By Alexian Heynez, C2ST Intern, Waubonsee Community College

Cancer is definitely one of the scariest diagnoses someone can hear from their doctor. One of the major contributors to the fear around cancer treatment is our reliance on treatments like chemotherapy and invasive surgeries to treat tumor development, with no guarantee that it won’t come back. These procedures weigh heavily on our bodies because of their more general and indiscriminate approach, which is necessary due to the uniqueness of everyone’s cancer. 

Cancer is a mutation of your own cells, which makes it exceedingly difficult for your body to identify and for doctors to treat with targeted therapies. Your immune system’s inability to detect cancer cells and the uniqueness of the genetic material that makes up those cells mean we can’t treat it like any other virus and simply make a vaccine for it. Or can we? Join me in an exploration of Dr. Balachandran’s work on personalized mRNA-based cancer vaccines that could potentially be revolutionary in increasing treatment outcomes. 

Machine learning is on track to revolutionize gene sequencing technology by way of its ability to comb through our massive genomic data sets and identify points of interest for scientists. Not only has AI/Machine learning made these processes more affordable, but it has also increased the efficiency by an unprecedented amount. This has led to a flood of clinical trials worldwide, with scientists exploring this technology for several applications. One of those trials aims to identify which specific cancerous mutations are most likely to be recognized by your immune system so that doctors can prepare your body to fight back against cancer. Dr. Balachandran co-conducted a clinical study in 2017 that demonstrated some patients with pancreatic cancer had more intense immune system reactions that could recognize cancer cells through differentiating molecules, and remember to attack those cells for long periods of time.

 The study found that patients with these intense immune system reactions created cancer-specific immune attack cells called T-cells. These cells can recognize and bind to cancer proteins and serve as a long-term memory system by staying in the bloodstream, in some cases for decades after the tumors are removed. In an interview with Scientific American, Dr. Balachandran shares that he and his collaborators wondered if they could use the capabilities of machine learning to understand a single individual’s cancer and the most recognizable mutations to that person’s immune system. All in the hopes that they may equip the majority of patients who don’t have the same immune system response with it through a vaccine. 

The clinical trial revealed that 50% or 8/16 of patients developed the strong T-cell immune system reaction they were looking for, which means it has meaningful potential to do a lot of good. Although the study was quite small and met with limited success, they found that mRNA vaccines could be produced promptly and have the potential to improve treatment outcomes. The only way to find out is with more research, so make sure to stay tuned to C2ST’s pages for more information.

 

References:
Rojas, L. A., Sethna, Z., Soares, K. C., Olcese, C., Pang, N., Patterson, E., … Balachandran, V. P. (2023). Personalized RNA neoantigen vaccines stimulate T cells in pancreatic cancer. Nature, 618(7963), 144–150. https://doi.org/10.1038/s41586-023-06063-y

Gerety, R. M. (2025, November 18). Personalized mRNA vaccines will revolutionize cancer treatment—if funding cuts don’t doom them. Scientific American. https://www.scientificamerican.com/article/personalized-mrna-vaccines-will-revolutionize-cancer-treatment-if-federal/

Mittal, S., Jena, M. K., & Pathak, B. (2024). Machine learning empowered next generation DNA sequencing: Perspective and prospectus. Chemical Science, 15(31), 12169–12188. https://doi.org/10.1039/d4sc01714e