Methylation Status of Corticotropin-Releasing Factor (CRF) Receptor Genes in Colorectal Cancer.
Maria PanagopoulouAntonia CheretakiMakrina KaraglaniIoanna BalgkouranidouEirini BiziotaKyriakos AmarantidisNikolaos XenidisStylianos KakolyrisStavroula BaritakiEkaterini ChatzakiPublished in: Journal of clinical medicine (2021)
The corticotropin-releasing factor (CRF) system has been strongly associated with gastrointestinal pathophysiology, including colorectal cancer (CRC). We previously showed that altered expression of CRF receptors (CRFRs) in the colon critically affects CRC progression and aggressiveness through regulation of colonic inflammation. Here, we aimed to assess the potential of CRFR methylation levels as putative biomarkers in CRC. In silico methylation analysis of CRF receptor 1 (CRFR1) and CRF receptor 2 (CRFR2) was performed using methylome data derived by CRC and Crohn's disease (CD) tissues and CRC-derived circulating cell-free DNAs (ccfDNAs). In total, 32 and 33 differentially methylated sites of CpGs (DMCs) emerged in CRFR1 and CRFR2, respectively, between healthy and diseased tissues. The methylation patterns were verified in patient-derived ccfDNA samples by qMSP and associated with clinicopathological characteristics. An automated machine learning (AutoML) technology was applied to ccfDNA samples for classification analysis. In silico analysis revealed increased methylation of both CRFRs in CRC tissue and ccfDNA-derived datasets. CRFR1 hypermethylation was also noticed in gene body DMCs of CD patients. CRFR1 hypermethylation was further validated in CRC adjuvant-derived ccfDNA samples, whereas CRFR1 hypomethylation, observed in metastasis-derived ccfDNAs, was correlated to disease aggressiveness and adverse prognostic characteristics. AutoML analysis based on CRFRs methylation status revealed a three-feature high-performing biosignature for CRC diagnosis with an estimated AUC of 0.929. Monitoring of CRFRs methylation-based signature in CRC tissues and ccfDNAs may be of high diagnostic and prognostic significance in CRC.
Keyphrases
- genome wide
- machine learning
- dna methylation
- cell free
- gene expression
- deep learning
- end stage renal disease
- oxidative stress
- copy number
- early stage
- molecular docking
- poor prognosis
- single cell
- ejection fraction
- risk assessment
- newly diagnosed
- chronic kidney disease
- electronic health record
- climate change
- prognostic factors
- nk cells