Novel liquid biopsy detects mutations in early lung cancer

By Naveed Saleh, MD, MS, for MDLinx
Published November 5, 2018

Key Takeaways

Researchers used the electric field-induced release and measurement (EFIRM) platform to detect two EGFR mutations in patients with early non-small cell lung cancer (NSCLC), according to new research published in the Journal of Molecular Diagnostics.

“Variants in circulating tumor DNA (ctDNA) fragments can be detected in the biofluids of patients in early stages of lung cancer,” wrote the authors, led by Fang Wei, PhD, School of Dentistry, University of California, Los Angeles, CA. “An increasing body of literature has demonstrated the ability to noninvasively screen for actionable variants in a process described as liquid biopsy (LB).”

NSCLC is often deadly because it is diagnosed at an advanced stage when surgery is no longer feasible. Researchers at the National Lung Screening Trial reported that low-dose CT screening significantly decreased death due to lung cancer in a high-risk population by identifying early-stage disease. However, CT diagnosis is limited by many false positives, leading to unnecessary costs and radiation exposure.

Elucidating genetic alterations in the EGFR gene, which is a target for tyrosine kinase inhibitors, is clinically useful because it illuminates chemotherapy options. In sum, 27% of NSCLC tumors exhibit EGFR mutations: either the p.L858R or exon19 del variants.

Typically, EGFR diagnosis is done at initial cancer diagnosis or at cancer recurrence using DNA extracted from small tissue biopsy samples harvested during surgery. However, this approach is expensive, invasive, and technically challenging.

EFIRM is a high-throughput technology that employs an electric field to improve hybridization efficiency and detect perfect duplexes. It is plate-based, automatable, and efficient, with the capability of analyzing either serum or saliva, making it a clinically useful for mutation monitoring.

In a previous study, Dr. Wei and colleagues used the EFIRM platform to detect ctDNA containing the two EGFR mutations—p.L858R or exon19 del—in the blood of patients with late-stage NSCLC.

In this study, investigators analyzed the ability of EFIRM LB to detect these variants in blood samples of patients with early NSCLC. They then confirmed these results using biopsy samples of the tumor.

The researchers enrolled 248 patients with pulmonary nodules determined by radiography. The team drew plasma samples before biopsy and histologic examination of the nodules. Of these patients, 44 were diagnosed with stage I or stage II NSCLC. On EFIRM platform analysis, sensitivity was 92% for p.L858R variants and 77% for exon19 del variants, with specificity ranging between 91% and 95%.

“This study demonstrates that EFIRM, a novel platform for LB, is capable of accurately detecting mutations in cell-free DNA in patients with early-stage lung cancer,” wrote the authors.

The authors noted that it may be appealing to assume that EGFR mutations predict cancer, this has yet to be elucidated.

“Further investigation will be necessary to determine the positive predictive value of detecting an EGFR mutation in the circulation of an individual with, for example, an indeterminate lung nodule or a high-risk smoking history,” the investigators wrote.

The study had certain limitations, which were discussed by the researchers.

"Currently, the clinical sensitivity of EFIRM to detect patients with NSCLC is limited by the percentage of tumors containing either or both of the two variants, which is estimated at 27% of NSCLC tumors," stated co-investigator Wu-Chou Su, MD, Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan. "We are presently developing a 10-variant panel that contains detecting mutations expressed in 50% of all lung malignancies."

In addition to boosting the number of mutations assessed using EFIRM, the investigators hope to automate the technology for improved sensitivity and mass screening. 

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