A Comparative Analysis of Chemotherapeutic Administrations in Inhibiting Glioblastoma Multiforme Cellular Growth Utilizing an Integration of Differentiation-Based Growth Models and Pharmacokinetic Equations

Anagha GowdaFollow

School Name

Spring Valley High School

Grade Level

11th Grade

Presentation Topic

Mathematics

Presentation Type

Non-Mentored

Abstract

Glioblastoma multiforme, a disease of grade IV astrocytoma, accounts for 60-70% of malignant brain tumors (D’Alessio et al., 2019). Despite its low survival rate, little is known about GBM and its treatment. The purpose of this study was to assess the comparative effectiveness of the most common drugs (temozolomide, carmustine, bevacizumab) in reducing tumor growth within GBM chemotherapy. It was hypothesized that due to their properties as alkylating agents inhibiting growth genes within GBM, temozolomide and carmustine would provide the most reduction in cellular growth mathematically (Thomas et al., 2013). VisualPDE simulations were used to model administration of temozolomide, carmustine, bevacizumab, and none in chemotherapy and provide the cellular GBM counts at any given time within five months (60 time points were used). Results showed cell growth reduction by temozolomide and carmustine, but most drastically by bevacizumab, and upon further analysis, a One-Way ANOVA yielded that the difference between at least two chemotherapeutic administrations were statistically significant (F(3, 236)=281.049, p<0.001). A post-hoc Tukey HSD test revealed a significant difference between no administration and each chemotherapeutic administration (TMZ: p<0.001, BCNU: p=0.046, BEV: p<0.001), as well as significant differences compared to bevacizumab, which was drastically more effective than TMZ and BCNU (p<0.001, p<0.001). Thus, it was concluded that BEV provided the optimal treatment in slowing GBM growth with the mathematical model through its ability to regulate proteins and drug resistance, allowing for its integration in future chemotherapy.

Location

RITA 367

Start Date

3-23-2024 11:00 AM

Presentation Format

Oral and Written

Group Project

No

COinS
 
Mar 23rd, 11:00 AM

A Comparative Analysis of Chemotherapeutic Administrations in Inhibiting Glioblastoma Multiforme Cellular Growth Utilizing an Integration of Differentiation-Based Growth Models and Pharmacokinetic Equations

RITA 367

Glioblastoma multiforme, a disease of grade IV astrocytoma, accounts for 60-70% of malignant brain tumors (D’Alessio et al., 2019). Despite its low survival rate, little is known about GBM and its treatment. The purpose of this study was to assess the comparative effectiveness of the most common drugs (temozolomide, carmustine, bevacizumab) in reducing tumor growth within GBM chemotherapy. It was hypothesized that due to their properties as alkylating agents inhibiting growth genes within GBM, temozolomide and carmustine would provide the most reduction in cellular growth mathematically (Thomas et al., 2013). VisualPDE simulations were used to model administration of temozolomide, carmustine, bevacizumab, and none in chemotherapy and provide the cellular GBM counts at any given time within five months (60 time points were used). Results showed cell growth reduction by temozolomide and carmustine, but most drastically by bevacizumab, and upon further analysis, a One-Way ANOVA yielded that the difference between at least two chemotherapeutic administrations were statistically significant (F(3, 236)=281.049, p<0.001). A post-hoc Tukey HSD test revealed a significant difference between no administration and each chemotherapeutic administration (TMZ: p<0.001, BCNU: p=0.046, BEV: p<0.001), as well as significant differences compared to bevacizumab, which was drastically more effective than TMZ and BCNU (p<0.001, p<0.001). Thus, it was concluded that BEV provided the optimal treatment in slowing GBM growth with the mathematical model through its ability to regulate proteins and drug resistance, allowing for its integration in future chemotherapy.