MétaCan
Menu
Back to cohort
Record W3213562715 · doi:10.3389/fonc.2021.679173

KIF15 Promotes Progression of Castration Resistant Prostate Cancer by Activating EGFR Signaling Pathway

2021· article· en· W3213562715 on OpenAlexaff
Lin Gao, Ru Zhao, Junmei Liu, Wenbo Zhang, Feifei Sun, Qianshuo Yin, Xin Wang, Meng Wang, Tingting Feng, Yiming Qin, Wenjie Cai, Qianni Li, Hanchen Dong, Xueqing Chen, Xueting Xiong, Hui Liu, Jing Hu, Weiwen Chen, Bo Han

Bibliographic record

VenueFrontiers in Oncology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaShandong University
KeywordsCancer researchProstate cancerPI3K/AKT/mTOR pathwayProtein kinase BSignal transductionBiologyCell biologyCancerGenetics

Abstract

fetched live from OpenAlex

Castration-resistant prostate cancer (CRPC) continues to be a major clinical problem and its underlying mechanisms are still not fully understood. The epidermal growth factor receptor (EGFR) activation is an important event that regulates mitogenic signaling. EGFR signaling plays an important role in the transition from androgen dependence to castration-resistant state in prostate cancer (PCa). Kinesin family member 15 (KIF15) has been suggested to be overexpressed in multiple malignancies. Here, we demonstrate that KIF15 expression is elevated in CRPC. We show that KIF15 contributes to CRPC progression by enhancing the EGFR signaling pathway, which includes complex network intermediates such as mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3-kinase (PI3K)/AKT pathways. In CRPC tumors, increased expression of KIF15 is positively correlated with EGFR protein level. KIF15 binds to EGFR, and prevents EGFR proteins from degradation in a Cdc42-dependent manner. These findings highlight the key role of KIF15 in the development of CRPC and rationalize KIF15 as a potential therapeutic target.

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 score0.042
Threshold uncertainty score0.460

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 head0.008
GPT teacher head0.278
Teacher spread0.271 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in OncologySame topicMicrotubule and mitosis dynamicsFrench-language works237,207