By now, the immunotherapeutic approach to fighting cancer has become so popular that you’ve most probably already heard of it—we’ve discussed it a few times too. While immunotherapy is currently one of the best weapons in our anticancer arsenal, it is not always effective; however, researchers at Zurich University have recently found a way to predict whether immunotherapy will be successful in a given patient [1].
Crash course on immunotherapy
In case you are not familiar with the concept of immunotherapy, it basically consists in priming the immune system to fight cancer cells. You might think that your immune cells and antibodies only deal with external pathogens to fight off infections, but their routine duties also include eliminating cancer cells; indeed, the decline of the immune system with age is a contributing factor to the higher incidence of cancer in the elderly.
Unfortunately, albeit astoundingly complex, our immune system is not perfect, and as it is, it will not prevent all cancers from manifesting. Additionally, cancer is an insidious enemy with the force of evolution on its side, and thus cancer cells sometimes find ways to elude immune surveillance and spread. The goal of immunotherapy is to enhance the immune system’s ability to fight cancer and other diseases, offering a more effective and safe alternative to current therapeutic approaches.
Predicting immunotherapy outcomes
While immunotherapy works so well that it can seek and destroy even metastasized cancer cells (that is, cancer cells that have spread to tissues apart from where they originated), and, in some cases, even fully cure patients, not every patient responds to immunotherapy equally well. In fact, up to half of cancer patients don’t respond to immunotherapy, and to add insult to injury, they suffer from its side effects, which may include nausea, fever, and muscle and joint aches and may be more or less severe.
Side effects and the disappointment of failures aside, patients who don’t respond to immunotherapy—or any other cancer treatment, for that matter—have bigger problems to worry about; namely, they haven’t got any time to spend undergoing treatments that don’t deliver. For this reason, being able to tell beforehand if a patient is likely to benefit from immunotherapy would be an edge, and the authors of today’s study may have found a way to do just that.
The method in a nutshell
Put simply, the researchers here have identified a biomarker that serves as a strong predictor of progression-free and overall survival in patients undergoing a specific kind of immunotherapy that’s especially effective against metastatic melanomas—namely, anti-PD-1 immunotherapy, which involves the inhibition of programmed cell death protein 1 (PD-1).
Using a technique called high-dimensional single-cell mass cytometry, the researchers analyzed immune cells from blood samples of stage-IV melanoma patients both before they received the anti-PD-1 treatment and after 12 weeks of it. Blood samples of patients who eventually responded positively to immunotherapy exhibited a different immune signature to that of nonresponders: the frequency of classical CD14+CD16−CD33+HLA-DRhi monocytes—that is, white blood cells exhibiting that particular sequence of surface receptors. The authors of the paper thus suggest that this particular biomarker may be a reliable predictor of patients’ likelihood to respond to anti-PD-1 immunotherapy.
Conclusion
Studies of this kind may take us a step forward to an age of precision medicine—an age when treatments can be specifically tailored for each patient, knowing beforehand what will work and what won’t—but as always, we need to be cautious and wait for further developments. This study was conducted on a fairly small cohort of 20 patients, and before this biomarker can become a standard tool for therapeutic assessment, larger, independent studies must be carried out.
Literature
[1] Krieg C., Nowicka M., Guglietta S., Schindler S., Hartmann F. J, Weber L. M, Dummer R, Robinson M. D, Levesque M. P & Becher B.. High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy. Nature Medicine, 8 January 2018.
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