Metabolomic-based biomarker discovery for non-invasive lung cancer screening: A case study

Author:

O’Shea KeironORCID,Cameron Simon J.S.ORCID,Lewis Keir E,Lu ChuanORCID,Mur Luis AJORCID

Abstract

AbstractBackgroundLung cancer (LC) is one of the leading lethal cancers worldwide, with an estimated 18.4% of all cancer deaths being attributed to the disease. Despite developments in cancer diagnosis and treatment over the previous thirty years, LC has seen little to no improvement in the overall five year survival rate after initial diagnosis.MethodsIn this paper, we extended a recent study which profiled the metabolites in sputum from patients with lung cancer and age-matched volunteers smoking controls using flow infusion electrospray ion mass spectrometry. We selected key metabolites for distinguishing between different classes of lung cancer, and employed artificial neural networks and leave-one-out cross-validation to evaluate the predictive power of the identified biomarkers.ResultsThe neural network model showed excellent performance in clas sification between lung cancer and control groups with the area under the receiver operating characteristic curve of 0.99. The sensitivity and specificity of for detecting cancer from controls were 96% and 94% respectively. Furthermore, we have identified six putative metabolites that were able todiscriminate between sputum samples derived from patients suffering small cell lung cancer (SCLC) and non-small cell lung cancer. These metabolites achieved excellent cross validation performance with a sensitivity of 80% and specificity of 100% for predicting SCLC.ConclusionsThese results indicate that sputum metabolic profiling may have potential for screening of lung cancer and lung cancer recurrence, and may greatly improve effectiveness of clinical intervention.

Publisher

Cold Spring Harbor Laboratory

Reference31 articles.

1. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008

2. Cancer Statistics, 2010

3. Analysis of aberrant methylation on promoter sequences of tumor suppressor genes and total dna in sputum samples: a promising tool for early detection of copd and lung cancer in smokers;Diagn Pathol,2012

4. Revisting wilson and Jungner in the genomic age: a review of screening criteria over the past 40 years

5. Metabolomic profiling of human serum in lung cancer patients using liquid chromatography/hybrid quadrupole time-of-flight mass spectrometry and gas chromatography/mass spectrometry;Journal of cancer research and clinical oncology,2015

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