BREATH TEST TO DETECT LUNG CANCER

CHICAGO — An advanced colorimetric sensor that analyzes breath can accurately identify lung cancer and characterize cancer histology, researchers report.

"We have certainly discovered a biomarker, but we still have a lot of work to do in technical validation and clinical validation," explained Peter Mazzone, MD, director of the lung cancer program at the Respiratory Institute at the Cleveland Clinic.

Dr. Mazzone presented the research here at CHEST 2013: the American College of Chest Physicians Annual Meeting.

He underscored the need for tools that can improve a physician's ability to identify patients with lung cancer.

The advanced colorimetric sensor is one such tool. It is designed to measure volatile organic compounds in the breath that reflect changes in the metabolome. To do this, it uses 36 chemically sensitive colorants impregnated in a filter.

Metabolic processes are different in those with and without lung cancer. The sensor evaluates these differences, which include the activity of antioxidant pathways, the handling of energy stress, and the metabolism of specific volatile organic compounds.

The sensor has a reported accuracy of approximately 75%, according to a previous study that Dr. Mazzone led (J Thorac Oncol. 2012;7:137-142). He noted that "we could improve the accuracy with models that include breath data and clinical data."

The research he presented builds on this work.

His team used improved technology such as nanoporous matrix for chemically reactive colorants.

The study involved patients with biopsy-proven untreated lung cancer, patients with a high clinical suspicion for lung cancer, and control subjects. There were slightly more patients with stage III and IV cancers than with stage I and II cancers.

Samples were obtained while subjects performed tidal breathing through a volatile organic compound filter. The end tidal carbon dioxide level triggered the collection of the alveolar portion of the breath.

Data were log-transformed to provide color values. The entire dataset was then reduced using univariate logistic regression, Dr. Mazzone explained.

First, the sensor was optimized with samples from 288 subjects. Accuracy was then tested with samples from 236 patients.

"We had good accuracy," reported Dr. Mazzone. "And with this project, we were able to perform some technical optimization."

This study used much more conservative statistical analyses than the previous study he was involved with. It also demonstrated a substantial improvement from that study when a diagnosis was made with breath alone.

"This could really be a huge benefit to diagnosing cancer," Michael Jantz, MD, from the University of Florida Health Sciences Center in Gainesville, told Medscape Medical News.

Members of the audience responded enthusiastically to the presentation. "That was awesome," said one. Two noted that they have been following Dr. Mazzone's work for some time and are impressed with all that he has accomplished.

Future efforts will focus on incorporating cancer phenotypes and trials conducted at multiple clinical centers.

Peter Mazzone reports being a member of advisory committees for Boehringer Ingelheim and Oncimmune, and receiving research support from Metabolomx. Dr. Jantz has disclosed no relevant financial relationships.

CHEST 2013: American College of Chest Physicians Annual Meeting. Presented October 27, 2013.