Correlation of <i>TACC3, FGFR3, MMSET</i> and <i>p21</i> expression with the t(4;14)(p16·3;q32) in multiple myeloma
Bibliographic record
Abstract
The t(4;14)(p16;q32) translocation seen in c. 18% of newly diagnosed multiple myeloma (MM) cases, results in FGFR3 activation and creation of an IGH/MMSET fusion transcript. We have recently shown that FGFR3 is activated in only 75% of t(4;14)(+) cases, suggesting that alternative genes near the breakpoint may be involved in the transforming event. The gene, TACC3, located just 50 kb telomeric of FGFR3, with transforming capacity, therefore represented a candidate gene. Using a real-time quantitative polymerase chain reaction-based approach on a cohort of 54 patients, we found a statistically significant, twofold increase in TACC3 expression in t(4;14)(+) cases. TACC3, MMSET and p21 values were positively correlated in all cases and, of particular interest, six patient samples [three t(4;14)(-), three t(4;14)(+)] samples showed a joint up-regulation of TACC3, MMSET and p21. Although a poor prognosis is linked with elevated MMSET expression, an extended follow-up period will be required to evaluate the significance of elevated TACC3 and p21 expression in this subgroup of MM.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".