The Molecular Oncology research group, led by Prof. Andrea Alimonti at the Institute of Oncology Research (IOR, affiliated with USI and part of Bios+), a member of the SenoTarg consortium, has uncovered a novel method using bioinformatics and artificial intelligence to selectively target and eliminate specific cells involved in metastasis.
The Problem
Metastasis, the spread of cancer cells from a primary tumor to distant organs, is responsible for nearly 90% of cancer-related deaths. Despite its deadly impact, our understanding of the biology behind metastasis is still in its early stages, and effective treatments to prevent it are lacking. To address this, Ph.D. students Martina Troiani and Manuel Colucci from Prof. Alimonti’s team at the IOR have identified a groundbreaking therapy that impedes metastasis formation.
Recent findings from Prof. Alimonti’s lab showed that standard chemotherapies induce a state called senescence—a process where cells stop proliferating but remain metabolically active. While senescence initially helps arrest tumor growth and promote immune response, prolonged senescence can actually promote tumor progression, migration, and metastasis.
Through advanced bioinformatics and artificial intelligence, Troiani and Colucci discovered a class of compounds that specifically target and eliminate these senescent tumor cells (Senolytic Therapy), thereby reducing metastatic spread. This research was published in Nature Communications in April 2022.
Background
Standard chemotherapy and radiotherapy often trigger senescence in tumor cells. These senescent cells, left in the tumor environment, can remain metabolically active and contribute to tumor proliferation and metastasis. This has led to the emergence of removing senescent tumor cells as a promising therapeutic approach. By using single-cell transcriptomics, the team developed an innovative bioinformatic tool to identify and target new cancer vulnerabilities.
The Discovery
The research team at IOR created the Senescence Index Tool (SIT), a cutting-edge bioinformatic resource to identify and characterize senescent tumor cells. For the first time, they revealed that senescent cells are a highly heterogeneous group, all depending on the same survival gene, MCL-1. Current senolytic therapies primarily target another gene, BCL-2 (with drugs like Navitoclax), but about 50% of senescent cells evade this approach by relying on MCL-1 for survival.
Troiani and Colucci, the co-first authors, explored both genetic and pharmacological ways to inhibit MCL-1 after chemotherapy. This intervention not only halted tumor growth but also significantly reduced metastasis formation.
This breakthrough has the potential to revolutionize chemotherapy treatments within the Molecular Oncology department under Prof. Alimonti’s leadership. He explains, “Cancer cells subjected to stress from anti-cancer therapies face two outcomes: death or entering a limbo state known as cellular senescence. By leveraging bioinformatics and machine learning, we’ve identified a new target to eradicate senescent tumor cells and thereby prevent metastasis.”
This work also included Prof. Cippà, a member as well of the SenoTarg group.
Outlook
The ability to pinpoint senescent cells at the single-cell level and recognize their diversity opens the door to new, precise therapies that could enhance the effectiveness of chemotherapy. This innovative bioinformatic approach allows for deeper insights into senescence and metastasis, building on the work already laid out by Prof. Alimonti’s team (Guccini et al., Cancer Cell 2021).
The Senescence Index Tool could lead to highly targeted senolytic therapies, improving oncology treatments and potentially aiding in the fight against aging and age-related diseases. This advancement offers hope for better outcomes for cancer patients and the elderly alike.