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Overcoming Self-Tolerance: Long-Term Protection Against Specific erbB2-Expressing Prostate Tumors Using Low Doses of Lentivirus-Transduced DCs.

2006· article· en· W2585783048 on OpenAlexaff
Miriam E. Mossoba, Jagdeep S. Walia, Vanessa I. Rasaiah, Daniel H. Fowler, Jeffrey A. Medin

Bibliographic record

VenueBlood · 2006
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsImmunotherapyCancer researchMedicineBone marrowViral vectorImmune toleranceAntigenCD86Prostate cancerDendritic cellGenetic enhancementCD80ImmunologyCancerBiologyCytotoxic T cellT cellImmune systemCD40Internal medicineIn vitroRecombinant DNA

Abstract

fetched live from OpenAlex

Abstract Anti-tumor immunotherapy is difficult to achieve in vivo in part due to naturally occurring peripheral tolerance. Our laboratory has developed a potent immunotherapy strategy that uses unusually low doses of dendritic cells (DCs) to break self-tolerance in a mouse model of prostate cancer. We constructed a lentiviral vector (LV) encoding a truncated form of the true self-antigen murine erbB2 (LV/erbB2tr). This protein is the murine form of HER-2/neu, a tumor associated antigen (TAA) upregulated in 20% of primary prostate tumors and 80% of metastatic cases. With LV/erbB2tr, we achieved highly efficient gene transfer into DCs that were generated from donor murine bone marrow, as up to 47% of DCs over-expressed erbB2tr following one infection (MOI of 3). Similar transduction levels were achieved using a control enGFP LV. The purity of transduced DCs was confirmed by flow cytometry for CD11c, CD80, CD86, and I-Ab expression. We then tested the ability of two low dose inoculations of these transduced DCs to overcome self-tolerance to erbB2 and protect against specific challenge in a bilateral tumor model. Mice were vaccinated twice, two weeks apart by administration of either 2 × 105 or 2 ×103 cells (i.p.). Six weeks later, the mice were injected on one hind flank with the highly aggressive murine tumor cell line RM1 and on the opposite flank with erbB2tr-transduced RM1 (RM1-erbB2tr). We saw complete protection from RM1-erbB2tr tumors in 100% of the mice receiving 2 × 105 erbB2tr-transduced DCs (n=6). Control RM1 tumors were not rejected. No systemic auto-immune responses to the self-antigen were observed, as all mice survived and the procedure was well tolerated. Furthermore, our strategy was effective even using 100-fold fewer DCs in the inoculations. In the mice receiving 2 ×103 erbB2tr-transduced DCs, 33% (2/6 animals) were completely protected from developing RM1-erbB2tr tumors and 2 others showed near-complete protection. At regular points throughout the experiment, serum levels of anti-erbB2tr antibodies were measured. In mice receiving the 2 ×105 DC dose, a peak antibody response was seen 1 week after the second immunization (4.6-fold above controls). Long-term antibody responses were detected beyond 6-weeks post-vaccination. T cell responses are being assessed by cytokine (IFN-γ, IL-2, IL-4, IL-5, and IL-10) secretion assays. Cytokine specificity data are pending. We speculated that the antigen-specific anti-tumor effect might have been modulated, in part, by apoptosis of regulatory T (Treg) cells that help maintain peripheral tolerance. Indeed, CD4+CD25+Foxp3+ Treg cells were consistently reduced in mice vaccinated with erbB2tr-transduced DCs, as shown by flow cytometry. Together these experiments show that we can overcome tolerance to an endogenously-expressed TAA, even using very low doses of erbB2-transduced DCs. Future studies will focus on testing our DC therapy in mice with established prostate tumors for a more clinically applicable model.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.226
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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