040 - Identifying Biomarkers and Pathways Associated with Medulloblastoma: A Meta-Analysis

Publication Number: 40.5251

Kevin Le, University of Central Florida College of Medicine, Orlando, FL, United States; Sarah Voskamp, University of Central Florida College of Medicine, Orlando, FL, United States; Vedic Sharma, University of Central Florida College of Medicine, Sanford, FL, United States; Jennifer S. Nelson, University of Central Florida College of Medicine, Orlando, FL, United States

Background: Medulloblastoma is the second most common malignant brain tumor in children. Although the cause of medulloblastoma is unclear, recent advancements regarding the pathogenesis of the disease due to epigenetic abnormalities have contributed to treatment guidelines that traditionally emphasized the extent of disease, tumor resection margins, and age of onset. Specifically, the WHO classification system outlines 4 molecularly distinct groups: WNT-activated, SHH-activated tumors ±TP53 mutation, and non-WNT/non-SHH group 3 and 4 tumors.

Objective: As there are concerns for long term sequelae of traditional treatment methods, this research will provide further insight into associated genetic markers that can be used for individualized therapy.

Design/Methods: The Search Tag Analyze Resource for NCBI’s Gene Expression Omnibus was utilized to identify and tag 98 medulloblastoma tumor samples and 38 healthy adult and pediatric cerebellum samples. Pathway analysis was conducted using Ingenuity Pathway Analysis and restricted to genes with a statistically significant difference (p < 0.05) between medulloblastoma and control and absolute experimental log ratio greater than 0.2, thus 4139 genes were included for analysis.

Results: Genes showing differential expression between medulloblastoma and control include genes previously described in the context of medulloblastoma such as SOX11, TBR1, VSNL1, PVALB as well as novel gene targets such as LHX2, UBE2C and HEPACAM. The top canonical pathways associated with medulloblastoma are cell cycle checkpoints, synaptogenesis signaling pathway, mitotic metaphase and anaphase, glutaminergic receptor signaling pathway, and mitotic prometaphase. The top upstream regulators are beta-estradiol, HTT, TGFB1, TP53, and TBX3, and the predicted causal networks include SOX2, VIRMA, DNMT3A, AGR2, and CUL7. Some of the top diseases and biological functions predicted as activated with medulloblastoma based on the differential genetic expression are motor dysfunction or movement disorder, cell proliferation of tumor cell lines, and seizure disorders, whereas the top predicted as inhibited are coordination, misalignment of chromosomes, and abnormal morphology of the nucleus.

Conclusion(s): Uncovering pathways and regulators associated with medulloblastoma assists in revealing the pathogenesis of disease and the alterations in physiology occurring in these children. Identifying target genes is the first step in discovering biomarkers for screening, prognosis predictions, and targeted treatment.

Figure 1
Synaptogenesis Signaling Pathway: One of the top canonical pathways predicted as inhibited in medulloblastoma samples compared to control, z-score = -6.304. Green = upregulated, red = downregulated, orange = predicted activation, blue = predicted inhibition.

Figure 2
Top canonical pathways showing predicted activation (orange) or inhibition (blue) based on gene expression in medulloblastoma samples versus control samples. Increasing bubble size indicates greater number of overlapping genes between the dataset and the canonical pathway.

Figure 3
Downstream effects of upstream regulator TP53. TP53 is predicted as inhibited, indicated by the blue color and z-score of -2.803. Genes from the top up and downregulated list that are impacted by inhibition of TP53 are shown.