Cytokine profile determined by data-mining analysis set into clusters of non-small-cell lung cancer patients according to prognosis

• Published in: Annals of oncology Vol. 26; no. 2; pp. 428 - 435
• Main Authors: Barrera, L., Montes-Servín, E., Barrera, A., Ramírez-Tirado, L.A., Salinas-Parra, F., Bañales-Méndez, J.L., Sandoval-Ríos, M., Arrieta, Ó.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.02.2015
• Subjects: Adult; Aged; biomarkers; Biomarkers, Tumor - analysis; Biomarkers, Tumor - immunology; Carcinoma, Non-Small-Cell Lung - classification; Carcinoma, Non-Small-Cell Lung - immunology; Carcinoma, Non-Small-Cell Lung - mortality; Carcinoma, Non-Small-Cell Lung - pathology; Cluster Analysis; cytokines; Cytokines - blood; Data Mining - methods; data-mining analysis; Enzyme-Linked Immunosorbent Assay; Female; Humans; Kaplan-Meier Estimate; Lung Neoplasms - classification; Lung Neoplasms - immunology; Lung Neoplasms - mortality; Lung Neoplasms - pathology; Male; Middle Aged; non-small-cell lung cancer; Prognosis; cytokines; prognosis; data-mining analysis; biomarkers; non-small-cell lung cancer
• ISSN: 0923-7534; 1569-8041; 1569-8041
• DOI: 10.1093/annonc/mdu549

We aim to associate a cytokine profile obtained through data mining with the clinical characteristics of patients with subgroups with advanced non-small-cell lung cancer (NSCLC). Our results provide evidence that complex cytokine networks may be used to identify patient sub-groups with different prognoses in advanced NSCLC that could serve as potential biomarkers for best treatment choices. Immunoregulatory cytokines may play a fundamental role in tumor growth and metastases. Their effects are mediated through complex regulatory networks. Human cytokine profiles could define patient subgroups and represent new potential biomarkers. The aim of this study was to associate a cytokine profile obtained through data mining with the clinical characteristics of patients with advanced non-small-cell lung cancer (NSCLC). We conducted a prospective study of the plasma levels of 14 immunoregulatory cytokines by ELISA and a cytometric bead array assay in 110 NSCLC patients before chemotherapy and 25 control subjects. Cytokine levels and data-mining profiles were associated with clinical, quality of life and pathological outcomes. NSCLC patients had higher levels of interleukin (IL)-6, IL-8, IL-12p70, IL-17a and interferon (IFN)-γ, and lower levels of IL-33 and IL-29 compared with controls. The pro-inflammatory cytokines IL-1b, IL-6 and IL-8 were associated with lower hemoglobin levels, worse functional performance status (Eastern Cooperative Oncology Group, ECOG), fatigue and hyporexia. The anti-inflammatory cytokines IL-4, IL-10 and IL-33 were associated with anorexia and lower body mass index. We identified three clusters of patients according to data-mining analysis with different overall survival (OS; 25.4, 16.8 and 5.09 months, respectively, P = 0.0012). Multivariate analysis showed that ECOG performance status and data-mining clusters were significantly associated with OS (RR 3.59, [95% CI 1.9–6.7], P < 0.001 and 2.2, [1.2–3.8], P = 0.005). Our results provide evidence that complex cytokine networks may be used to identify patient subgroups with different prognoses in advanced NSCLC. These cytokines may represent potential biomarkers, particularly in the immunotherapy era in cancer research.