Differentiated glioma cell-derived Fibromodulin activates Integrin-dependent Notch signaling in endothelial cells to promote tumor angiogenesis and growth

  1. Shreoshi Sengupta
  2. Mainak Mondal
  3. Kaval Reddy Prasasvi
  4. Arani Mukherjee
  5. Prerna Magod
  6. Serge Urbach
  7. Dinorah Friedmann-Morvinski  Is a corresponding author
  8. Philippe Marin  Is a corresponding author
  9. Kumaravel Somasundaram  Is a corresponding author
  1. Indian Institute of Science Bangalore, India
  2. Tel Aviv University, Israel
  3. Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, France

Abstract

Cancer stem cells (CSCs) alone can initiate and maintain tumors, but the function of non-cancer stem cells (non-CSCs) that form the tumor bulk remains poorly understood. Proteomic analysis showed a higher abundance of the extracellular matrix small leucine-rich proteoglycan Fibromodulin (FMOD) in the conditioned medium of differentiated glioma cells (DGCs), the equivalent of glioma non-CSCs, compared to that of glioma stem-like cells (GSCs). DGCs silenced for FMOD fail to cooperate with co-implanted GSCs to promote tumor growth. FMOD downregulation neither affects GSC growth and differentiation nor DGC growth and reprogramming in vitro. DGC-secreted FMOD promotes angiogenesis by activating Integrin-dependent Notch signaling in endothelial cells. Furthermore, conditional silencing of FMOD in newly generated DGCs in vivo inhibits the growth of GSC-initiated tumors due to poorly developed vasculature and increases mouse survival. Collectively, these findings demonstrate that DGC-secreted FMOD promotes glioma tumor angiogenesis and growth through paracrine signaling in endothelial cells and identifies a DGC-produced protein as a potential therapeutic target in glioma.

Data availability

Label-free mass spectrometry data between the GSC and DGC showing protein ratios in the GSC and DGC secretome and p values are shown in Supplementary File 1 for proteins exhibiting significant differences in abundance in both conditions. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD032958.

Article and author information

Author details

  1. Shreoshi Sengupta

    Department of Microbiology and Cell Biology, Indian Institute of Science Bangalore, Bangalore, India
    Competing interests
    The authors declare that no competing interests exist.
  2. Mainak Mondal

    Department of Microbiology and Cell Biology, Indian Institute of Science Bangalore, Bangalore, India
    Competing interests
    The authors declare that no competing interests exist.
  3. Kaval Reddy Prasasvi

    Department of Microbiology and Cell Biology, Indian Institute of Science Bangalore, Bangalore, India
    Competing interests
    The authors declare that no competing interests exist.
  4. Arani Mukherjee

    Department of Microbiology and Cell Biology, Indian Institute of Science Bangalore, Bangalore, India
    Competing interests
    The authors declare that no competing interests exist.
  5. Prerna Magod

    School of Neurobiology, Biochemistry and Biophysics, Tel Aviv University, Tel Aviv, Israel
    Competing interests
    The authors declare that no competing interests exist.
  6. Serge Urbach

    Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
  7. Dinorah Friedmann-Morvinski

    School of Neurobiology, Biochemistry and Biophysics, Tel Aviv University, Tel Aviv, Israel
    For correspondence
    dino@tauex.tau.ac.il
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6394-9876
  8. Philippe Marin

    Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France
    For correspondence
    philippe.marin@igf.cnrs.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5977-7274
  9. Kumaravel Somasundaram

    Department of Microbiology and Cell Biology, Indian Institute of Science Bangalore, Bangalore, India
    For correspondence
    skumar1@iisc.ac.in
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6228-9741

Funding

Department of Biotechnology, Ministry of Science and Technology, India

  • Kumaravel Somasundaram

Department of Science and Technology, Ministry of Science and Technology, India

  • Kumaravel Somasundaram

Indo-French Centre for the Promotion of Advanced Research (n{degree sign} IFC/5603-C/2016/503)

  • Kumaravel Somasundaram

Israel Science Foundation (Grant no.1315/15 and 1429/20)

  • Dinorah Friedmann-Morvinski

Fondation pour la Recherche Médicale

  • Philippe Marin

Indo-French Centre for the Promotion of Advanced Research (n{degree sign} IFC/5603-C/2016/503)

  • Philippe Marin

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: The Institute Ethical Committee for Animal Experimentation (Institute Animal Ethics Committee [IAEC] Project Number: CAF/Ethics/752/2020)

Reviewing Editor

  1. Caigang Liu, Shengjing Hospital of China Medical University, China

Publication history

  1. Received: March 25, 2022
  2. Preprint posted: April 6, 2022 (view preprint)
  3. Accepted: May 29, 2022
  4. Accepted Manuscript published: June 1, 2022 (version 1)
  5. Accepted Manuscript updated: June 6, 2022 (version 2)
  6. Version of Record published: July 6, 2022 (version 3)

Copyright

© 2022, Sengupta et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 877
    Page views
  • 356
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Shreoshi Sengupta
  2. Mainak Mondal
  3. Kaval Reddy Prasasvi
  4. Arani Mukherjee
  5. Prerna Magod
  6. Serge Urbach
  7. Dinorah Friedmann-Morvinski
  8. Philippe Marin
  9. Kumaravel Somasundaram
(2022)
Differentiated glioma cell-derived Fibromodulin activates Integrin-dependent Notch signaling in endothelial cells to promote tumor angiogenesis and growth
eLife 11:e78972.
https://doi.org/10.7554/eLife.78972
  1. Further reading

Further reading

    1. Biochemistry and Chemical Biology
    2. Cancer Biology
    Stefania Monterisi, Johanna Michl ... Pawel Swietach
    Research Article Updated

    Growth of cancer cells in vitro can be attenuated by genetically inactivating selected metabolic pathways. However, loss-of-function mutations in metabolic pathways are not negatively selected in human cancers, indicating that these genes are not essential in vivo. We hypothesize that spontaneous mutations in ‘metabolic genes’ will not necessarily produce functional defects because mutation-bearing cells may be rescued by metabolite exchange with neighboring wild-type cells via gap junctions. Using fluorescent substances to probe intercellular diffusion, we show that colorectal cancer (CRC) cells are coupled by gap junctions assembled from connexins, particularly Cx26. Cells with genetically inactivated components of pH regulation (SLC9A1), glycolysis (ALDOA), or mitochondrial respiration (NDUFS1) could be rescued through access to functional proteins in co-cultured wild-type cells. The effect of diffusive coupling was also observed in co-culture xenografts. Rescue was largely dependent on solute exchange via Cx26 channels, a uniformly and constitutively expressed isoform in CRCs. Due to diffusive coupling, the emergent phenotype is less heterogenous than its genotype, and thus an individual cell should not be considered as the unit under selection, at least for metabolite-handling processes. Our findings can explain why certain loss-of-function mutations in genes ascribed as ‘essential’ do not influence the growth of human cancers.

    1. Cancer Biology
    2. Computational and Systems Biology
    Erika K Ramos, Chia-Feng Tsai ... Huiping Liu
    Research Article

    Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is co-expressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.