TERT promoter mutations are commonly associated with 1p/19q codeletion in IDH-mutated gliomas. However, whether these mutations have an impact on patient survival independent of 1p/19q codeletion is unknown. In this study, we investigated the impact of TERT promoter mutations on survival in IDH-mutated glioma cases. Detailed clinical information and molecular status data were collected for a cohort of 560 adult patients with IDH-mutated gliomas. Among these patients, 279 had both TERT promoter mutation and 1p/19q codeletion, while 30 had either TERT promoter mutation (n = 24) or 1p/19q codeletion (n = 6) alone. A univariable Cox proportional hazard analysis for survival using clinical and genetic factors indicated that a Karnofsky performance status score (KPS) of 90 or 100, WHO grade II or III, TERT promoter mutation, 1p/19q codeletion, radiation therapy, and extent of resection (90–100%) were associated with favorable prognosis (p < 0.05). A multivariable Cox regression model revealed that TERT promoter mutation had a significantly favorable prognostic impact (hazard ratio = 0.421, p = 0.049), while 1p/19q codeletion did not have a significant impact (hazard ratio = 0.648, p = 0.349). Analyses incorporating patient clinical and genetic information were further conducted to identify subgroups showing the favorable prognostic impact of TERT promoter mutation. Among the grade II-III glioma patients with a KPS score of 90 or 100, those with IDH-TERT co-mutation and intact 1p/19q (n = 17) showed significantly longer survival than those with IDH mutation, wild-type TERT, and intact 1p/19q (n = 185) (5-year overall survival, 94% and 77%, respectively; p = 0.032). Our results demonstrate that TERT promoter mutation predicts favorable prognosis independent of 1p/19q codeletion in IDH-mutated gliomas. Combined with its adverse effect on survival among IDH-wild glioma cases, the bivalent prognostic impact of TERT promoter mutation may help further refine the molecular diagnosis and prognostication of diffuse gliomas.

Background: Noninvasive detection of early stage cancers with accurate prediction of tumor tissue-of-origin could improve patient prognosis. Because miRNA profiles differ between organs, circulating miRNomics represent a promising method for early detection of cancers, but this has not been shown conclusively. Methods: A serum miRNA profile (miRNomes)–based classifier was evaluated for its ability to discriminate cancer types using advanced machine learning. The training set comprised 7931 serum samples from patients with 13 types of solid cancers and 5013 noncancer samples. The validation set consisted of 1990 cancer and 1256 noncancer samples. The contribution of each miRNA to the cancer-type classification was evaluated, and those with a high contribution were identified. Results: Cancer type was predicted with an accuracy of 0.88 (95% confidence interval [CI] = 0.87 to 0.90) in all stages and an accuracy of 0.90 (95% CI = 0.88 to 0.91) in resectable stages (stages 0-II). The F1 score for the discrimination of the 13 cancer types was 0.93. Optimal classification performance was achieved with at least 100 miRNAs that contributed the strongest to accurate prediction of cancer type. Assessment of tissue expression patterns of these miRNAs suggested that miRNAs secreted from the tumor environment could be used to establish cancer type–specific serum miRNomes. Conclusions: This study demonstrates that large-scale serum miRNomics in combination with machine learning could lead to the development of a blood-based cancer classification system. Further investigations of the regulating mechanisms of the miRNAs that contributed strongly to accurate prediction of cancer type could pave the way for the clinical use of circulating miRNA diagnostics.

BACKGROUND: Glioblastoma (GBM) is a rapidly growing and most life-threatening malignant brain tumor. The significance of early treatment to the clinical outcomes of patients with GBM is unclear. OBJECTIVE: To determine whether early diagnosis and surgery improve the preoperative and postoperative Karnofsky performance status (KPS) and prognosis of patients with GBM. METHODS: Data of isocitrate dehydrogenase-wildtype patients with GBM treated at our institution between January 2010 and December 2019 were reviewed. Patients were classified into early or late diagnosis groups with a threshold of 14 days from initial symptoms. In addition, patients were divided into early, intermediate, and late surgery groups with thresholds of 21 and 35 days. Representative symptoms and patient prognoses were examined. RESULTS: Of 153 patients, 72 and 81 were classified into the early and late diagnosis groups. The median tumor volume was significantly smaller in the former group. The proportion of patients with preoperative KPS scores 90 was 48.6% and 29.6% in the early and late diagnosis groups (P = .016). The early, intermediate, and late surgery groups included 43, 24, and 86 patients. The median overall survival was significantly longer in the early surgery group than in the late surgery group (28.4 vs 18.7 months, P = .006). Multivariate analysis demonstrated that significant predictors of shorter survival included extent of tumor resection (partial or biopsy), preoperative and postoperative KPS 60, and O6-methylguanine-DNA-methyltransferase promoter status (unmethylated). CONCLUSION: Early diagnosis within 2 weeks and surgical interventions within 3 weeks from the symptom onset are associated with prolonged patient survival. Early GBM treatment will benefit patients with GBM.