Extramedullary Multiple Myeloma: A Patient-Focused Review of the Pathogenesis of Bone Marrow Escape
Bibliographic record
Abstract
Multiple myeloma (MM) is a neoplastic clonal proliferation of plasma cells, predominantly in the bone marrow. The presentation of MM in extramedullary tissue, particularly the liver, is uncommon with only a few reported cases in literature. We report a rare and unusual presentation of kappa light chain restricted MM with progression of disease to involve the liver. MM was initially diagnosed on bone marrow biopsy, initially treated with carfilzomib, lenalidomide and dexamethasone, later changed to bortezomib, daratumumab and dexamethasone. There was subsequent progression with a new biopsy-proven myelomatous liver lesion. The patient could not receive high-dose chemotherapy due to multiple co-morbidities and extent of disease and eventually succumbed to her disease rapidly. This article emphasizes the poor prognosis of extramedullary involvement in MM and the pathogenic mechanisms by which it develops. Based on a review of the literature of other cases and case series of solitary or diffuse myeloma involvement in the liver, high-dose chemotherapy in combination with proteasome inhibitors and immunomodulators has the best success rate with less relapse and progressive disease in extramedullary myeloma. Our analysis concluded that the gain of CD44, loss of CD56, loss of very late antigen-4 (VLA-4), imbalance of the chemokine receptor-4-chemokine ligand-12 (CXCR4-CXCL12) axis, metastasis-associated lung adenocarcinoma 1 (MALAT1) upregulation, RAS pathway activation as well as 13q and 17p deletions show an increased propensity of malignant plasma cells to leave the bone marrow and hone in extramedullary sites giving rise to more aggressive extramedullary diseases. Targeted therapeutics such as CD44v-directed therapy and reactivation of p53 to wild-type conformation could potentially be evaluated as treatment options in the future to improve outcomes in this aggressive form of MM, especially in patients with advanced disease and limited treatment options.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".