Clinical proteomics is a rapidly emerging frontier in laboratory medicine. High-throughput proteomic investigations of biopsy tissues provide mechanistic insights into complex human diseases. For large-scale proteomics, formalin-fixed and paraffin-embedded (FFPE) tissue samples offer a viable alternative to fresh-frozen (FF) tissues that have restricted availability. In this context, meningioma is one of the most common primary brain tumors where innovation in diagnostics and therapeutic targets can benefit from clinical proteomics. We present here an integrated workflow for quantitative proteomics and biomarker validation of meningioma FFPE tissues. Applying label-free quantitative (LFQ) proteomics, we reproducibly (Pearson's correlation: 0.84-0.91) obtained an in-depth proteome coverage (nearly 4000 proteins per sample) from 120 min gradient of single unfractionated mass spectrometry run. Furthermore, building upon LFQ data and literature curated set of meningioma-associated proteins, we validated VIM, AHNAK, and CLU from FFPE tissues using selected reaction monitoring (SRM) assay and compared its performance with FF tissues. This study illustrates how knowledge from label-free proteomics can be integrated for selecting peptides for targeted validation and suggests that FFPE tissues are comparable to FF tissues for SRM assays. This quantitative clinical proteomics workflow is scalable for large-scale clinical diagnostics studies in the future, for example, utilizing the global repository of FFPE tissues in meningioma and possibly in other cancers.
Keywords: biomarker validation; cancer research; clinical proteomics; meningioma; omics workflow; targeted proteomics.