High level expression of functional human IgMs in human PER.C6® cells
Bibliographic record
Abstract
Natural IgM antibodies play an important role in the body's defense mechanisms against transformed cells in the human body and are currently being exploited both in prognoses of malignant lesions and in the therapy of cancer patients. However, despite growing interest and clinical promise, thus far the IgM class of antibodies has failed to gain widespread commercial interest as these are considered to be difficult to produce recombinantly. IgMs are polymeric and have a relatively large mass. In addition, IgM molecules are heavily glycosylated and, when produced in non-human cell lines, they may contain non-human glycan structures which may be potentially immunogenic. Clearly, production systems capable of expressing human recombinant IgM antibodies are needed. We have successfully used PER.C6 cells-a human cell line-to generate three separate human recombinant monoclonal IgMs in suspension cultures in protein-free medium. All three of the IgMs were constructed with joining (J) chain and were expressed in the pentameric form. One of the IgMs was also expressed as a hexamer without J chain. Clones with cell specific productivities greater than 20 pg/cell/day were generated, which led to yields of 0.5 g/L to 2g/L in fed-batch production. All the IgMs expressed were biologically active as shown in binding and cytotoxicity assays. These studies demonstrate the potential of PER.C6 cells for the production of high levels of functional recombinant IgM and other polymeric molecules, using a straightforward and rapid stable cell line generation method.
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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 | 0.000 |
| 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 | 0.001 | 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".