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Abstract LB-33: Pre-clinical evaluation of AB-16B5, a monoclonal antibody specific for tumor-associated sCLU, demonstrates therapeutic potential as an inhibitor of EMT in prostate, pancreatic and lung cancer

2011· article· en· W2313936515 on OpenAlexaff
Gilles B. Tremblay, Elisabeth Viau, Mireille Malouin, Émilie Turcotte, Annie Fortin, Mario Filion

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldMedicine
TopicClusterin in disease pathology
Canadian institutionsAlethia Biotherapeutics (Canada)
Fundersnot available
KeywordsDU145Cancer researchPancreatic cancerProstate cancerMedicineCancerVimentinIn vivoGemcitabineMonoclonal antibodyProstateClusterinDocetaxelApoptosisEpithelial–mesenchymal transitionImmunohistochemistryCancer cellAntibodyPathologyInternal medicineImmunologyMetastasisChemistryBiology

Abstract

fetched live from OpenAlex

Abstract Secreted clusterin (sCLU) exhibits elevated expression in several cancer indications. sCLU plays a pro-survival role in tumors and, more recently, it was found to be a potent stimulator of the epithelial-to-mesenchymal transition (EMT). These findings led to the development of a monoclonal antibody, AB-16B5, that interacts with a specific EMT-inducing domain in sCLU resulting in abrogation of migration and invasion of many types of cancer cells. In previous studies, AB-16B5 reduced the invasion of tumors in models of metastatic breast cancer suggesting that the antibody blocked EMT in vivo. Here we present pre-clinical findings in models of prostate cancer, pancreatic cancer, and NSCLC. DU145 and PC-3 prostate cancer cells implanted in SCID mice grew slower in the groups treated with AB-16B5 as a monotherapy or in combination with docetaxel. This observation suggested that blocking sCLU with AB-16B5 enhanced the chemo-responsiveness to cytotoxic drugs, a finding that was consistent with the proposed role of sCLU as an inhibitor of apoptosis in cancer cells. Immunohistochemical examination of sections prepared from the prostate tumors exposed to AB-16B5 showed an increase in E-cadherin, a marker of epithelial cells, and a reduction of vimentin, a marker of mesenchymal cells, which indicated that EMT was blocked or even reversed in vivo. Additional analyses of tumors derived from human pancreatic cancer showed that sCLU was expressed in this indication as well, especially in tumors that were resistant to gemcitabine. In agreement with the role of sCLU as an inducer of EMT, AB-16B5 inhibited the invasion of PANC-1 pancreatic cancer cells in vitro. Importantly, treatment of SCID mice harboring BxPC-3 pancreatic tumors with AB-16B5 resulted in a significant enhancement of the response to gemcitabine. Similarly, the growth of tumors grown from the NSCLC cell line, A549, was also inhibited by AB-16B5. To explore the behavior of AB-16B5 in cynomolgus monkeys, the antibody was administered by i.v. infusion every 14 days at two doses of 10 and 50 mg/kg. Results indicated that AB-16B5 was well tolerated and no signs of toxicity were observed. Finally, to address the mechanism of action of sCLU, cell biology experiments indicated that sCLU is internalized in cancer cells, which leads to the activation of critical signaling pathways that favor cell proliferation and survival, including those pathways leading to a stimulation of NF-kappaB. Our studies imply that the combination of increased epithelial character of tumor cells exposed to AB-16B5 coupled with a reduction in the activation of survival pathways contribute to an increase in the sensitivity to chemotherapy and a significant reduction of tumor growth, in particular in cancer types such as pancreatic cancer, where EMT likely contributes to increased chemo-resistance. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-33. doi:10.1158/1538-7445.AM2011-LB-33

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.196
GPT teacher head0.519
Teacher spread0.322 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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