Prognostic significance of the proliferation signature in mantle cell lymphoma measured using digital gene expression in formalin-fixed paraffin-embedded tissue biopsies.
Bibliographic record
Abstract
7510 Background: Mantle cell lymphoma (MCL) is a group of aggressive B-cell lymphomas displaying heterogeneous outcomes after treatment. A number of prognostic indices have been described. A powerful biomarker, the “proliferation signature”, was developed using gene expression in fresh frozen material in 2003 (Rosenwald et al Cancer Cell). Here we describe the training and validation of a new assay that measures the proliferation signature in RNA derived from routinely available formalin-fixed paraffin-embedded (FFPE) biopsies. Methods: FFPE biopsies were used to train an assay on the NanoString platform using Affymetrix U133 microarray gene expression in matched fresh frozen biopsies as a gold standard. The locked assay (including gene coefficients and score thresholds to define high, intermediate and low risk groups) was then applied to pre-treatment FFPE lymph node biopsies from an independent cohort of 110 patients uniformly treated with R-CHOP chemotherapy at the BC Cancer Agency. In 59 of these patients, aged 65 years or younger, there was intention-to-treat with an autologous stem cell transplant to consolidate response (the “ASCT-ITT” group). The MIPI was available for 95 patients. Results: The MCL55 assay, containing a 16-gene proliferation signature, yielded gene expression of sufficient quality to assign a score and risk group in 108/110 (98%) archival FFPE biopsies and assigned patients to high (26% of patients), intermediate (29%), and low (45%) risk groups with significantly different overall survival (OS); median OS of 1.1, 2.6 and 8.6 years, respectively (logrank for trend P<0.001). Within the ASCT-ITT group the median OS in these 3 risk groups were 1.4 years, 5.9 years, and not reached, respectively (logrank for trend P<0.001). In multivariate analysis, the risk groups assigned by the MCL55 assay and by the MIPI were independently associated with OS in the total cohort (P<0.001 for both variables). Conclusions: The newly developed and validated MCL55 assay for FFPE biopsies uses the proliferation signature to define groups of patients with MCL with significantly different OS independent of the MIPI.
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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".