Patients with ovarian cancer have a 92% five-year survival rate if they are diagnosed at stage I. But a lack of effective screening methods and absence of symptoms in its early stages makes ovarian cancer particularly difficult to catch before it spreads. Patients and clinicians need a kind of internal alarm system, a device that can detect and communicate the presence of cancer cells in the body before they have a chance to inflict damage.

Messenger RNA (mRNA) vaccines have been shown to elicit immunity against a number of infectious diseases—including, notably, COVID-19—as well as several types of cancer. Unlike traditional vaccines, which introduce a small amount of the pathogen into the body, mRNA vaccines provide the body with instructions for how to make a specific protein found on the surface of a virus or cancer cell. Once the vaccine is delivered, molecular machines called ribosomes bind to the mRNA, “read” its instructions, and build the protein. This, in turn, prompts the immune system to produce the corresponding antibodies, so that it is ready when it encounters the real virus or cancer cell. Importantly, the mRNA molecules that contain these protein-making instructions are broken down by the cell after they have delivered their “message.”

The rise of single-cell RNA sequencing in recent years has transformed the study of gene expression, providing researchers with a detailed picture of how and when genes get turned “on” and “off” in individual cells within a given tissue. Analyzing cells’ RNA sequences, or transcriptomes, can reveal cell-to-cell variability, or in the case of cancer, mutations carried by small populations of tumor cells. Current single-cell sequencing methods, however, fail to capture the location of the cell within the tissue. Spatial transcriptomics techniques, on the other hand, define the spatial distribution of RNA molecules within a tissue sample, but lack single-cell resolution. To put this on a human scale, consider the different information you get about a neighborhood from a phone book versus a satellite image.

Damon Runyon has announced its newest cohort of 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 measuring cell-to-cell genetic variability within a tumor or developing algorithms that can predict if therapy will be effective, their projects extend the boundaries of what is possible in cancer research, allowing them to tackle fundamental biological and clinical questions.

For many patients with colon cancer, the advent of immune checkpoint inhibitors has substantially improved their treatment options. Immune checkpoint inhibitors (ICIs) work by removing the “brakes” from immune T cells, unleashing them on cancer cells. Unfortunately, however, ICIs do not work for everyone, and they can have life-threatening side effects for some patients. Given these factors, ICIs should only be used in patients who have the potential to benefit from them—the problem is, clinicians are often unable to predict who those patients will be.

CAR (chimeric antigen receptor) T cell therapy, in which a patient’s own immune cells are genetically engineered to target and kill cancer cells, has revolutionized the treatment of certain blood cancers. However, up to 60% of patients receiving CAR T therapy still experience relapse and up to 80% of patients experience serious side effects, including neuroinflammation—both of which present an obstacle to CAR T therapy’s widespread adoption.

Many blood cancers, including leukemia and multiple myeloma, arise when early blood-forming cells do not develop properly. Mistakes in cell differentiation—the process of maturing from a stem cell into a specialized cell type—can cause these abnormal blood cells to grow and divide uncontrollably. But exactly what goes wrong (and why) in the course of cell development is often difficult to determine after the tumor has already grown.

For the past 15 years, a group of researchers at the University of Illinois at Urbana-Champaign has been developing chemical building blocks for the synthesis of organic (carbon-based) small molecules. These building blocks, called MIDA boronates, snap together like puzzle pieces and can be assembled into a range of products, from manufacturing materials to food ingredients. The team even created a molecule-building machine to automate the process. As versatile as MIDA boronates are, however, they are much more stable in flat molecules than in 3D space. To advance in the world of chemical synthesis, scientists need Legos, not puzzle pieces.

New research indicates that hyaluronic acid (HA), a sugar-based compound naturally produced by the body and a popular ingredient in skincare products, also plays a role in fueling pancreatic cancer growth. Former Damon Runyon Fellow and Breakthrough Scientist Costas A. Lyssiotis, PhD, at the University of Michigan explains this finding in a recent paper published in eLife.

Translocation renal cell carcinoma (tRCC) is a rare but aggressive type of kidney cancer that disproportionately affects women and children. These cancers arise when part of a chromosome breaks off and fuses to a different chromosome, an event known as translocation. In tRCC, the fusion occurs between genes in the MiT/TFE family, which code for proteins called transcription factors that turn other genes on or off. Beyond this, however, the molecular basis of the disease is poorly understood. Due to this cancer’s rarity, doctors have an incomplete picture of its clinical features and no established standard of care. As a result, patients with tRCC are treated with therapies developed for other kidney cancers, with uneven success.