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Freenome Unveils Promising Data for Innovative Lung Cancer Blood Test

Freenome's Groundbreaking Blood Test for Lung Cancer Detection

Freenome, a pioneering early cancer detection organization, has recently revealed significant findings regarding its investigational blood-based screening test for lung cancer. This novel approach aims to enhance the detection rates of one of the most lethal cancers, which frequently goes undiagnosed until later stages.

Multiomic Approach for Enhanced Detection

The latest data, which showcases the initial development of the test, was generated from a comprehensive study designed to hone the methodology of ongoing test improvements. It highlights the advantages of a multiomic strategy that integrates DNA methylation analysis alongside protein markers to accurately identify lung cancer in individuals considered at high risk.

These promising results underscore the potential effectiveness of Freenome’s innovative method. At the upcoming American Association for Cancer Research (AACR) Annual Meeting in April, this data will be presented, emphasizing the test's development and performance metrics.

Presentation Details

- Abstract Number: 1107
- Title: Development and performance of a multiomics lung cancer screening blood test
- Presenter: Ofer Shapira, Director of Computational Biology at Freenome
- Session Title: Early Detection Biomarkers 1
- Date and Time: Sunday, April 19, 200 PM - 500 PM PDT

The Study and Findings

In this groundbreaking study, an artificial intelligence and machine learning (AI/ML) classifier was employed, trained on a substantial dataset consisting of both tissue and plasma samples. Specifically, researchers scrutinized data from 136 tissue specimens and an impressive 6,716 plasma samples, ultimately evaluating the test's accuracy based on 673 plasma samples—which included 363 lung cancer cases across various stages and 310 controls without cancer history.

Freenome's cutting-edge multiomics platform demonstrated an impressive adjusted sensitivity of 90.7% at a specificity of 50% for detecting lung cancer. This figure improved slightly to 80.4% at a specificity of 75%. In comparison, a version of the test focusing solely on methylation yielded sensitivity rates of 85.8% and 78.2% for the same specificity thresholds, indicating a clear advantage for the multiomic approach.

Remarkably, this test was effective across all three evaluated lung cancer subtypes—adenocarcinoma, squamous cell carcinoma, and small-cell lung cancer—demonstrating adjusted sensitivity of 77.1% at 50% specificity for Stage I lung cancer cases. This is particularly significant, as early detection is crucial in improving survival rates for patients diagnosed with this aggressive disease.