Current use of bispecific antibodies to treat multiple myeloma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Targeted immunotherapy has significantly improved the outcome of patients with hematological malignancies by leveraging the power of the immune system to eliminate tumor cells. In multiple myeloma (MM), bispecific T-cell engagers (BsAb) targeting B-cell maturation antigen (BCMA), G protein-coupled receptor, class C, group 5, member D (GPRC5D), and Fc receptor-like 5 (FcRL5) have already demonstrated remarkable clinical activity in triple-class refractory patients. However, responses to BsAb are not universal, and resistance often emerges while on therapy. Mechanisms mediating resistance are tumor intrinsic or immune dependent. Reported tumor intrinsic factors include antigenic loss (biallelic or functional) through deletions or mutations of target genes, increased soluble BCMA (for BCMA targeting BsAb), high tumor burden, and extramedullary disease. Immune-mediated resistance are largely dependent on T-cell fitness and tolerant immune environment. Understanding these mechanisms will allow the design of optimized BsAb therapy and an informed approach to sequencing and combining these molecules with other anti-MM agents and immune therapies.
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.
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 | 0.001 |
| 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 | 0.001 |
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 it