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Record W4236560338 · doi:10.1016/s1525-0016(16)42887-x

57. Anti-Angiogenic Cancer Therapy with Microencapsulated Cells

2002· article· en· W4236560338 on OpenAlexfundno aff

Bibliographic record

VenueMolecular Therapy · 2002
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchMcMaster University
KeywordsCancer therapyCancer researchCancer cellCancerMedicineInternal medicine

Abstract

fetched live from OpenAlex

Inhibition of angiogenesis has led to tumor suppression in several cancer models.Although administering purified recombinant antiangiogenic product is effective, alternative approaches through genetic manipulation may be more cost-effective.We propose to implant nonautologous recombinant cells secreting angiostatin for systemic delivery of angiostatin in cancer treatment.These cells are protected from graft rejection in alginate microcapsules to function as "micro-organs" to deliver angiostatin in vivo.This approach was tested by implanting encapsulated mouse myoblast C2C12 cells genetically modified to secrete angiostatin into mice bearing solid tumor.Angiostatin was detected in sera of the treated mice.Efficacy was demonstrated by suppression of palpable tumor growth and improved survival.At autopsy, angiostatin localized to residual tumors and high levels of angiostatic activity were detected in tumor extracts.Tumor tissues showed increased apoptosis and necrosis compared with those from untreated or mock-treated mice.Immunohistochemical staining against von Willebrand factor, an endothelial cell marker, showed that within tumors from the treated mice, the neovasculature was poorly defined by endothelial cells, many of which were undergoing apoptosis.However, the tumors eventually developed neovasculature independent of endothelial cells.Such vascular mimicry would account for the lack of long-term efficacy despite persistent angiostatin delivery.In conclusion, implantation with nonautologous microencapsulated cells is feasible for systemic delivery of angiostatin, resulting in localization of angiostatin to tumors and targeted apoptosis of the endothelial cells.Clinical efficacy was demonstrated by suppression of tumor growth and extension of life span.Although the potential of this cell-based approach for angiostatin-mediated cancer therapy is confirmed, long-term efficacy must take into account the possible escape by some tumors from angiogenesis inhibition.1065 OVERVIEW SUMMARY Inhibition of angiogenesis by angiostatin has been shown to be an effective treatment in several animal models of cancer.In this study, we examine a potentially cost-effective strategy of delivering angiostatin by implanting nonautologous, genetically engineered cells that were immunoisolated from the host by microencapsulation.The advantage of this approach is that, once a suitable recombinant cell line is created, it can be used to treat patients without causing irreversible genetic changes as in most gene-based therapies.We now show that biologically active angiostatin can be delivered systemically from encapsulated cells engineered to secrete angiostatin.In tumor-bearing mice, the delivered angiostatin was found to reside predominantly in tumors, concurrent with endothelial cell apoptosis within the tumor mass.Mice bearing solid B16/F0/neu melanoma tumors re-ceiving this treatment showed tumor growth suppression and improved survival.Therefore, the implantation of immunoisolated, nonautologous cells capable of delivering angiostatin is a viable means of treating melanoma and potentially other cancers.

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 score0.002
Threshold uncertainty score0.005

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.018
GPT teacher head0.239
Teacher spread0.221 · 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

Citations2
Published2002
Admission routes1
Has abstractyes

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