Peter Markus Deckert

Prof. Dr. Peter Markus Deckert

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Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 March 2025 in Diagnostics
Verified
Journal Article
Open access
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FNFelicitas Anna Ottilie Neumann
Felicitas Anna Ottilie Neumann
MMMarkus Müller
Markus Müller
GMGregor Mattert
Gregor Mattert
SLSven Liebig
Sven Liebig
VHVictor Herbst
Victor Herbst
MRMark Reinwald
Mark Reinwald
Background/Objectives: Pneumocystis jirovecii pneumonia (PJP) is the most frequently diagnosed AIDS-defining illness in Europe, with especially high mortality in HIV-negative patients caused by delayed diagnosis and low awareness. This study aims to evaluate cytokine release assays (CRA) to facilitate a less invasive and resource-efficient PJP specific diagnostic test. We focus on the P. jirovecii antigens Kexin 1 (KEX1), MSG1, and MSG2, which were identified in prior studies as immunologically relevant. Methods: Whole blood samples from 50 participants—22 healthy individuals and 28 immunocompromised individuals, including 8 with proven PJP—were stimulated in vitro with full-length and partial KEX1, MSG1, MSG2, and a combination of all three antigens (PJ-MIX). Following 24 h incubation at 37 °C, cytokine levels of IL-2, IFN-γ, IL-17A, and IL-17F were measured. Results: Stimulation with full-length KEX1, MSG1, MSG2, and PJ-MIX antigens induced higher IL-2 concentrations in the healthy control group compared to the groups IL-2 baseline levels and to the group of proven PJP cases. Similarly, stimulation with full-length KEX1, MSG1, and PJ-MIX elevated IFN-γ levels in the healthy control group compared to baseline IFN-γ levels. Conclusions: Our findings highlight the potential of IL-2 and IFN-γ release following stimulation with PJ antigens, with PJ-MIX eliciting the strongest and most significant responses, suggesting a cumulative antigen effect. This pilot study establishes a foundation for a PJP-specific CRA, deepening our knowledge of T-cell immunity against PJP. Clinically, such a test could, among other applications, evaluate at-risk patients who should receive prophylaxis and may consequently reduce PJP-related morbidity and mortality.

12 November 2024 in Cancers
Verified
Journal Article
Open access
PDF file
CLChristian Linke
Christian Linke
THThilo von Hänisch
Thilo von Hänisch
JSJulia Schröder
Julia Schröder
Werner DammermannWerner Dammermann
Werner Dammermann
PDPeter Markus Deckert
Peter Markus Deckert
SSSandra Schwarck
Sandra Schwarck
Background: Improving precision medicine in chemotherapy requires highly sensitive and easily applicable diagnostic tools. In addition, non-invasive molecular real-time monitoring of cytotoxic response is highly desirable. Here, we employed the kinetics of DNA double-strand breaks (DSB) and cell-free DNA (cfDNA) in a cell model of topoisomerase II-inhibitors in T cell leukemia (Jurkat cells) compared to normal cells (peripheral blood mononuclear cells, PBMCs). Methods: We applied automated microscopy to quantify immuno-stained phosphorylated H2AX (γH2AX) as a marker for either DNA damage response (DDR) or cell death and quantitative PCR-based analysis of nuclear and mitochondrial cfDNA concentrations. Results: Jurkat cells displayed a DDR to cytotoxic drug treatment significantly earlier than PBMCs, and etoposide (ETP) induced DSB formation faster than doxorubicin (DOX) in both Jurkat and PBMCs. Jurkat cells exhibited an earlier cytotoxic response compared to PBMC, with a significantly increased mitochondrial cfDNA formation after 2 h of DOX application. In PBMCs, increased cell death was detected after 4 h of incubation with ETP, whereas DOX treatment was less effective. Conclusions: Both automated microscopy and mitochondrial cfDNA quantification analysis indicate that (malignant) Jurkat cells are more sensitive to DOX than (healthy) PBMC. Our real-time approach can improve DDR inducing drug selection and adaptation in cancer therapy and aids in decisions for optimal patient biosampling.