New Molecular Assay for the Proliferation Signature in Mantle Cell Lymphoma Applicable to Formalin-Fixed Paraffin-Embedded Biopsies
Bibliographic record
Abstract
Purpose Mantle cell lymphoma is an aggressive B-cell neoplasm that displays heterogeneous outcomes after treatment. In 2003, the Lymphoma/Leukemia Molecular Profiling Project described a powerful biomarker-the proliferation signature-using gene expression in fresh frozen material. Herein, 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 Forty-seven FFPE biopsies were used to train an assay on the NanoString platform, using microarray gene expression data of matched fresh frozen biopsies as a gold standard. The locked assay was applied to pretreatment FFPE lymph node biopsies from an independent cohort of 110 patients uniformly treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone. Seventeen biopsies were tested across three laboratories to assess assay reproducibility. Results The MCL35 assay, which contained a 17-gene proliferation signature, yielded gene expression of sufficient quality to assign an assay score and risk group in 108 (98%) of 110 archival FFPE biopsies. The MCL35 assay assigned patients to high-risk (26%), standard-risk (29%), and low-risk (45%) groups, with different lengths of overall survival (OS): a median of 1.1, 2.6, and 8.6 years, respectively (log-rank for trend, P < .001). In multivariable analysis, these risk groups and the Mantle Cell Lymphoma International Prognostic Index were independently associated with OS ( P < .001 for both variables). Concordance of risk assignment across the three independent laboratories was 100%. Conclusion The newly developed and validated MCL35 assay for FFPE biopsies uses the proliferation signature to define groups of patients with significantly different OS independent of the Mantle Cell Lymphoma International Prognostic Index. Importantly, the analytic and clinical validity of this assay defines it as a reliable biomarker to support risk-adapted clinical trials.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".