Our immune system is marvelous. It can protect our body from infections and other types of diseases by identifying foreign disease-causing bacteria and viruses. It can also detect cancer cells and eliminate them. For cancer cells to proliferate in the body, they undergo genetic mutations that make them divide uncontrollably, but also making them exposed to the immune system Therefore, cancer cells also develop a mechanism that allows them to evade the immune system.
Immunotherapy drugs, such as immune checkpoint inhibitors (ICI), interfere with this escape mechanism and have demonstrated impressive outcomes. Unfortunately, while these ICI drugs are very effective, only 20-30% of the patients will respond to immunotherapy, and most patients will relapse.
As part of his Ph.D. research at the Carmi Lab, Tel Aviv University, our Senior Researcher at Nucleai, Amit Gutwillig, has discovered a unique morphological structure that can be detected in immune-resistant cancer cells. The study was published in the journal eLife in an article titled, “Transient cell-in-cell formation underlies tumor relapse and resistance to immunotherapy.” and made headlines in the New York Times.
The discovery of these unique cell-in-cell structures, made by cancer cells to avoid the immune system’s attacks, may help identify novel targets for immunotherapy and set the framework for designing more effective cancer treatments.
“After years of basic science, I get to see the other end of it, the impact this research provides for patients struggling with cancer” said Amit Gutwillig “Discoveries like this can truly make a difference in patients’ lives and I am extremely honored to take part in such meaningful work.”
T cell (green at the top) kills outer cancer cell while the inner cancer cell remains intact. Red – Cancer cell’s membrane, Green – Cancer cell’s nuclei Yaron Carmi and Amit Gutwilling, The Carmi Lab/Tel Aviv University
At Nucleai, we apply powerful AI models to spatially “map” the tumor landscape of cancer patients to predict response to immunotherapy. Nucleai’s technology allows us to combine key insights in cancer biology and immunology, like this research, with big data and spatial features, extracted by our deep learning models from patient’s histological sections to make real-life advances in clinical oncology.
This groundbreaking discovery of unique morphological cell structure in immunotherapy-resistant tumors is one example of a spatial feature that can be identified through our AI-powered analysis models to improve cancer therapy and directly contribute to patients’ health and life.
Spatial cellular features like this discovery are another step towards a future of personalized medicine where treatments are customized to each patient to optimize clinical outcomes. To make precision medicine a reality, we must continue to work closely with cutting-edge scientific research to advance clinical outcomes for oncology patients.
