With lung cancer being the leading cause of cancer deaths, a new scientific experiment shows that lung-related carcinoma can be detected at an early stage by a simple blood test.
Lung cancer is the leading cause of cancer deaths worldwide. The American Cancer Society estimates that in 2021 there will be “About 235,760 new cases of lung cancer (119,100 in men and 116,660 in women)” and “About 131,880 deaths from lung cancer (69,410 in men and 62,470 in women).”
The lung cancer five-year survival rate (18.6 percent) is lower than many other leading cancer sites, such as colorectal (64.5 percent), breast (89.6 percent) and prostate (98.2 percent), writes the American Lung Association website, taking the data from U.S. National Institute Of Health, National Cancer Institute. SEER Cancer Statistics Review, 1975–2015.
With such a deadly disease facing them, researchers write in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) that “The current high mortality of human lung cancer stems largely from the lack of feasible, early disease detection tools.”
Early-stage lung cancer is “mostly asymptomatic,” a news release explains. Thus if a method were to detect lung cancers early without resorting to low dose spiral CT imaging, which is “not feasible as a widespread screening test for the general population due to high cost and the radiation hazard of repeated screenings” it would be a welcome addition to the battery of cancer screening tests.
A new study, funded by the National Cancer Institute, suggests that a drop of blood is all that may be needed to detect lung cancer in triage patients. The study was co-led by researchers at Massachusetts General Hospital (MGH): Leo Cheng, PhD, associate biophysicist, in Pathology, Radiology, and the Athinsula A. Martinos Center for Biomedical Imaging, and David Christiani, MD, MPH, pulmonary and critical care physician.
“Our study demonstrates the potential for developing a sensitive screening tool for the early detection of lung cancer,” says Cheng. “The predictive model we constructed can identify which people may be harboring lung cancer. Individuals with suspicious findings would then be referred for further evaluation by imaging tests, such as low-dose CT, for a definitive diagnosis.”
Cheng, Christiani, and their co-investigators built a “lung-cancer predictive model” based on metabolomics profiles in blood. “Metabolomics, which is defined as the comprehensive analysis of metabolites in a biological specimen, is an emerging technology that holds promise to inform the practice of precision medicine,” says the US National Institutes of Health. “Historically, small numbers of metabolites have been used to diagnose complex metabolic diseases as well as monogenic disorders such as inborn errors of metabolism.”
The news release explains that the metabolome is the “dynamic biochemical suite found in all cells, fluids, and tissues of the body”. When a patient has lung cancer, their blood metabolites produced or consumed by cancer cells in the lungs give signs of the illness.
The researchers employed high-resolution magnetic resonance spectroscopy to measure metabolomics profiles in blood samples, detecting “the collective reactions of metabolites” within living cells.
The scientists screened tens of thousands of blood specimens stored in Massachusetts General Hospital’s biobank and others and diagnosed 25 patients with non-small cell lung cancer (NSCLC) with stored blood samples taken at the time of their diagnosis and at least six months before their diagnosis. They matched the 25 cancer patients with 25 healthy controls.
The researchers tested the blood of cancer patients and the healthy control group, and also tested the cancer patients’ blood before their diagnoses, which revealed “values between the healthy controls and the patients at the time of their diagnosis.”
“This was very encouraging, because screening for early disease should detect changes in blood metabolomic profiles that are intermediate between healthy and disease states,” says Cheng. The investigators then tested their model with a different group of 54 patients with NSCLC using blood samples obtained before their cancer diagnosis, which confirmed that the model’s predictions were accurate.
The news release also notes that values from the predictive model measured from prior-to-diagnosis blood samples could also predict five-year survival for patients – ”which may be useful in guiding clinical strategies and treatment decisions.”
While the research team concedes that larger studies are needed to validate the use of blood metabolomics models as non-small cell lung cancer (NSCLC) early screening tools, they show promise.
The researchers will focus on metabolomic profiles of lung cancer’s clinical characteristics next, in order to better understand the disease and to be able to recommend targeted therapies.
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