A Risk Prediction Model of DNA Methylation Improves Prognosis Evaluation and Indicates Gene Targets in Prostate Cancer

Abstract

Aim: Prostate cancer (PCa) is the most common malignancy found in males worldwide. Although it is mostly indolent, PCa still poses a serious threat to long-term health. Materials & methods: The Cancer Genome Atlas data were randomly divided into training and validation groups. Least absolute shrinkage and selection operator regression on DNA methylation data in the training group was conducted to build the model, which was validated in the validation group. Weighted correlation network analysis was conducted on RNA-seq data to identify the therapy target. Functional validation (western blot, quantitative real-time PCR, cell transfection, Cell Counting Kit-8 assay, colony formation assay, wound healing assay and transwell invasion assay) for the target was conducted. Results: The model is an independent predictor of prognosis. The knockdown of FOXD1 inhibits cell proliferation, migration and invasion of PCa. Conclusion: The risk of patients could be evaluated by the model, which revealed that FOXD1 might promote poor prognosis.

A Prognostic Prediction Model Developed Based on Four CpG Sites and Weighted Correlation Network Analysis Identified DNAJB1 as a Novel Biomarker for Pancreatic Cancer

“…The circulating tumor DNA methylation markers can be utilized to generate a risk model for the diagnosis and prognosis prediction of ovarian cancer, colorectal cancer, and hepatocellular carcinoma (13,48,49). Additionally, the DNA methylation markers originating from tissues can also be employed to construct a prognosis prediction model for esophageal, gastric, and prostate cancers (11,12,14). These studies demonstrated that the DNA methylation status can serve as novel biomarkers to generate the prognosis prediction model.…”

“…The R package "minfi" was used to normalize the β-values of methylation data. The Mann-Whitney U test was performed to select the differentially methylated CpG sites with adjusted p-value < 0.05 and | log2 fold-change| > 2 (11,18). The samples of patients with pancreatic cancer exhibiting survival time of less than 30 days were removed.…”

“…Moreover, specific DNA methylation signatures in the circulating DNA from pancreatic juice and plasma can be used as novel biomarkers for pancreatic cancer (9,10). Several prognostic prediction models using DNA methylation data have been proposed for prostate, gastric, colorectal, and esophageal cancers (11)(12)(13)(14). These studies indicated that the DNA methylation status is closely associated with the prognosis of multiple cancers.…”

A signature of glucose metabolism and DNA methylation improves prognostic prediction for urinary bladder cancer

“…A large number of studies have provided deep insights into molecular mechanisms of glucose metabolism alterations in cancers [8][9][10][11][12], by which we are more convinced of the critical role glucose metabolism plays in malignant tumors. Meanwhile, with abnormal alterations widely appearing in different cancers, DNA methylation has been recently analyzed by computational models to discover potential biomarkers for prediction of early diagnosis or prognosis of cancers [18][19][20].…”

“…For some genes, methylation has been found to be responsible for early carcinogenesis [17]. Thus, it has become a trend for DNA methylation to act as early diagnostic and prognostic biomarkers for tumors [18][19][20] because of its relative stability [21] and easy access to detection in blood. For instance, several studies have proved that hepatocellular carcinoma patients could be discriminated from healthy individuals with high sensitivities by detecting methylation of CpGs [22][23][24].…”