Lymphoplasmacytic Lymphoma and Marginal Zone Lymphoma in the Bone Marrow: Paratrabecular Involvement As an Important Distinguishing Feature
Bibliographic record
Abstract
Abstract Lymphoplasmacytic lymphoma and marginal zone lymphoma in the bone marrow: paratrabecular involvement as an important distinguishing feature Assia Bassarova, Gunhild Tr¿en, Signe Spetalen, Francesca Micci, Anne Tierens, Delabie Abstract Lymphoplasmacytic lymphoma (LPL) is a neoplasm of small B-lymphocytes, lymphoplasmacytoid and plasma cells involving bone marrow and sometimes lymph nodes and spleen. Lymphoplasmacytic lymphoma is often accompanied by Waldenström macroglobulinemia. Since the original description, Waldenström macroglobulinemia has become recognized as a distinct clinicopathological entity defined by serum IgM paraprotein and bone marrow involvement by lymphoplasmacytic lymphoma. Since serum IgM paraprotein in itself is not specific and can be seen in a variety of small B-cell lymphoproliferative disorders, notable chronic lymphatic leukemia and marginal zone lymphoma, as well as in rare cases of myeloma, the diagnosis of Waldenström macroglobulinemia rests largely upon the proper diagnosis of LPL in the bone marrow. The differential diagnosis between bone marrow involvement by lymphoplasmacytic lymphoma (LPL) and marginal zone lymphoma (MZL) is challenging because histology and immunophenotype of both diseases overlap. The diagnosis may be helped by demonstrating the MYD88 L265P mutation, seen in most LPL. However, the mutation is also present in MZL, although at a lower frequency. To better define the distinguishing features of LPL we studied a series of bone marrow trephine biopsies of 59 patients with Waldenström's macroglobulinemia (WM) without extramedullary involvement and compared the findings with bone marrow biopsies from 23 patients with well-characterized MZL who also had bone marrow involvement. H&E and immunoperoxidase-stained sections of bone marrow trephine biopsies as well as flow cytometry and classical cytogenetics performed on aspirations were reviewed. The study was complemented with MYD88L265P mutation analysis on the bone marrow trephine biopsies of all patients. The features are summarized in Table 1. The most distinguishing features of LPL with respect to MZL were focal paratrabecular involvement (p<0.001), the presence of lymphoplasmacytoid cells (p<0.001), Dutcher bodies (p<0.001), increased numbers of mast cells (p<0.001) and the MYD88L265P mutation (p<0.001). Other features such as sinusoidal infiltration and immunophenotype were not distinguishing. Table 1. Summary of the pathology features of lymphoplasmacytic and marginal zone lymphoma in bone marrow trephine biopsies Lymphoplasmacytic lymphoma Marginal zone lymphoma p Infiltration pattern* Paratrabecular Nodular non-paratrabecular Paratrabecular and non-paratrabecular Intrasinusoidal Diffuse 37% (10/27) 0% (0/27) 56% (15/27) 37% (10/27) 0% (0/27) 0% (0/16) 75% (12/16) 0% (0/16) 37% (6/16) 25% (4/16) <0,001 <0,001 <0,001 1 0,015 Cytology Small lymphoid cells Plasmacytoid cells Plasma cells Dutcher nuclear inclusions Mast cells 100% (59/59) 100% (59/59) 93% (55/59) 90% (53/59) 87% (49/56) 100% (23/23) 0% (0/23) 78% (18/23) 0% (0/23) 9% (2/23) - <0,001 0,108 <0,001 <0,001 Immunophenotype of the lymphoma CD20 CD138 (plasma cells) CD5 CD23 IgK IgL IgM IgG Focal CD21+ or CD23+ follicular dendritic cell network in the stroma 100% (59/59) 88% (50/57) 21% (12/52) 29% (15/51) 81% (48/59) 19% (11/59) 97% (57/59) 3% (2/59) 20% (10/51) 100% (23/23) 80% (12/15) 0% (0/23) 13% (5/23) 26% (5/19) 10% (2/19) 64% (7/11) 0% (0/11) 48% (11/23) - - 0,014 0,580 - - - - 0,024 MYD88 L265P mutation 96% (45/47) 20% (3/15) 0,001 *the analysis was only performed on bone marrow trephine biopsies showing less than 66% lymphoma infiltration In conclusion, LPL can reliably be distinguished from MZL in the bone marrow by using a combination of pathology characteristics. In contrast to other studies, our findings stress the diagnostic importance of paratrabecular infiltration in LPL. Disclosures No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".