Posted February 2, 2022

Postdoc position: The Roles of Radiotherapy on the Tumor Microenvironment

In the Aviesan ITMO Cancer funded project “RADIO-3R: Understanding and REFINING the influence of RADIOtherapy on the tumor microenvironment, by applying novel models to REDUCE and REPLACE animal models” two research laboratories in Strasbourg are collaborating in developing and applying photon and proton irradiation protocols in 3D cell cultures and in tumor mice with the goal to understand the impact of radiotherapy on the tumor microenvironment and to develop surrogates for tumor mouse models. A major goal is to enhance on-target effects of radiotherapy with the future aim to improve immune checkpoint therapy. A 24 months postdoc position is available in the Tumor Microenvironment group of Gertraud Orend (INSERM U1109, Strasbourg). This laboratory ( is specialized in the analysis of the tumor microenvironment with particular emphasis on the extracellular matrix molecule tenascin-C (Midwood et al., 2016, J Cell Sci). We have demonstrated pivotal roles of tenascin-C in tumor angiogenesis (Saupe et al., 2013, Cell Reports, Rupp et al., 2016, Cell Reports), metastasis (Sun et al., 2018, Cancer Res, Sun et al., 2019, Mat Bio) and tumor immunity (Deligne 2020, Cancer Immun Res, Spenle et al., 2021, Front Immunol). We showed that tenascin-C orchestrates an immune suppressive microenvironment and established a novel concept that could explain how matrix counteracts immune checkpoint therapy by demonstrating that tenascin-C immobilizes CD8 TIL thus physically separating them from the tumor cells (Spenlé et al., 2020, Cancer Immun Res, Murdamoothoo et al., 2021 EMBO Mol Med). In frame of this project the candidate will investigate irradiated tumor mice and tumor organoids in a comprehensive manner by using flow cytometry, tissue staining, gene expression analysis, proteomics and gain and loss of function approaches. We offer: a highly dynamic and supportive group of colleagues including researchers, postdocs, PhD and master students and technical personnel with expertise in extracellular matrix research, murine tumor models and tumor immunity. The salary remuneration follows INSERM guidelines taking into account previous experience. We search: a highly motivated scientist with background in tumor biology, mouse tumor models, immunology and cell culture, high team spirit and good English communication skills.

Interested candidates are invited to send their CV together with a motivation letter and the names of three referees to Gertraud Orend (email, homepage).

Posted November 5, 2021

Postdoc position: Tumor stroma and extracellular matrix as a modulator of immunotherapy efficacy, CCIT-DK, Copenhagen University Hospital, Herlev, Denmark.

The "Tumor Stroma and Matrix Immunology" (TSMI) group headed by Associate Professor and Lundbeck Fellow, Daniel H. Madsen at the National Center for Cancer Immunotherapy (CCIT-DK), Copenhagen University Hospital, Denmark, is seeking a highly motivated candidate for a 3-years postdoc position (February 1st, 2022 or after agreement) within the field of cancer immunology/matrix biology. The applicant must have a background in cancer biology, matrix biology, or immunology. Prior in vivo research expertise with mouse work is an advantage.

For more information and to submit your application, please visit this website: link

Posted September 30, 2021

Two-year fixed-term contract signaling in Oncogenesis, Angiogenesis and Permeability, Cancer & Immunology Research Center, INSERM, CNRS, Nantes University.

The “Signaling in Oncogenesis, Angiogenesis and Permeability” (SOAP) team is interested in deciphering how tumor cells pirate basic signaling pathways to sustain their survival and unlimited proliferation, as well as the way in which they interact within their environment. Fundamental signaling mechanisms are explored with a specific emphasis on deleterious remodeling of the vascular network associated to tumor. We developed a specific expertise in the characterization of intracellular signaling pathways with a focus on brain tumors. More specifically, we have identified key factors released in the tumor microenvironment involved in tumor/endothelial bidirectional interactions. How this is translated into endothelial plasticity in the course of tumor progression warrants further investigation. Our project combines high throughput unbiased screens (proteomic, genomic and chemical) with state-of-the-art biochemistry and cell biology (2D/3D cell models, super-resolution), as well as integrated models (mouse models and clinical samples) to explore intracellular signaling and cell communication. We anticipate that our results will increase our knowledge on basic signaling mechanisms involved in tumor initiation, progression and resistance, and may help the design of new strategies to face devastating human cancers.

For more information visit this link.

Posted March 27, 2021

One postdoctoral fellowships in Dr. Van Obberghen-Schilling's Lab, Institute of Biology Valrose, Université Côte d’Azur (UCA).

3IA Côte d’Azur Research Axis : AI for Computational Biology and Bio-Inspired AI


Applications are invited for a 2-year 3iA Côte d’Azur postdoctoral position in tumor/ECM biology to study functional and structural features of the extracellular matrix (ECM) in the immunosuppressive tumor microenvironment of head and neck cancer. Immunomodulatory therapies are promising for this tumor type, yet resistance rates are high since less than 20% of patients respond. We are specifically interested in exploring the tumor ECM environment, together with immune cell signatures, for gaining mechanistic insights into invasive disease and resistance to immunotherapy. Our previous work on ECM topology based on confocal images of cell-derived ECM has provided a framework for quantitative description and modeling of matrix features associated with disease states. The present project involves quantitative characterization of ECM architecture in in vitro models and human tumor tissue using multiplex immunofluorescence imaging, empowered by deep learning approaches.
For more information visit this link.