Three cancer researchers are being honored by the ECOG-ACRIN Cancer Research Group for their outstanding contributions. Dr. Valsamo Anagnostou from Johns Hopkins University is the Young Investigator of the Year for her pioneering work in lung cancer. Dr. Jordan Berlin of Vanderbilt University receives the Remarkable Mentor in Oncology Award for his dedication to nurturing oncology talent. Dr. Olisaemeka Ogbue of Mayo Clinic is awarded a grant for his innovative research on cancer survivorship.

Many of the deadliest forms of cancer are caused by a pathological mutation in the RAS protein. Yet, to date, no effective treatment for this cancer protein has been found. A new research approach aims to prevent the protein from forming in the first place by destroying its blueprint – the mRNA. Based on this strategy, the research group led by Peng Wu at the Max Planck Institute of Molecular Physiology has now developed a new type of “molecular eraser” targeting the mRNA of the cancer protein NRAS.

Conventional cancer treatments, such as chemotherapy, often lack specificity and can damage both cancerous and healthy cells, leading to severe side effects. With this in mind, researchers at Indian Institute of Technology Gandhinagar (IITGN) have developed DNA nanostructures called tetrahedrons and modified them by attaching a Vitamin E-derived molecule called alpha-tocopherol succinate (αT), which can disrupt vital functions inside cancer cells while acting protectively in healthy cells. By incorporating αT into the DNA tetrahedrons, the researchers significantly enhanced cellular uptake and improved anticancer efficacy, resulting in more selective and effective elimination of cancer cells.

A research paper by scientists from Sun Yat-sen University Cancer Center represented the largest prospective validation to date of AI-based treatment planning for NPC, demonstrating real-time feasibility, robust generalizability, and consistent clinical quality.

The new research paper, published on May. 18 in the journal Cyborg and Bionic Systems, developed and clinically validated a deep‑learning‑based automated planning system that generates high‑quality treatment plans in real time – within an integrated CT‑linear accelerator (CT‑linac) “all‑in‑one” (AIO) workflow.

MIT researchers developed a new approach to ultrasound imaging that allows the user to visualize a 3D, augmented-reality image of the object being scanned. This technique could be deployed in hospitals or used to assist training technicians in ultrasound interpretation.