Bioinformatics analysis of multi-omics data identifying molecular biomarker candidates and epigenetically regulatory targets associated with retinoblastoma

Abstract

Retinoblastoma (RB) is the commonest malignant tumor of the infant retina. Besides genetic changes, epigenetic events are also considered to implicate the occurrence of RB. This study aimed to identify significantly altered protein-coding genes, DNA methylation, microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and their molecular functions and pathways associated with RB, and investigate the epigenetically regulatory mechanism of DNA methylation modification and non-coding RNAs on key genes of RB via bioinformatics method. We obtained multi-omics data on protein-coding genes, DNA methylation, miRNAs, and lncRNAs from the Gene Expression Omnibus database. We identified differentially expressed genes (DEGs) using the Limma package in R, discerned their biological functions and pathways using enrichment analysis, and conducted the modular analysis based on protein-protein interaction network to identify hub genes of RB. Survival analyses based on The Cancer Genome Atlas clinical database were performed to analyze prognostic values of key genes of RB. Subsequently, we identified the differentially methylated genes, differentially expressed miRNAs (DEMs) and lncRNAs (DELs), and intersected them with key genes to analyze possible targets of the underlying epigenetic regulatory mechanisms. Finally, the ceRNA network of lncRNAs-miRNAs-mRNAs was constructed using Cytoscape. A total of 193 DEGs, 74 differentially methylated-DEGs (DM-DEGs), 45 DEMs, 5 DELs were identified. The molecular pathways of DEGs were enriched in cell cycle, p53 signaling pathway, and DNA replication. A total of 10 key genes were identified and found significantly associated with poor survival outcome based on survival analyses, including CDK1, BUB1, CCNB2, TOP2A, CCNB1, RRM2, KIF11, KIF20A, NDC80, and TTK. We further found that hub genes MCM6 and KIF14 were differentially methylated, key gene RRM2 was targeted by DEMs, and key genes TTK, RRM2, and CDK1 were indirectly regulated by DELs. Additionally, the ceRNA network with 222 regulatory associations was constructed to visualize the correlations between lncRNAs-miRNAs-mRNAs. This study presents an integrated bioinformatics analysis of genetic and epigenetic changes that may be associated with the development of RB. Findings may yield many new insights into the molecular biomarker candidates and epigenetically regulatory targets of RB.

Molecular Changes in Retinoblastoma beyond RB1: Findings from Next-Generation Sequencing

“…Future studies may expand upon these results by considering more downstream analytes, such as DNA methylation or RNA expression, to assess biological differences between patients either dependent or independent of DNA mutations. For example, recent studies have considered genome-wide methylation and found expression patterns unique to retinoblastoma, suggesting their importance to oncogenesis [ 40 , 41 ]. Further clinical assessment of patient phenotypes alongside various biological measurements may yield important insight into the progression of retinoblastoma from DNA mutation to unique clinicopathological features of retinoblastoma.…”

Ribonucleotide reductase subunit M2 promotes proliferation and epithelial–mesenchymal transition via the JAK2/STAT3 signaling pathway in retinoblastoma

“…As the catalytic subunit of RR, RRM2 is the rate-limiting enzyme for DNA synthesis and repair, and its expression level is associated with the sensitivity of cancer cells to chemotherapy drugs and endocrine therapy drugs [ 10 , 25 , 28 ]. Previous studies indicated that in neuroblastoma, a highly malignant brain tumor, patients with high RRM2 expression are associated with a worse prognosis [ 29 ]. A previous study also suggests that RRM2 upregulation contributes to RB cell cycle progression [ 30 ].…”

Investigation of Key Signaling Pathways Associating miR-204 and Common Retinopathies

“…Also, the study of Zeng et al demonstrated that bioinformatics analysis of the GSE97508 dataset, with the approach of examining epigenetic factors in retinoblastoma, can create significant diagnostic or therapeutic methods. TTK , RRM2 , and CDK1 were selected as candidates [ 55 ]. In the present study, RRM2 was also selected as a candidate gene related to miR-204.…”