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Immunotherapies to treat pancreatic cancer—a disease with a nearly 90 percent mortality rate—have been the subject of intensive research efforts in recent years, largely because they have succeeded where other treatment approaches have failed. New developments in mRNA vaccines, immune-enhancing therapies, and combination immunotherapy-chemotherapy regimens have marked a new era in pancreatic cancer treatment. But still, for many patients, nothing seems to work.
Just as the study of a growing plant or animal must take into account its environment, cancer researchers must look beyond a tumor to understand how the surrounding tissue impacts its development. In the case of gliomas, the most common and aggressive type of brain tumor, this means looking at neurons—what signals they emit, and how these signals may play a role in brain tumor progression.
A recent study by former Damon Runyon-Sohn Fellow Kathryn R. Taylor, PhD, and her colleagues at Stanford University sheds new light on these questions.
Renal cell carcinoma ranks among the top ten most common cancers globally, with the clear cell subtype (ccRCC) accounting for the majority of metastatic cases. While some ccRCC tumors respond to immunotherapy treatment, it is often difficult to predict which patients will benefit. But those who do likely have something else in common—which is why, as with many problems involving pattern recognition, researchers are turning to artificial intelligence (AI) to help them figure out what this “something” is.
Only about one percent of the human genome contains what we recognize as protein-coding genes: DNA sequences that are transcribed into RNA sequences and then translated into proteins. Much of the intervening space between genes consists of mobile DNA sequences, known as transposable elements, which have the ability to “copy and paste” themselves throughout the genome.
Metastatic pancreatic cancer is often resistant to chemotherapy-based treatments, and clinicians do not currently have a good way to predict whether a patient’s cancer will respond or not. At the Abramson Cancer Center of the University of Pennsylvania, former Damon Runyon-Rachleff Innovator Gregory L. Beatty, MD, PhD, and his colleagues are seeking to uncover the factors that determine response so that patients and clinicians can make better informed treatment decisions.
Ductal carcinoma in situ (DCIS), a non-invasive form of breast cancer found in the milk ducts, is a precursor to invasive breast cancer, but until recently, its progression has remained enigmatic. This is partly because standard methods of preserving tissue—as formalin-fixed paraffin-embedded (FFPE) samples—have made single-cell genetic analysis difficult.
More than 90% of the world’s population has been infected with Epstein-Barr Virus (EBV), and for most people, the infection is mild and passes in childhood. But for some, the virus persists in the body and increases the risk of certain cancers, including lymphoma, leukemia, and head and neck cancer. How exactly EBV leads to cancer, however, has until now remained poorly understood.
A team of scientists at Yale University School of Medicine, led by former Damon Runyon Innovator Jason M. Sheltzer, PhD, recently cracked a century-old scientific mystery: the role of aneuploidy, or abnormal chromosome number, in driving cancer. As far back as the 19th century, scientists looking under a microscope noticed that when cancer cells divide, the chromosomes sometimes split unequally, resulting in two aneuploid daughter cells.
Glioblastoma, the most common and aggressive form of brain cancer, is notoriously difficult to treat. Once arisen, the tumor rapidly invades healthy brain tissue, making removal by surgery nearly impossible and chemotherapy or radiation therapy success short-lived. Even immunotherapy drugs, increasingly relied upon when first lines of treatment fail, have proven ineffective, leaving glioblastoma patients with very few options. But this may change soon.
In 2018, the Foundation for the National Institutes of Health (FNIH) established the FNIH Trailblazer Prize for Clinician-Scientists to recognize “the outstanding contributions of early career clinician-scientists” whose research “translates basic scientific observations into new paradigm-shifting approaches for diagnosing, preventing, treating or curing disease.”