We profiled the secretomes of six NSCLC cell lines with varying IC50-values for cisplatin, using label-free GeLC-MS/MS-based proteomics. Out of a total dataset of 2618 proteins, 304 proteins showed significant differences in expression levels between cisplatin sensitive and insensitive cell lines. Functional data mining revealed that the secretion of typically extracellular factors was associated with a higher sensitivity towards cisplatin, while cisplatin insensitivity correlated with increased secretion of theoretically intra-cellular proteins, in line with enhanced levels of non-conventional secretion in cisplatin insensitive cell lines. Stringent statistical analysis and quantitative filtering yielded 41 top biomarker candidates, many of which could also be detected in NSCLC patient sputum using label-free GeLC-MS/MS-based proteomics. A published gene expression dataset was used to determine which of our top secretome cisplatin response prediction candidates might have predictive value in terms of overall survival in patients that received platinum-based treatment. This analysis yielded two cisplatin sensitivity (UGGT1 and MATN2) and one cisplatin resistance (MAP4) candidates that may serve as potential biomarkers for cisplatin response prediction in NSCLC patients in the future.