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Record W2885847247 · doi:10.1158/1538-7445.am2018-5449

Abstract 5449: Characterization of clinically relevant mechanism of resistance to angiogenic inhibitors in different growth patterns of human colorectal cancer liver metastases (CRCLM) by studying the angiopoietins-Tie2 mechanisms

2018· article· en· W2885847247 on OpenAlexaff
Nisreen Ibrahim, Anthoula Lazaris, Stephanie Petrillo, Abdellatif Amri, Zu‐Hua Gao, Peter Metrakos

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineColorectal cancerRegimenBevacizumabOncologyChemotherapyInternal medicineCancerAngiogenesis

Abstract

fetched live from OpenAlex

Abstract Colorectal carcinoma (CRC) remains the third leading cause of cancer death in the Western world. Over 50% of CRC patients develop liver metastases (LM) and 90% will die from metastatic disease. Angiogenic inhibitors AIs (bevacizumab, Bev) were introduced with chemotherapy as first-line therapy for CRCLMs. While some patients respond well to this therapeutic strategy, the outcomes have fallen short of expectations. Recently we have reported the outcomes of resected CRCLM patients who have received neoadjuvant chemotherapy with or without AIs stratified by histologic growth patterns (HGPs): Desmoplastic HGP (DHGP), Pushing HGP (PHGP) and Replacement HGP (RHGP). The majority of metastases were either DHGPs, which derive the majority of their blood supply via sprouting angiogenesi,s or RHGP, which derive their blood supply from vessel co-option. When the neoadjuvant regimen included Bev, the DHGP patients more than doubled their 5-year overall survival (OS) compared to RHGP patients receiving the same Bev regimen. This OS difference was lost when both groups of patients were treated with chemo alone (no Bev). Although sprouting angiogenesis has been studied extensively and there is some understating of those mechanisms, we have no understanding of the mechanism behind co-option, and furthermore, apart from cytotoxic chemotherapy we have no targeted therapies for these patients. Theoretical Model: Cancer cells that arrive to the liver have to vascularize in order to increase in size, or as evidence has recently suggested, can grow avascularly in vascularized tissue by co-option of existing mature vessels. We hypothesize that there are several steps required for this process to occur. In our recent work, we have shown that cancer cell motility is essential for co-option. The angiopoietins-Tie2 mechanisms are critically involved in angiogenesis. Using human samples (chemonaïve, chemo-only and chemo plus Bev), we have evidence that Ang1-Tie2 mechanism is differently expressed in RHGP vs. DHGP metastases. The ratio of Ang2: Ang1 expression in DHGP tumors was higher compared to RHGP tumors, whereas VEGF appears to be equally expressed in both. Furthermore, a significant expression of Ang1 was detected in the hepatocytes at the interface region of the tumor and liver in RHGP. Thus, vascular quiescence maintained by Ang1-Tie2 mechanism prevails in RHGP verses DHGP metastasis; therefore this mechanism may be important in the development of vessel co-option vs. angiogenesis. Interestingly, Tie2 expression was expressed not only by vessels and tumor cells but also found in the leucocytes that were more abundant in DHGP vs. RHGP. This study will allow us to characterize the factors and mechanisms by which vessel co-option occurs in a metastatic setting and will stratify patients in terms of treatment. Citation Format: Nisreen Samir Ibrahim, Anthoula Lazaris, Stephanie Petrillo, Abdellatif Amri, Zu-Hua Gao, Peter Metrakos. Characterization of clinically relevant mechanism of resistance to angiogenic inhibitors in different growth patterns of human colorectal cancer liver metastases (CRCLM) by studying the angiopoietins-Tie2 mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5449.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

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)0.0030.000

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 head0.044
GPT teacher head0.356
Teacher spread0.312 · 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 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
Published2018
Admission routes1
Has abstractyes

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