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Abstract 2777: LOXL4-expressing neutrophils are found in colorectal cancer liver metastases resistant to anti-angiogenic therapy

2019· article· en· W2955474624 on OpenAlexaff
Vincent Palmieri, Anthoula Lazaris, Stephanie Petrillo, Hussam Alamri, Abdellatif Amri, Woong‐Yang Park, Zu‐Hua Gao, Peter Metrakos

Bibliographic record

VenueTumor Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineImmunostainingColorectal cancerPathologicalMetastasisBevacizumabAngiogenesisOncologyBiomarkerPathologyCancer researchImmunohistochemistryInternal medicineCancerChemotherapyBiology

Abstract

fetched live from OpenAlex

Three different histopathological growth patterns (HGP) have been identified in colorectal cancer liver metastases (CRCLM) resected from patients: the desmoplastic HGP, the pushing HGP, and the replacement HGP. Evidence suggests that the predominant growth pattern with which a CRCLM presents has clinically relevant prognostic implications. We have shown that patients with replacement HGP lesions who received bevacizumab plus chemotherapy had a worse pathological response and five-year overall survival than those with desmoplastic HGP lesions receiving the same treatment. We have also demonstrated that CRCLM with the replacement HGP promote vessel co-option for vascularization, rather than sprouting angiogenesis as seen in desmoplastic HGP metastases. These findings point to the growth patterns in CRCLM possibly serving as predictive biomarkers of response to anti-angiogenic therapy, when no such biomarker has been validated to date. However, HGP scoring is performed on resected liver metastatic tissue, implying that preoperative treatment precedes growth pattern assessment. Therefore, surrogate markers for the HGPs that can be appraised prior to surgery would be helpful to inform clinical decision-making about whether a patient with CRCLM may benefit from anti-angiogenic treatment.This project aims to identify genes that are differentially expressed between CRCLM presenting with either the replacement or desmoplastic HGP. RNA sequencing (RNA-Seq) was used to compare the transcriptional profiles of these distinct CRCLM. A gene expression signature was generated from the RNA-Seq data to include genes that were upregulated in the replacement HGP liver metastases. Immunostaining of select genes from this signature was performed to validate these findings on human tumor tissue.Initial analysis of our RNA-Seq data identified 525 genes that are differentially expressed between the replacement and desmoplastic HGP CRCLM, of which 53 genes met the criteria for the gene expression signature. Pathway analysis of these genes identified pathways involved in the immune system and extracellular matrix (ECM) to be upregulated in the replacement HGP lesions. Subsequent immunostaining revealed the expression pattern of lysyl oxidase like-4 (LOXL4) protein to be distinct between the HGPs - significantly greater quantities of LOXL4-expressing neutrophils were detected in the replacement HGP tumor microenvironment.Characterizing differences in gene expression between replacement and desmoplastic HGP CRCLM is expected to provide some insight into the mechanisms responsible for generating these distinct growth patterns. Our findings suggest that further investigations into the role of tumor-associated leukocytes and ECM remodelling may ultimately lead to the development of biomarkers and new therapeutic targets for replacement HGP CRCLM.Citation Format: Vincent Palmieri, Anthoula Lazaris, Stephanie Petrillo, Hussam Alamri, Abdellatif Amri, Woong-Yang Park, Zu-hua Gao, Peter Metrakos. LOXL4-expressing neutrophils are found in colorectal cancer liver metastases resistant to anti-angiogenic therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2777.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.913

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 head0.290
Teacher spread0.269 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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