ArticleMolecular genetics and genomics : MGG2022
Epigenetic inactivation of DNA repair genes as promising prognostic and predictive biomarkers in urothelial bladder carcinoma patients.
Article in Molecular genetics and genomics : MGG, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 8 citations in OpenAlex.
- Intervention of machine learning in bladder cancer research using multi-omics datasets: systematic review on biomarker identification.Discover oncology · 2025Review
- Artificial intelligence for predicting response to neoadjuvant chemotherapy for bladder cancer A comprehensive systematic review and meta-analysis.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2024Review
- Analysis of urine cell-free DNA in bladder cancer diagnosis by emerging bioactive technologies and materials.Frontiers in bioengineering and biotechnology · 2024Review
- Antimicrobial Peptide MPX with Broad-Spectrum Bactericidal Activity Promotes Proper Abscess Formation and Relieves Skin Inflammation.Probiotics and antimicrobial proteins · 2023Article
- Epigenetics of Thymic Epithelial Tumors.Cancers · 2023Review
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We sought to examine epigenetic inactivation of DNA damage repair (DDR) genes as prognostic and predictive biomarkers for urothelial bladder cancer (UBC) as there are currently no reliable prognostic biomarkers that identify UBC patients who would benefit from chemotherapy. Genome-wide DNA methylome using the cancer genome atlas-bladder cancer (TCGA-BLCA) datasets (primary tumors = 374 and normal tissues = 37) was performed for 154 DDR genes. The most two significant differentially methylated genes, Retinoblastoma binding protein 8 (RBBP8) and MutS homologue 4 (MSH4), between primary tumors and normal tissues of TCGA-BLCA were validated by methylation-specific PCR (MSP) in UBC (n = 70) compared to normal tissues (n = 30). RBBP8 and MSH4 expression was measured using qRT-PCR. We developed a predictive model for therapeutic response based on the RBBP8- and MSH4-methylation along with patients' clinical features. Then, we assessed the prognostic significance of RBBP8 and MSH4. RBBP8- and MSH4 methylation and corresponding gene downregulation significantly associated with muscle-invasive phenotype, prolonged progression-free survival (PFS) and increased susceptibility to cisplatin chemotherapy in UBC. Promoter methylation of RBBP8 and MSH4 was positively correlated with each other and with their corresponding gene repression. The best machine-learning classification model predicted UBC patients' response to cisplatin-based chemotherapy with an accuracy of 90.05 ± 4.5%. Epigenetic inactivation of RBBP8 and MSH4 in UBC could sensitize patients to DNA-damaging agents. A predictive machine-learning modeling approach based on the clinical features along with RBBP8- and MSH4-methylation might be a promising tool for stratification of UBC responders from nonresponders to chemotherapy.
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