Abstract 3249: The development of a tissue-agnostic genome-wide methylome enrichment assay for lung cancer
Bibliographic record
Abstract
Abstract Background: Lung cancer remains the leading cause of cancer-related death in the United States. Precision oncology is revolutionizing early-stage non-small cell lung cancer (NSCLC) treatment, showing promising results in improving outcomes. Utilization of molecular residual disease (MRD) testing has the potential to improve outcomes by detecting relapse ahead of clinical presentation. Currently, up to 38% of patients are ineligible for tumor-informed MRD tests due to insufficient tissue, often resulting from risks associated with invasive procedures, small biopsy sizes (e.g., FNAs), low tumor purity, competing demands for tissue (e.g., PD-L1 staining), or complete response to neoadjuvant treatment.1, 2 Herein, we demonstrate the feasibility of a tissue-agnostic genome-wide methylome enrichment platform utilizing cell-free methylated DNA immunoprecipitation followed by high-throughput sequencing (cfMeDIP-seq) for cancer detection, cancer signal quantification, and prognostication in lung cancer. 3, 4 Methods: In this feasibility study, a total of 24 patients (136 samples) with early-stage lung cancers (87.5% Stage I [IA (50%), IB (37.5%), IIA (4.2%) and IIB (8.3%)]); 19 were analyzed based on inclusion/exclusion criteria and assessed for their correlation with recurrence-free survival (RFS). Blood collections for each patient occurred prior to surgery, after surgery and at irregular intervals before recurrence or last clinical follow-up. 5-10 ng of cfDNA isolated from each plasma sample was used for cfMeDIP-seq. The analysis considers multiple MRD tests over a surveillance period following surgery. RFS is compared between groups using a log-rank test. The Hazard Ratio (HR) is estimated using Cox proportional hazards model. Results: With a median follow up duration of 85.6 months, 10 patients experienced recurrence, and 9 patients remained recurrence-free. Patients with a positive MRD test showed significantly worse RFS than those who tested negative (HR 3.58; 95% CI, 1.00, 12.89). The lead time between MRD positivity and clinical recurrence was up to 35.91 months, with a median of 13.08 months. Conclusions: The analysis demonstrates that MRD detection with a tissue-agnostic, genome-wide methylome enrichment platform in patients with lung cancer after curative intent treatment correlates strongly with RFS. References: 1. Khan S, et al. JCO 2024. 2. Aggarwal C, et al. JAMA Oncology 2019.3. Shen SY, et al. Nature 2018 4. Liu G, et al. Annals Oncol 2024 Citation Format: Harvey I. Pass, Collin A. Melton, Shu Yi Shen, Ben Brown, Justin M. Burgener, Junjun Zhang, Yarong Wang, Jun Min, Owen Hall, Karan Budhraja, Abel Licon, Alan Williams, Scott V. Bratman, Brian A. Allen, Jing Zhang, Daniel D. De Carvalho, Anne-Renee Hartman. The development of a tissue-agnostic genome-wide methylome enrichment assay for lung cancer [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 3249.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".