Blood-Based cfDNA Test Shows Strong Potential for Detecting Lung Cancer in Nonsmokers

Early findings from the FANSS study, presented at ESMO Asia 2025, point to a potential shift in how clinicians identify lung cancer in a population that currently lacks formal screening guidelines. The U.S. based prospective study, led by researchers at NYU Langone Health in collaboration with DELFI Diagnostics, is evaluating whether low dose CT scanning combined with a fragmentomics blood test can support early detection in Asian women with no smoking history.

Asian women who have never smoked remain an understudied yet vulnerable population. Although the biological reasons for elevated risk are not fully understood, high rates of EGFR mutations and other oncogenic drivers are frequently observed. This gap in evidence has left clinicians without structured screening recommendations, even as global data signal that incidence is rising.

"We enrolled 1,000 participants who underwent baseline LDCT, and 13 were diagnosed with invasive lung adenocarcinoma, a 1.3% detection rate," said Dr. Elaine Shum, assistant professor of oncology at NYU Grossman School of Medicine, and the study's lead investigator. “This rate is higher than what was observed in heavy smokers in the National Lung Screening Trial.”

The FANSS study enrolled 1,000 eligible women aged 40 to 74, all of Asian descent and with fewer than 100 lifetime cigarettes. Each participant received a baseline low-dose CT scan and provided plasma samples for a genome-wide cell-free DNA fragmentation assay designed by DELFI Diagnostics. Of the cohort, 13 women were diagnosed with invasive lung adenocarcinoma, yielding a 1.3 percent detection rate. Nine of these cases were Stage IA, underscoring the ability of systematic screening to identify disease at its most treatable phase. Two cases were Stage IIB and two were Stage IIIB or IIIC. An additional 14 participants with Lung-RADS 3 or 4 findings remain under evaluation.

A total of 1,159 plasma samples collected across study visits were processed using a fragmentomics approach that profiles genome-wide cfDNA patterns. Sequencing achieved a target depth of 4X with a low failure rate of 0.43 percent and an average turnaround time of 5 days. The dataset is being used to train machine learning classifiers that may eventually allow clinicians to integrate an inexpensive, noninvasive assay into lung cancer screening workflows.

"These results demonstrate the feasibility of incorporating plasma biomarker analysis into screening studies for high-risk populations who currently lack formal guidelines," said Amoolya Singh, PhD, Chief Technology Officer for DELFI Diagnostics.

The FANSS study is the first U.S.-based initiative focused specifically on lung cancer detection among never-smoking Asian women. The study is supported by private philanthropy, DELFI Diagnostics, and AstraZeneca Pharmaceuticals and is registered under NCT05164757. While follow-up continues for individuals with indeterminate CT findings, early results strengthen the case for tailored screening approaches and highlight the potential of fragmentomics to broaden early cancer detection beyond traditional risk categories.