Abstract

Abstract Medulloblastoma is the most common malignant brain tumor found in children. It is a cerebellar tumor that affects motor and cognitive processes such as coordination and movement. The standard of care is surgical removal, radiation, and chemotherapy. These treatments can be very damaging to the developing child, in that they can impair vision and walking, among other body functions. Due to this, new treatments are necessary. Treatment plans for children with medulloblastoma need to be tailored to the specific subtype that they have. Genetic studies have revealed that there are four subtypes of pediatric medulloblastoma: Group 3, Group 4, SHH, and WNT. Beyond these bulk-resolution subtypes, we hypothesize intratumor heterogeneity as a barrier to new effective treatments. I have mined single-cell RNA sequencing data to investigate cellular heterogeneity and predict compound response. I analyzed Medulloblastoma patient tumor data along with data obtained from a 10X Genomics Chromium single-cell RNA sequencing experiment performed in the laboratory from a Tg (Neurod-Smoothened*A1) mouse. We hypothesize that distinct cell populations within medulloblastoma should show different predicted compounds that would target them. We have ranked compound predictions to investigate whether compounds may selectively target any of these populations using transcriptional response signatures derived from the LINCS L1000 perturbagen-response dataset. We also hypothesize that Medulloblastoma tumors have distinct subtypes of cells that are preferentially sensitive to BET bromodomain, casein kinase, and ATM/ATR inhibitors. Our analysis identified ten transcriptionally distinct cell types across these medulloblastoma tumors as well as compounds predicted to target them in each transcriptional subtype. Furthermore, we identified bromodomain and casein kinase inhibitors as a potential combination therapy due to their predicted synergy at targeting all cell populations within medulloblastoma. Our studies show the importance of considering cellular heterogeneity when identifying new treatments for medulloblastoma and other brain cancers.

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