Abstract

BackgroundIdentification of biomarkers in lung cancer, a leading cause of cancer-related mortality, has a meaningful clinical relevance in the quest of novel prognostic factors and therapeutic targets. The glycan-binding protein galectin-1 (Gal-1) modulates tumor progression by mediating cell–cell and cell–extracellular matrix interactions, as well as angiogenesis and tumor immune-escape. Previous works reported the expression of Gal-1 in lung cancer, although its clinical significance remains uncertain. ObjectiveTo assess the clinicopathologic relevance and prognostic value of Gal-1 expression in a cohort of 103 Stage I–III non-small cell lung cancer (NSCLC) patients. MethodsGal-1 expression was determined by immunohistochemistry in tumor tissue samples. The percentage of immunoreactive tumor cells and stroma, as well as the presence of blood vessels with positively stained endothelium in the tumor and surrounding normal tissue, were recorded. Results were correlated with the clinicopathologic factors of the patients (Spearman's rank correlation coefficient, chi-square test) and overall survival by univariate (Kaplan Meier) and multivariate analyses (Cox regression hazard model). ResultsWe did not observe significant associations between Gal-1 expression and relevant clinicopathologic features at diagnosis of NSCLC. However, Kaplan Meier analysis revealed a significant association between Gal-1 expression and overall survival, when Gal-1 expression was analyzed on tumor cells alone (“tumor cell percentage”) or when an integrated score accounting for tumor cell as well as stromal expression of Gal-1 (“total score”) was assessed. Patients showing high Gal-1 expression evidenced a poorer clinical outcome. Furthermore, “total score” remained significantly associated with survival by multivariate Cox regression analysis in the whole cohort of patients, even when controlling for the classical predictors and prognostic factors of NSCLC. ConclusionWe conclude that Gal-1 expression may be a useful biomarker for better prediction of the clinical outcome and management of NSCLC patients.

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