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Record W4388267794 · doi:10.3390/curroncol30110687

High Expression of Fas-Associated Factor 1 Indicates a Poor Prognosis in Non-Small-Cell Lung Cancer

2023· article· en· W4388267794 on OpenAlexvenueno aff
De Jin Hu, Hidetaka Yamada, Katsuhiro Yoshimura, Tsutomu Ohta, Kazuo Tsuchiya, Yusuke Inoue, Kazuhito Funai, Takafumi Suda, Yuji Iwashita, Takuya Watanabe, Hiroshi Ogawa, Nobuhito Kurono, Kazuya Shinmura, Haruhiko Sugimura

Bibliographic record

VenueCurrent Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsnot available
FundersSmoking Research Foundation
KeywordsLung cancerCancer researchDownregulation and upregulationMedicineApoptosisCancerOncologyViability assayInternal medicineBiologyGeneGenetics

Abstract

fetched live from OpenAlex

Fas-associated factor 1 (FAF1) is a death-promoting protein identified as an interaction partner of the death receptor Fas. The downregulation and mutation of FAF1 have been reported in a variety of human tumors, but there have been few studies on lung cancer. Here, we investigated the prognostic significance of FAF1 expression in non-small-cell lung cancer (NSCLC), and whether aberrant FAF1 expression may be involved in the pathogenesis and prognosis of NSCLC. FAF1 expression was examined in NSCLC specimens as well as human lung cancer cell lines. In addition, changes in cell viability and apoptosis upon regulating FAF1 expression were investigated in lung cancer cell lines. As a result, high FAF1 expression was significantly associated with a poor prognosis in NSCLC. In lung cancer cell lines, FAF1 downregulation hindered cell viability and tended to promote early apoptosis. In conclusion, this is the first study of the clinical significance of FAF1 in NSCLC, showing that FAF1 overexpression is associated with a poor prognosis in NSCLC and that FAF1 acts as a dangerous factor rather than an apoptosis promoter in NSCLC.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.072
GPT teacher head0.390
Teacher spread0.318 · 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 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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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