Molecular characterization and clonal evolution in Richter transformation: Insights from a case of plasmablastic lymphoma (RT‐PBL) arising from chronic lymphocytic leukaemia (CLL) and review of the literature
Notice bibliographique
Résumé
Richter transformation (RT) represents a high-grade transformation observed in chronic lymphocytic leukaemia (CLL)/small lymphocytic lymphoma, leading to increased aggressiveness and unfavourable outcomes. Among the variants of RT, diffuse large B-cell lymphoma (RT–DLBCL) is the most commonly encountered, whereas transformation into plasmablastic lymphoma (RT–PBL) is an exceptionally rare event [1, 2]. PBL is characterized by the presence of large atypical B cells displaying plasmablastic or immunoblastic morphology and exhibiting a terminal B-cell differentiation phenotype. Typically, PBL arises de novo in patients with immune deficiency or dysregulation [2, 3]. In this context, we report a compelling case of RT in a patient with unmutated CLL who experienced transformation to PBL 14 months following the initial diagnosis. A 71-year-old man presented with new-onset lymphocytosis (17.9–22.7 × 10^9/L), without B symptoms or lymphadenopathy. Flow cytometry confirmed a CLL immunophenotype. After 2 months, the patient experienced fatigue, decreased appetite and weight loss, with a significant increase in lymphocyte count (76 × 10^9/L). Radiological investigation revealed mesenteric, retroperitoneal and pelvic lymphadenopathy. Bone marrow biopsy revealed 90% involvement by CLL. There was no histological evidence of transformation on bone marrow or peripheral blood (Figure 1). The patient was started on Ibrutinib treatment. He remained stable for 12 months, and his lymphocyte count normalized to 2.7 × 10^9/L. Subsequently, he presented with a 2-week history of left leg swelling and immobility. A CT scan revealed extensive lymphadenopathy, including a 15.6 cm conglomerate mass involving abdominal organs. A lymph node biopsy showed effacement by large cells with abundant pale cytoplasm, vesicular nuclei and prominent nucleoli (Figure 1). Mitoses and apoptosis were abundant. Immunohistochemical analysis demonstrated positive staining for plasmacytic markers CD138 and MUM-1 and a proliferation index close to 100% (Figure 2). HHV8 and Epstein–Barr virus (EBV) were negative. A summary of the immunohistochemical features for both diagnoses is provided in Table S1. Due to multifactorial medical complications, the patient required ICU admission shortly after. Two cycles of CHOP chemotherapy were administered at reduced dosages but soon switched to palliative treatment. The patient passed away 4 months after RT and 19 months after the initial workup for lymphocytosis. IGHV mutation status testing was conducted on the bone marrow biopsy with CLL and the lymph node biopsy with PBL. The CLL and PBL populations were found to have identical clonal IGH gene rearrangements (IGHV3-30-301, IGHJ6-02, IGHD3-3*01) that were unmutated (100% homology to IGHV IGMT reference set) [4]. FISH testing with a CLL prognostic panel [5] was performed on the bone marrow with CLL which showed the signal pattern for the centromere of chromosome 12 (CEP12)(D12Z1) probe consistent with trisomy 12 in 68% of nuclei. CEP12 FISH analysis on the PBL was also positive. FISH testing with MYC, BCL2 and BCL6 break-apart probes was conducted on PBL only. The MYC and BCL2 break-apart probes were positive, whereas a subsequent FISH with the dual fusion IGH/BCL2 probe was negative indicating a non-IGH partner. Next-generation sequencing (NGS) was performed on both samples using the Illumina TruSight Oncology 500 (TSO500) targeted hybrid-capture-based NGS assay covering a comprehensive list of 500 genes (Supporting Information Data 1) [6]. Sequencing analysis of CLL revealed two sequence variants. The NOTCH1 gene variant (NM_017617.5): c.7375C > T (p.Gln2459Ter) was detected at a frequency of 44%, and the SPEN gene variant (NM_015001.3): c.5920dupA (p.Thr1974fsTer6) was identified at a frequency of 42%. In PBL, the same sequence variants of NOTCH1 and SPEN were present at similar frequencies of 47% and 43%, respectively (Table S2). The analysis revealed the presence of copy number variants, specifically amplifications, in the BRAF, CDK6, EGFR and MET genes within PBL. Additionally, sequence variants were identified in ARID1B, BCL2 and ERBB2 (Table S3). A review of the literature on PBL arising in the context of CLL yielded 15 cases [2, 7–16], the findings of which are summarized in Table S4. The male-to-female ratio was 4:1 and age at primary CLL diagnosis ranged from 52 to 77 years. None of the patients had a known history of immunodeficiency. Three cases had both CLL and PBL diagnosed simultaneously [2, 10, 11], whereas for the remaining 12 cases, the time between CLL diagnosis and PBL diagnosis varied from 14 to 132 months. Four patients had received prior treatment with Ibrutinib for a duration of 18–96 months before developing plasmablastic lymphoma. In 10 out of 12 cases, a clonal relationship between CLL and PBL was established. The two cases that were clonally unrelated according to IGH sequencing were attributed to PBL development as a secondary lymphoma due to immunosuppression resulting from previous CLL treatments (fludarabine and cladribine, respectively) [15, 16]. The interval between PBL diagnosis and death was generally short, with 12 patients succumbing within 6 months. Of the 14 tested cases, 11 were negative for EBV, and 3 were positive. FISH analysis was conducted on nine cases of CLL [2, 7–9], with the most common alterations being 17p13.1 abnormalities (4/9), followed by 13q14.3 deletions (3/9). Trisomy 12 was detected in two cases, and 11q22 deletion was found in one. One case exhibited trisomy 12 and a 17p13.1 deletion, along with a TP53 mutation.14 In two cases, FISH analysis was performed for BCL2, BCL6, CCND1, MYC and TP53 abnormalities in both the CLL and PBL. One CLL case had a t(12;14). rearrangement with MYC rearrangement at transformation, whereas the second case had an MYC rearrangement, which persisted in the subsequent PBL [7]. Four of seven cases that underwent MYC rearrangement studies on PBL were positive. BCL2 and BCL6 FISH studies were performed on five cases, revealing gains in BCL2 and BCL6 in two and three cases, respectively. The results of NGS analysis performed on five cases are summarized in Table S5. Although reviewing the literature revealed that TP53 abnormalities were the most common genetic change in RT–PBL with no NOTCH1 mutation previously reported, this case showed NOTCH1 and SPEN mutations but not TP53. MYC rearrangements are found in both de novo PBL and RT–PBL indicating their significant role in disease progression [14]. In this review, five patients developed RT–PBL after ibrutinib, raising the possibility that CLL transforms to RT–PBL as a mechanism of resistance to BCR inhibition or that minor RP–PBL subclones might have been present at treatment initiation potentially selected with a BCR inhibition. A notable distinguishing factor between RT and de novo PBL is the absence of EBV in most cases of RT, whereas de novo PBL is typically EBV-positive [17]. In conclusion, our case adds to the understanding of the genetic and molecular characteristics of PBL as RT. Not many studies have shown a distinct genetic or molecular abnormality that differentiates RT–PBL from RT–DLBCL or de novo PBL [18], although this needs further large cohort analysis [19, 20]. However, our case demonstrated the concurrence of two mutually exclusive genetic pathways observed in CLL to DLBCL transformations: the TP53 mutation with MYC activation pathway and trisomy 12 with NOTCH1 mutated pathway [21]. Further investigations, including NGS analysis of PBL as RT cases, are warranted to identify unique genetic factors contributing to the development of PBL as RT over DLBCL. Study design; acquisition; assembly; analysis and interpretation of data; drafting of the manuscript; critical revision of the manuscript for important intellectual content: Ali Sakhdari. Study design; acquisition; interpretation of data; drafting of the manuscript; critical revision of the manuscript: Megan C. Ramsey. Acquisition; analysis; and interpretation of molecular data; drafting of the manuscript; critical revision of the manuscript: Peter J. B. Sabatini and Adam C. Smith. The authors declare that they have no conflicts of interest. The authors received no specific funding for this work. This study followed the University Health Network and patients’ ethics. The study was approved by the “Research Ethics Board [REB]” of the University Health Network and conducted in compliance with the Declaration of Helsinki. The authors have confirmed clinical trial registration is not needed for this submission. The authors have confirmed patient consent statement is not needed for this submission. The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».