The document discusses a study analyzing cell-free DNA (cfDNA) methylation as a predictive biomarker of response to neoadjuvant chemotherapy for muscle-invasive bladder cancer patients. Researchers developed an mR-score biomarker using machine learning that predicted response to chemotherapy. The mR-scores were stable after chemotherapy started and may help stratify bladder cancer risk. Future studies aim to validate the risk stratification model and further explore the translational potential of cfDNA methylation analysis.

1. Dr Preetham Dev
Consultant Uro-Oncologist,
Manipal Hospital, Hebbal, Bangalore

2. Disclosure Information<br />Relationships with Companies
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3. cfDNA Methylation as a Predictive Biomarker of Response to Neoadjuvant Chemotherapy For Patients With MIBC in SWOG S1314
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4. Background
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5. S1314 Schema
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6. Plasma Cell-free DNA (cfDNA) Methylation Analysis
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7. Infinium MethylationEPIC BeadChip Array For cfDNA Methylome Analysis
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8. Data with Consistent Quality in Patient Samples
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9. Patient characteristics: Well-balanced Between Responders And Non-responders
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10. Machine Learning Predictive Biomarker: mR-Score
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11. mR-scores: A Biomarker of Chemotherapy Response
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12. mR-scores Were Stable After Starting Chemotherapy
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13. Circulating Bladder DNA analysis
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14. Proposed MIBC Risk Stratification Model:<br />To be Validated in Future Studies
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15. Conclusions
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16. Translational Potential and Future Studies
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17. Acknowledgements
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18. ● Cost-effectiveness in the Indian population
● Collaborative with different population
● Different probes available
● cfDNA vs CTC
● No conventional biomarkers
● Extension into screening