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The Impact of CACN1AE in Glioblastoma

Not scheduled
20m
Hampton University Student Center (Hampton University, Hampton, VA, United States)

Hampton University Student Center

Hampton University, Hampton, VA, United States

200 William R Harvey Way
Poster Presentation School of Science – Graduate Abstract Research Symposium

Description

Glioblastomas are one of the most aggressive and malignant types of brain cancers. Due to its severity, many modern therapies do not help its poor prognosis (Hanif et al.,2017). After the diagnosis of glioblastomas, the average prognosis is between 12 to 18 months for middle aged adults with varying differences by other age groups. The progression of glioblastoma, and many other cancers depend on a signaling pathway becoming dysregulated. Amongst this is calcium channel signaling, which aids in promoting excitability in neurotransmitters (Bootman, M. D., & Bultynck, G. 2020). Voltage Gated Calcium Channels help facilitate depolarization caused by calcium into neurons, which CACNA1E is a voltage gated calcium channel. CACNA1E is a multi-subunit complex that is involved in neural regulation of excitability patterns. This subunit has patterns that are specific to the subtypes in a glioblastoma, which ranges from mesenchymal to neural subtypes. This specific gene has not been explored in detail with respect to dysregulated mechanisms or characterization within glioblastoma.
An analysis of 422 glioblastoma patients was conducted using the Verhaak molecular subtypes to evaluate the CACNA1E expression. Mesenchymal, proneural, classical, neural, and unclassified were a part of the subtypes studied. The analysis included age, MGMT, methylation survival, and vital status. The expression of CACN1AE was low and survival ranged significantly based on subtype. The investigation showed a median age of 59 with a median survival of 383 days, and a high event of deaths (340). Cases with complete annotations were used, and any information that was missing was disclosed. CACNA1E shows different signatures depending on subtype; it has potential to be a leading biomarker for individualized risk assessment in brain cancer treatment. It also may play a role in a more accurate glioma prediction model.

Author

Chioma West (Hampton University)

Co-author

Dr Jermel Watkins (Hampton University)

Presentation materials

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