NCT/UCC MALDI Imaging Unit

MALDI Imaging Unit – Targeting the protein landscape of cancer

Matrix-associated laser-based desorption and ionization imaging, in short MALDI Imaging, combines two major fields of bioanalytical methods: molecule analysis determined by means of mass spectra according to time-of-flight masses (m/z), and the macroscopic anatomy of the tissue compartments. Regions of interest (ROI) of human cancer tissue slides defined by pathologists are translated into mass spectra pattern and can be used for subsequent bio-statistical analyses of protein, peptide or lipid composition and quantification. In addition to the knowledge gained from differing mass spectra in e.g. tumor versus normal tissue areas, morphologically indistinguishable tumors can be subdivided and analyzed for molecule-dependent heterogeneity by segmentation of mass intensities at a very high resolution (down to 5x5 micrometer).

In addition to the significance of conventional MALDI analysis for routine diagnostics and to conducting medical research projects using experimental setups, the MALDI Imaging Unit is researching on bioinformatic workflows and deep learning pipelines to utilize the big data information e.g. for automation purposes.

Figure 1: MALDI Imaging instrument. Rapflex MALDI Tissuetyper (Bruker Daltonik GmbH) to perform MALDI Imaging analyzation based on time of flight molecule mass detection.

Figure 2: Visualization of mass spectra pattern on tissue slides via segmentation. A pancreatic tumor sample was analyzed by MALDI imaging. Left side: Visualization of mass spectra as segmentation map based on trained regions of interest of specified tissue compartments. Right side: Grayscale image scan of the same tissue. Red: pancreatic tissue, orange: tumor tissue, dark red: stroma, yellow: fatty tissue, pink: lymph node, lilac/rose: background.

Research focus

Tumor classification of rare tumor types
Segmentation of (intra-) tumor heterogeneity
Lipid, protein and peptide mass spectra identification of novel tumor subtypes
Generation of a consistently growing database of tumor vs normal tissue mass spec data
MALDI segmentation pipelines based on Deep learning
3D MALDI imaging approaches

Samples types for MALDI imaging:

Fresh frozen tissue
Formalin fixed and paraffin embedded (FFPE) tissue
Samples with and without enzyme digestion on slide
Embedded organoids, spheres or cell culture blocks

Technical information:

Positive and negative flight mode detected by linear or reflector detector
Mass range (positive mode e.g.): peptides: 600-3200 m/z, proteins 1000-500.000 m/z
Scan range: 5x5µm to 150x150µmresulting field size
Automated batch run option
External calibration and quality controls provided
Big data storage (data file from 20-100GB)

Figure 3: Mass spectra of tumor region. Example of one mass spectra pattern in a range of 600-3200 m/z of a tumor region (FFPE sample).

Coordination

Dr. rer. med. Pia Hönscheid
Group leader
E-Mail: pia.hoenscheid(at)uniklinikum-dresden.de
Phone: +49 (0)351 45813038

Director

Prof. Dr. med. Gustavo Baretton
Director of Institute of Pathology Dresden
E-Mail: Gustavo.Baretton(at)uniklinikum-dresden.de
Phone: +49 (0)351 4583000

Team

Christian Sperling
Medical Technical Assistant
E-Mail: Christian.Sperling(at)uniklinikum-dresden.de
Phone: +49 (0)351 458-13009

Maxime le Floch
MD Student
E-Mail: maxime.lefloch(at)medforum-dresden.de
Phone: +49 (0)351 458-3009

Maximilian Weiss
Physician in further education
E-Mail: Maximilian.Weiss(at)ukdd.de
Phone: +49 (0)351 458-5266