MS-Imaging inteRASomics: spatially resolved RAS interacting proteins enable to decipher RAS mutational status in thyroid cancer

Isabella Piga

First

2023-01-01

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Abstract

Thyroid cancer is one of the first tumours where activating RAS mutations were discovered. In particular, RAS are the most frequently mutated oncogenes in follicular patterned lesions, and they have been associated with all three mutant isoforms of the RAS gene (NRAS, HRAS and KRAS). Among the follicular patterned lesions, the non-invasive follicular tumours with papillary-like features (NIFTPs) is a challenging lesion that does not have a clear cut benign or malignant morphology both in the pre-operative/cytological setting, and even after the analysis of the surgical specimens, thus maintaining its indeterminate status. While the NIFTPs are often characterised by RAS-type mutations, the NIFTP category is becoming a basket that include also a large number of questionable cases which are however RAS wild-type. The aim of the present study was to characterise NIFTPs lesions and to decipher RAS mutational status using Matrix-Assisted Laser Desorption/Ionization (MALDI)–Mass Spectrometry Imaging (MSI) proteomics. Archived FFPE samples from ten NIFTP (n=6 NRAS/HRAS-mutated and n=4 RAS-wild type) were investigated by MALDI-MSI proteomics within the m/z 750 to 3000 mass range and images were acquired with 50 μm spatial resolution. MALDI matrix was then analysed to identify proteins by nLC-ESI-MS/MS. Finally, tissues were stained with haematoxylin and eosin (H&E) thus allowing the integration of proteomic and morphological data. Furthermore, laser-capture microdissection, using the LMD7 instrument (Leica Microsystem, Wetzlar, Germany), was performed on selected cases to maximise the genetic content of the dissected tissue, in order to investigate the intratumoral genetic heterogeneity. Our data were combined with the protein-protein RAS interaction network obtained using the IntAct database. RAS interactome highlighted 526 and 559 interactors with NRAS and HRAS, respectively, and in our data, 20 out of 727 proteins identified by LC–ESI-MS/MS were common interactors with NRAS and HRAS. Among these, only four proteins (PPIA, ATP1A1, CANX, BCAP31) were identified with an error lower than 100 ppm in our MALDI–MSI analysis and their signals were used for an unsupervised pixel-by-pixel automatic segmentation. This targeted MALDI–MSI proteomic approach showed that the NIFTPs were stratified in two groups, corresponding to RAS-mutant and wild-type, thus highlighting the potential role of spatially resolved proteomics tool to interrogate the protein interactomes of RAS in order to gain more insight into RAS oncogene in thyroid cancer.