New research maps the immune cells that fight tumors—and the ones that help them
Peer-Reviewed Publication
Updates every hour. Last Updated: 22-Jun-2026 08:16 ET (22-Jun-2026 12:16 GMT/UTC)
New research from MUSC Hollings Cancer Center is aimed at understanding and preventing relapse in pediatric brain cancers, particularly medulloblastoma, the most common malignant brain tumor in children. The work focuses on why some tumors return after treatment and how resistant cancer stem cells may drive that recurrence.
The research is led by pediatric researcher Jezabel Rodriguez-Blanco, Ph.D., whose lab studies the biological mechanisms behind relapse in hopes of identifying new therapeutic targets. The researchers are investigating how tumors evolve after treatment and why recurrent tumors often behave differently from the original disease, one reason current therapies frequently fail once the cancer returns.
The study underscores Hollings’ growing investment in pediatric cancer research and translational science, with the long-term goal of developing combination therapies that could stop resistant tumor cells before they spark recurrence. The work also reflects a broader push to move discoveries from the lab into treatments that improve outcomes for children facing aggressive brain cancers.
A new AI model developed by UC San Diego researchers could make it possible to predict treatment response based only on a tumor's genetics.
Esophageal squamous cell carcinoma (ESCC) represents a significant global health burden characterized by a high mortality rate, primarily due to uncontrolled tumor proliferation and the prevalence of distant metastases at the time of diagnosis. Despite significant advances, there remains a critical need to identify the underlying molecular mechanisms to establish new therapeutic approaches.
An artificial intelligence–driven transfer learning strategy enabled the discovery of a novel indolopyridine-based small molecule (Compound 8a) that directly targets gp130, potently suppresses the JAK2/STAT3 signaling pathway, and effectively inhibits colorectal cancer growth in vitro and in vivo, offering a promising lead and a feasible computational paradigm for developing gp130‑targeted anticancer agents.