LncRNA promoter present a global hyper-methylation character in colon cancer
Alteration of DNA methylation has been implicated in tumor progression and disease development, some studies have point out DNA methylation have potential role in early screening of colon cancer [31]. Here, we investigate the DNA methylation character in lncRNA promoter for colon cancer. We have successfully mapped 51,544 methylation probes to lncRNA promoter regions (Fig. 1A), which is enough for studying DNA methylation in lncRNA. Next, we identified differentially methylated sites (DMSs) in lncRNAs, and finally get 1,809 DMSs (p < 0.01, absolute methylation difference > 0.2, Fig. 1B). Generally, we observed most DMSs display higher methylation value in cancer samples than normal samples (Fig. 1B). So, we classified DMSs as hyper- (methylation difference > 0) or hypo-methylation site (methylation difference < 0), hyper-DMSs are more than hypo-DMSs in all chromosomes, besides, we found chromosome 19 only have hyper-DMSs in lncRNA promoters (Fig. 1C). In addition, we found the number of hyper-DMSs is much more than hypo-DMSs in antisense, lincRNA and process transcript (9.8, 4.2, 7.7 fold respectively, Fig. 1C). These hyper- or hypo DMSs are potential regulators for the host lncRNAs, and may participate in the pathogenic processes for colon cancer.
Dissecting the relationship between promoter methylation and lncRNA in colon cancer
To investigate the role of our identified DMSs in lncRNA transcription regulation, we systematically identified correlated DNA methylation site-lncRNA pairs in colon cancer (Fig. 2A), and named it as lncQTMs. We found in most chromosomes, promoter methylation sites prone to negatively regulate the lncRNA expression, besides, in some chromosomes (such as chromosome 1, 9, 14, 17, 18, 21, 22), there are no positive lncQTM pairs (Fig. 2B). In total, there are 392 negtive lncQTMs (correlation coefficient < 0, 87.9%) and 54 postive lncQTMs (correlation coefficient > 0, 12.1%) (Fig. 2C). This observation indicates promoter methylation site are more likely to inhibit lncRNA expression in colon cancer, which is consist with previous findings for DNA methylation in protein coding genes regulation [32]. In addition, we classified lncQTMs according to the distance between methylation sites and TSSs in positive and negative lncQTMs respectively. For negative lncQTMs, methylation sites with closer distance to lncRNA TSSs display a higher significant character (Fig. 2D), however, for positive lncQTMs, some methylation sites located within the 1500 pb to 2000 bp of lncRNA TSSs show more significant character than the methylation sites within TSS 200 bp (Fig. 2E). Furthermore, we analyzed correlation size for the lncQTMs in different distance class, in negative lncQTMs, DNA methylation site located within 500 bp for TSS present a strong correlation with lncRNA (Mann-Whitney U test, p < 0.01), and there is no significant difference when the distance increased (Fig. 2F). For positive lncQTMs, the correlation coefficient significantly increased when the distance between methylation sites and lncRNA TSSs reach in 1500–2000 bp scale (Mann-Whitney U test, p < 0.05, Fig. 2G). This result suggest lncRNA promotor methylation sites are likely to inhibit expression, the sites located closer to the TSS display a more significant and stronger correlation with the corresponding lncRNAs.
Identification Acting Tf Around Lncqtms In Colon Cancer
DNA methylation can modulate gene expression through multiple ways [33], specifically, it can shape TF binding events across human tissues [34, 35]. We thus speculate human TFs might sensitive to the changes of DNA methylation in lncQTMs. Based on this, we scanned TF motif occurrence in lncQTMs using FIMO tool (Fig. 3A), for the significant motifs (p < 0.0001, the methylation site located within the motif), we expect TF motifs are more enriched in lncQTMs than all lncRNA promoter methylation sites (lower OR > 1.1). After filtering, we got 155 motifs around lncQTMs (Fig. 3B). These motifs associated TFs are potential regulators of the corresponding lncRNAs. To confirm the relationship between TFs, methylation sites, and lncRNAs, we identified significantly correlated TF-methylation site and TF-lncRNA pairs by pearson method (p < 0.01). Finally, we obtained 16 TF-methylation-lncRNA relationships in colon cancer, which comprising 13 TFs, 15 methylation sites and 15 lncRNAs (Fig. 3C). Among 15 lncRNAs regulated by the interplay between TF and methylation, 8 lncRNAs are display a differential expression pattern (t test, p < 0.01, Fig. 4D) between cancer and normal samples. Of these lncRNAs, lncRNA HAND2-AS1 have been proved to sponge miR-1275 and suppress colon cancer development [36]; besides, hypo-methylation in lncRNA LINC00460 can promote colon cancer and served as potential biomarker [37]. As a result, these TF-methylation-lncRNA events may modulate colon cancer progression, altering the interaction between them may beneficial for therapy and prognosis.
LncRNAs can serve as predictors for drug response in colon cancer
Recently, lncRNAs have shed light on drug response in human cancer [38]. Here, we also investigate the association between lncRNA and anticancer drug response. We downloaded pharmacological and lncRNA profiles for colon cancer from CCLE database. We totally got 24 drug components in colon cancer, and explore the effect of lncRNAs (derived from TF-methylation-lncRNA network) in drug sensitivity. We divided cancer samples into two group by lncRNA median expression value, and investigate the drug response (activity area) difference between two groups. During this process, we got 3 lncRNAs that can distinguish 5 drugs response (5 lncRNA-drug pairs, CAHM and 17-AAG, RP11-834C11.4 and Sorafenib, RP11-834C11.4 and TKI258, RP11-834C11.4 and RAF265, LINC00460 and Topotecan) among cancer samples (Fig. 4A, Mann-Whitney U test, p < 0.01). Next, we further stratified colon cancer samples into resistant and sensitive group for each drug, and use lncRNA expression to predict drug response by logistic regression model. For the resulted 5 lncRNA-drug pairs, each lncRNA can have good performance to the corresponding drug response (Fig. 4B-F). Interestingly, as our previous result shows, RP11-834C11.4 and LINC00460 have been demonstrate to participate in the progress of colon cancer.
Mining Tf-methylation-lncrna Prognostic Signature In Colon Cancer
The TF-methylation-lncRNA regulatory events detected by our research might affect patient prognosis in colon cancer. So, from a more comprehensive aspect, we consider the interaction between TF-methylation-lncRNA, and did multivariate Cox proportional regression by TF, methylation site and lncRNA on the patient OS time. Based on the regression result, we designed a risk model to evaluate patient prognosis across colon cancer samples (method). Each patient will get a risk score in this process, we stratified patients into low and high-risk group by median risk score among patients, after that, we did survival analysis by Kaplan-Meier estimate method. For the identified TF-methylation-lncRNA relationships, we identified 2 of them (HES1_cg24685006 _RP4-728D4.2, SREBF1_cg05372727_LINC00460) are significantly associated with survival outcome in colon cancer (log rank p < 0.05, Fig. 5). Interestingly, LINC00460 have been identified as topotecan response predictor in our study, this result emphasizes the important role of LINC00460 in drug sensitivity prediction and prognosis stratification in colon cancer.