Hyaluronic acid (HA) is a key component of the extracellular matrix that plays a critical role in tissue homeostasis, cell signaling, and wound healing. In cancer, however, HA becomes dysregulated and functions as an active driver of tumor progression, metastasis, immune evasion, and therapy resistance. Elevated HA levels and altered molecular weight distributions are associated with aggressive tumor phenotypes across multiple cancer types. Interactions between HA and its receptors, such as CD44 and RHAMM, further activate oncogenic signaling pathways, highlighting HA as a targetable molecular regulator within the tumor microenvironment. Despite growing recognition of HA’s role in tumor biology, effective therapeutic strategies specifically targeting HA-mediated mechanisms remain limited. Recent advances in targeted therapeutics --enabled by bioengineering, biomaterials, and nanotechnology-- offer new opportunities to modulate HA dynamics and exploit its tumor-specific functions for cancer treatment.
This Research Topic aims to address the critical need for innovative therapeutic strategies targeting the hyaluronic acid–cancer axis through interdisciplinary approaches. While HA has long been recognized as a structural component of the tumor microenvironment, emerging evidence underscores its active role in regulating tumor growth, mechanotransduction, and immune interactions, positioning it as a promising molecular target. However, current approaches to therapeutically modulate HA remain limited in specificity and efficacy.
We seek to highlight recent advances in target-specific and mechanism-driven strategies, including HA-modulating biomaterials, enzyme-responsive systems, peptide-based targeting approaches, and nanocarriers designed to exploit HA-rich tumor environments. Particular emphasis will be placed on studies that integrate molecular design with therapeutic function, such as improving drug delivery, enhancing tissue penetration, overcoming resistance mechanisms, and demonstrating proof-of-concept efficacy in relevant models. Additionally, this Topic aims to explore translational pathways, bridging fundamental discoveries in HA biology with clinically relevant therapeutic applications.
This Research Topic welcomes contributions that investigate both mechanistic insights into HA as a molecular target and the development of targeted therapeutic strategies. We encourage submissions spanning fundamental, preclinical, and early translational studies.
Topics of interest include, but are not limited to:
- HA-based and HA-targeting biomaterials for cancer therapy - Peptide- and ligand-based targeting of HA receptors (e.g., CD44) - Novel systems and analytical approaches to detect and quantify HA in cancer - Nanotechnology and drug delivery systems exploiting HA-rich tumor microenvironments - Enzymatic modulation of HA (e.g., hyaluronidase-based therapeutic strategies) - HA molecular weight as a determinant of tumor progression and therapeutic response - Engineering approaches to remodel the tumor extracellular matrix for therapeutic benefit - HA in metastasis, mechanobiology, and cancer stem cell niches - Preclinical and early-stage studies targeting HA pathways
Topic Editor Tuğba Özdemir is the founder of Hyaluropsy, LLC. The other Topic Editors declare no competing interests with regard to the Research Topic subject.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Clinical Trial
Editorial
FAIR² Data
General Commentary
Hypothesis and Theory
Methods
Mini Review
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Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Clinical Trial
Editorial
FAIR² Data
General Commentary
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Review
Systematic Review
Technology and Code
Keywords: Hyaluronic acid, Cancer microenvironment, Bioengineering, Biomaterials, Drug delivery
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