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Novel Method Targeting the Tumor Microenvironment as Therapeutic Treatments for Metastatic Cancers

  • Stage: Preclinical in vivo
  • Type: Therapeutic
  • Categories: Biomarker, Target

Technology Overview

Solid tumors and tumor cell clusters form intercellular cavities called Microlumen. These microlumen are enclosed pockets between two or more cancer cells that are bound by cell-cell junctions and separated from surrounding extracellular spaces. Cancer cells use the unique architecture of these Microlumen to restrict protein diffusion and aggregate growth factors. These mitogen reservoirs support tumor growth, promote metastasis, and elevate therapeutic resistance making cancer more difficult to treat. To overcome these obstacles, researchers at Fred Hutch have devised a method to identify and disrupt tumor cells’ Microlumen. Through targeted RNA interference (RNAi), pharmacological inhibition, and immunotherapy, Dr. Cheung and his research team can disrupt microlumen integrity and deprive tumor cells of growth sustaining signals. Microlumenal targeting creates a whole new approach in amplifying therapeutic efficacy (e.g., adoptive cell therapy) and improving prognosis for a wide spectrum of cancers.

Applications

  • Inhibit cluster-dependent tumor proliferation and suppress metastatic outgrowth of tumor cell clusters
  • Reduce growth factor signaling and increase susceptibility of tumor cells to other therapies

Advantages

  • Slows tumor growth and improves outcomes in combination therapy with growth factor inhibitors
  • Cluster-dependent tumor profiling facilitates precision therapy

Patent Information

Patent pending

Market Overview

The metastatic cancer treatment market was estimated $54 billion in 2017 and is expected to reach $98 billion by 2025 with a CAGR of 7.7%. Biologicals and biosimilars are a key component of this rapidly expanding market due to ascending approval from regulatory bodies and increasing adoption rates.

Investigator Overview

  • Kevin Cheung, MD - Public Health Sciences Division and Human Biology Division
Tech ID: 19-151
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