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Mutant‑allele tumor heterogeneity in malignant glioma effectively predicts neoplastic recurrence

  • Authors:
    • Pengfei Wu
    • Wei Yang
    • Jianxing Ma
    • Jingyu Zhang
    • Maojun Liao
    • Lunshan Xu
    • Minhui Xu
    • Liang Yi

  • View Affiliations

  • Published online on: October 11, 2019     https://doi.org/10.3892/ol.2019.10978
  • Pages: 6108-6116

  • Copyright: © Wu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Intra‑tumor heterogeneity (ITH) is one of the most important causes of therapy resistance, which eventually leads to the poor outcomes observed in patients with glioma. Mutant‑allele tumor heterogeneity (MATH) values are based on whole‑exon sequencing and precisely reflect genetic ITH. However, the significance of MATH values in predicting glioma recurrence remains unclear. Information of patients with glioma was obtained from The Cancer Genome Atlas database. The present study calculated the MATH value for each patient, analyzed the distributions of MATH values in different subtypes and investigated the rates of clinical recurrence in patients with different MATH values. Gene enrichment and Cox regression analyses were performed to determine which factors influenced recurrence. A nomogram table was established to predict 1‑, 2‑ and 5‑year recurrence probabilities. MATH values were increased in patients with glioma with the wild‑type isocitrate dehydrogenase (NADP(+)) (IDH)1/2 (IDH‑wt) gene (P=0.001) and glioblastoma (GBM; P=0.001). MATH values were negatively associated with the 2‑ and 5‑year recurrence‑free survival (RFS) rates in patients with glioma, particularly in the IDH1/2‑wt and GBM cohorts (P=0.001 and P=0.017, respectively). Furthermore, glioma cases with different MATH levels had distinct patterns of gene mutation frequencies and gene expression enrichment. Finally, a nomogram table that contained MATH values could be used to accurately predict the probabilities of the 1‑, 2‑ and 5‑year RFS of patients with glioma. In conclusion, the MATH value of a patient may be an independent predictor that influences glioma recurrence. The nomogram model presented in the current study was an appropriate method to predict 1‑, 2‑ and 5‑year RFS probabilities in patients with glioma.
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December-2019
Volume 18 Issue 6

Print ISSN: 1792-1074
Online ISSN:1792-1082

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Spandidos Publications style
Wu P, Yang W, Ma J, Zhang J, Liao M, Xu L, Xu M and Yi L: Mutant‑allele tumor heterogeneity in malignant glioma effectively predicts neoplastic recurrence. Oncol Lett 18: 6108-6116, 2019.
APA
Wu, P., Yang, W., Ma, J., Zhang, J., Liao, M., Xu, L. ... Yi, L. (2019). Mutant‑allele tumor heterogeneity in malignant glioma effectively predicts neoplastic recurrence. Oncology Letters, 18, 6108-6116. https://doi.org/10.3892/ol.2019.10978
MLA
Wu, P., Yang, W., Ma, J., Zhang, J., Liao, M., Xu, L., Xu, M., Yi, L."Mutant‑allele tumor heterogeneity in malignant glioma effectively predicts neoplastic recurrence". Oncology Letters 18.6 (2019): 6108-6116.
Chicago
Wu, P., Yang, W., Ma, J., Zhang, J., Liao, M., Xu, L., Xu, M., Yi, L."Mutant‑allele tumor heterogeneity in malignant glioma effectively predicts neoplastic recurrence". Oncology Letters 18, no. 6 (2019): 6108-6116. https://doi.org/10.3892/ol.2019.10978