Tear Sampling and Biomarker Discovery: A Robust Workflow for Routine Clinical Applications Using UHPLC-MS/MS and Schirmer Strips

Abstract

Human tear analysis is gaining increasing attention as a non-invasive tool for several applications such as proteomics and biomarker identification in various diseases, including cancer. The choice of the correct sampling method determines the result of the analysis. In this study, we developed and validated a robust method for tear protein quantification using ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS). Tear samples were collected with Schirmer strips, a low-cost and practical tool for tear collection. It is the first time that internal standards have been used to enhance the analytical performance of a method based on Schirmer strips for tear sampling, overcoming the issues widely reported in the literature regarding protein extraction and data reproducibility. Non-human proteins were used for method development, ensuring improved accuracy and analytical precision. The method demonstrated excellent recovery, high sensitivity, and reproducibility. The use of Schirmer strips, combined with this advanced analytical method, highlights their potential as a reliable support for tear protein quantification and biomarker discovery. This study provides a cost-effective and reliable workflow for tear proteome analysis and contributes to the growing field of tear-based diagnostics, making it suitable for routine clinical and research applications in precision medicine.