Telomere Architecture Correlates with Aggressiveness in Multiple Myeloma
Bibliographic record
Abstract
The prognosis of multiple myeloma (MM), an incurable B-cell malignancy, has significantly improved through the introduction of novel therapeutic modalities. Myeloma prognosis is essentially determined by cytogenetics, both at diagnosis and at disease progression. However, for a large cohort of patients, cytogenetic analysis is not always available. In addition, myeloma patients with favorable cytogenetics can display an aggressive clinical course. Therefore, it is necessary to develop additional prognostic and predictive markers for this disease to allow for patient risk stratification and personalized clinical decision-making. Genomic instability is a prominent characteristic in MM, and we have previously shown that the three-dimensional (3D) nuclear organization of telomeres is a marker of both genomic instability and genetic heterogeneity in myeloma. In this study, we compared in a longitudinal prospective study blindly the 3D telomeric profiles from bone marrow samples of 214 initially treatment-naïve patients with either monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), or MM, with a minimum follow-up of 5 years. Here, we report distinctive 3D telomeric profiles correlating with disease aggressiveness and patient response to treatment in MM patients, and also distinctive 3D telomeric profiles for disease progression in smoldering multiple myeloma patients. In particular, lower average intensity (telomere length, below 13,500 arbitrary units) and increased number of telomere aggregates are associated with shorter survival and could be used as a prognostic factor to identify high-risk SMM and MM patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".