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Defining the identity and differentiation pathways of the immune-stimulating fibroblastic tumor stroma

Applicant Ludewig Burkhard
Number 177208
Funding scheme Sinergia
Research institution Institut für Immunbiologie Kantonsspital St. Gallen
Institution of higher education Cantonal hospital of St.Gallen - KSPSG
Main discipline Interdisciplinary
Start/End 01.01.2018 - 31.12.2021
Approved amount 3'177'365.00
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All Disciplines (5)

Experimental Cancer Research
Immunology, Immunopathology

Keywords (9)

antitumor immunity; CyTOF; mass cytometry; fate mapping; lineage tracing; RNA-seq; lung cancer; fibroblastic stromal cells; tertiary lymphoid structures

Lay Summary (German)

Um Tumorerkrankungen der Lunge besser zu verstehen und behandeln zu können, gehen Forschende des Kantonsspitals St. Gallen und der Universität Zürich in diesem Sinergia Projekt einen neuen Weg: Immunstimulierende Fibroblasten sollen in präklinischen Tumormodellen und in menschlichen Tumoren identifiziert und molekular charakterisiert werden, um diese Zellen in späteren Untersuchungen gezielt verändern zu können.
Lay summary

Neben den eigentlichen Tumorzellen, die unterschiedliche genetische Veränderungen aufweisen, finden sich in der Tumormasse nichttransformierte Zellen. Dazu gehören Fibroblasten, die das strukturelle Grundgerüst des Tumors bilden und die Tumorzellen mit Nährstoffen und Überlebensfaktoren versorgen. Das Ziel dieses Projekts ist es, neue Erkenntnisse über die unterschiedlichen fibroblastischen Tumorstromazellen zu gewinnen. Insbesondere sollen Fibroblasten identifiziert werden, die schützende Immunantworten gegen die Tumorzellen fördern. Im Institut für Immunbiologie des Kantonsspitals St. Gallen wurden dazu präklinische Modellsysteme entwickelt, um immunstimulierende Fibroblasten im Tumorstroma zu charakterisieren und zu testen, ob ein gezielter Angriff auf diese Zellen einen therapeutischen Vorteil mit sich bringt. Im Institut für Experimentelle Immunologie der Universität Zürich wird untersucht, ob immunstimulierende Fibroblasten strukturierte Aussenposten des Immunsystems im Gewebe des Lungentumors bilden können. Neue molekulare Untersuchungsmethoden wie RNA Sequenzierung und auf Massenspektrometrie basierte Bildgebung, die im Institut für Molekulare Biologie der Universität Zürich entwickelt wurden, sollen angewandt werden, um die zellulären und molekularen Interaktionen zwischen Tumorzellen und immunstimulierenden Fibroblasten zu klären. Wir erwarten, dass die Definition von einzigartigen Wirkmechanismen in der Mikroumgebung des Tumors die Entwicklung von neuen Therapien fördern wird.

Direct link to Lay Summary Last update: 13.12.2017

Responsible applicant and co-applicants


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Eleven grand challenges in single-cell data science
Lähnemann David, Köster Johannes, Szczurek Ewa, McCarthy Davis J., Hicks Stephanie C., Robinson Mark D., Vallejos Catalina A., Campbell Kieran R., Beerenwinkel Niko, Mahfouz Ahmed, Pinello Luca, Skums Pavel, Stamatakis Alexandros, Attolini Camille Stephan-Otto, Aparicio Samuel, Baaijens Jasmijn, Balvert Marleen, Barbanson Buys de, Cappuccio Antonio, Corleone Giacomo, Dutilh Bas E., Florescu Maria, Guryev Victor, Holmer Rens, et al. (2020), Eleven grand challenges in single-cell data science, in Genome Biology, 21(1), 31-31.
pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single-cell RNA-seq preprocessing tools
Pierre-Luc Germain (2020), pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single-cell RNA-seq preprocessing tools, in bioRxiv, 1-31.
CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets
Nowicka Malgorzata, Krieg Carsten, Crowell Helena L., Weber Lukas M., Hartmann Felix J., Guglietta Silvia, Becher Burkhard, Levesque Mitchell P., Robinson Mark D. (2019), CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets, in F1000Research, 6, 748-748.
On the discovery of population-specific state transitions from multi-sample multi-condition single-cell RNA sequencing data
HelenaCrowell (2019), On the discovery of population-specific state transitions from multi-sample multi-condition single-cell RNA sequencing data, in bioRxiv, 1-24.

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference Poster Harnessing lymphoid neogenesis for prognosis and treatment of solid tumors. 25.11.2019 Paris, France Movahedian Attar Farkhondeh; van den Broek Maries; Silina Karina;

Use-inspired outputs

Associated projects

Number Title Start Funding scheme
159188 Ontogeny and functional characterization of splenic fibroblastic reticular cells (FRCs) and their mesenchymal precursors during homeostasis and infection 01.09.2015 Project funding (Div. I-III)
182583 Stromal Cell Niches at the Nexus of the Innate Lymphoid Cell Interactome 01.01.2019 Project funding (Div. I-III)
141918 Imaging-based Systems Biology Analysis of Lymph Node Structure and Function in Viral Infection 01.08.2012 Sinergia
125447 Examining the function of lymphoid organ structure during antiviral immune responses using microscopic and mesoscopic imaging 01.06.2009 Sinergia
175841 Beyond the average: computational tools for discovery in high-throughput single cell datasets 01.11.2017 Project funding (Div. I-III)


Lung cancer is the most frequent cause of death in cancer patients in industrialized countries. A particular property of non-small cell lung cancer is the composition of the tumor microenvironment (TME) with a very high proportion of stromal cells. Whereas the stroma of normal tissues represents a natural barrier for tumor cells, the stroma within cancer tissues has coevolved with the neoplastic tissue to support its growth and spread. In particular, fibroblasts can be reprogrammed to secrete growth factors, proteases and extra-cellular matrix components that support tumor progression. Nevertheless, recent studies reveal that subsets of fibroblasts can play a tumor-suppressive role, providing an explanation as to why global anti-stromal cell therapies have sometimes resulted in exacerbated malignant growth. Hence, it is important to determine the origin of such tumor-suppressive fibroblastic stromal cells (FSC) and to delineate the molecular pathways that govern fibroblast differentiation in the tumor milieu. Moreover, expression of several immune-stimulating genes that mediate attraction of immune cells and/or foster formation of protective tertiary lymphoid structures, is associated with improved survival of lung cancer patients. However, little is known about the nature of the fibroblastic cells that determine the establishment of such immune-stimulating niches in the lung cancer microenvironment. The main hypothesis underlying the planned research is that expansion and maturation of a distinct fibroblast subset fosters the development of immune-stimulating microenvironments within the lung tumor, which in turn promotes antitumor immunity. We have designed an interdisciplinary approach to dissect the origin, identity, and function of immune-stimulating fibroblasts in relation to other fibroblast subsets of the lung tumor stroma. The work on the first aim of the research program is built on the assumption that a lineage of tissue-resident fibroblasts exhibits immune-stimulating potential once exposed to the tumor microenvironment. Novel fibroblast subset-specific fate-mapping models will be used to define the differentiation trajectories of immune-stimulating FSC at single cell resolution during lung cancer development. The goal of the second aim is to establish a causal relationship between the maturation of immune-stimulating fibroblasts in the lung TME and the formation of tumor-associated tertiary lymphoid structures. To this end, cell type-specific ablation of key fibroblast maturation factors and targeted ablation of immune-stimulating fibroblasts in experimental lung tumors will be utilized to assess the impact of such fibroblasts on antitumor immunity. The goals of the third aim are to identify immune-stimulating FSC in human lung cancer and to develop a data-based model of tumor-induced changes to the lung stroma. To gauge the transcriptional diversity between fibroblast lineages within the tumor stroma, RNA-sequencing (RNA-seq) of small, defined cohorts of fluorescently-marked fibroblasts will be performed. Single cell RNA-seq of human lung cancer FSC will be complemented in the forth aim by single cell mass cytometry to provide important information for refined subset definition. Finally, we will validate our data-based model of lung fibroblast differentiation using tissue mass cytometry on lung and tumor tissue from patients with adenocarcinoma or squamous cell carcinoma. Together, the collaborative approach proposed here will reveal novel insight into the origin, identity, function and relation of immune-stimulating fibroblasts in the context of the lung tumor stroma. Moreover, we expect that these studies will reveal putative therapeutic targets to bias the composition of the tumor stroma by promoting the differentiation of an immune-stimulating environment.