Targeted Re-engineering of the Tumor Matrix to Advance Immunotherapy

This project aims to disrupt the pro-fibrotic loop in pancreatic cancer using engineered biomimetics to enhance immune therapy efficacy by normalizing the tumor microenvironment.

Subsidie
€ 2.499.783
2024

Projectdetails

Introduction

Immunotherapy can prolong the lives of cancer patient subgroups, but it fails in solid tumors with dense fibrotic stroma, such as pancreatic cancer. Fibrotic stroma prevents the recruitment and activation of immune effector cells, thereby dampening the efficacy of immunotherapy.

Mechanism of Fibrosis

Mechanistically, cancer-associated fibroblasts (CAFs) initiate extracellular matrix (ECM) production, which aggravates fibrosis by reciprocal mechanoactivation and crosstalk with tumor-associated myeloid cells, forming a self-sustainable “pro-fibrotic loop.” However, the central pathways initiating this vicious cycle and signaling compensation maintaining fibrosis under therapeutic conditions remain unclear. Consequently, clinical solutions to disrupt this pro-fibrotic loop are lacking.

Hypothesis

I hypothesize that identifying and targeting the multi-step pro-fibrotic loop can be exploited to re-engineer and normalize the perturbed ECM, increasing tumor accessibility for immune effector cells and immunotherapy.

Approach

To disrupt the pro-fibrotic loop, I will exploit an engineered modular peptido-/nanobio-mimetic toolbox, comprising nature-inspired targeting systems based on in silico design and experimental validation. The peptidomimetics and nano-biomimetics will target cellular interaction mechanisms to:

  1. Inhibit CAF–ECM interactions driving tissue stiffening and fibrosis.
  2. Train tumor myeloid cells towards matrix-degrading effectors to restructure fibrotic ECM.

These biomimetics will be examined in advanced 3D in vitro and in vivo pancreatic tumor models.

Integration and Outcomes

The combined effects of biomimetics on the matrisome, matrix architecture, and single-cell transcriptomics will be integrated using machine learning to identify ECM fingerprints. OpenMatrix will:

  1. Deliver mechanistic insights into endogenous fibrosis drivers and antagonists.
  2. Engage these cell-intrinsic mechanisms to revert fibrosis.
  3. Reactivate immune effector function and advance immunotherapy.

Financiële details & Tijdlijn

Financiële details

Subsidiebedrag€ 2.499.783
Totale projectbegroting€ 2.499.783

Tijdlijn

Startdatum1-9-2024
Einddatum31-8-2029
Subsidiejaar2024

Partners & Locaties

Projectpartners

  • UNIVERSITEIT TWENTEpenvoerder
  • STICHTING RADBOUD UNIVERSITAIR MEDISCH CENTRUM

Land(en)

Netherlands

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