Abstract 118: Detecting early cancer using cfDNA methylation signatures with nanopore sequencing.

Abstract Early cancer screening improves survival by enabling timely treatment before the disease progresses. However, current population-wide screening tools are limited to a few cancer types, highlighting the need for novel detection methods that can be routinely used to detect multiple cancers. Plasma tumour-derived cell-free DNA (cfDNA) carries the tumour’s genetic and epigenetic alterations and can be used to develop new screening methods. Here, we aim to identify precancerous and early tumour-associated cfDNA methylation signatures. We analyzed nanopore sequencing data performed on plasma collected up to 10 years before clinical diagnosis from patients with breast or prostate cancer, and stage II diagnostic plasma from breast cancer patients. Preliminary data revealed global hypomethylation and increased inter-patient variability in the diagnostics breast cancer samples, both of which were more pronounced in younger patients. Notably, global hypomethylation was found in Triple Negative Breast Cancer (TNBC) and ER+/HER2- Breast Cancer, but not in other subtypes. These global alterations were not observed in precancerous lesions in both cancer types, suggesting such epigenetic alterations may arise or become detectable during malignant transformation rather than early tumour initiation. To identify loci that are associated with precancerous epigenetic alterations, differentially methylated regions (DMRs) were selected across different functional elements in the genome. Using these DMRs, an ensemble random forest model was built in the discovery cohort (pre-breast: n = 33; pre-prostate: n = 35) for each cancer type. The trained model showed moderate discriminability for both breast (AUC = 0.76, pre-breast: n = 12; stage II breast: n = 12) and prostate (AUC = 0.83, n = 5) cancer in the validation set, and both models performed better in the older age group. In addition, promoter methylation signatures are also capable of stratifying patients into high-risk and low-risk of developing breast cancer. Pathway enrichment analysis will be performed to investigate the oncogenic relevance of selected features. Success in this project will define how early cancer can be detected through liquid biopsy and advance the timeline of early detection. This project has the potential to develop a single blood test for multi-cancer detection and monitoring. Citation Format: Yi Yang Hou, Nicholas Cheng, Jared T. Simpson, Philip Awadalla. Detecting early cancer using cfDNA methylation signatures with nanopore sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 118.

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Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-118
Primary Topic
Cancer Genomics and Diagnostics
Type
article
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article

Abstract 118: Detecting early cancer using cfDNA methylation signatures with nanopore sequencing.

Jared T. Simpson, Philip Awadalla, Nicholas Cheng, Yi Yang Hou
Cancer Research
Cancer Genomics and Diagnostics
article

Abstract 118: Detecting early cancer using cfDNA methylation signatures with nanopore sequencing.

Jared T. Simpson, Philip Awadalla, Nicholas Cheng, Yi Yang Hou
article en

Abstract

Abstract Early cancer screening improves survival by enabling timely treatment before the disease progresses. However, current population-wide screening tools are limited to a few cancer types, highlighting the need for novel detection methods that can be routinely used to detect multiple cancers. Plasma tumour-derived cell-free DNA (cfDNA) carries the tumour’s genetic and epigenetic alterations and can be used to develop new screening methods. Here, we aim to identify precancerous and early tumour-associated cfDNA methylation signatures. We analyzed nanopore sequencing data performed on plasma collected up to 10 years before clinical diagnosis from patients with breast or prostate cancer, and stage II diagnostic plasma from breast cancer patients. Preliminary data revealed global hypomethylation and increased inter-patient variability in the diagnostics breast cancer samples, both of which were more pronounced in younger patients. Notably, global hypomethylation was found in Triple Negative Breast Cancer (TNBC) and ER+/HER2- Breast Cancer, but not in other subtypes. These global alterations were not observed in precancerous lesions in both cancer types, suggesting such epigenetic alterations may arise or become detectable during malignant transformation rather than early tumour initiation. To identify loci that are associated with precancerous epigenetic alterations, differentially methylated regions (DMRs) were selected across different functional elements in the genome. Using these DMRs, an ensemble random forest model was built in the discovery cohort (pre-breast: n = 33; pre-prostate: n = 35) for each cancer type. The trained model showed moderate discriminability for both breast (AUC = 0.76, pre-breast: n = 12; stage II breast: n = 12) and prostate (AUC = 0.83, n = 5) cancer in the validation set, and both models performed better in the older age group. In addition, promoter methylation signatures are also capable of stratifying patients into high-risk and low-risk of developing breast cancer. Pathway enrichment analysis will be performed to investigate the oncogenic relevance of selected features. Success in this project will define how early cancer can be detected through liquid biopsy and advance the timeline of early detection. This project has the potential to develop a single blood test for multi-cancer detection and monitoring. Citation Format: Yi Yang Hou, Nicholas Cheng, Jared T. Simpson, Philip Awadalla. Detecting early cancer using cfDNA methylation signatures with nanopore sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 118.

Cancer ResearchVol. 86(7_Supplement)
Ontario Institute for Cancer Research (CA), University of Toronto (CA), University of Oxford (GB)
Reduced inequalities
Openalex Percentile: Top 13%
Cancer Genomics and Diagnostics
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