Identification of a multidimensional transcriptome signature predicting tumor regrowth of clinically non‑functioning pituitary adenoma

Cheng,Sen; Guo,Jing; Zhang,Yazhuo; Li,Zhenye; Li,Chuzhong

doi:10.3892/ijo.2020.5087

Identification of a multidimensional transcriptome signature predicting tumor regrowth of clinically non‑functioning pituitary adenoma

Authors:
- Sen Cheng
- Jing Guo
- Yazhuo Zhang
- Zhenye Li
- Chuzhong Li
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Affiliations: Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, P.R. China, Beijing Neurosurgical Institute, Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing Institute for Brain Disorders Brain Tumor Center, China National Clinical Research Center for Neurological Diseases, Key Laboratory of Central Nervous System Injury Research, Beijing 100070, P.R. China, Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing Neurosurgical Institute, Beijing 100070, P.R. China
Published online on: June 23, 2020 https://doi.org/10.3892/ijo.2020.5087
Pages: 804-812

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Abstract

Clinically non‑functioning pituitary adenoma (NFPA) represents approximately one third of all pituitary adenomas. Tumor regrowth is an important feature of NFPA; however, the effective methods with which to predict this are limited. The present study analyzed the expression of protein‑coding genes and long non‑coding RNA in 66 patients with NFPA. Cox regression analysis was performed to identify genes associated with regrowth or progression‑free survival (PFS). Kaplan‑Meier, random survival forest analysis and receiver operating characteristic curve (ROC) analyses were performed to generate a multi‑protein‑coding gene (PCG) and long non‑coding RNA (lncRNA) signature with a maximum area under the ROC curve (AUC). In total, 1 PCG (CHST12) and 2 lncRNAs (COA6‑AS1 and RP11‑23N2.4) were identified that were significantly associated with tumor regrowth. The multi‑transcriptome signature exhibited a high predictive accuracy for tumor regrowth, with an AUC of 0.869/0.726 in the training/testing set, and the discriminative power of this signature was better than that of age. On the whole, the present study indicates that the combined PCG and lncRNA signature may be beneficial as a marker for the prediction of the prognosis of patients with NFPA.

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