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Poster session 09

1185P - Clinical applications of a novel blood-based fragmentomics assay for lung cancer detection

Date

14 Sep 2024

Session

Poster session 09

Topics

Cancer Diagnostics

Tumour Site

Small Cell Lung Cancer;  Non-Small Cell Lung Cancer

Presenters

Marc Siegel

Citation

Annals of Oncology (2024) 35 (suppl_2): S762-S774. 10.1016/annonc/annonc1599

Authors

M. Siegel1, J. Kibler2, K. Fathe3, A. Carson4, B. Leatham5, M. Wang4, K. Cabrera3, M. Smith5, M. Salmans5, B.I. Lee5, M. Francis6

Author affiliations

  • 1 -, MT Group, # 317 - Los Angeles/US
  • 2 Business Development, MT Group, # 317 - Los Angeles/US
  • 3 Scientific Alliances, Genece Health, 92130 - San Diego/US
  • 4 Bioinformatics, Genece Health, 92130 - San Diego/US
  • 5 Research And Development, Genece Health, 92130 - San Diego/US
  • 6 Medical, Genece Health, 92130 - San Diego/US

Resources

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Abstract 1185P

Background

The escalating use of thoracic and abdominal computed tomography (CT) scans, in part owing to greater compliance with lung cancer screening programs in many countries, has led to an increase in the discovery of pulmonary nodules. The management of each pulmonary nodule is based on an evaluation of imaging and patient history to ascertain its malignancy risk using guidelines from leading medical societies. The incorporation of a molecular diagnostic tool, such as an assay that detects circulating tumor DNA (ctDNA) and differentiates between benign and malignant pulmonary nodules,will allow physicians to refine their treatment plans, offer a more personalized and precise approach to patient care, and optimize therapeutic outcomes. Here, we present the performance of a novel assay designed to detect lung nodule ctDNA from a blood draw, highlighting its potential to meaningfully impact clinical decision making.

Methods

The assay’s performance was established in a cohort of 50 lung cancer samples, 54 samples from patients with common comorbidities or benign pulmonary nodules, and 87 presumed normal samples. cfDNA was extracted from double-spun plasma, processed into libraries, and underwent low pass whole genome sequencing (LP-WGS). Sequencing data was processed through Genece Health’s proprietary machine learning classifier.

Results

Our results demonstrate >90% sensitivity and >85% specificity in clinical concordance testing. There was a significant (P<0.01) difference between the classifier’s final cancer prediction scores in the group with malignant pulmonary nodules when compared to the benign pulmonary nodules, COPD, and smoking groups. Reproducibility and precision testing showed concordance in results of >90%. The assay’s clinical Limit of Detection was established in a cohort of early-stage lung cancer samples in which sensitivity of the assay was >85% in stage I samples, and >90% in stage II samples.

Conclusions

We demonstrate reproducible and robust performance of the Genece Health Lung Assay to detect lung cancer, across all stages of the disease, by specifically identifying ctDNA from a blood draw. This assay will provide critical insights to clinicians as they care for an increasing number of patients with lung nodules.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Genece Health.

Funding

The sample acquisition for this study was undertaken by MT Group, sponsored by Genece Health.

Disclosure

M. Siegel, J. Kibler: Financial Interests, Personal, Full or part-time Employment: MT Group. K. Fathe: Financial Interests, Institutional, Stocks or ownership: Genece Health; Financial Interests, Personal, Stocks/Shares: ChromaCode Inc. A. Carson, M. Wang, K. Cabrera, M. Smith, B.I. Lee, M. Francis: Financial Interests, Institutional, Stocks or ownership: Genece Health. B. Leatham: Financial Interests, Institutional, Stocks or ownership: Genece Health, ChromaCode. M. Salmans: Financial Interests, Institutional, Stocks or ownership: Genece Health; Financial Interests, Personal, Stocks/Shares: Illumina.

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