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Landscape of TP53 Alterations in Chronic Lymphocytic Leukemia via Data Mining Mutation Databases

Soussi, Thierry, Baliakas, Panagiotis·2022·Frontiers in Oncology
DOI 10.3389/fonc.2022.808886
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Abstract

Locus-specific databases are invaluable tools for both basic and clinical research. The extensive information they contain is gathered from the literature and manually curated by experts. Cancer genome sequencing projects generate an immense amount of data, which are stored directly in large repositories (cancer genome databases). The presence of a TP53 defect (17p deletion and/or TP53 mutations) is an independent prognostic factor in chronic lymphocytic leukemia (CLL) and TP53 status analysis has been adopted in routine clinical practice. For that reason, TP53 mutation databases have become essential for the validation of the plethora of TP53 variants detected in tumor samples. TP53 profiles in CLL are characterized by a great number of subclonal TP53 mutations with low variant allelic frequencies and the presence of multiple minor subclones harboring different TP53 mutations. In this review, we describe the various characteristics of the multiple levels of heterogeneity of TP53 variants in CLL through the analysis of TP53 mutation databases and the utility of their diagnosis in the clinic.

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Metadata

Authors
Soussi, T., & Baliakas, P.
Venue
Frontiers in Oncology
Publisher
Frontiers Media SA
Published
2022-02-16
Volume
12
ISSN
2234-943X
DOI
10.3389/fonc.2022.808886
Cited by
17
References
7
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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CoChat. (2026). Citation check: Landscape of TP53 Alterations in Chronic Lymphocytic Leukemia via Data Mining Mutation Databases. https://app.cochat.ai/papers/10.3389/fonc.2022.808886
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Soussi, T., & Baliakas, P. (2022). Landscape of TP53 Alterations in Chronic Lymphocytic Leukemia via Data Mining Mutation Databases. Frontiers in Oncology. https://doi.org/10.3389/fonc.2022.808886

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