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ERIC recommendations for TP53 mutation analysis in chronic lymphocytic leukemia—2024 update

Malcikova, Jitka, Pavlova, Sarka, Baliakas, Panagiotis, Chatzikonstantinou, Thomas, Tausch, Eugen, Catherwood, Mark, Rossi, Davide, Soussi, Thierry, Tichy, Boris, Kater, Arnon P., Niemann, Carsten U., Davi, Frederic, Gaidano, Gianluca, Stilgenbauer, Stephan, Rosenquist, Richard, Stamatopoulos, Kostas, Ghia, Paolo, Pospisilova, Sarka·2024·Leukemia
DOI 10.1038/s41375-024-02267-x
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Abstract

In chronic lymphocytic leukemia (CLL), analysis of TP53 aberrations (deletion and/or mutation) is a crucial part of treatment decision-making algorithms. Technological and treatment advances have resulted in the need for an update of the last recommendations for TP53 analysis in CLL, published by ERIC, the European Research Initiative on CLL, in 2018. Based on the current knowledge of the relevance of low-burden TP53-mutated clones, a specific variant allele frequency (VAF) cut-off for reporting TP53 mutations is no longer recommended, but instead, the need for thorough method validation by the reporting laboratory is emphasized. The result of TP53 analyses should always be interpreted within the context of available laboratory and clinical information, treatment indication, and therapeutic options. Methodological aspects of introducing next-generation sequencing (NGS) in routine practice are discussed with a focus on reliable detection of low-burden clones. Furthermore, potential interpretation challenges are presented, and a simplified algorithm for the classification of TP53 variants in CLL is provided, representing a consensus based on previously published guidelines. Finally, the reporting requirements are highlighted, including a template for clinical reports of TP53 aberrations. These recommendations are intended to assist diagnosticians in the correct assessment of TP53 mutation status, but also physicians in the appropriate understanding of the lab reports, thus decreasing the risk of misinterpretation and incorrect management of patients in routine practice whilst also leading to improved stratification of patients with CLL in clinical trials.

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Cited by

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Metadata

Authors
Malcikova, J., Pavlova, S., Baliakas, P., Chatzikonstantinou, T., Tausch, E., Catherwood, M., Rossi, D., Soussi, T., Tichy, B., Kater, A. P., Niemann, C. U., Davi, F., Gaidano, G., Stilgenbauer, S., Rosenquist, R., Stamatopoulos, K., Ghia, P., & Pospisilova, S.
ORCID
Venue
Leukemia
Publisher
Springer Science and Business Media LLC
Published
2024-05-16
Volume
38
Issue
7
Pages
1455-1468
ISSN
  • 0887-6924
  • 1476-5551
DOI
10.1038/s41375-024-02267-x
Cited by
44
References
8
Language
en
Licence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: ERIC recommendations for TP53 mutation analysis in chronic lymphocytic leukemia—2024 update. https://app.cochat.ai/papers/10.1038/s41375-024-02267-x
The paper
Malcikova, J., Pavlova, S., Baliakas, P., Chatzikonstantinou, T., Tausch, E., Catherwood, M., Rossi, D., Soussi, T., Tichy, B., Kater, A. P., Niemann, C. U., Davi, F., Gaidano, G., Stilgenbauer, S., Rosenquist, R., Stamatopoulos, K., Ghia, P., & Pospisilova, S. (2024). ERIC recommendations for TP53 mutation analysis in chronic lymphocytic leukemia—2024 update. Leukemia. https://doi.org/10.1038/s41375-024-02267-x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.