based variable selection procedure , we identified all the candidate ceRNA interactions in which both the constituent RNAs were regulated by at least one common miRNA .', 'Then we applied several filtering layers to select the final ceRNA interactions out of those candidate ceRNA pairs .', 'Two RNAs were considered to have a ceRNA interaction if they had a significant number of shared miRNAs , and their expression profiles were both significantly correlated ( correlation ≥ 0 . 5 , p-value < 0 . 05 ) and had significantly positive sensitivity correlation ( empirical p-value < 0 . 05 ) .', 'Table 5 summarizes the number of ceRNA interactions and the constituent ceRNAs in those interactions for each cancer type .', 'Details of the selected ceRNA interactions could be found in S1 File .', 'Overall , the selected ceRNA interactions were very specific to each cancer type .', 'We found only one common ceRNA interaction in all the three cancer types .', 'The number of common ceRNA interactions between any two cancer types was also very low ( 9 between BRCA and KIRC , 22 between BRCA and HNSC , and 32 between KIRC and HNSC ) .', 'In all three cancer types , almost all ceRNA interactions were between mRNAs ( 84% ( BRCA ) , 99% ( KIRC ) , and 95% ( HNSC ) ) .', 'In BRCA and HNSC , many lncRNAs that were involved in lncRNA-lnRNA ceRNA interactions also participated in mRNA-lncRNA ceRNA interactions .', 'Specifically , out of 57 lncRNAs ( BRCA ) and 20 lncRNAs ( HNSC ) involved in lncRNA-lncRNA ceRNA interactions , 41 ( BRCA ) and 14 ( HNSC ) of those lncRNAs also participated in mRNA-lncRNA ceRNA interactions .', 'In this section , we examine the technical importance of the two major steps in the Cancerin pipeline .', 'The LASSO-based variable selection to select miRNA-mRNA interactions ( step', '2 ) and sensitivity correlation-based filtering to select ceRNA interactions ( step', '3 ) were two key components in Cancerin .', 'To assess the importance of those two steps , we modified/deactivated those steps to see how it would alter the final ceRNA interaction network topology .', 'Specifically , we kept steps 1 and 3 in Cancerin , but in step 2 , we replaced the LASSO-based variable selection procedure by ordinary least square ( OLS ) multiple regression .', 'For each RNA , its candidate miRNA regulators were selected if their coefficients from OLS were negative and p-values < 0 . 05 .', 'We termed this method “Cancerin ( OLS regression ) ” .', 'We also kept steps 1 and 2 in Cancerin , but in step 3 , we deactivated the ceRNA filtering criterion based on sensitivity correlation .', 'We termed this method “Cancerin ( sensitivity correlation filtering step deactivated ) ” .', 'The Cancerin pipeline with no modification is referred to as “Cancerin ( original ) ” .', 'To compare Cancerin to other existing methods , we replicated the method used in [26 , 27] , which inferred ceRNA interactions based on negative expression correlation between miRNA and RNA targets and positive expression correlation between RNA targets .', 'We referred to this method as “Correlation-based” method .', 'The method did not consider the other types of regulators besides miRNA ( i . e . , TF , CNA , and DNA methylation ) as potential regulators of gene expression and it also did not take into account the additive effects of multiple regulators on controlling gene expression .', 'Table 7 summarizes the number of selected ceRNA interactions obtained by applying the “Cancerin ( original ) ” , “Cancerin ( OLS regression ) ” , “Cancerin ( sensitivity correlation filtering step deactivated ) ” , and “Correlation-based method” .', 'As expected , using only expression correlation to infer ceRNA interactions resulted in many ceRNA pairs .', 'Compared to Cancerin , the number of correlation-based ceRNA interactions was more than 6-fold higher in BRCA , 10-fold higher in KIRC , and 6-fold higher in HNSC .', 'All ceRNA interactions found by “Cancerin ( original ) ” were included in the “Correlation-based” method .', 'There were also more ceRNA interactions found by “Cancerin ( OLS regression ) ” than by “Cancerin ( original ) ” but the increased size was smaller compared to the “Correlation-based” method .', 'There is a low overlap between the ceRNA interactions found in “Cancerin original” and the those from “Cancerin ( OLS regression ) ” .', 'Specifically , with respect to interactions found in “Cancerin ( original ) ” , the percentages of common interactions that were also found in “Cancerin ( OLS regression ) ” were 26 . 8% ( BRCA ) , 40% ( KIRC ) , and 33 . 2% ( HNSC ) .', 'Compared to “Cancerin ( original ) ” , deactivation of sensitivity correlation filtering step also increased the number of ceRNA interactions .', 'The fold-change increase in each cancer type was 1 . 7 ( BRCA ) , 4 . 1 ( KIRC ) , and 3 . 0 ( HNSC ) .', 'In overall , this comparative analysis indicated that due to several filtering layers used in “Cancerin ( original ) ” , the pipeline is more selective than other methods in selecting ceRNA interactions .', 'We also checked the number of PPIs and TF-gene interactions that were also inferred ceRNA interactions obtained by modifying particular steps in Cancerin or using the “Correlation-based” method .', 'As expected , compared to ceRNA interactions obtained by “Cancerin ( original ) ” , with other methods we observed an increase of ceRNA interactions that were also PPI or TF-gene interactions .', 'Especially the ceRNA interactions inferred by the “Correlation-based” method contained consistently higher percentage of PPI and TF-gene interactions ( see S1 Table ) .', 'These results suggest that the ceRNA interaction predictions obtained from pairwise expression correlation methods could have high false positive rate .', 'To assess the accuracy of the inferred ceRNA interactions to predict gene expression change , we employed shRNA-mediated perturbation assays data obtained from the Library of Integrated Network-based Cellular Signature ( LINCS ) database [32] .', 'In the LINCS-L1000 shRNA-perturbation database , gene knockdown experiments using shRNAs were conducted on multiple disease cell lines , making the database a valuable resource to assess gene-gene interactions inferred from computational methods .', 'Each experiment reported gene expression changes of 978 genes as response to the knockdown of a specific gene , which was targeted by a specific shRNA .', 'We referred to the knocked down genes as upstream genes and to the 978 expression-profiled genes as downstream genes .', 'Details of how we used the LINCS-L1000 dataset to evaluate the accuracy of inferred ceRNA interactions in predicting gene expression change were described in S1 Text .', 'In brief , if an upstream ceRNA is silenced , the upstream ceRNA’s miRNA regulators become more available to bind and thereby downregulate the downstream ceRNA partners .', 'Thus , given a downstream ceRNA , its expression level should be lower in response to the silencing of upstream ceRNA partners in comparison to the silencing of other upstream genes .', 'Ratio Fold Change ( RFC ) of a downstream ceRNA is defined as ratio of its expression fold change following the knockdown of its ceRNA partners to its expression fold change following the knockdown of upstream genes that are not its ceRNA partners .', 'A downstream ceRNA’s RFC was expected to be smaller than 1 .', 'Lower value of RFC indicated better prediction of gene expression change due to ceRNA interactions .', 'Recently , Chiu et al . [74] used the LINCS shRNA-mediated perturbation assays to assess Hermes algorithm , their genome-wide ceRNA interaction prediction tool [29] .', 'We also used the same LINCS dataset ( L1000-MCF7 ) that had been used in [74] to validate our results and to compare accuracy of Cancerin with Hermes .', 'We defined the accuracy of a ceRNA network as the percentage of downstream ceRNAs whose RFCs were smaller than 1 .', 'As gene expression in the MCF7 dataset was measured in two different time points ( 96h and 144h ) , our analysis was applied on each time point ( Table 8 ) .', 'At 96h , out of all downstream ceRNAs ( 77 in Cancerin and 22 in Hermes ) , the number of ceRNAs whose RFC was smaller than 1 was 55 in Cancerin ( accuracy 71 . 4% ) and 17 in Hermes ( accuracy 77 . 2% ) .', 'At 144h , out of all downstream ceRNAs ( 46 in Cancerin and 15 in Hermes ) , the number of ceRNAs whose RFC was smaller than 1 was 32 in Cancerin ( accuracy 69 . 6% ) and 9 in Hermes ( accuracy 60% ) .', 'While overall accuracy ( i . e . , percentage of total downstream ceRNAs whose RFC was smaller than 1 at both time points ) between Cancerin and Hermes was approximately equal ( 70 . 7% in Cancerin and 70 . 2% in Hermes ) , Cancerin showed consistent accuracy values at both time points .', 'We also computed the RFC values for the downstream ceRNAs obtained when the individual steps in Cancerin pipeline were modified and when only miRNAs were used as potential regulators in the variable selection step ( i . e . , Cancerin ( only_miRNA ) ) .', 'Cancerin outperformed those methods based on the overall accuracy ( see Table 8 ) .'], ['In this study , we developed Cancerin , a tool to infer genome-wide cancer-associated ceRNA interaction networks and applied it to three types of cancer .', 'Unlike existing ceRNA inference tools that considered miRNAs as the only type of gene regulator , Cancerin considered other types of gene regulators besides miRNAs , namely transcription factors , copy number alteration , and DNA methylation .', 'In addition , using the sensitivity correlation metric proposed in [28] , our method directly modeled the ceRNA hypothesis , which posited that the expression profiles of two ceRNAs should be positively correlated and that correlation was conditioned on the expression of their shared miRNA regulators .', 'The inferred ceRNA networks in all the three cancer types were scale-free networks as the ceRNAs’ degree distribution followed power-law with high fitness .', 'There were very few overlapping interactions between the inferred ceRNA interactions and the PPIs or TF-gene interactions .', 'Only a subset of input DE RNAs were selected as ceRNAs in the final ceRNA networks .', 'In all three cancer types , the ceRNAs were significantly enriched with cancer-related genes whereas DE RNAs that were not in the ceRNA networks did not have a significant enrichment .', 'To further explore the biological importance of our inferred ceRNA networks , we clustered ceRNA networks into modules and performed functional enrichment on each module .', 'Various cancer hallmark terms , biological processes , and pathways were enriched in the ceRNA modules across all the three cancer types .', 'In addition , some ceRNA modules were associated with multiple cancer hallmark terms , making the ceRNAs in such modules valuable biomarkers to be further investigated .', 'To examine the prognostic capability of the inferred ceRNA networks , we performed univariate Cox proportional hazard models for each ceRNA and non-ceRNA .', 'In all the three cancer types , compared to non-ceRNAs , ceRNAs exhibited higher association with cancer outcome .', 'We also observed that KIRC ceRNAs had low hazard ratios indicating that they might act as tumor-suppressors .', 'We also examined the functional importance of the miRNAs that mediated ceRNA interactions .', 'The miRNAs that mediated the highest number of ceRNA interactions ( i . e . , let-7a-5p , miR-106b-5p , and miR-9-5p ) are well-known in cancer literature; however , their prevalent roles in mediating ceRNA interactions could suggest a novel role in cancer pathogenesis .', 'Validation of computationally predicted ceRNA interactions is challenging due to the low number of experimentally-validated ceRNA interactions .', 'To address this challenge , we employed the LINCS-MCF7 dataset [32] to check whether the knockdowns of ceRNAs would cause downregulation of their predicted ceRNA partners .', 'We also compared Cancerin’s accuracy with that of Hermes [29] , a ceRNA inference tool based on mutual information criterion .', 'Based on the prediction of gene expression change using the inferred ceRNA interactions , Cancerin achieved approximately equal accuracy as Hermes; however the accuracy values from Cancerin at different experimental time points were more consistent .', 'In summary , we present Cancerin , a computational method that integrates genomic , transcriptomic , and epigenetic regulatory factors to infer genome-wide ceRNA interactions in cancer .', 'Analysis of the inferred ceRNA networks constructed by Cancerin would provide novel insights on the biological functions of this novel layer of gene regulation , especially on how it contributes to cancer pathogenesis .']]
['Introduction', 'Materials and methods', 'Results', 'Discussion']
['MicroRNAs ( miRNAs ) inhibit expression of target genes by binding to their RNA transcripts .', 'It has been recently shown that RNA transcripts targeted by the same miRNA could “compete” for the miRNA molecules and thereby indirectly regulate each other .', 'Experimental evidence has suggested that the aberration of such miRNA-mediated interaction between RNAs—called competing endogenous RNA ( ceRNA ) interaction—can play important roles in tumorigenesis .', 'Given the difficulty of deciphering context-specific miRNA binding , and the existence of various gene regulatory factors such as DNA methylation and copy number alteration , inferring context-specific ceRNA interactions accurately is a computationally challenging task .', 'Here we propose a computational method called Cancerin to identify cancer-associated ceRNA interactions .', 'Cancerin incorporates DNA methylation , copy number alteration , gene and miRNA expression datasets to construct cancer-specific ceRNA networks .', 'We applied Cancerin to three cancer datasets from the Cancer Genome Atlas ( TCGA ) project .', 'Our results indicated that ceRNAs were enriched with cancer-related genes , and ceRNA modules in the inferred ceRNA networks were involved in cancer-associated biological processes .', 'Using LINCS-L1000 shRNA-mediated gene knockdown experiment in breast cancer cell line to assess accuracy , Cancerin was able to predict expression outcome of ceRNA genes with high accuracy .']
['CeRNA interaction is a post-transcriptional gene regulation that involves interactions between RNAs competing for common miRNA regulators .', 'Dysregulation of ceRNA interactions have been implicated in multiple diseases including cancer .', 'Here we propose a computational pipeline called Cancerin that infers genome-wide ceRNA interactions in cancer .', 'Unlike existing ceRNA inference tools that consider miRNAs as the only factor that regulate gene expression , Cancerin considers other types of gene regulators besides miRNAs , namely transcription factors , copy number alteration , and DNA methylation .', 'To identify miRNA regulators for each gene , Cancerin incorporates a LASSO-based variable selection procedure that leverages both sequence-based and gene expression information .', 'Then multiple expression-based filtering conditions are employed to select ceRNA interactions .', 'Cancerin was applied to three cancer datasets from TCGA .', 'Functional analysis indicated that the inferred ceRNAs were enriched with cancer-related genes , and ceRNAs within ceRNA modules ( densely-connected ceRNAs ) were involved in cancer-associated biological processes .', 'Survival analysis showed that compared to non-ceRNAs , ceRNAs hold better prognostic power to predict survival outcomes .', 'Our results showed that Cancerin can be used to identify genome-wide and functionally important ceRNA interactions , which makes it a valuable tool to better understand this recently discovered gene regulation mechanism and its role in cancer biology .']
['medicine and health sciences', 'gene regulation', 'cancer risk factors', 'long non-coding rnas', 'oncology', 'regulator genes', 'micrornas', 'gene types', 'epigenetics', 'dna', 'chromatin', 'dna methylation', 'research and analysis methods', 'sequence analysis', 'chromosome biology', 'bioinformatics', 'gene expression', 'biological databases', 'chromatin modification', 'dna modification', 'biochemistry', 'rna', 'genetic causes of cancer', 'sequence databases', 'cell biology', 'nucleic acids', 'database and informatics methods', 'genetics', 'biology and life sciences', 'non-coding rna']