Sandra Rauser

Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a powerful tool for investigating the distribution of proteins and small molecules within biological systems through the in situ analysis of tissue sections. MALDI-IMS can determine the distribution of hundreds of unknown compounds in a single measurement and enables the acquisition of cellular expression profiles while maintaining the cellular and molecular integrity. In recent years, a great many advances in the practice of imaging mass spectrometry have taken place, making the technique more sensitive, robust, and ultimately useful. In this review, we focus on the current state of the art of MALDI-IMS, describe basic technological developments for MALDI-IMS of animal and human tissues, and discuss some recent applications in basic research and in clinical settings.

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.

Normalization is critically important for the proper interpretation of matrix-assisted laser desorption/ionization (MALDI) imaging datasets. The effects of the commonly used normalization techniques based on total ion count (TIC) or vector norm normalization are significant, and they are frequently beneficial. In certain cases, however, these normalization algorithms may produce misleading results and possibly lead to wrong conclusions, e.g. regarding to potential biomarker distributions. This is typical for tissues in which signals of prominent abundance are present in confined areas, such as insulin in the pancreas or β-amyloid peptides in the brain. In this work, we investigated whether normalization can be improved if dominant signals are excluded from the calculation. Because manual interaction with the data (e.g., defining the abundant signals) is not desired for routine analysis, we investigated two alternatives: normalization on the spectra noise level or on the median of signal intensities in the spectrum. Normalization on the median and the noise level was found to be significantly more robust against artifact generation compared to normalization on the TIC. Therefore, we propose to include these normalization methods in the standard "toolbox" of MALDI imaging for reliable results under conditions of automation.

PURPOSE: Aurora kinase A (AURKA/STK15/BTAK) encodes a serine/threonine kinase associated with chromosomal distribution and its up-regulation induces chromosomal instability, thereby leading to aneuploidy and cell transformation in several types of cancer. In this study, we investigated the role of AURKA in head and neck squamous cell carcinoma (HNSCC). EXPERIMENTAL DESIGN: The mRNA expression levels of AURKA were compared in tumor tissues of 66 HNSCC patients with those in corresponding normal squamous epithelium by real-time quantitative reverse transcriptase-PCR. In addition, the association between AURKA mRNA and protein expression, centrosome abnormalities, and aneuploidy was studied in a subset of cases (n=34). All molecular variables were correlated to histomorphologic findings and clinical follow-up data of the patients. RESULTS: AURKA mRNA up-regulation was significantly associated with tumor stage and the occurrence of regional lymph node, as well as distant metastasis (P<0.0001 for all). Similarly, a correlation was found for protein expression and the occurrence of regional lymph node (P=0.0183) and distant metastasis (P=0.03). The mRNA was positively associated with protein expression (P=0.003) and centrosome abnormalities (P=0.03). Cox regression analysis revealed that AURKA mRNA up-regulation correlated with disease-free survival of the patients (P=0.03) as well as shorter overall survival (P<0.001). CONCLUSIONS: We conclude that the up-regulation of AURKA mRNA may play a critical role in the tumor progression of HNSCC and provides useful information as a prognostic factor for HNSCC patients.