Tumour-Promoting Stromal Myofibroblasts in Human Carcinomas

  • Urszula M. Polanska
  • Kieran T. Mellody
  • Akira Orimo
Part of the Cancer Drug Discovery and Development book series (CDD&D)


Carcinomas are complex tissues comprised of neoplastic cells and a non-cancerous compartment referred to as the “stroma.” The stroma consists of an extracellular matrix (ECM) and a variety of mesenchymal cells, notably including fibroblasts, myofibroblasts, endothelial cells, pericytes and leukocytes. During tumourigenesis, the tumour-associated stroma is continuously exposed to substantial paracrine signals released by nearby carcinoma cells, and is often populated by considerable numbers of myofibroblasts. These cells are a hallmark of “activated fibroblasts” that are commonly observed in injured and fibrotic tissue. Importantly, their presence in large numbers within the stroma of human carcinomas is related to high-grade malignancies and poor prognoses in patients. Tumour-derived stromal myofibroblast-rich cell populations propagated in vitro stably maintain their myofibroblastic state, as well as an ability to significantly promote tumour growth in xenograft models. Differentiation of stromal cells into myofibroblasts within the tumour corroborates the evolution of the normal stroma towards a tumour-promoting stroma. However, the selective pressures responsible for instigating the generation of an altered stroma, and the molecular alterations that stably maintain the unique tumour-promoting myofibroblastic phenotype remain unclear. This chapter highlights the biological role of the tumour-associated stroma, with a particular focus on myofibroblasts and their ability to promote tumour progression through their interactions with carcinoma cells.


Idiopathic Pulmonary Fibrosis Idiopathic Pulmonary Fibrosis Patient Stromal Fibroblast Fibroblast Activation Protein Myofibroblast Differentiation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We would like to extend our gratitude to Dr. Robert A. Weinberg, Whitehead Institute for Biomedical Research, for his ongoing guidance and excellent supervision. We also thank Dr. Radoslaw Polanski for the critical reading of this chapter and Cancer research UK for the funding.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Urszula M. Polanska
  • Kieran T. Mellody
  • Akira Orimo
    • 1
  1. 1.CR-UK Stromal-Tumour Interaction Group, Paterson Institute for Cancer ResearchThe University of ManchesterManchesterUK

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