Hospital tissue repositories host an invaluable supply of diseased samples with matched retrospective clinical information. In this work, a recently optimized method for extracting full-length proteins from formalin-fixed, paraffin-embedded (FFPE) tissues was evaluated on lung neuroendocrine tumor (LNET) samples collected from hospital repositories. LNETs comprise a heterogeneous spectrum of diseases, for which subtype-specific diagnostic markers are lacking. Six archival samples diagnosed as typical carcinoid (TC) or small cell lung carcinoma (SCLC) were subjected to a full-length protein extraction followed by a GeLC-MS/MS analysis, enabling the identification of over 300 distinct proteins per tumor subtype. All identified proteins were categorized through DAVID software, revealing a differential distribution of functional classes, such as those involved in RNA processing, response to oxidative stress and ion homeostasis. Moreover, using spectral counting for protein abundance estimation and beta-binomial test as statistical filter, a list of 28 differentially expressed proteins was generated and submitted to pathway analysis by means of Ingenuity Pathway Analysis software. Differential expression of chromogranin-A (more expressed in TCs) and stathmin (more expressed in SCLCs) was consistently confirmed by immunohistochemistry. Therefore, FFPE hospital archival samples can be successfully subjected to proteomic investigations aimed to biomarker discovery following a GeLC-MS/MS label-free approach.
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