Immune Phenotypes and Target Antigens of Clonally Expanded Bone Marrow T Cells in Treatment-Naïve Multiple Myeloma
Bibliographic record
Abstract
Multiple myeloma is a hematologic malignancy of monoclonal plasma cells that accumulate in the bone marrow. Despite their clinical and pathophysiologic relevance, the roles of bone marrow-infiltrating T cells in treatment-naïve patients are incompletely understood. We investigated whether clonally expanded T cells (i) were detectable in multiple myeloma bone marrow, (ii) showed characteristic immune phenotypes, and (iii) whether dominant clones recognized antigens selectively presented on multiple myeloma cells. Single-cell index sorting and T-cell receptor (TCR) αβ sequencing of bone marrow T cells from 13 treatment-naïve patients showed dominant clonal expansion within CD8+ cytolytic effector compartments, and only a minority of expanded T-cell clones expressed the classic immune-checkpoint molecules PD-1, CTLA-4, or TIM-3. To identify their molecular targets, TCRs of 68 dominant bone marrow clones from five selected patients were reexpressed and incubated with multiple myeloma and non-multiple myeloma cells from corresponding patients. Only 1 of 68 TCRs recognized antigen presented on multiple myeloma cells. This TCR was HLA-C-restricted, self-peptide-specific and could be activated by multiple myeloma cells of multiple patients. The remaining dominant T-cell clones did not recognize multiple myeloma cells and were, in part, specific for antigens associated with chronic viral infections. In conclusion, we showed that dominant bone marrow T-cell clones in treatment-naïve patients rarely recognize antigens presented on multiple myeloma cells and exhibit low expression of classic immune-checkpoint molecules. Our data provide experimental context for experiences from clinical immune-checkpoint inhibition trials and will inform future T cell-dependent therapeutic strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".