Abstract LB-187: MALDI imaging-guided microproteomics workflow for intratumor heterogeneity studies
Authors: Alberts Deborah , Longuespée Rémi , Pottier Charles , Smargiassio Nicolas , Mazzucchelli Gabriel , Baiwir Dominique , Delvenne Philippe , Hamm Gregory , Linehan Stefan , Pamelard Fabien , Picard de Muller Gael , De Pauw Edwin 
Published: July 2016

A single tumoral tissue can bear phenotypically different cell populations. This phenomenon called intra-tumor heterogeneity can lead to differential behaviors regarding metastasis seeding and therapy resistance [1]. MALDI imaging has proven its efficiency for revealing hidden molecular features offering an insight into distinct cellular regions based on their molecular content. Further, proteomics applied to these regions could allow depicting the molecular context associated to particular cells groups and enable the collection of qualitative, quantitative and spatial information for each protein.

Breast cancer Formalin Fixed and Paraffin Embedded (FFPE) tissues, from patients whose outcome had been recorded over a period of 10 years, were used for this study. After Citric Acid Antigen Retrieval and trypsin digestion, images were obtained by MALDI-TOF/TOF-MS (Bruker, Germany). Analytical data analysis were applied to the measured large normalized datasets using the cloud software Multimaging (ImaBioTech, France) in order to find potential biomarkers that could be correlated to different patient survivals.

Small tissue areas were obtained by laser microdissection (LEICA LMD 700, Germany), upon which a combination of chemical processes was applied to ensure optimal protein antigen retrieval, extraction and digestion. Finally, the tissue pieces obtained were analyzed by LC-MS/MS using UPLC Waters Nanoacquity and Thermo Q-Exactive instruments.

Based on mathematical calculations carried out on the MALDI imaging datasets, ROIs could be detected in a single tumor. We aimed to compare the proteomic profiles of these intra-tumoral ROIs for several MALDI datasets. Recently, Longuespée [2] published a method to retrieve the identification of more than 1400 proteins from microdissected tissue pieces containing only 2700 cells. This whole procedure allowed us to identify a panel of proteins that characterizes tissue heterogeneity within a single tumor and to associate their presence with the information of each patient, such as their prognosis. This proves the applicability of the combination of MALDI imaging for the discovery of tumoral heterogeneity without a priori, on a mathematical basis, and classical proteomics applied on laser-microdissected tissue samples of very restricted areas. This way, we will be able to retrieve the extensive molecular context associated to a bad patient prognosis and/or therapy resistance.

The described workflow combines the unique advantages of MALDI imaging for de novo molecular feature characterization and LMD-based microproteomics. It offers the possibility to identify protein/peptide markers that will have the power to predict the outcome of the breast cancer patient at the beginning of their treatment, and thus, improve the clinical care for the benefit of the patients.

[1] Zardavas et al., Nature Rev. Clin. Onc. (2015)

[2] Longuespée et al., Methods (2015)

Citation Format: Deborah Alberts, Rémi Longuespée, Charles Pottier, Nicolas Smargiassio, Gabriel Mazzucchelli, Dominique Baiwir, Philippe Delvenne, Gregory Hamm, Stefan Linehan, Fabien Pamelard, Gael Picard de Muller, Edwin De Pauw. MALDI imaging-guided microproteomics workflow for intratumor heterogeneity studies. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-187.