Evaluating lung cancer clinical characteristics and tumor subtypes using cell-free DNA fragmentomes.

8074 Background: Liquid biopsies provide an opportunity for non-invasive lung cancer detection and tumor subtyping when tumor tissue is not available. Here we evaluate a blood-based liquid biopsy approach and its relationship to clinical and tumor subtype characteristics of lung cancer cases using a cohort of 578 individuals from a prospective clinical trial (LEMA, NCT02894853). Methods: Pre-treatment plasma samples were processed using the DELFI assay, a cell-free DNA (cfDNA) approach using a genome-wide fragmentomics based machine learning classifier. Clinical data, including overall cancer stage (I=164, II=59, III=133, IV=184), tumor stage, histologic subtypes, lymph node invasion, comorbidities, medications, smoking history, treatment type, and overall-survival (OS) data were collected for all patients. Tissue molecular profiling was performed to identify actionable alterations in driver oncogenes (ALK, BRAF, EGFR, ERBB, KRAS, ROS1, RET, MET) and cancer-specific protein levels (CEA, CA153, CA125, CYFRA, HE4) were measured in the plasma collected from 445 cancer cases. Results: DELFI scores were significantly higher with increasing tumor stage. T2 cases had a 1.3-fold increase in mean scores compared to T1 (p<0.001, Wilcoxon rank-sum), while T4 cases had a 16.2-fold increase (p<0.0001). A similar trend was observed with node staging, with N2 cases having an 11.3-fold higher mean scores compared to N0 (p<0.0001, Wilcoxon rank-sum), while N3 stage cases had a 27-fold increase (p<0.0001). Lung adenocarcinoma (ADC) displayed lower DELFI scores compared to squamous cell carcinomas (SCC) (p<0.01, Wilcoxon rank-sum), while small-cell lung cancer cases had the highest scores among all subtypes (p<0.0001, Wilcoxon rank-sum). cfDNA fragmentome changes in patients with ADC and SCC reflected chromosomal alterations observed in TCGA cohorts (ADC n=518; SCC n=501). The combination of DELFI cfDNA fragmentome characteristics with plasma protein measurements were used to train and cross-validate a classifier that could differentiate ADC from SCC (AUC for stage I=0.71, II=0.85, III=0.85, IV=0.82). Patients with low DELFI scores (below the median) had longer overall-survival (OS) compared to patients with high DELFI score (low DELFI score=18.51 months; high DELFI score=6.58 months; p<0.01, log-rank). DELFI scores were unaffected by underlying patient comorbidities, tumor-specific mutations, or medication status. Conclusions: Overall, this study revealed that DELFI scores are related to tumor burden, predict survival outcomes, and that cfDNA fragmentome analyses can be used to identify lung cancer subtypes. These results suggest future opportunities for subtype-specific treatments in lung cancer based on non-invasive plasma-only analyses. Clinical trial information: NCT02894853 .

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Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.8074
Primary Topic
Cancer Genomics and Diagnostics
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article
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article

Evaluating lung cancer clinical characteristics and tumor subtypes using cell-free DNA fragmentomes.

Peter B. Bach, Victor E. Velculescu, Milou Schuurbiers, Garrett T. Graham et al.
Journal of Clinical Oncology
Cancer Genomics and Diagnostics
article

Evaluating lung cancer clinical characteristics and tumor subtypes using cell-free DNA fragmentomes.

Peter B. Bach, Victor E. Velculescu, Milou Schuurbiers, Garrett T. Graham, Jamie E. Medina, Kim Monkhorst, Zachary L. Skidmore, Nicholas C. Dracopoli, Michel M. van den Heuvel, Robert B. Scharpf, Bryan Chesnick, Stephen Cristiano, Lorenzo Rinaldi, Alessandro Leal, Daan van den Broek, Paul van der Leest
article en

Abstract

8074 Background: Liquid biopsies provide an opportunity for non-invasive lung cancer detection and tumor subtyping when tumor tissue is not available. Here we evaluate a blood-based liquid biopsy approach and its relationship to clinical and tumor subtype characteristics of lung cancer cases using a cohort of 578 individuals from a prospective clinical trial (LEMA, NCT02894853). Methods: Pre-treatment plasma samples were processed using the DELFI assay, a cell-free DNA (cfDNA) approach using a genome-wide fragmentomics based machine learning classifier. Clinical data, including overall cancer stage (I=164, II=59, III=133, IV=184), tumor stage, histologic subtypes, lymph node invasion, comorbidities, medications, smoking history, treatment type, and overall-survival (OS) data were collected for all patients. Tissue molecular profiling was performed to identify actionable alterations in driver oncogenes (ALK, BRAF, EGFR, ERBB, KRAS, ROS1, RET, MET) and cancer-specific protein levels (CEA, CA153, CA125, CYFRA, HE4) were measured in the plasma collected from 445 cancer cases. Results: DELFI scores were significantly higher with increasing tumor stage. T2 cases had a 1.3-fold increase in mean scores compared to T1 (p<0.001, Wilcoxon rank-sum), while T4 cases had a 16.2-fold increase (p<0.0001). A similar trend was observed with node staging, with N2 cases having an 11.3-fold higher mean scores compared to N0 (p<0.0001, Wilcoxon rank-sum), while N3 stage cases had a 27-fold increase (p<0.0001). Lung adenocarcinoma (ADC) displayed lower DELFI scores compared to squamous cell carcinomas (SCC) (p<0.01, Wilcoxon rank-sum), while small-cell lung cancer cases had the highest scores among all subtypes (p<0.0001, Wilcoxon rank-sum). cfDNA fragmentome changes in patients with ADC and SCC reflected chromosomal alterations observed in TCGA cohorts (ADC n=518; SCC n=501). The combination of DELFI cfDNA fragmentome characteristics with plasma protein measurements were used to train and cross-validate a classifier that could differentiate ADC from SCC (AUC for stage I=0.71, II=0.85, III=0.85, IV=0.82). Patients with low DELFI scores (below the median) had longer overall-survival (OS) compared to patients with high DELFI score (low DELFI score=18.51 months; high DELFI score=6.58 months; p<0.01, log-rank). DELFI scores were unaffected by underlying patient comorbidities, tumor-specific mutations, or medication status. Conclusions: Overall, this study revealed that DELFI scores are related to tumor burden, predict survival outcomes, and that cfDNA fragmentome analyses can be used to identify lung cancer subtypes. These results suggest future opportunities for subtype-specific treatments in lung cancer based on non-invasive plasma-only analyses. Clinical trial information: NCT02894853 .

Journal of Clinical OncologyVol. 43(16_suppl)
Johns Hopkins University (US), Radboud University Nijmegen (NL), Dutch Cancer Society (NL), Radboud University Medical Center (NL), The Netherlands Cancer Institute (NL), NYU Langone Health (US), Sidney Kimmel Comprehensive Cancer Center (US)
Openalex Percentile: Top 83%
Cancer Genomics and Diagnostics
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