Integration of 3D multimodal imaging data of a head and neck cancer and advanced feature recognition

Lotz, Judith M.; Hoffmann, Franziska; Lotz, Johannes; Heldmann, Stefan; Trede, Dennis; Oetjen, Janina; Becker, Michael; Ernst, Günther; Maas, P.M.F. van der; Alexandrov, Theodore; Guntinas‐Lichius, Orlando; Thiele, Herbert; Eggeling, Ferdinand von

doi:10.1016/j.bbapap.2016.08.018

Cited by 31 publications

(27 citation statements)

References 43 publications

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“…The transfer of these two modalities (MSI and optical microscopy) into the same coordinate system allowed all 3D data to be viewed next to each other, which led to a better understanding of the functional heterogeneity within the tumor as spatial context and progression can readily be determined from the H&E (Fig. 5a) [70]. The visual integration of MSI data with data from in vivo imaging techniques also harbors great potential by combining the molecular and anatomical information from different spatial scales.…”

Section: Multimodal 3d Imagingmentioning

confidence: 99%

Experimental and Data Analysis Considerations for Three-Dimensional Mass Spectrometry Imaging in Biomedical Research

et al. 2020

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Mass spectrometry imaging (MSI) enables the visualization of molecular distributions on complex surfaces. It has been extensively used in the field of biomedical research to investigate healthy and diseased tissues. Most of the MSI studies are conducted in a 2D fashion where only a single slice of the full sample volume is investigated. However, biological processes occur within a tissue volume and would ideally be investigated as a whole to gain a more comprehensive understanding of the spatial and molecular complexity of biological samples such as tissues and cells. Mass spectrometry imaging has therefore been expanded to the 3D realm whereby molecular distributions within a 3D sample can be visualized. The benefit of investigating volumetric data has led to a quick rise in the application of single-sample 3D-MSI investigations. Several experimental and data analysis aspects need to be considered to perform successful 3D-MSI studies. In this review, we discuss these aspects as well as ongoing developments that enable 3D-MSI to be routinely applied to multi-sample studies.

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Section: Multimodal 3d Imagingmentioning

confidence: 99%

Experimental and Data Analysis Considerations for Three-Dimensional Mass Spectrometry Imaging in Biomedical Research

et al. 2020

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“…Since MALDI MSI is still a novel technique besides our own [ 72 ] no studies have been published with regard to the analysis of FFPE tissues of head and neck squamous cell carcinoma (HNSCC). FFPE tissues are readily available in large quantities from pathology archives.…”

Section: Omic Techniques Compatible With Microdissectionmentioning

confidence: 99%

Microdissection—An Essential Prerequisite for Spatial Cancer Omics

Eggeling

Hoffmann

2020

Proteomics

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The problem with cancer tissue is that its intratumoral heterogeneity and its complexity is extremely high as cells possess, depending on their location and function, different mutations, different mRNA expression and the highest intricacy in the protein pattern. Prior to genomic and proteomic analyses, it is therefore indispensable to identify the exact part of the tissue or even the exact cell. Laser‐based microdissection is a tried and tested technique able to produce pure and well‐defined cell material for further analysis with proteomic and genomic techniques. It sheds light on the heterogeneity of cancer or other complex diseases and enables the identification of biomarkers. This review aims to raise awareness for the reconsideration of laser‐based microdissection and seeks to present current state‐of‐the‐art combinations with omic techniques.

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“…Most of the HNC are squamous cell carcinoma that are developed as the result of field cancerization . Those tissue specimens contain, besides the cancer tissue, a multitude of nontumorous tissues such as different stages of dysplasia, well differentiated epithelium, and tumor stroma . The global primary treatment for most HNC cases is radiation.…”

Section: Introductionmentioning

confidence: 99%

“…Since MALDI–MSI is still novel, besides our own studies, there are only a few extant studies on using MSI for proteomic evaluation in HNC . To date, no study has been published in which formalin‐fixed and paraffin‐embedded (FFPE) tissues of head and neck squamous cell carcinoma (HNSCC) were analyzed using MALDI–MSI.…”

Section: Introductionmentioning

confidence: 99%

Identification of Proteomic Markers in Head and Neck Cancer Using MALDI–MS Imaging, LC–MS/MS, and Immunohistochemistry

Hoffmann

Umbreit

Krüger

et al. 2018

Proteomics Clinical Apps

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Purpose The heterogeneity of squamous cell carcinoma tissue greatly complicates diagnosis and individualized therapy. Therefore, characterizing the heterogeneity of tissue spatially and identifying appropriate biomarkers is crucial. MALDI–MS imaging (MSI) is capable of analyzing spatially resolved tissue biopsies on a molecular level. Experimental design MALDI–MSI is used on snap frozen and formalin‐fixed and paraffin‐embedded (FFPE) tissue samples from patients with head and neck cancer (HNC) to analyze m/z values localized in tumor and nontumor regions. Peptide identification is performed using LC–MS/MS and immunohistochemistry (IHC). Results In both FFPE and frozen tissue specimens, eight characteristic masses of the tumor's epithelial region are found. Using LC–MS/MS, the peaks are identified as vimentin, keratin type II, nucleolin, heat shock protein 90, prelamin‐A/C, junction plakoglobin, and PGAM1. Lastly, vimentin, nucleolin, and PGAM1 are verified with IHC. Conclusions and Clinical Relevance The combination of MALDI–MSI, LC‐MS/MS, and subsequent IHC furnishes a tool suitable for characterizing the molecular heterogeneity of tissue. It is also suited for use in identifying new representative biomarkers to enable a more individualized therapy.

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Integration of 3D multimodal imaging data of a head and neck cancer and advanced feature recognition

Cited by 31 publications

References 43 publications

Experimental and Data Analysis Considerations for Three-Dimensional Mass Spectrometry Imaging in Biomedical Research

Experimental and Data Analysis Considerations for Three-Dimensional Mass Spectrometry Imaging in Biomedical Research

Microdissection—An Essential Prerequisite for Spatial Cancer Omics

Identification of Proteomic Markers in Head and Neck Cancer Using MALDI–MS Imaging, LC–MS/MS, and Immunohistochemistry

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