MALDI Mass Spectrometry Imaging Linked with Top-Down Proteomics as a Tool to Study the Non-Small-Cell Lung Cancer Tumor Microenvironment

Abstract

Advanced non-small-cell lung cancer (NSCLC) is generally linked with a poor prognosis and is one of the leading causes of cancer-related deaths worldwide. Since only a minority of the patients respond well to chemotherapy and/or targeted therapies, immunotherapy might be a valid alternative in the lung cancer treatment field, as immunotherapy attempts to strengthen the body’s own immune response to recognize and eliminate malignant tumor cells. However, positive response patterns to immunotherapy remain unclear. In this study, we demonstrate how immune-related factors could be visualized from single NSCLC tissue sections (Biobank@UZA) while retaining their spatial information by using matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI), in order to unravel the molecular profile of NSCLC patients. In this way, different regions in lung cancerous tissues could be discriminated based on the molecular composition. In addition, we linked visualization (MALDI MSI) and identification (based on liquid chromatography higher resolution mass spectrometry) of the molecules of interest for the correct biological interpretation of the observed molecular differences within the area in which these molecules are detected. This is of major importance to fully understand the underlying molecular profile of the NSCLC tumor microenvironment.

Mass Spectrometry Imaging Reveals Neutrophil Defensins as Additional Biomarkers for Anti-PD-(L)1 Immunotherapy Response in NSCLC Patients

“…Identification of these three peptides of interest was not possible with top-down peptidomics, as performed earlier for an identification of other MALDI MSI targets with higher-energy collisional dissociation (HCD) [23]. Although the precursors for these peptides could be selected for fragmentation, the corresponding fragmentation spectra did not yield sufficient fragments to allow peptide identification.…”

“…We have demonstrated earlier that MALDI mass spectrometry imaging (MSI) is a powerful tool to visualize the NSCLC tumor microenvironment based on the endogenous peptidomic profile (m/z range 800-5000 Da) [23]. The analysis of differential peptide expression in the tumor versus nontumor region revealed two molecules at m/z 3369.5 and m/z 3440.6.…”

“…We have demonstrated earlier that matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) can be a powerful tool to better understand the lung tumor microenvironment on a molecular level [23]. MALDI MSI is a multiplexed analysis that enables the screening of all molecules that can be ionized (i.e., a broad variety of biomolecules, such as peptides, proteins, glycans, nucleic acids, lipids, metabolites, etc.)…”

“…Beside these advantages of MALDI MSI, it is still cumbersome and often difficult to identify interesting MSI targets directly from the tissue itself. In order to overcome this problem, we linked the molecular images with high resolution liquid chromatography (LC)-coupled mass spectrometry, which made it feasible to obtain a reliable identification of interesting peptides/small proteins, while retaining their spatial distribution throughout the lung tissue [23]. Since no prior knowledge of molecular identities is required for MALDI MSI experiments, we used this technology to compare the presence and distribution of naturally-occurring peptides in tumor and peripheral tissue.…”

Increasing Complexity to Simplify Clinical Care: High Resolution Mass Spectrometry as an Enabler of AI Guided Clinical and Therapeutic Monitoring

“…For each m / z , an image is constructed that reflects the spatial distribution of the sample chemical composition. This technique has been used to study tumor microenvironments [ 136–143 ] and other tissue sections in an attempt to segregate diseased versus nondiseased tissue, providing potential protein or biomarker targets for treatment. While high resolution mass spectrometry in clinical research has shown promising results, the time and cost involved in acquiring and analyzing data has been a significant barrier of entry for use in routine clinical care.…”