Vikas Patil1, Kulandaivelu Mahalingam2. 1. Department of Bio-Medical Sciences, School of Biosciences and Technology, VIT University, Vellore 632014, Tamil Nadu, India. 2. Department of Bio-Medical Sciences, School of Biosciences and Technology, VIT University, Vellore 632014, Tamil Nadu, India. Electronic address: kmahalingam@vit.ac.in.
Abstract
BACKGROUND: Glioma is a wide category of brain tumor originates from glial cells. Lower-Grade Glioma (LGG) consists of World Health Organization (WHO) grade II and grade III gliomas. Since the LGGs can infiltrate into adjacent areas, the complete removal of tumor is difficult and it results in recurrence and malignant progression to high grade glioma. Our study uncovers robust survival indicators in LGG which can be checked by immunohistochemistry to predict the outcome of lower grade. In addition, it unravelled the novel therapeutic targets in order to improve the survival of LGG patients. METHODS: To identify a prognostic signature based on protein expression in LGGs, we analysed Reverse Phase Protein Array data of LGG samples (n = 380) from The Cancer Genome Atlas cohort. We made random stratification of samples into discovery (n = 228) and validation datasets (n = 152). We performed multivariate Cox proportional hazards regression analysis of proteins (n = 219) using discovery dataset with age, WHO grade and IDH mutation status. RESULTS: We identified four-protein prognostic signature that can segregate patients into high- and low-risk. The signature estimates poor overall survival for high-risk patients in both discovery (hazard ratio [HR] = 4.11; 95% confidence interval [CI] = 2.18-7.75; p < 0.0001) and validation datasets (HR = 3.49; 95% CI = 1.52-8.01; p < 0.0001). Among the four markers, CHK2_pT68 was found to be protective, while MSH6, ARID1A and PAXILLIN were associated with poor survival. Additionally, Multivariate Cox proportional hazards regression analysis of this signature with age, WHO grade and IDH mutation status revealed this prognostic signature to be an independent prognosticator in both datasets. CONCLUSIONS: Our finding discovered a set of potential protein biomarkers to predict survival and it will help in the subsequent treatment management of LGG patients.
BACKGROUND:Glioma is a wide category of brain tumor originates from glial cells. Lower-Grade Glioma (LGG) consists of World Health Organization (WHO) grade II and grade III gliomas. Since the LGGs can infiltrate into adjacent areas, the complete removal of tumor is difficult and it results in recurrence and malignant progression to high grade glioma. Our study uncovers robust survival indicators in LGG which can be checked by immunohistochemistry to predict the outcome of lower grade. In addition, it unravelled the novel therapeutic targets in order to improve the survival of LGG patients. METHODS: To identify a prognostic signature based on protein expression in LGGs, we analysed Reverse Phase Protein Array data of LGG samples (n = 380) from The Cancer Genome Atlas cohort. We made random stratification of samples into discovery (n = 228) and validation datasets (n = 152). We performed multivariate Cox proportional hazards regression analysis of proteins (n = 219) using discovery dataset with age, WHO grade and IDH mutation status. RESULTS: We identified four-protein prognostic signature that can segregate patients into high- and low-risk. The signature estimates poor overall survival for high-risk patients in both discovery (hazard ratio [HR] = 4.11; 95% confidence interval [CI] = 2.18-7.75; p < 0.0001) and validation datasets (HR = 3.49; 95% CI = 1.52-8.01; p < 0.0001). Among the four markers, CHK2_pT68 was found to be protective, while MSH6, ARID1A and PAXILLIN were associated with poor survival. Additionally, Multivariate Cox proportional hazards regression analysis of this signature with age, WHO grade and IDH mutation status revealed this prognostic signature to be an independent prognosticator in both datasets. CONCLUSIONS: Our finding discovered a set of potential protein biomarkers to predict survival and it will help in the subsequent treatment management of LGG patients.