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Digital PCR After MALDI–Mass Spectrometry Imaging to Combine Proteomic Mapping and Identification of Activating Mutations in Pulmonary Adenocarcinoma
Author(s) -
Kazdal Daniel,
Longuespée Rémi,
Dietz Steffen,
Casadonte Rita,
Schwamborn Kristina,
Volckmar AnnaLena,
Kriegsmann Jörg,
Kriegsmann Katharina,
Fresnais Margaux,
Stenzinger Albrecht,
Sültmann Holger,
Warth Arne,
Kriegsmann Mark
Publication year - 2019
Publication title -
proteomics – clinical applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.948
H-Index - 54
eISSN - 1862-8354
pISSN - 1862-8346
DOI - 10.1002/prca.201800034
Subject(s) - digital polymerase chain reaction , maldi imaging , mass spectrometry , matrix assisted laser desorption/ionization , mass spectrometry imaging , proteomics , computational biology , pathology , biology , medicine , chemistry , polymerase chain reaction , gene , genetics , chromatography , desorption , organic chemistry , adsorption
Purpose Matrix assisted laser desorption/ionization time‐of‐flight mass spectrometry imaging (MALDI–MSI) is a powerful tool to analyze the spatial distribution of peptides in tissues. Digital PCR (dPCR) is a method to reliably detect genetic mutations. Biopsy material is often limited due to minimally invasive techniques, but information on diagnosis, prognosis, and prediction is required for subsequent clinical decision making. Thus, saving tissue material during diagnostic workup is highly warranted for best patient care. The possibility to combine proteomic analysis by MALDI–MSI and mutational analysis by dPCR from the same tissue section is evaluated. Experimental design Ten 0.5 × 0.5 cm formalin‐fixed paraffin embedded tissue samples of pulmonary adenocarcinomas with known EGFR or KRAS mutations are analyzed by MALDI–MSI. Subsequently, DNA is extracted from the analyzed tissue material and tested for the respective driver mutation by dPCR. Results Detection of driver gene mutations after MALDI MSI analysis is successful in all analyzed samples. Determined mutant allele frequencies are in good agreement with values assessed from untreated serial tissue sections with a mean absolute deviation of 0.16. Conclusion and clinical relevance It has been demonstrated that MALDI–MSI can be combined with genetic analysis, like dPCR. Workflows enabling the subsequent analysis of proteomic and genetic markers are particularly promising for the analysis of limited sample material such as biopsy specimen.