As cancer cells evolve in response to treatment or other environmental pressures, a patient may end up with a highly diverse population of cancer cells circulating throughout their body. In these cases, a single biopsy from the tissue where the cancer originated is not enough to fully understand the cancer’s genome or how best to target it. Liquid biopsies are thus increasingly used to study circulating tumor cells (CTCs) in the blood, with single-cell CTC sequencing emerging as the next step in unraveling the mysteries of disease progression and treatment response.

One way to determine how successfully a patient’s cancer treatment has eradicated the disease is to check the bloodstream for free-floating DNA originating from tumor cells, also known as circulating tumor DNA (ctDNA). The detection of ctDNA can serve as a powerful prognostic tool, allowing clinicians to assess the effectiveness of treatment and predict the likelihood of disease recurrence.

Researchers at Stanford University have discovered sugar-bound RNA strands protruding from the cell surface, challenging the long-held assumption that these two types of molecules are kept separate within the cell. These newfound “glycoRNAs,” identified by former Damon Runyon Fellow Ryan Flynn, MD, PhD, may serve an important role in immune signaling. A shock to biologists across disciplines, this finding has particular significance in the world of cancer research, as the development of effective immunotherapies hinges on our understanding of how the immune system is activated.

Immune checkpoint blockades are remarkably effective at exposing tumor cells to immune system attack, but only in the minority of patients with highly mutated tumors. While a high number of genetic mutations may seem like a bad thing, more mutations mean tumors produce more antigens, making them more recognizable to immune T-cells, and thus more susceptible to immunotherapy. In a groundbreaking report, Damon Runyon alumni Robert K. Bradley, PhD, and Omar Abdel-Wahab, MD, offer proof of concept that introducing errors in the short-lived RNA—rather than permanent DNA damage—still causes tumors to present antigens on their cell surface, stimulating immune response. The hope is that drugs that induce such RNA errors could be used in combination with checkpoint blockades to shrink therapy-resistant tumors.

Selection bias occurs when those chosen to participate in a study are not representative of the target population, limiting how much we can trust the study results. In order to quantify this selection bias, researchers have come up with a metric known as the diagnosis-to-treatment interval (DTI), which measures treatment urgency among trial participants. DTI, however, is not an ideal metric for selecting trial participants, as non-biological factors like access to medical care also influence the amount of time between diagnosis and treatment. Finding a biological basis for DTI would offer a more objective measure of clinical urgency, and thus be more useful in mitigating selection bias.