Abstract 3338: A CpG methylation based epigenetic signature for recurrence prediction in stage II/III colorectal cancer: <i>The CENSURE Study</i>

Introduction: Adjuvant chemotherapy (ACT) is the standard of care for patients with stage III or high-risk stage II colorectal cancer (CRC) following curative-intent resection. However, over 30% of these patients experience recurrence despite treatment, highlighting the urgent need for developing predictive biomarkers of response to ACT. This study sought to identify epigenetic biomarkers for predicting recurrence in stage II/III CRC. Patients and Methods: This study included three phases: discovery, training, independent testing. In the discovery phase, we performed genomewide methylation profiling analysis between recurrent (recurrence-free survival, RFS &amp;lt; 5 years) and non-recurrent patients with CRC. A LASSO-based machine learning algorithm was employed to refine and optimize the candidate CpG sites. Subsequently, we developed and tested a methylation biomarker panel by quantitative pyrosequencing assays, followed by eXtreme Gradient Boosting (XGB) machine-learning algorithm in both the training (n = 236) and testing (n = 175) cohorts. Finally, we established the CENSURE (CpG mEthylatioN-based epigenetic SignatURE) model, which combined the CpG methylation panel and carcinoembryonic antigen (CEA) levels, to predict recurrence in stage II/III CRC. Results: A panel of 8 CpG candidates identified in the discovery phase was refined to 6 using XGB in the training cohort. The 6-CpG panel demonstrated robust ability to predict recurrence, with AUC values of 91.2% and 79.3% in the training and testing cohorts, respectively. Multivariate Cox regression analysis revealed that CEA ≥ 5 ng/mL (HR 2.92; 95% CI: 1.81-4.70) and the CpG panel (HR 19.5; 95% CI: 8.78-43.1) were independent predictors of recurrence. Building on this, we developed the CENSURE model, which integrates the CpG panel with CEA. The CENSURE model achieved AUC values of 95.2% and 86.1%, with sensitivities of 83.9% and 83.3% in the training and testing cohorts, respectively. CENSURE high-risk patients exhibited significantly higher 5-year (71.5% vs 8.0%) and 2-year recurrent rates (48.0% vs 5.4%). Notably, the CENSURE model outperformed CEA risk stratification alone, correctly predicting an additional 46.5% (40 out of 86) of recurrence cases in the entire study cohort. Conclusions: In conclusion, the CENSURE assay represents a novel potential advance with a significant clinical impact for postoperative recurrence prediction in stage II/III CRC. Citation Format: Caiming Xu, Silei Xu, Joan Maurel, Man Li, Ajay Goel. A CpG methylation based epigenetic signature for recurrence prediction in stage II/III colorectal cancer: The CENSURE Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3338.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-3338
Primary Topic
Radiomics and Machine Learning in Medical Imaging
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Abstract 3338: A CpG methylation based epigenetic signature for recurrence prediction in stage II/III colorectal cancer: The CENSURE Study

Man Li, Joan Maurel, Caiming Xu, Ajay Goel et al.
Cancer Research
Radiomics and Machine Learning in Medical Imaging
article

Abstract 3338: A CpG methylation based epigenetic signature for recurrence prediction in stage II/III colorectal cancer: The CENSURE Study

Man Li, Joan Maurel, Caiming Xu, Ajay Goel, Silei Xu
article en

Abstract

Introduction: Adjuvant chemotherapy (ACT) is the standard of care for patients with stage III or high-risk stage II colorectal cancer (CRC) following curative-intent resection. However, over 30% of these patients experience recurrence despite treatment, highlighting the urgent need for developing predictive biomarkers of response to ACT. This study sought to identify epigenetic biomarkers for predicting recurrence in stage II/III CRC. Patients and Methods: This study included three phases: discovery, training, independent testing. In the discovery phase, we performed genomewide methylation profiling analysis between recurrent (recurrence-free survival, RFS &amp;lt; 5 years) and non-recurrent patients with CRC. A LASSO-based machine learning algorithm was employed to refine and optimize the candidate CpG sites. Subsequently, we developed and tested a methylation biomarker panel by quantitative pyrosequencing assays, followed by eXtreme Gradient Boosting (XGB) machine-learning algorithm in both the training (n = 236) and testing (n = 175) cohorts. Finally, we established the CENSURE (CpG mEthylatioN-based epigenetic SignatURE) model, which combined the CpG methylation panel and carcinoembryonic antigen (CEA) levels, to predict recurrence in stage II/III CRC. Results: A panel of 8 CpG candidates identified in the discovery phase was refined to 6 using XGB in the training cohort. The 6-CpG panel demonstrated robust ability to predict recurrence, with AUC values of 91.2% and 79.3% in the training and testing cohorts, respectively. Multivariate Cox regression analysis revealed that CEA ≥ 5 ng/mL (HR 2.92; 95% CI: 1.81-4.70) and the CpG panel (HR 19.5; 95% CI: 8.78-43.1) were independent predictors of recurrence. Building on this, we developed the CENSURE model, which integrates the CpG panel with CEA. The CENSURE model achieved AUC values of 95.2% and 86.1%, with sensitivities of 83.9% and 83.3% in the training and testing cohorts, respectively. CENSURE high-risk patients exhibited significantly higher 5-year (71.5% vs 8.0%) and 2-year recurrent rates (48.0% vs 5.4%). Notably, the CENSURE model outperformed CEA risk stratification alone, correctly predicting an additional 46.5% (40 out of 86) of recurrence cases in the entire study cohort. Conclusions: In conclusion, the CENSURE assay represents a novel potential advance with a significant clinical impact for postoperative recurrence prediction in stage II/III CRC. Citation Format: Caiming Xu, Silei Xu, Joan Maurel, Man Li, Ajay Goel. A CpG methylation based epigenetic signature for recurrence prediction in stage II/III colorectal cancer: The CENSURE Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3338.

Cancer ResearchVol. 85(8_Supplement_1)
City of Hope (US), Hospital Clínic de Barcelona (ES), Beckman Research Institute
Good health and well-being
Openalex Percentile: Top 88%
Radiomics and Machine Learning in Medical Imaging
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