A multi-analyte serum test for the detection of non-small cell lung cancer

• Published in: British journal of cancer Vol. 103; no. 8; pp. 1221 - 1228
• Main Authors: FARLOW, E. C, VERCILLO, M. S, COON, J. S, BASU, S, KIM, A. W, FABER, L. P, WARREN, W. H, BONOMI, P, LIPTAY, M. J, BORGIA, J. A
• Format: Journal Article
• Language: English
• Published: Basingstoke Nature Publishing Group 12.10.2010
• Subjects: Adult; Aged; Aged, 80 and over; Algorithms; Biological and medical sciences; Biomarkers, Tumor - analysis; Biomarkers, Tumor - blood; Blood Chemical Analysis - methods; Carcinoma, Non-Small-Cell Lung - blood; Carcinoma, Non-Small-Cell Lung - diagnosis; Case-Control Studies; Cohort Studies; Early Detection of Cancer - methods; Female; Humans; Lung cancer; Lung Neoplasms - blood; Lung Neoplasms - diagnosis; Male; Medical sciences; Middle Aged; Molecular Diagnostics; Pneumology; Serum - chemistry; Tumors; Tumors of the respiratory system and mediastinum; non-small cell lung cancer; Lung disease; Cancerology; Respiratory disease; Lung cancer; Bronchus disease; Serum; Malignant tumor; Diagnosis; non-small cell lung carcinoma; Luminex; Cancer
• ISSN: 0007-0920; 1532-1827
• DOI: 10.1038/sj.bjc.6605865

In this study, we appraised a wide assortment of biomarkers previously shown to have diagnostic or prognostic value for non-small cell lung cancer (NSCLC) with the intent of establishing a multi-analyte serum test capable of identifying patients with lung cancer. Circulating levels of 47 biomarkers were evaluated against patient cohorts consisting of 90 NSCLC and 43 non-cancer controls using commercial immunoassays. Multivariate statistical methods were used on all biomarkers achieving statistical relevance to define an optimised panel of diagnostic biomarkers for NSCLC. The resulting biomarkers were fashioned into a classification algorithm and validated against serum from a second patient cohort. A total of 14 analytes achieved statistical relevance upon evaluation. Multivariate statistical methods then identified a panel of six biomarkers (tumour necrosis factor-α, CYFRA 21-1, interleukin-1ra, matrix metalloproteinase-2, monocyte chemotactic protein-1 and sE-selectin) as being the most efficacious for diagnosing early stage NSCLC. When tested against a second patient cohort, the panel successfully classified 75 of 88 patients. Here, we report the development of a serum algorithm with high specificity for classifying patients with NSCLC against cohorts of various 'high-risk' individuals. A high rate of false positives was observed within the cohort in which patients had non-neoplastic lung nodules, possibly as a consequence of the inflammatory nature of these conditions.