Team CRISPRcode
CRISPR and Computational Strategies Against DIPG
Team Members: Mihika Darbha (Redmond HS, Redmond, WA)
Year: 2025-26 Coding Gene.us Challenge
Abstract
This project explores how CRISPR gene editing can help us better understand and potentially treat Diffuse Intrinsic Pontine Glioma (DIPG), an aggressive and often fatal pediatric brain tumor. Due to its location deep in the brainstem and specific genetic mutations, DIPG is extremely difficult to treat with current methods. We identify and analyze key genes that drive DIPG growth or serve as therapeutic targets, focusing on two categories: first, the core driver mutation in H3F3A, which codes for a histone protein controlling DNA packaging into chromatin, the H3K27M mutation disrupts this packaging and interferes with the repressive H3K27me3 tag, causing developmental genes that should stay silent to turn on and fuel tumor growth; second, cell-surface proteins IL13RA2, CD276, and B4GALNT1 (GD2), which are overexpressed on DIPG cells and explored as targets for immunotherapies. Students analyze real DNA sequences from public databases like NCBI using a Google Colab notebook with Python libraries including Biopython, Pandas, and Matplotlib to simulate CRISPR targeting by locating PAM sequences—the Protospacer Adjacent Motif (NGG), a short DNA sequence that acts as a recognition signal the CRISPR-Cas9 enzyme needs to bind and cut DNA identifying all possible guide RNA sites based on PAM locations, and visualizing accessibility by comparing targetable sites across the four genes to understand why some DIPG targets are more amenable to CRISPR than others. We also explore practical challenges like off-target effects and the ethical implications of editing genes in human cells, demonstrating how computational methods are essential tools driving cancer genetics research and therapy development.
