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Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma
BACKGROUND: Uterine corpus endometrial carcinoma (UCEC) is a clinically heterogeneous disease, and this heterogeneity is associated with tumor development, clinical characteristics, and prognostic outcomes. Mutant-allele tumor heterogeneity (MATH) is a novel, non-biased, quantitative measure to asse...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186654/ https://www.ncbi.nlm.nih.gov/pubmed/32355783 http://dx.doi.org/10.21037/atm.2020.02.136 |
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author | Hou, Yufang Li, Tiegang Gan, Wenqiang Lv, Silin Zeng, Zifan Yan, Zheng Wang, Weiqi Yang, Min |
author_facet | Hou, Yufang Li, Tiegang Gan, Wenqiang Lv, Silin Zeng, Zifan Yan, Zheng Wang, Weiqi Yang, Min |
author_sort | Hou, Yufang |
collection | PubMed |
description | BACKGROUND: Uterine corpus endometrial carcinoma (UCEC) is a clinically heterogeneous disease, and this heterogeneity is associated with tumor development, clinical characteristics, and prognostic outcomes. Mutant-allele tumor heterogeneity (MATH) is a novel, non-biased, quantitative measure to assess intra-tumor heterogeneity based on next-generation sequencing data. We aimed to explore the use of MATH as a measure for tumor heterogeneity and its prognostic role in UCEC patients. METHODS: We calculated MATH scores from the available data of 560 UCEC patients from The Cancer Genome Atlas (TCGA) and investigated their correlations with clinical characteristics, genetic alterations, and overall survival. Predictive accuracy was quantified using the area under the receiver operating characteristic curve (AUC) and the index of concordance (C-index). RESULTS: In total, 242 MATH scores were obtained from the UCEC cohort. MATH scores were significantly related to age, race, cancer type, clinical stage, histological grade, molecular type, targeted molecular therapy, and hormonal therapy. Furthermore, the genomic pattern on the basis of MATH scores showed that mutation rates of TP53 (tumor protein p53) and ARID1A (AT-rich interaction domain 1A) were independently associated with MATH scores. Correlation analysis revealed a significantly positive association of MATH scores with the fraction of somatic copy number alteration (SCNA). Importantly, a high MATH score was significantly associated with shorter overall survival [hazard ratio (HR), 2.342; 95% confidence interval (CI), 1.110–4.942]. Multivariate Cox regression combined with stratified analysis revealed that the MATH score is an independent prognostic factor in UCEC patients under 60 years old, and predictive quantification showed the MATH score had an AUC of 0.756 and a C-index of 0.845. CONCLUSIONS: Our results suggest that MATH, a practical and useful way to measure intra-tumor heterogeneity, may serve as a significant biomarker for the prognosis of patients with UCEC, enabling more accurate prediction of clinical outcomes. |
format | Online Article Text |
id | pubmed-7186654 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-71866542020-04-30 Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma Hou, Yufang Li, Tiegang Gan, Wenqiang Lv, Silin Zeng, Zifan Yan, Zheng Wang, Weiqi Yang, Min Ann Transl Med Original Article BACKGROUND: Uterine corpus endometrial carcinoma (UCEC) is a clinically heterogeneous disease, and this heterogeneity is associated with tumor development, clinical characteristics, and prognostic outcomes. Mutant-allele tumor heterogeneity (MATH) is a novel, non-biased, quantitative measure to assess intra-tumor heterogeneity based on next-generation sequencing data. We aimed to explore the use of MATH as a measure for tumor heterogeneity and its prognostic role in UCEC patients. METHODS: We calculated MATH scores from the available data of 560 UCEC patients from The Cancer Genome Atlas (TCGA) and investigated their correlations with clinical characteristics, genetic alterations, and overall survival. Predictive accuracy was quantified using the area under the receiver operating characteristic curve (AUC) and the index of concordance (C-index). RESULTS: In total, 242 MATH scores were obtained from the UCEC cohort. MATH scores were significantly related to age, race, cancer type, clinical stage, histological grade, molecular type, targeted molecular therapy, and hormonal therapy. Furthermore, the genomic pattern on the basis of MATH scores showed that mutation rates of TP53 (tumor protein p53) and ARID1A (AT-rich interaction domain 1A) were independently associated with MATH scores. Correlation analysis revealed a significantly positive association of MATH scores with the fraction of somatic copy number alteration (SCNA). Importantly, a high MATH score was significantly associated with shorter overall survival [hazard ratio (HR), 2.342; 95% confidence interval (CI), 1.110–4.942]. Multivariate Cox regression combined with stratified analysis revealed that the MATH score is an independent prognostic factor in UCEC patients under 60 years old, and predictive quantification showed the MATH score had an AUC of 0.756 and a C-index of 0.845. CONCLUSIONS: Our results suggest that MATH, a practical and useful way to measure intra-tumor heterogeneity, may serve as a significant biomarker for the prognosis of patients with UCEC, enabling more accurate prediction of clinical outcomes. AME Publishing Company 2020-03 /pmc/articles/PMC7186654/ /pubmed/32355783 http://dx.doi.org/10.21037/atm.2020.02.136 Text en 2020 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Hou, Yufang Li, Tiegang Gan, Wenqiang Lv, Silin Zeng, Zifan Yan, Zheng Wang, Weiqi Yang, Min Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma |
title | Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma |
title_full | Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma |
title_fullStr | Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma |
title_full_unstemmed | Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma |
title_short | Prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma |
title_sort | prognostic significance of mutant-allele tumor heterogeneity in uterine corpus endometrial carcinoma |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186654/ https://www.ncbi.nlm.nih.gov/pubmed/32355783 http://dx.doi.org/10.21037/atm.2020.02.136 |
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