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Record W2324692647 · doi:10.1158/1535-7163.targ-11-b12

Abstract B12: The effects of Irinophore C™ on the microenvironment and vasculature of a primary orthotopic model of colorectal cancer.

2011· article· en· W2324692647 on OpenAlexaff
May Q. Wong, Tamanna Karim, Navdeep Gill, Dawn Waterhouse, Marcel B. Bally, David Owen, Isabella T. Tai, Sylvia S. W. Ng, Donald T. Yapp

Bibliographic record

VenueMolecular Cancer Therapeutics · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsVancouver General HospitalUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsColorectal cancerIrinotecanMedicineCancerTumor microenvironmentPrimary tumorPathologyIn vivoCancer researchInternal medicineMetastasisBiology

Abstract

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Abstract Introduction: Colorectal cancer is a common cancer that accounts for ∼10% of cancer cell deaths in North America. There are numerous in vivo xenograft models for colorectal cancer available, but in general, these are derived from immortalized cell lines and fail to capture the complexities and heterogeneity of tumors seen in the clinic. Our group has developed a series of orthotopic, primary tumors from samples of human colorectal cancer tissue obtained during surgical resection that maintain the characteristics of the original sample. The effects of Irinophore C™, (a liposomal formulation of irinotecan that is more efficacious and less toxic than the parent drug) on the microenvironment and vascular function of these primary colorectal tumors were examined in the present study. Materials and Methods: Primary tumor tissues, obtained from colorectal cancer patients, were validated by a reference pathologist and implanted subcutaneously in SCID mice. Small pieces of subcutaneous tumors that grew successfully were then passaged orthotopically on the ascending colon of new mice. When these tumors reached ∼200mm3, groups of mice were treated with vehicle control (0.9% saline), irinotecan (50mg/kg), or Irinophore C™ (25mg/kg) once a week for 6 weeks. Separate groups of tumors were harvested on days 3 and 42 after treatment started. Immunofluorescence staining was performed on tumor cryosections followed by computerized image analysis to determine levels of cell proliferation, apoptosis, hypoxia, and vessel density. Results: 4 of 14 samples were successfully propagated orthotopically and were characterized by a reference pathologist. The tumors maintain their original morphology, and one is a highly mucinous adenocarcinoma whereas the others are typical colorectal adenocarcinomas. Treatment with irinotecan and Irinophore C™ reduced tumor volumes by 54% and 92%, respectively, compared to the vehicle control. No toxic effects were seen with Irinophore C™. Immunostaining data showed that the distance between blood vessels remained the same for Irinotecan when compared to control, but increased with Irinophore C™ treatment (+30%; P<0.01). However, perfusion was not significantly different between the three treatment groups. Furthermore, compared to the vehicle treatment group, tumors treated with irinotecan are 42% (P<0.05) more necrotic and tumors treated with Irinophore C™ are 97% less hypoxic. Conclusion: An orthotopic model of colorectal cancer was successfully developed using patient tumor materials that retained the morphology of the primary tumor. Irinophore C™ was more effective in controlling tumor growth than irinotecan despite being delivered at a lower dose. In addition, treatment with Irinophore C™ appeared to improve overall vascular function in the tumor. Based on these data, it is clear that Irinophore C™ has different mechanisms of action and is more efficacious than irinotecan against primary models of colorectal cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr B12.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.020
GPT teacher head0.251
Teacher spread0.231 · 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 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

Citations1
Published2011
Admission routes1
Has abstractyes

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