Editors' ChoiceCancer

Finding Needles in the Haystack

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Science Translational Medicine  14 May 2014:
Vol. 6, Issue 236, pp. 236ec84
DOI: 10.1126/scitranslmed.3009307

Lung cancer screening has received much attention from researchers, clinicians, and the general public in recent years. The National Lung Screening Trial (NLST), which enrolled over 50,000 high-risk individuals, demonstrated that annual low-dose computed tomography (CT) scans among selected high-risk patients decrease lung cancer mortality by 20%. Recently, widespread lung cancer screening according to this model was endorsed by the United States Preventive Services Task Force.

Lung cancer screening has raised several questions and concerns, among them cost, impact on smoking cessation rates, and effects of radiation exposure from CT scans. Perhaps one of the most pressing concerns is the handling of vast numbers of false-positive screens. CT scans are highly sensitive, but not specific, for lung cancer. In the NLST, ~25% of all CT screens were positive, but only 4% of these were ultimately found to be cancer. Increasing the specificity of radiographic findings could spare thousands of patients the anxiety and subsequent procedures that arise from a false-positive test result.

Efforts to identify biomarkers so as to supplement radiographic results for lung cancer screening go back decades. In the most recent take on this quest, Mathé and colleagues have identified a urinary metabolic profile that may not only help identify lung cancer cases but also provide prognostic information. Specifically, they used unbiased liquid chromatography–mass spectrometry to measure small molecules (<1500 daltons) in urine collected from a training set of 469 lung cancer patients and 536 healthy controls. Putative biomarkers were validated at two different time points and in an independent sample set. Creatine riboside and N-acetylneuraminic acid (NANA) were each significantly elevated in lung cancer and associated with worse outcomes. Both metabolites were also enriched in tumor tissue compared with adjacent normal tissue, implicating a role in tumor metabolism.

A urinary biomarker offers numerous advantages: It is noninvasive, the source is abundant and requires minimal preparation, and there is no radiation risk. Although considerable work lies ahead, we can only hope that these or other biomarkers—whether alone or as an adjunct to CT—will one day help identify early-stage lung cancer in an efficient, cost-effective, and straightforward fashion.

E. A. Mathé et al., Non-invasive urinary metabolic profiling identifies diagnostic and prognostic markers in lung cancer. Cancer Res. 10.1158/0008-5472.CAN-14-0109 (2014). [Abstract]

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