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Discovery of Molecular DNA Methylation-Based Biomarkers through Genome-Wide Analysis of Response Patterns to BCG for Bladder Cancer
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Background: Bacillus Calmette-Guérin (BCG) immunotherapy, the standard adjuvant intravesical therapy for some intermediate and most high-risk non-muscle invasive bladder cancers (NMIBCs), suffers from a heterogenous response rate. Molecular markers to help guide responses are scarce and currently not used in the clinical setting. Methods: To identify novel biomarkers and pathways involved in response to BCG immunotherapy, we performed a genome-wide DNA methylation analysis of NMIBCs before BCG therapy. Genome-wide DNA methylation profiles of DNA isolated from tumors of 26 BCG responders and 27 failures were obtained using the Infinium MethylationEPIC BeadChip. Results: Distinct DNA methylation patterns were found by genome-wide analysis in the two groups. Differentially methylated CpG sites were predominantly located in gene promoters and gene bodies associated with bacterial invasion of epithelial cells, chemokine signaling, endocytosis, and focal adhesion. In total, 40 genomic regions with a significant difference in methylation between responders and failures were detected. The differential methylation state of six of these regions, localized in the promoters of the genes GPR158, KLF8, C12orf42, WDR44, FLT1, and CHST11, were internally validated by bisulfite-sequencing. GPR158 promoter hypermethylation was the best predictor of BCG failure with an AUC of 0.809 (p-value < 0.001). Conclusions: Tumors from BCG responders and BCG failures harbor distinct DNA methylation profiles. Differentially methylated DNA regions were detected in genes related to pathways involved in bacterial invasion of cells or focal adhesion. We identified candidate DNA methylation biomarkers that may help to predict patient prognosis after external validation in larger, well-designed cohorts.
MDPI AG
Dafina Ilijazi
Walter Pulverer
Iris E. Ertl
Ursula Lemberger
Shoji Kimura
Mohammad Abufaraj
David D’Andrea
Benjamin Pradere
Andreas Bruchbacher
Anna Graf
Francesco Soria
Martin Susani
Andrea Haitel
Luca Molinaro
Armin Pycha
Evi Comploj
Stephan Pabinger
Andreas Weinhäusel
Gerda Egger
Shahrokh F. Shariat
Melanie R. Hassler
Title: Discovery of Molecular DNA Methylation-Based Biomarkers through Genome-Wide Analysis of Response Patterns to BCG for Bladder Cancer
Description:
Background: Bacillus Calmette-Guérin (BCG) immunotherapy, the standard adjuvant intravesical therapy for some intermediate and most high-risk non-muscle invasive bladder cancers (NMIBCs), suffers from a heterogenous response rate.
Molecular markers to help guide responses are scarce and currently not used in the clinical setting.
Methods: To identify novel biomarkers and pathways involved in response to BCG immunotherapy, we performed a genome-wide DNA methylation analysis of NMIBCs before BCG therapy.
Genome-wide DNA methylation profiles of DNA isolated from tumors of 26 BCG responders and 27 failures were obtained using the Infinium MethylationEPIC BeadChip.
Results: Distinct DNA methylation patterns were found by genome-wide analysis in the two groups.
Differentially methylated CpG sites were predominantly located in gene promoters and gene bodies associated with bacterial invasion of epithelial cells, chemokine signaling, endocytosis, and focal adhesion.
In total, 40 genomic regions with a significant difference in methylation between responders and failures were detected.
The differential methylation state of six of these regions, localized in the promoters of the genes GPR158, KLF8, C12orf42, WDR44, FLT1, and CHST11, were internally validated by bisulfite-sequencing.
GPR158 promoter hypermethylation was the best predictor of BCG failure with an AUC of 0.
809 (p-value < 0.
001).
Conclusions: Tumors from BCG responders and BCG failures harbor distinct DNA methylation profiles.
Differentially methylated DNA regions were detected in genes related to pathways involved in bacterial invasion of cells or focal adhesion.
We identified candidate DNA methylation biomarkers that may help to predict patient prognosis after external validation in larger, well-designed cohorts.
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