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Record W4388589205 · doi:10.1093/neuonc/noad179.1083

TMIC-17. THE ROLE OF ICAM1 IN GLIOBLASTOMA TUMORIGENESIS UNDER HYPOXIC CONDITIONS

2023· article· en· W4388589205 on OpenAlexaff
Sheila Mansouri, Kaviya Devaraja, Gelareh Zadeh, Olivia Singh, Hafsah Ali, Qinxqia Wei, Julio Sosa, Vikas Patil

Bibliographic record

VenueNeuro-Oncology · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsUniversity of TorontoToronto Western HospitalThe Scarborough HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsCancer researchTumor microenvironmentBiologyCarcinogenesisCancer

Abstract

fetched live from OpenAlex

Abstract Glioblastoma (GBM) is a deadly brain cancer in adults with limited treatment options. Cell adhesion molecules (CAMs) mediate cell-cell interactions and migration. Intercellular adhesion molecule 1 (ICAM-1) is a CAM expressed by various cell types in solid tumors, including macrophages, tumor and endothelial cells. We previously demonstrated that ICAM-1 expression is linked to shorter overall survival in GBM patients. We observed elevated ICAM-1 levels in hypoxic regions of GBMs. Considering the role of tumor-associated macrophages (TAMs) in GBM tumorigenicity, our objective was to investigate how ICAM-1 expression in TAMs contributes to GBM growth within the hypoxic tumor microenvironment (TME). We employed a comprehensive approach utilizing in vitro and in vivo models, as well as genomic analyses at both bulk and single-cell levels, to elucidate the association between ICAM-1 and TAMs in tumorigenicity. Our findings demonstrated that injecting GBM cells into ICAM-1 knockout mice led to prolonged survival, smaller tumors, reduced macrophage infiltration, and enhanced M1-like polarization of TAMs. Additionally, bone marrow reconstitution experiments confirmed the tumor-promoting role of ICAM-1-expressing TAMs. Cell deconvolution, immunohistochemical, and flow cytometry analyses of mouse tumors supported these findings. Gene set enrichment analysis of differentially expressed genes in xenografted tumors revealed that ICAM-1 presence upregulated key tumorigenic pathways, including epithelial-mesenchymal transition, IL2-STAT5, TNF-α via NFκB, IL6-JAK-STAT3, and RAS/MAPK. In vitro analysis indicated that ICAM-1 promoted macrophage migration and polarization towards M2-like state, which was further augmented by hypoxia-induced ICAM1 expression. Flow cytometry, cytometry by time of flight (cyToF), and single-cell RNA sequencing analysis of human and mouse GBMs revealed elevated ICAM-1 expression in hypoxic TAMs, suggesting the hypoxic microenvironment promotes the tumorigenic functions of TAMs. In conclusion, ICAM1 likely enhances GBM tumorigenesis by promoting TAM migration into the TME. Furthermore, environmental factors such as hypoxia contribute to increased ICAM-1 expression in TAMs, further exacerbating GBM tumorigenicity.

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 score0.003
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)0.0030.001

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 head0.013
GPT teacher head0.273
Teacher spread0.259 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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