A Landmark Paper That Introduced Proteasome Inhibition in Myeloma
Bibliographic record
Abstract
The ongoing therapeutic revolution in multiple myeloma care can be traced to the turn of the millennium with the unanticipated discovery in 1999 that the cereblon binding small molecule thalidomide had profound clinical effectiveness and, simultaneously, the emergence of a new class of targeted therapies inhibiting the proteasome, both of which ultimately target ubiquitinated protein degradation. These contemporaneous discoveries forever changed the landscape of multiple myeloma care, substantially extending survival. Foreshadowing this seismic change, Nobel Prize winning work on the proteasome ubiquitin pathway had stimulated the development of highly specific proteasome inhibitor small molecules, particularly PS-341 (later named bortezomib). An abundance of the proteasome in hematologic malignancies had been recognized and thus PS-341 was logically being explored in relevant preclinical models. Concurrent with phase I trials, which were soon to prove the significant clinical relevance of preclinical models, the laboratory of Dr. Kenneth Anderson and colleagues at Dana-Farber, in partnership with Dr. Julian Adams and scientists at ProScript (later Millennium Pharmaceuticals) first demonstrated that the proteasome inhibitor PS-341 inhibited growth, induced apoptosis, and overcame drug resistance in human multiple myeloma cells. This landmark paper in Cancer Research set the stage for a paradigm shift in how multiple myeloma was managed across all stages of the disease, which changed the lives of patients worldwide. See related article by Hideshima and colleagues, Cancer Res 2001;61:3071-6.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".