PSATluca is a Nomogram Predictor of Survival and Treatment of Lung Cancer Patients Based on Serum and Clinical Characters
Abstract
To date, albeit a great number of serum biomarkers for early cancer diagnosis have been well characterized and widely used in clinics, the prognostic value of these serum biomarkers remains to be comprehensively analyzed. Here, we applied our previously built prognosis analysis database Long-term Outcome and Gene Expression Profiling Database of pan-cancers (LOGpc) to screen the commonly used serum biomarkers with prognostic values. Univariate and multivariate Cox analysis were conducted to evaluate the prognostic value of serum biomarkers and clinical factors in outcome measurement. By analyzing the LOGpc database, high cytokeratin 19 (KRT19) messenger RNA (mRNA) expression was found to be significantly correlated with poor overall survival (OS) in non-small cell lung cancer (NSCLC). A total of 232 serum samples were collected for validation, which reaffirmed that increased CYFRA21-1 (fragmented protein form of KRT19) was independently associated with poor OS in NSCLC. A nomogram integrating serum CYFRA21-1 level and clinico-pathological factors was constructed. This nomogram showed good accuracy in predicting OS, and could recommend treatment options based on CYFRA21-1 abundances and patient characteristics. A web implementation of this nomogram called PSATluca (Predictor of Survival And Treatment of lung cancer Patient) is provided and accessible to users at https://bioinfo.henu.edu.cn/PSATluca/index.jsp. This tool can assist clinicians in evaluating prognosis of NSCLC patients and selecting appropriate treatment options.