Clinical laboratory testing for HER2 status in breast cancer tissues is critically important for therapeutic decision making. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a powerful tool for investigating proteins through the direct and morphology-driven analysis of tissue sections. We hypothesized that MALDI-IMS may determine HER2 status directly from breast cancer tissues. Breast cancer tissues (n = 48) predefined for HER2 status were subjected to MALDI-IMS, and protein profiles were obtained through direct analysis of tissue sections. Protein identification was performed by tissue microextraction and fractionation followed by top-down tandem mass spectrometry. A discovery and an independent validation set were used to predict HER2 status by applying proteomic classification algorithms. We found that specific protein/peptide expression changes strongly correlated with the HER2 overexpression. Among these, we identified m/z 8404 as cysteine-rich intestinal protein 1. The proteomic signature was able to accurately define HER2-positive from HER2-negative tissues, achieving high values for sensitivity of 83%, for specificity of 92%, and an overall accuracy of 89%. Our results underscore the potential of MALDI-IMS proteomic algorithms for morphology-driven tissue diagnostics such as HER2 testing and show that MALDI-IMS can reveal biologically significant molecular details from tissues which are not limited to traditional high-abundance proteins.

Mass spectrometry is being used in many clinical research areas ranging from toxicology to personalized medicine. Of all the mass spectrometry techniques, mass spectrometry imaging (MSI), in particular, has continuously grown towards clinical acceptance. Significant technological and methodological improvements have contributed to enhance the performance of MSI recently, pushing the limits of throughput, spatial resolution, and sensitivity. This has stimulated the spread of MSI usage across various biomedical research areas such as oncology, neurological disorders, cardiology, and rheumatology, just to name a few. After highlighting the latest major developments and applications touching all aspects of translational research (i.e. from early pre-clinical to clinical research), we will discuss the present challenges in translational research performed with MSI: data management and analysis, molecular coverage and identification capabilities, and finally, reproducibility across multiple research centers, which is the largest remaining obstacle in moving MSI towards clinical routine.

Formalin-fixed and paraffin-embedded (FFPE) tissue specimens are the gold standard for histological examination, and they provide valuable molecular information in tissue-based research. Metabolite assessment from archived tissue samples has not been extensively conducted because of a lack of appropriate protocols and concerns about changes in metabolite content or chemical state due to tissue processing. We present a protocol for the in situ analysis of metabolite content from FFPE samples using a high-mass-resolution matrix-assisted laser desorption/ionization fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FT-ICR-MSI) platform. The method involves FFPE tissue sections that undergo deparaffinization and matrix coating by 9-aminoacridine before MALDI-MSI. Using this platform, we previously detected ∼1,500 m/z species in the mass range m/z 50-1,000 in FFPE samples; the overlap compared with fresh frozen samples is 72% of m/z species, indicating that metabolites are largely conserved in FFPE tissue samples. This protocol can be reproducibly performed on FFPE tissues, including small samples such as tissue microarrays and biopsies. The procedure can be completed in a day, depending on the size of the sample measured and raster size used. Advantages of this approach include easy sample handling, reproducibility, high throughput and the ability to demonstrate molecular spatial distributions in situ. The data acquired with this protocol can be used in research and clinical practice.