We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

LabMedica

Download Mobile App
Recent News Expo WHX Labs Dubai 2026 Clinical Chem. Molecular Diagnostics Hematology Immunology Microbiology Pathology Technology Industry Focus

Liquid Biopsy Lung Cancer Screening Method Developed

By LabMedica International staff writers
Posted on 09 Apr 2020
Image: Histological sections of a moderately well differentiated squamous cell carcinoma of the lung showing infiltrating sheets and tongues of malignant squamous cells with whorls of keratin (Photo courtesy of Department of Health Western Australia).
Image: Histological sections of a moderately well differentiated squamous cell carcinoma of the lung showing infiltrating sheets and tongues of malignant squamous cells with whorls of keratin (Photo courtesy of Department of Health Western Australia).
Genomic blood tests for cancer screening and early detection have become the focus of attention in the molecular diagnostic space, though most activity so far has been either toward pan-cancer screening tools, or in a few other specific tumor types like colorectal cancer, where tests hope to vie against colonoscopy and existing stool-based methods.

Radiologic screening of high-risk adults reduces lung-cancer-related mortality; however, a small minority of eligible individuals undergo such screening in the USA. The availability of blood-based tests could increase screening uptake. A novel circulating tumor DNA (ctDNA) detection assay has been developed that could help physicians screen individuals at risk for lung cancer.

A large team of scientists at Stanford University (Stanford, CA, USA) and their colleagues have described a method, called Lung-CLiP (lung cancer likelihood in plasma), involves targeted sequencing of cell-free DNA (cfDNA) from plasma and matched white blood cell DNA to assess copy number and single nucleotide variants, coupled with a machine learning model that estimates the probability that a cfDNA mutation is tumor-derived. The estimate is based on biological and technical features specific to each variant, such as background frequency, cfDNA fragment size, the gene affected, and the likelihood of clonal hematopoiesis.

The team first trained and optimized Lung-CLiP in an initial sample of 104 patients with early stage non-small cell lung cancer and 56 matched controls. When they then applied it to an independent set of validation samples (46 cases and 48 risk-matched controls), the test was able to discriminate early-stage lung cancer patients with sensitivity and specificity levels that the authors believe suggest a significant benefit to the clinic: depending on where they set their specificity threshold, the method could achieve 63% sensitivity for stage I tumors and up to 75% sensitivity in detecting patients with stage III disease. Setting their cutoff at 98% specificity, the investigators found that Lung-CLiP detected 41% of patients with stage I disease, 54% of patients with stage II disease and 67% of those with stage III disease.

Ash Alizadeh, MD, PhD, an associate professor of Oncology and a senior author of the study, said, “Lung-CLiP could help increase the rate of early detection. This would be analogous to how stool-based testing proposes to improve screening for colorectal cancers, especially in populations where adoption of colonoscopy is lower than currently recommended.” The study was published on March 25, 2020 in the journal Nature.

Related Links:
Stanford University

Gold Member
Collection and Transport System
PurSafe Plus®
POC Helicobacter Pylori Test Kit
Hepy Urease Test
Anterior Nasal Specimen Collection Swabs
53-1195-TFS, 53-0100-TFS, 53-0101-TFS, 53-4582-TFS
Sperm Quality Analyis Kit
QwikCheck Beads Precision and Linearity Kit

Channels

Immunology

view channel
Image: The TmS computational biomarker analyzes tumor gene expression and microenvironment data to guide treatment decisions (Photo courtesy of MD Anderson Cancer Center)

New Biomarker Predicts Chemotherapy Response in Triple-Negative Breast Cancer

Triple-negative breast cancer is an aggressive form of breast cancer in which patients often show widely varying responses to chemotherapy. Predicting who will benefit from treatment remains challenging,... Read more

Pathology

view channel
Image: The innovative classifier can guide treatment for PDAC and other immunotherapy-resistant cancers (Photo courtesy of Adobe Stock))

Single Sample Classifier Predicts Cancer-Associated Fibroblast Subtypes in Patient Samples

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers, in part because of its dense tumor microenvironment that influences how tumors grow and respond to treatment.... Read more

Industry

view channel
Image: QuidelOrtho has entered into a strategic supply agreement with Lifotronic to expand its global immunoassay portfolio (Photo courtesy of QuidelOrtho)

QuidelOrtho Collaborates with Lifotronic to Expand Global Immunoassay Portfolio

QuidelOrtho (San Diego, CA, USA) has entered a long-term strategic supply agreement with Lifotronic Technology (Shenzhen, China) to expand its global immunoassay portfolio and accelerate customer access... Read more