The silencing of SPARC (secreted protein acid and rich in cysteine) gene through methylation of its promoter region represents a common event in many solid tumors and it is frequently associated with tumor progression and an aggressive clinical outcome. Anyhow, the data concerning the epigenetic mechanism of SPARC deregulation and its prognostic value in lung cancer are still incomplete. We explored the aberrant methylation of SPARC and its effects in 4 non-small cell lung cancer (NSCLC) cell lines and 59 NSCLC tissues and correlated the methylation levels with clinical-pathological features and disease outcome of patients. In 3 out of 4 tumor cell lines high SPARC methylation levels were observed. An inverse correlation between the epigenetic silencing and SPARC expression was confirmed by 5-Aza-2′-deoxycytidine ((5-Aza-CdR) treatment that also significantly induced a reduction in cell viability, proliferation and tumor cell migration. In tissues, the DNA methylation levels of the SPARC gene were significantly lower in paired non-neoplastic lungs (NLs) and normal lungs distant from tumor (NLDTs) than in NSCLCs (p = 0.002 and p = 0.0034 respectively). A promoter hypermethylation was detected in 68% of squamous cell carcinoma (SqCCs, 17/25) and 56% of adenocarcinoma (ADCs, 19/34), with SqCC showing the highest levels of methylation. Higher SPARC methylation levels were significantly associated with higher mortality risk both in all NSCLCs early stage patients (Hazard Ratio, HR = 1.97; 95% Confidence Interval, CI: 1.32–2.93; p = 0.001) and in those with SqCC (HR = 2.96; 95% CI: 1.43–6.12; p = 0.003). Promoter methylation of SPARC gene should represent an interesting prognostic biomarker in NSCLC, with potential application in the squamous early-stage context. Further research in this setting on larger independent cohorts of lung patients with different histologies and stages of disease are warranted.
The increased expression and aberrant methylation of SHC1 in non–small cell lung cancer: Integrative analysis of clinical and bioinformatics databases
