<scp>DNA</scp> methylation as a new tool for the differential diagnosis between T‐<scp>LBL</scp> and lymphocyte‐rich thymoma

T-lymphoblastic lymphoma (T-LBL) and thymoma are two rare primary tumors of the thymus deriving either from T-cell precursors or from thymic epithelial cells, respectively. Some thymoma subtypes (AB, B1, and B2) display numerous reactive terminal deoxynucleotidyl transferase-positive (TdT<sup>+</sup>) T-cell precursors masking epithelial tumor cells. Therefore, the differential diagnosis between T-LBL and TdT<sup>+</sup> T-lymphocyte-rich thymoma could be challenging, especially in the case of needle biopsy. To distinguish between T-LBL and thymoma-associated lymphoid proliferations, we analyzed the global DNA methylation using two different technologies, namely MeDIP array and EPIC array, in independent samples series [17 T-LBLs compared with one TdT<sup>+</sup> lymphocyte-rich thymoma (B1 subtype) and three normal thymi, and seven lymphocyte-rich thymomas compared with 24 T-LBLs, respectively]. In unsupervised principal component analysis (PCA), T-LBL and thymoma samples clustered separately. We identified differentially methylated regions (DMRs) using MeDIP-array and EPIC-array datasets and nine overlapping genes between the two datasets considering the top 100 DMRs including ZIC1, TSHZ2, CDC42BPB, RBM24, C10orf53, and MACROD2. In order to explore the DNA methylation profiles in larger series, we defined a classifier based on these six differentially methylated gene promoters, developed an MS-MLPA assay, and demonstrated a significant differential methylation between thymomas (hypomethylated; n = 48) and T-LBLs (hypermethylated; n = 54) (methylation ratio median 0.03 versus 0.66, respectively; p < 0.0001), with MACROD2 methylation status the most discriminating. Using a machine learning strategy, we built a prediction model trained with the EPIC-array dataset and defined a cumulative score taking into account the weight of each feature. A score above or equal to 0.4 was predictive of T-LBL and conversely. Applied to the MS-MLPA dataset, this prediction model accurately predicted diagnoses of T-LBL and thymoma. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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Publication Details

Journal
The Journal of Pathology
Published
2024-09-27
DOI
https://doi.org/10.1002/path.6346
Citations
5
Primary Topic
Myasthenia Gravis and Thymoma
Type
article
Field-Weighted Citation Impact
1.85

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article

DNA methylation as a new tool for the differential diagnosis between T‐LBL and lymphocyte‐rich thymoma

Vincent de Montpréville, Stéphane Jamain, Violaine Latapie, Cécile Badoual et al.
5 citations
The Journal of Pathology
Myasthenia Gravis and Thymoma
1.85
article

DNA methylation as a new tool for the differential diagnosis between T‐LBL and lymphocyte‐rich thymoma

Vincent de Montpréville, Stéphane Jamain, Violaine Latapie, Cécile Badoual, Nathalie Garnier, Christoph Plass, Aurore Touzart, Lara Chalabreysse, Benjamin Besse, Julie Bruneau, Mehdi Latiri, Alexander Marx, Mohamed Belhocine, Antoine Pinton, Charlotte Smith, Guillaume P. Andrieu, Estelle Balducci, Laure Gibault, Elizabeth Macintyre, Thierry Jo Molina, Nicolas M Girard, Salvatore Spicuglia, Vahid Asnafi
article en
5 citations

Abstract

T-lymphoblastic lymphoma (T-LBL) and thymoma are two rare primary tumors of the thymus deriving either from T-cell precursors or from thymic epithelial cells, respectively. Some thymoma subtypes (AB, B1, and B2) display numerous reactive terminal deoxynucleotidyl transferase-positive (TdT<sup>+</sup>) T-cell precursors masking epithelial tumor cells. Therefore, the differential diagnosis between T-LBL and TdT<sup>+</sup> T-lymphocyte-rich thymoma could be challenging, especially in the case of needle biopsy. To distinguish between T-LBL and thymoma-associated lymphoid proliferations, we analyzed the global DNA methylation using two different technologies, namely MeDIP array and EPIC array, in independent samples series [17 T-LBLs compared with one TdT<sup>+</sup> lymphocyte-rich thymoma (B1 subtype) and three normal thymi, and seven lymphocyte-rich thymomas compared with 24 T-LBLs, respectively]. In unsupervised principal component analysis (PCA), T-LBL and thymoma samples clustered separately. We identified differentially methylated regions (DMRs) using MeDIP-array and EPIC-array datasets and nine overlapping genes between the two datasets considering the top 100 DMRs including ZIC1, TSHZ2, CDC42BPB, RBM24, C10orf53, and MACROD2. In order to explore the DNA methylation profiles in larger series, we defined a classifier based on these six differentially methylated gene promoters, developed an MS-MLPA assay, and demonstrated a significant differential methylation between thymomas (hypomethylated; n = 48) and T-LBLs (hypermethylated; n = 54) (methylation ratio median 0.03 versus 0.66, respectively; p < 0.0001), with MACROD2 methylation status the most discriminating. Using a machine learning strategy, we built a prediction model trained with the EPIC-array dataset and defined a cumulative score taking into account the weight of each feature. A score above or equal to 0.4 was predictive of T-LBL and conversely. Applied to the MS-MLPA dataset, this prediction model accurately predicted diagnoses of T-LBL and thymoma. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The Journal of PathologyVol. 264(3)
Université Claude Bernard Lyon 1 (FR), Hôpital Necker-Enfants Malades (FR), Centre National de la Recherche Scientifique (FR), Inserm (FR), German Cancer Research Center (DE), Université de Versailles Saint-Quentin-en-Yvelines (FR), Université Paris-Est Créteil (FR), Université Paris Cité (FR), Aix-Marseille Université (FR), Heidelberg University (DE), Université Paris-Saclay (FR), Institut Gustave Roussy (FR), Institut Necker Enfants Malades (FR), La Ligue Contre le Cancer (FR), Assistance Publique – Hôpitaux de Paris (FR), Hospices Civils de Lyon (FR), Hôpital Européen Georges-Pompidou (FR), Universitätsmedizin Göttingen (DE), Hôpital Marie Lannelongue (FR), Institut du Thorax (FR), Institut Mondor de Recherche Biomédicale (FR), Arabian Gulf University (BH), Institut Curie (FR), Epigenomics (Germany) (DE)
Institut National Du Cancer
Openalex Percentile: Top 14%
Myasthenia Gravis and Thymoma
1.85
DOIOpen Access PDFOpenAlex
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