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©Julia Hess I Helmholtz Munich
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Molecular Targets and Therapeutics Center Research Unit Radiation Cytogenetics (ZYTO)

The research unit focusses on translational oncology with a special focus on markers and mechanisms of therapy response pursuing the mission of optimizing personalized cancer treatment strategies.

The research unit focusses on translational oncology with a special focus on markers and mechanisms of therapy response pursuing the mission of optimizing personalized cancer treatment strategies.

About our Research

Precision therapy of cancers requires a stratification of patients and an identification of therapeutic targets by integration of multi-level omics data, metabolic data and clinical data from oncological cohorts.

ZYTO collaborates tightly with local (LMU and TUM), national and international clinics and research partners. We have a particular focus on the investigation of radiotherapy response and the therapy of tumor recurrences of various cancer entities such as head and neck cancer and glioblastoma.

The personalized treatment of cancer requires finer grained stratification of patients for which we develop stratification markers and models predicting local and distant tumor control after radiotherapy. The grand challenges in clinical oncology are therapy failure and the occurrence of tumor relapses after radiotherapy. Main causes of therapy failures are tumor heterogeneity, tumor immune escape, tumor metabolic processes and tumor-intrinsic signaling that lead to therapeutic resistance. To this end, ZYTO identifies molecular and metabolic subtypes of tumors that reflect the aforementioned determinants of therapeutic failure. At the same time, we use these insights to identify novel therapeutic targets and combination therapies.

To achieve these research goals ZYTO combines the following research fields:

  1. Translational bioinformatics: multi-big data bulk and single-cell omics for the in-depth characterization of oncological cohorts and model systems. Regression and deep learning-based prognostic models.
  2. Therapeutic targets and intervention: clinical cohorts and multi-omics data forprognostic patient stratification markers and therapeutic intervention targets. Clinical implications of tumor heterogeneity and tumor-microenvironment interaction.
  3. Metabolic therapy response: tumor metabolism and therapy response. Metabolic characterization and stratification. Multi-level data from clinical samples and pre-clinical models for metabolic intervention strategies.

Our Research Groups

Helmholtz Munich | Kristian Unger
Unger Lab

Translational Bioinformatics

In-depth characterization of oncological cohorts and model systems by multi-big data bulk and single-cell omics. Regression and deep learning based prognostic models.

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Helmholtz Munich | Julia Hess
Hess Lab

Therapeutic Targets and Interventions Group

Clinical cohorts and multi-omics data for prognostic patient stratification markers and therapeutic intervention targets. Clinical implications of tumor heterogeneity and tumor-microenvironment interaction.

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Helmholtz Munich | ©Martin Selmansberger
Selmansberger Lab

Metabolic therapy response

Identification of metabolic characteristics in clinical samples and model systems, related to clinical therapy response by integration of multi-level (high-dimensional) data.

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Our Staff at Radiation Cytogenetics

PD Dr. Kristian Unger

Head of Translational Bioinformatics/Deputy Head of Research Unit View profile

Dr. Julia Heß

Head of Therapeutic Targets and Intervention View profile

Dr. Martin Selmansberger

Postdoc View profile

Doris Mittermaier

Project Assistant/Secretary of Research Unit

Marion Böttner

Laboratory Assistent

Dr. Peter Weber

Postdoc

Randolph Caldwell

Senior Scientist

Daniel Samaga

Scientist

Benedek Dankó

PhD Student

Claire Innerlohinger

Technician

Aaron Selmeier

Technician

Laura Holler

Technician

Isabella Zagorski

Technician

Gisela Dettweiler

Latest Publications of Our Research Unit

See all

2022 Cancers DOI: 10.3390/cancers14153745

Hess J, Unger K, Maihoefer C, Schüttrumpf L, Weber P, Marschner S, Wintergerst L, Pflugradt L, Baumeister P, Walch A, Woischke C, Kirchner T, Werner M, Sörensen K, Baumann M, Tinhofer I, Combs SE, Debus J, Schäfer H, Krause M, Linge A, von der Grün J, Stuschke M, Zips D, Canis M, Lauber K, Ganswindt U, Henke M, Zitzelsberger H, Belka C.

Integration of p16/HPV DNA status with a 24-miRNA-defined molecular phenotype improves clinically relevant stratification of head and neck cancer patients.

2022 Clin Cancer Res. DOI: 10.1158/1078-0432.CCR-21-2244

Weber P, Künstner A, Hess J, Unger K, Marschner S, Idel C, Ribbat-Idel J, Baumeister P, Gires O, Walz C, Rietzler S, Valeanu L, Herkommer T, Kreutzer L, Klymenko O, Drexler G, Kirchner T, Maihöfer C, Ganswindt U, Walch A, Sterr M, Lickert H, Canis M, Rades D, Perner S, Berriel Diaz M, Herzig S, Lauber K, Wollenberg B, Busch H, Belka C, Zitzelsberger H.

Therapy-Related Transcriptional Subtypes in Matched Primary and Recurrent Head and Neck Cancer.

2019 Clin Cancer Res. DOI:: 10.1158/1078-0432.CCR-18-0776.

Hess J, Unger K, Maihoefer C, Schüttrumpf L, Wintergerst L, Heider T, Weber P, Marschner S, Braselmann H, Samaga D, Kuger S, Pflugradt U, Baumeister P, Walch A, Woischke C, Kirchner T, Werner M, Werner K, Baumann M, Budach V, Combs SE, Debus J, Grosu AL, Krause M, Linge A, Rödel C, Stuschke M, Zips D, Zitzelsberger H, Ganswindt U, Henke M, Belka C.

A Five-MicroRNA Signature Predicts Survival and Disease Control of Patients with Head and Neck Cancer Negative for HPV Infection.

Contact Research Unit Office

Doris Mittermaier

Project Assistant/Secretary of Research Unit