Author Interviews, Biomarkers, Lung Cancer / 12.07.2025
Mount Sinai Scientists Develop Test for Lung Cancer Biomarker Detection from Common Pathology Slides
MedicalResearch.com Interview with:
Gabriele Campanella, PhD
Assistant Professor
Windreich Department of Artificial Intelligence and Human Health
Icahn School of Medicine at Mount Sinai
MedicalResearch.com: What is the background for this study?
Response: Lung cancer is the most lethal cancer in the US. Lung adenocarcinoma (LUAD) is the most common form of lung cancer with an incidence of over 100k per year in the US. EGFR mutations are common driver mutations in LUAD, and importantly, these mutations can be targeted by TKI therapy, which has high response rates. Because of this, EGFR testing via NGS (Next Generation Sequencing) is considered mandatory by guidelines for any LUAD diagnosis.
In high-resource settings, rapid EGFR testing is done while waiting for confirmation via NGS. This is because NGS takes about 2 weeks on average, while the rapid testing has a median TAT of 2 days. Early treatment decisions could be made based on the rapid test results. Rapid tests have some important drawbacks, most notably, it exhausts tissue. In lung cancer, tissue is scarce in the first place, and up to 25% of cases, after rapid testing there is not enough tissue for NGS. In those circumstances, patients have to be biopsied again, which adds unnecessary risk for the patient. Even worse, in some cases, the NGS is never done. A non-tissue-exhaustive computational biomarker could be used instead of the tissue-based rapid test.
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