Reviews:
Understanding the interplay between extracellular matrix topology and tumor-immune interactions: Challenges and opportunities
PDF | Full Text | How to cite | Press Release
Metrics: PDF 111 views | Full Text 498 views | ?
Abstract
Yijia Fan1,2, Alvis Chiu1, Feng Zhao1 and Jason T. George1,2,3,4
1 Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA
2 Translational Medical Sciences, Texas A&M University Health Science Center, Houston, TX 77030, USA
3 Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA
4 Department of Hematopoietic Biology and Malignancy, MD Anderson Cancer Center, Houston, TX 77030, USA
Correspondence to:
Jason T. George, | email: | [email protected] |
Keywords: ECM; tumor-T cell evolution; tumor microenvironment
Received: July 12, 2024 Accepted: October 11, 2024 Published: November 07, 2024
ABSTRACT
Modern cancer management comprises a variety of treatment strategies. Immunotherapy, while successful at treating many cancer subtypes, is often hindered by tumor immune evasion and T cell exhaustion as a result of an immunosuppressive tumor microenvironment (TME). In solid malignancies, the extracellular matrix (ECM) embedded within the TME plays a central role in T cell recognition and cancer growth by providing structural support and regulating cell behavior. Relative to healthy tissues, tumor associated ECM signatures include increased fiber density and alignment. These and other differentiating features contributed to variation in clinically observed tumor-specific ECM configurations, collectively referred to as Tumor-Associated Collagen Signatures (TACS) 1–3. TACS is associated with disease progression and immune evasion. This review explores our current understanding of how ECM geometry influences the behaviors of both immune cells and tumor cells, which in turn impacts treatment efficacy and cancer evolutionary progression. We discuss the effects of ECM remodeling on cancer cells and T cell behavior and review recent in silico models of cancer-immune interactions.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 License.
PII: 28666