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Record W4317708657 · doi:10.1016/j.jare.2023.01.015

IQGAP3 is relevant to prostate cancer: A detailed presentation of potential pathomechanisms

2023· article· en· W4317708657 on OpenAlexafffund
Wenjuan Mei, Ying Dong, Yan Gu, Anil Kapoor, Xiaozeng Lin, Yingying Su, Sandra Vega Neira, Damu Tang

Bibliographic record

VenueJournal of Advanced Research · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversitySt. Joseph's Hospital
FundersInstitute of Cancer ResearchCanadian Institutes of Health Research
KeywordsProstate cancerImmune systemCancer researchImmune checkpointCancerCarcinogenesisMetastasisLNCaPImmunotherapyBiologyMedicineOncologyInternal medicineImmunology

Abstract

fetched live from OpenAlex

INTRODUCTION: IQGAP3 possesses oncogenic actions; its impact on prostate cancer (PC) remains unclear. OBJECTIVE: We will investigate IQGAP3's association with PC progression, key mechanisms, prognosis, and immune evasion. METHODS: IQGAP3 expression in PC was examined by immunohistochemistry and using multiple datasets. IQGAP3 network was analyzed for pathway alterations and used to construct a multigene signature (SigIQGAP3NW). SigIQGAP3NW was characterized using LNCaP cell-derived castration-resistant PCs (CRPCs), analyzed for prognostic value in 26 human cancer types, and studied for association with immune evasion. RESULTS: Increases in IQGAP3 expression associated with PC tumorigenesis, tumor grade, metastasis, and p53 mutation. IQGAP3 correlative genes were dominantly involved in mitosis. IQGAP3 correlated with PLK1 and TOP2A expression at Spearman correlation/R = 0.89 (p ≤ 3.069e-169). Both correlations were enriched in advanced PCs and Taxane-treated CRPCs and occurred at high levels (R > 0.8) in multiple cancer types. SigIQGAP3NW effectively predicted cancer recurrence and poor prognosis in independent PC cohorts and across 26 cancer types. SigIQGAP3NW stratified PC recurrence after adjustment for age at diagnosis, grade, stage, and surgical margin. SigIQGAP3NW component genes were upregulated in PC, metastasis, LNCaP cell-produced CRPC, and showed an association with p53 mutation. SigIQGAP3NW correlated with immune cell infiltration, including Treg in PC and other cancers. RELT, a SigIQGAP3NW component gene, was associated with elevations of multiple immune checkpoints and the infiltration of Treg and myeloid-derived suppressor cells in PC and across cancer types. RELT and SigIQGAP3NW predict response to immune checkpoint blockade (ICB) therapy. CONCLUSIONS: In multiple cancers, IQGAP3 robustly correlates with PLK1 and TOP2A expression, and SigIQGAP3NW and/or RELT effectively predict mortality risk and/or resistance to ICB therapy. PLK1 and TOP2A inhibitors should be investigated for treating cancers with elevated IQGAP3 expression. SigIQGAP3NW and/or RELT can be developed for clinical applications in risk stratification and management of ICB therapy.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.055
GPT teacher head0.433
Teacher spread0.377 · 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 designTheoretical or conceptual
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

Citations10
Published2023
Admission routes2
Has abstractyes

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