Improvement of Pharmacokinetic Profile of TRAIL via Trimer-Tag Enhances its Antitumor Activity in vivo
Bibliographic record
Abstract
TNF-related apoptosis-inducing ligand (TRAIL/Apo2L) has long been considered a tantalizing target for cancer therapy because it mediates activation of the extrinsic apoptosis pathway in a tumor-specific manner by binding to and trimerizing its functional receptors DR4 or DR5. Despite initial promise, both recombinant human TRAIL (native TRAIL) and dimeric DR4/DR5 agonist monoclonal antibodies (mAbs) failed in multiple human clinical trials. Here we show that in-frame fusion of human C-propeptide of α1(I) collagen (Trimer-Tag) to the C-terminus of mature human TRAIL leads to a disulfide bond-linked homotrimer which can be expressed at high levels as a secreted protein from CHO cells. The resulting TRAIL-Trimer not only retains similar bioactivity and receptor binding kinetics as native TRAIL in vitro which are 4-5 orders of magnitude superior to that of dimeric TRAIL-Fc, but also manifests more favorable pharmacokinetic and antitumor pharmacodynamic profiles in vivo than that of native TRAIL. Taken together, this work provides direct evidence for the in vivo antitumor efficacy of TRAIL being proportional to systemic drug exposure and suggests that the previous clinical failures may have been due to rapid systemic clearance of native TRAIL and poor apoptosis-inducing potency of dimeric agonist mAbs despite their long serum half-lives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".