Recombinant expression, characterization, and quantification in human cancer cell lines of the Anaplastic Large-Cell Lymphoma-characteristic NPM-ALK fusion protein
Bibliographic record
Abstract
Systemic anaplastic large cell lymphoma (ALCL) is an aggressive T-cell lymphoma most commonly seen in children and young adults. The majority of pediatric ALCLs are associated with the t(2;5)(p23;q35) translocation which fuses the Anaplastic Lymphoma Kinase (ALK) gene with the Nucleophosmin (NPM) gene. The NPM-ALK fusion protein is a constitutively-active tyrosine kinase, and plays a major role in tumor pathogenesis. In an effort to advance novel diagnostic approaches and the understanding of the function of this fusion protein in cancer cells, we expressed in E. coli, purified and characterized human NPM-ALK fusion protein to be used as a standard for estimating expression levels in cultured human ALCL cells, a key tool in ALCL pathobiology research. We estimated that NPM-ALK fusion protein is expressed at substantial levels in both Karpas 299 and SU-DHL-1 cells (ca. 4-6 million molecules or 0.5-0.7 pg protein per cell; based on our in-house developed NPM-ALK ELISA; LOD of 40 pM) as compared to the ubiquitous β-actin protein (ca. 64 million molecules or 4.5 pg per lymphocyte). We also compared NPM-ALK/ β-actin ratios determined by ELISA to those independently determined by two-dimensional electrophoresis and showed that the two methods are in good agreement.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".