Session: Parallel session 4 - Spatial OMICs and MS Imaging

MALDI imaging-based microdissection workflow for proteomics characterization of primary liver cancers

Helene CAZIER¹, Rovelyne PISSA¹, Joana LIPECKA², Aurélie BEAUFRERE^1,3, Ghalia BEN GHEDIFA¹, Chiara GUERRERA², Valérie PARADIS^1,3

¹Université Paris Cité, INSERM, UMR-S1149, Centre de Recherche sur l’Inflammation (CRI), Laboratoire d’Excellence Inflamex, F-75018, Paris, France
²Necker Proteomics, Université Paris Cité, SFR Necker, INSERM US24, Paris, France
³AP-HP.Nord, Département de chirurgie HPB et de transplantation hépatique, Department of HPB Surgery and Liver Transplantation, Hopital Beaujon, Clichy, France

Primary liver cancers include hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), and combined hepato-cholangiocarcinoma (cHCC-CCA) composed of both tumor components (HCC and CCA). The diagnosis of cHCC-CCA is challenging mainly because of its great intratumor heterogeneity. Deciphering tumor heterogeneity is crucial to propose the best management and treatment to patients with cHCC-CCA. Routine histological analysis including immunohistochemistry (IHC) is unable to fully capture tumour heterogeneity. In order to address this complexity and improve diagnosis of cHCC-CCA, we integrated mass spectrometry imaging (MSI) to a complete workflow combining LC-MS/MS analysis of microdissected tumoral regions from FFPE tissues slides.

Based on segmentation provided by MALDI imaging, 34 regions of interest (ROI) from FFPE samples of 17 cancers (4 HCC, 4 CCA and 9 cHCC-CCA) were microdissected (16-113 mm²) using Millisect system (Roche) and analyzed using MSI using RapifleX (Bruker) and LC-MS/MS (EvosepOne, TimsTOF-HT, Bruker). Microdissected samples were prepared combining BeatBox® tissue homogenizer and the iST technology (PreOmics) optimized for FFPE sample preparation processing.

The study allowed the quantification of 5444 to 7470 proteins per ROI, with a median CV of 30%. Amongst differential proteins, we could identify protein as marker for HCC and CCA, acting as positive controls, along with a larger panel of proteins contributing to the discrimination of these tumors. Furthermore, proteins specific to different ROI within the same combined hepato-cholangiocarcinoma (cHCC-CCA) were also found compared to control.

This study illustrates the complementarity of proteomic approaches and demonstrates the power of advanced proteomics techniques like MSI and LC-MS to identify large numbers of proteins from tiny tissue samples. Upon validation, our results will provide new tissue diagnostic biomarkers of cHCC-CCA.