Abstract 1950: Enhanced detection of pancreatic cancer through methylation-based liquid biopsy: insights into tumor heterogeneity, early alterations, and stromal contributions

Abstract Pancreatic cancer is one of the deadliest malignancies, with a high mortality rate attributed to late-stage diagnosis and limited treatment options. Recent advancements in liquid biopsy, particularly through cell-free DNA (cfDNA) analyses, offer hope for early detection and prognosis. Specifically, cfDNA methylation profiling shows promise, outperforming traditional mutation-based methods such as single nucleotide variants (SNVs) and copy number variations (CNVs) in terms of sensitivity and specificity. In this study, we conducted paired CAPP-seq and EM-seq analyses on 29 pancreatic cfDNA samples. Our results indicated that methylation-based detection achieved a detection rate of 62.10% with 95% specificity, significantly higher than the 44.82% detection rate observed with CAPP-seq. Following the application of JEEPERS (Jagged-End Error Polishing of Enzymatically misRepaired Sequences) to mitigate methylation errors from jagged ends, the detection rate further improved to 72.41%. This aligns with existing literature highlighting the superior sensitivity of methylation profiling. We propose three hypotheses to explain this enhanced sensitivity: (1) Some pancreatic tumors exhibit CNVs prior to SNVs or contain subclonal KRAS mutations that are not detectable via SNV-based methods; (2) Methylation alterations may occur early during the PanIN stage, allowing the release of both normal and tumor-derived epithelial cells into circulation, identifiable by tissue-specific methylation markers; (3) PDAC tumors characterized by increased fibroblast content and epithelial-to-mesenchymal transition engage unique methylation signatures. To validate these hypotheses, we analyzed both pancreatic tumor tissues and cfDNA samples using CAPP-seq, LPWGS, emWGS, and single-cell nuclear sequencing data. Our findings confirm that CNVs frequently precede SNVs and highlight that pancreatic cfDNA comprises a notable proportion of epithelial cells. Importantly, methylation-based methodologies are capable of detecting signals from both normal and tumor-derived epithelial cells, leveraging cell-type-specific patterns. In contrast, SNV-based approaches are restricted to tumor-only signals. Furthermore, fibroblast methylation markers elucidate stromal contributions to the overall methylation landscape. These findings underscore the potential of methylation-based cfDNA analysis as a robust method for pancreatic cancer detection. We advocate for further validation through the development of a targeted panel that integrates SNVs, CNVs, and cell-type-specific markers to enhance diagnostic accuracy in clinical settings. Citation Format: Rui Wang, Diego Almanza, Mari Olsen, Xiaoman Kang, Daniel King, Maximilian Diehn, Ash Alizadeh. Enhanced detection of pancreatic cancer through methylation-based liquid biopsy: insights into tumor heterogeneity, early alterations, and stromal contributions [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 1950.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-1950
Primary Topic
Cancer Genomics and Diagnostics
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article
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article

Abstract 1950: Enhanced detection of pancreatic cancer through methylation-based liquid biopsy: insights into tumor heterogeneity, early alterations, and stromal contributions

Maximilian Diehn, Ash A. Alizadeh, Xiaoman Kang, Daniel King et al.
Cancer Research
Cancer Genomics and Diagnostics
article

Abstract 1950: Enhanced detection of pancreatic cancer through methylation-based liquid biopsy: insights into tumor heterogeneity, early alterations, and stromal contributions

Maximilian Diehn, Ash A. Alizadeh, Xiaoman Kang, Daniel King, Diego Almanza, Rui Wang, Mari Olsen
article en

Abstract

Abstract Pancreatic cancer is one of the deadliest malignancies, with a high mortality rate attributed to late-stage diagnosis and limited treatment options. Recent advancements in liquid biopsy, particularly through cell-free DNA (cfDNA) analyses, offer hope for early detection and prognosis. Specifically, cfDNA methylation profiling shows promise, outperforming traditional mutation-based methods such as single nucleotide variants (SNVs) and copy number variations (CNVs) in terms of sensitivity and specificity. In this study, we conducted paired CAPP-seq and EM-seq analyses on 29 pancreatic cfDNA samples. Our results indicated that methylation-based detection achieved a detection rate of 62.10% with 95% specificity, significantly higher than the 44.82% detection rate observed with CAPP-seq. Following the application of JEEPERS (Jagged-End Error Polishing of Enzymatically misRepaired Sequences) to mitigate methylation errors from jagged ends, the detection rate further improved to 72.41%. This aligns with existing literature highlighting the superior sensitivity of methylation profiling. We propose three hypotheses to explain this enhanced sensitivity: (1) Some pancreatic tumors exhibit CNVs prior to SNVs or contain subclonal KRAS mutations that are not detectable via SNV-based methods; (2) Methylation alterations may occur early during the PanIN stage, allowing the release of both normal and tumor-derived epithelial cells into circulation, identifiable by tissue-specific methylation markers; (3) PDAC tumors characterized by increased fibroblast content and epithelial-to-mesenchymal transition engage unique methylation signatures. To validate these hypotheses, we analyzed both pancreatic tumor tissues and cfDNA samples using CAPP-seq, LPWGS, emWGS, and single-cell nuclear sequencing data. Our findings confirm that CNVs frequently precede SNVs and highlight that pancreatic cfDNA comprises a notable proportion of epithelial cells. Importantly, methylation-based methodologies are capable of detecting signals from both normal and tumor-derived epithelial cells, leveraging cell-type-specific patterns. In contrast, SNV-based approaches are restricted to tumor-only signals. Furthermore, fibroblast methylation markers elucidate stromal contributions to the overall methylation landscape. These findings underscore the potential of methylation-based cfDNA analysis as a robust method for pancreatic cancer detection. We advocate for further validation through the development of a targeted panel that integrates SNVs, CNVs, and cell-type-specific markers to enhance diagnostic accuracy in clinical settings. Citation Format: Rui Wang, Diego Almanza, Mari Olsen, Xiaoman Kang, Daniel King, Maximilian Diehn, Ash Alizadeh. Enhanced detection of pancreatic cancer through methylation-based liquid biopsy: insights into tumor heterogeneity, early alterations, and stromal contributions [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 1950.

Cancer ResearchVol. 85(8_Supplement_1)
Hofstra University (US), Palo Alto University (US), Stanford University (US)
Openalex Percentile: Top 90%
Cancer Genomics and Diagnostics
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