Research Advances from the Metastasis Research Network (MetNet)
Discoveries from MetNet have advanced the understanding of metastasis and revealed mechanistic insights into the spread of cancer, which are informing the development of new cancer treatment strategies.
Mechanisms of Metastasis
By analyzing sequencing data and using computational approaches, investigators with the Stanford Breast Metastasis MetNet Center found that germline-mediated immunoediting shapes breast cancer subtypes and metastatic potential. When describing the research, Dr. Christina Curtis (lead investigator of the study) said, “We find that the path to tumor development is constrained by hereditary factors and immunity. This new result unearths a new class of biomarkers to forecast tumor progression and an entirely new way of understanding breast cancer origins.”
Scientists with the Johns Hopkins University MetNet Project showed that claudin 7 suppresses breast cancer invasion and metastasis via repression of a smooth muscle actin gene program.
Researchers with the Rockefeller University MetNet Center discovered that a common germline variant in PCSK9 drives breast cancer metastasis and is associated with reduced survival. They also showed that inhibition of PCSK9 with an antibody already approved for patients with high cholesterol suppresses breast cancer metastasis in preclinical models.
Scientists with the Albert Einstein College of Medicine MetNet Project found that macrophages in the lung regulate the timing of breast cancer metastasis. "Understanding how immune cells keep disseminated cancer cells in check could lead to new anti-metastatic cell therapies among other strategies," said Dr. Aguirre-Ghiso (lead investigator of the study).
Investigators with the Stanford Brain Metastasis MetNet Center showed that treatment with mebendazole (a drug used to treat intestinal worm infections) inhibits brain metastasis and improves survival in preclinical models of triple-negative breast cancer.
Development of New Tools and Models for Metastasis Research
Researchers with the NYU MetNet Center developed MetFinder, a computational tool for the automated quantitation of metastasis burden in tissue sections from preclinical models.
Scientists with the MIT MetNet Center developed a perfusable microvasculature-on-a-chip model that recapitulates human vasculature and enables studies of circulating tumor cells and metastasis.