Oncotarget

Research Papers:

IDH1/2 mutation status combined with Ki-67 labeling index defines distinct prognostic groups in glioma

Ailiang Zeng, Qi Hu, Yanwei Liu, Zheng Wang, Xiaoming Cui, Rui Li, Wei Yan and Yongping You _

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Oncotarget. 2015; 6:30232-30238. https://doi.org/10.18632/oncotarget.4920

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Abstract

Ailiang Zeng1, Qi Hu1, Yanwei Liu2, Zheng Wang2, Xiaoming Cui1, Rui Li1, Wei Yan1, Yongping You1

1Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, PR China

2Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, PR China

Correspondence to:

Yongping You, e-mail: [email protected]

Wei Yan, e-mail: [email protected]

Keywords: IDH1/2 mutation, Ki-67 labeling index, prognosis, glioma, molecular classification

Received: March 24, 2015     Accepted: August 07, 2015     Published: August 18, 2015

ABSTRACT

The current World Health Organization (WHO) classification of human gliomas is mainly based on morphology. However, it has limitations in prognostic prediction. We examined whether combining isocitrate dehydrogenase (IDH) 1/2 mutation status with the Ki-67 labeling index would improve the definition of prognostically distinct entities. We investigated the correlation of Ki-67 expression with IDH1/2 mutation status and their impact on clinical outcome in 703 gliomas. Low Ki-67 expression closely overlapped with IDH1/2 mutation in our cohort (P < 0.0001). Patients with IDH1/2 mutation survived significantly longer than patients with wild-type IDH1/2 did (P < 0.0001); higher Ki-67 expression was associated with shorter progression-free survival and overall survival (OS) (P < 0.0001). IDH1/2 combined with Ki-67 was used to re-classify glioma patients into five groups. IDH1/2 mutant patients with low and moderate Ki-67 expression (Group1) had the best prognosis, whereas patients with wild-type IDH1/2 and high Ki-67 expression (Group5) had the worst prognosis (Median OS = 1527 vs. 355 days, P < 0.0001). To summarize, our new classification model distinguishes biologically distinct subgroups and provides prognostic information regardless of the conventional WHO grade. Classification based on IDH1/2 mutation status and Ki-67 expression level could be more convenient for clinical application and guide personalized treatment in malignant gliomas.


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