Systems Immunology and Single Cell Biology

Our research program is structured around three interconnected pillars that together define a quantitative framework for Spatial Immunometabolism.

1. Quantifying Metabolic States in Human Tissues

We develop and apply high-dimensional single-cell and spatial technologies to measure metabolic regulation directly in intact human tissues.

Using antibody-based metabolic profiling, multiplexed imaging, and spatial mass spectrometry approaches, we quantify the metabolic states of immune, stromal, and malignant cells in situ. Rather than relying solely on transcriptional inference, we measure the regulatory protein networks that determine pathway activity and functional capacity.

A central focus is the analysis of human clinical samples, where we investigate how spatially resolved metabolic states relate to tumor progression, immune dysfunction, and clinical outcome.

2. Computational Modeling of Metabolic Programs

Spatial single-cell data are inherently multimodal and high-dimensional. We develop computational frameworks that integrate metabolic state, cellular composition, and spatial organization into interpretable multicellular programs.

Instead of analyzing individual markers in isolation, we identify coordinated metabolic and cellular patterns that define tumor–immune ecosystem states. Our goal is to transform complex spatial data into mechanistic and predictive models of tissue organization.

3. Mechanistic Dissection of Metabolic Niches

Quantitative mapping and modeling generate hypotheses about how metabolic interactions shape immune function. We test these hypotheses using patient-derived tumor organoids and ex vivo tissue systems.

By genetically perturbing metabolic enzymes using CRISPR-based approaches, we examine how specific tumor or stromal metabolic programs influence T cell and macrophage function within controlled microenvironments.

This allows us to move from correlation to causation and to define actionable metabolic interactions that may be therapeutically targeted.

Immune cells operate in metabolically constrained environments.
Tumors exploit nutrient competition, hypoxia, and metabolite signaling to suppress immunity.

Current immunotherapies often fail because these metabolic barriers remain poorly understood and insufficiently targeted.

By quantifying metabolic regulation directly in tissues, we aim to:

• Reveal mechanisms of immune dysfunction
• Identify predictive biomarkers of therapeutic response
• Inform rational metabolic interventions in cancer

Our research is supported by competitive national and international funding, including:

• European Research Council (ERC Starting Grant 2023)
• Helmholtz Young Investigator Program
• DKTK (German Cancer Consortium)
• Foundation and industry-supported research initiatives

These awards support a long-term program to establish quantitative spatial immunometabolism as a central framework in cancer research.

We train scientists to think mechanistically about immune regulation in complex human tissues. Our work integrates systems immunology, spatial proteomics, and metabolic modeling with a strong focus on human cancer and translational relevance.

Trainees in the lab work on clinically grounded questions such as: How do metabolic niches shape immune cell fate? How do tumor and stromal interactions reprogram immune metabolism? Which spatially organized metabolic states predict response to immunotherapy?

To address these questions, lab members are trained across complementary experimental and computational platforms:

• High-dimensional single-cell and spatial proteomics
• Multimodal data integration and machine learning–based modeling
• Patient-derived tumor slice cultures and organoid systems
• CRISPR-based perturbation of metabolic regulators in human tumor models
• Co-culture systems combining patient-derived tumor organoids with autologous immune cells

Our organoid platform enables trainees to move from descriptive spatial profiling in patient tissues to mechanistic perturbation experiments in genetically controlled, three-dimensional human tumor models, and to test how metabolic interventions alter immune function.

Close integration with clinical collaborators within the NCT and DKTK network provides access to well-annotated patient cohorts and translational endpoints. Projects frequently combine large clinical sample sets with controlled experimental systems, fostering a bidirectional exchange between discovery and validation.

We emphasize conceptual clarity, quantitative rigor, and scientific independence. Trainees are expected to design hypothesis-driven studies, engage deeply with computational analysis, and contribute to the development of new technologies and analytical frameworks.

Alumni from the lab have transitioned to competitive doctoral positions at leading research institutions in Paris, Stockholm, Bonn, and Berlin.

We are committed to communicating our research beyond academia and contributing to public understanding of cancer immunology and metabolism. Our work aims not only to uncover fundamental biological principles but also to inform clinical innovation and societal dialogue around cancer therapy.

Our research explained
In a recorded lecture as part of the ‘Akademische Mittagspause’, Felix Hartmann explains how tumor metabolism shapes immune responses and why spatial technologies are transforming our understanding of cancer immunotherapy. Link to the YouTube video.

Feature article – DKFZ Einblick magazine
Our research on metabolic niches in the tumor microenvironment and their role in immunotherapy response was featured in the DKFZ science magazine Einblick. Link to the article. 

Through these activities, we aim to make complex biological mechanisms understandable, support evidence-based discussion of cancer research, and foster interdisciplinary exchange between scientists, clinicians, and the public.

We seek highly motivated researchers with backgrounds in:

• Immunology
• Computational biology
• Systems biology
• Spatial omics technologies
• Quantitative modeling

Successful candidates are intellectually independent, collaborative, and motivated to work at the interface of technology development and mechanistic biology.

Our trainees benefit from:

• Strong international collaborations
• Interdisciplinary mentoring
• Exposure to cutting-edge spatial and computational technologies
• Competitive national and international research networks

PhD and postdoctoral applicants are encouraged to contact us with a CV, brief research statement, and references.

Recent news, updates and celebrations are posted on our LinkedIn

Our research integrates experimental innovation with computational modeling. To enable reproducibility and downstream development, we provide open access to datasets, code, and experimental protocols underlying our published work. These resources are designed to support rigorous benchmarking, methodological extension, and multimodal data integration in spatial and single-cell biology. This includes the original protocols and datasets for single-cell metabolic profiling (scMEP), developed during my postdoctoral work and now broadly used across laboratories.

All collected experimental protocols can be found on our Protocols.io

All code and data analysis packages are located on our GitHub

scMEP resources (Nature Biotechnology 2021): Publication | Protocols | Datasets | Validated Antibodies