Two College of Idaho students earned top honors at a National Institutes of Health conference for their presentation of findings from their research into a fast-growing brain tumor. Ruby Olvera, a junior double majoring in biomedical science and business administration, and Colton Troxel, a junior majoring in biomedical science, were awarded the Best Undergraduate Student Oral Presentation at the 2025 Western Regional IDeA Conference in Anchorage, Alaska, in February. Their talk was titled “An Analysis of Glioblastoma Gene Expression Using Single-Cell RNA Sequencing.” The conference is held every two years. It brings together students and faculty from each of the Western states (Hawaii, Alaska, Idaho, Montana, Wyoming, Nevada, and New Mexico) in the National Institutes of Health-IDeA Networks of Biomedical Research Excellence. “They did a fantastic job explaining the project and fielding questions from the audience,” says Dr. Luke Daniels, professor of biology. “And, when they presented, talks weren’t divided by career stage. Rather, Ruby and Colton were in a session with graduate students and faculty. But I think the reason they got the award is that this is far and away not a typical project undergraduates would take on at most institutions –both the type of project and the combination of lab techniques and data science.” Previous research by Daniels provided the foundation for the students’ work. For the past decade, he has been studying glioblastoma (GBM),which has a five-year survival rate of only 5 percent. “One of the hard things about understanding how cancer grows and treating cancer is that tumor cells aren’t all identical,” he says. In the spring of 2024, Emily Freko, a senior majoring in biomedical science, embarked on a new project in the lab, preparing GBM cells for sequencing. She cultured cells in several different ways — a standard way used in most labs and another method that coaxes the cells into behaving like mini-tumors (so much so that cells grown in this way can be directly implanted into mice, where they form tumors). Prior to leaving for a highly competitive summer internship at Massachusetts Institute of Technology focused on biology and neuroscience, Freko sent the cells for sequencing, which paved the way for Olvera and Troxel to obtain the data necessary to launch their own project. Their project evaluated the differences between cells to get a sense of how different the tumor cells are from each other and in what ways. They did this by looking at which genes were turned on and off in each
of about 10,000 cells. To do this, they had to sequence the mRNA that is expressed in each of the 10,000 cells, which resulted in more than 100 million individual sequences. “This amount of data becomes tricky to deal with pretty quickly,” says Daniels, “so the only way to make sense of it is through large-scale data analysis techniques, such as machine learning, which required Ruby and Colton to learn the programming language R.” Using machine learning, Olvera and Troxel generated results that contribute to a better understanding of gene expression in GL261 cells and suggest candidate genes that may be responsible for glioma tumor formation.