Damon Runyon News

A major challenge in treating brain cancer is delivering drugs across the blood-brain barrier (BBB), the dense network of cells and blood vessels that prevents toxins and pathogens from entering the brain. Unfortunately, the BBB also bars entry to therapeutic molecules, leaving highly toxic radiation or chemotherapy treatment as the only recourse for many patients with brain cancer.

Cancer immunotherapies work by triggering the body’s immune response against tumors. Tumor cells can evade destruction by the immune system, however, by attracting helper T cells, the “peacekeepers” of the immune system. Unlike cytotoxic T cells, which attack and kill pathogens, helper T cells suppress the immune response, essentially telling killer immune cells to “stand down.” While helper T cell function is vital for preventing autoimmune flare-ups, cancer cells can exploit this function, luring the immune system into a false sense of calm when there is in fact a threat.

Glioblastomas (GBMs) are the most common—and the most aggressive—type of cancer originating in the brain. Part of the reason these tumors are so hard to treat is that the cancer cells suppress the immune cells that enter their environment. Not only can they outcompete immune cells for critical nutrients, effectively starving the immune cells, but some GBMs can even adjust their metabolism to produce metabolites that directly inhibit immune cell activity.

Damon Runyon has announced its 2023 Quantitative Biology Fellows, three exceptional early-career scientists who are applying the tools of computational science to generate and interpret cancer research data at extraordinary scale and resolution. Whether constructing synthetic synapses to study cellular communication or engineering tumor models to predict treatment response, their projects seek to extend the boundaries of what is possible in cancer research by approaching fundamental biology questions from a new direction.

P53, the most frequently mutated gene across all human cancers, is mutated in the majority of pancreatic cancers. But despite the overwhelming evidence that p53 mutations contribute to cancer progression, therapies targeting mutant p53 have had limited success, suggesting an incomplete understanding of the protein’s function. In order to understand what goes wrong when p53 mutates, researchers need a clearer picture of how normal p53 prevents tumor development in the first place.

Damon Runyon scientists and industry partners gathered in person on Thursday, March 9 for the 2023 Accelerating Cancer Cures Symposium, hosted by Amgen at their new campus in South San Francisco.

Human papillomavirus (HPV) was first identified as a cancer driver in the 1970s, when a German doctor named Harald zur Hausen discovered that the virus causes about 75% of human cervical cancers. HPV has since been linked to several other types of human cancer, including head and neck cancer, as discovered by then-Damon Runyon Clinical Investigator Maura L. Gillison, MD, PhD, in 2000.

Cancer cells are often assumed to be “hypermetabolic,” meaning their energy-producing cycles run on overdrive to fuel the uncontrolled division and growth that defines a tumor. But new findings from former Damon Runyon Fellow Caroline R. Bartman, PhD, and her colleagues at Princeton University challenge this assumption, revealing how much we still have to learn about cancer metabolism.

The process of transcription, in which DNA is copied into RNA, is carried out by a complex cellular machinery that controls which genes are expressed as proteins. Researchers have observed certain organizational features of this machinery, such as the clumping of certain proteins into “condensates,” which function as a unit though unbound by a membrane.

Messenger RNA conveys instructions for how to build a protein in the form of codons—sequences of three nucleotides (A, C, G, or U) that correspond to a specific amino acid. The codons CGU, CGC, and CGA, for example, all correspond to the amino acid arginine. During the process of translation, ribosomes move along the messenger RNA, “reading” out the codons and building a chain of amino acids as translational RNAs (tRNAs) deliver them one by one.