Improved Therapeutic Responses in a Xenograft Model of Human B Lymphoma (Namalwa) for Liposomal Vincristine<b><i>versus</i></b>Liposomal Doxorubicin Targeted via Anti-CD19 IgG2a or Fab′ Fragments
Bibliographic record
Abstract
PURPOSE: Monoclonal antibody-mediated targeting of liposomal anticancer drugs to surface antigens expressed on malignant B cells can be an effective strategy for treating B-cell malignancies. In a murine model of human B-cell lymphoma, we have made in vitro and in vivo comparisons of long-circulating sterically stabilized (Stealth) immunoliposome (SIL) formulations of two anticancer drugs, vincristine (VCR) and doxorubicin (DXR), with different mechanisms of action and drug release rates. EXPERIMENTAL DESIGN: SIL formulations of VCR or DXR were conjugated to the monoclonal antibody anti-CD19 (SIL[alphaCD19]) or its Fab' fragments (SIL[Fab']). Specific binding of SILs to Namalwa cells was studied using radiolabeled liposomes, and cytotoxicities of DXR- or VCR-loaded SILs were quantitated by a tetrazolium assay. Pharmacokinetic and drug leakage experiments were performed in mice using dual-labeled liposomes, and the therapeutic responses of SILs were evaluated in a Namalwa (human B lymphoma) cell xenograft model. RESULTS: SIL[alphaCD19] or SIL[Fab'] had higher association with and cytotoxicity against Namalwa cells than nontargeted liposomes. SIL[Fab'] had longer circulation times than SIL[alphaCD19], and VCR had faster release rates from the liposomes than DXR. SIL formulations of either VCR or DXR had significantly better therapeutic outcomes than nontargeted liposomes or free drugs. SILs loaded with VCR were superior to those loaded with DXR. SIL[Fab'] had better therapeutic outcomes than SIL[alphaCD19] for the drug DXR but were equally efficacious for the drug VCR. CONCLUSIONS: Treatment of a B lymphoma model with single injections of anti-CD19-targeted liposomal formulations of VCR resulted in high levels of response and long-term survivors. Responses to anti-CD19-targeted liposomal DXR were more modest, although the longer circulation times of SIL[Fab'] versus SIL[alphaCD19] led to superior therapeutics for DXR-loaded immunoliposomes.
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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 | 0.000 |
| 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 | 0.001 |
| 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".