Next-Generation Sequencing Reveals a Diagnostic and Prognostic Role of the TP53 R273C Mutation in Lower-Grade, IDH-Mutant Astrocytomas

The current WHO grading of central nervous system tumors relies exclusively on histopathological criteria for diagnosing lower-grade, IDH-mutant astrocytomas (LGIMAs), overlooking genetic features. The <i>TP53</i> R273C mutation, frequently observed in brain tumors, may influence LGIMA biology and aggressiveness. We analyzed 14 <i>TP53</i>-mutant LGIMAs using NGS. Five tumors (33.3%) carried the R273C mutation; these were mostly of grade 2 and all from female patients. Ki-67 levels in R273C-mutant tumors were higher compared with those in other <i>TP53</i>-mutant grade 2 tumors but lower than those in grade 3 tumors, which may suggest that R273C defines a more aggressive grade 2 profile. This mutation was linked to loss of the wild-type allele, supporting a loss-of-function mechanism. Its frequency was found to be potentially higher in women, and this sex-based difference reached statistical significance when incorporating TCGA LGIMA data. Overall, the R273C mutation, although mechanistically unclear, is more prevalent than other <i>TP53</i> variants and defines a distinct biological subset of LGIMAs, marked by increased Ki-67 and female predominance. Incorporating <i>TP53</i> and broader genetic profiling via NGS could improve our understanding of LGIMAs and support a refined classification system, enhancing diagnostic and prognostic accuracy.

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Journal
International Journal of Molecular Sciences
Published
2025-11-27
DOI
https://doi.org/10.3390/ijms262311483
Primary Topic
Glioma Diagnosis and Treatment
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article
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article

Next-Generation Sequencing Reveals a Diagnostic and Prognostic Role of the TP53 R273C Mutation in Lower-Grade, IDH-Mutant Astrocytomas

Esther Roselló-Sastre, Teresa San‐Miguel, Javier Megías, Lara Navarro et al.
International Journal of Molecular Sciences
Glioma Diagnosis and Treatment
article

Next-Generation Sequencing Reveals a Diagnostic and Prognostic Role of the TP53 R273C Mutation in Lower-Grade, IDH-Mutant Astrocytomas

Esther Roselló-Sastre, Teresa San‐Miguel, Javier Megías, Lara Navarro, Irene Salazar-Saura, Moisés Sánchez-Pardo
article en

Abstract

The current WHO grading of central nervous system tumors relies exclusively on histopathological criteria for diagnosing lower-grade, IDH-mutant astrocytomas (LGIMAs), overlooking genetic features. The <i>TP53</i> R273C mutation, frequently observed in brain tumors, may influence LGIMA biology and aggressiveness. We analyzed 14 <i>TP53</i>-mutant LGIMAs using NGS. Five tumors (33.3%) carried the R273C mutation; these were mostly of grade 2 and all from female patients. Ki-67 levels in R273C-mutant tumors were higher compared with those in other <i>TP53</i>-mutant grade 2 tumors but lower than those in grade 3 tumors, which may suggest that R273C defines a more aggressive grade 2 profile. This mutation was linked to loss of the wild-type allele, supporting a loss-of-function mechanism. Its frequency was found to be potentially higher in women, and this sex-based difference reached statistical significance when incorporating TCGA LGIMA data. Overall, the R273C mutation, although mechanistically unclear, is more prevalent than other <i>TP53</i> variants and defines a distinct biological subset of LGIMAs, marked by increased Ki-67 and female predominance. Incorporating <i>TP53</i> and broader genetic profiling via NGS could improve our understanding of LGIMAs and support a refined classification system, enhancing diagnostic and prognostic accuracy.

International Journal of Molecular SciencesVol. 26(23)
Universitat de València (ES), Hospital General Universitario De Valencia (ES), INCLIVA Health Research Institute (ES)
Openalex Percentile: Top 46%
Glioma Diagnosis and Treatment
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Next-Generation Sequencing Reveals a Diagnostic and Prognostic Role of the TP53 R273C Mutation in Lower-Grade, IDH-Mutant Astrocytomas — Esther Roselló-Sastre, Teresa San‐Miguel, et al. · International Journal of Molecular Sciences (2025) | TGRS Research Map | TGRS