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Record W1533533749 · doi:10.3892/or.2015.4051

MicroRNA-153 is a prognostic marker and inhibits cell migration and invasion by targeting SNAI1 in human pancreatic ductal adenocarcinoma

2015· article· en· W1533533749 on OpenAlex
Jiangli Sun, Xiaobo Wang, Hai Wang, Honghong Pei, Zhengliang Zhang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Post-publication record

NatureRetraction
ReasonConcerns/Issues about Image;Duplication of/in Image;Manipulation of Images;
Date11/16/2022 0:00
Flagged by OpenAlex?Yes

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.

Bibliographic record

VenueOncology Reports · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsnot available
FundersPublic Health Agency of Canada
KeywordsSNAI1OncogeneCancer researchMetastasisDownregulation and upregulationmicroRNABiologyMolecular medicineEctopic expressionOncomirPancreatic cancerClinical significanceCell cycleCellCancerInternal medicineOncologyCell cultureCarcinogenesisMedicineEpithelial–mesenchymal transitionGene

Abstract

fetched live from OpenAlex

Human pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer type with early metastasis, which leads to poor prognosis for patients. Mounting evidence suggests that microRNAs (miRNAs) act as critical factors for tumor recurrence and metastasis. miR-153 has been suggested as a novel tumor-associated miRNA, which is involved in tumor metastasis. However, the clinical significance of miR-153 and its role in PDAC remains to be investigated. The aim of the present study was to investigate the expression levels of miR-153 using RT-qPCR in human PDAC cell lines and tissues. A clinical association analysis was performed to investigate the clinical significance of miR-153. The results showed that, the relative expression of miR-153 in PDAC cells was obviously decreased as compared to that in the normal human pancreatic duct epithelial cell line. The mean expression of miR-153 in PDAC tissues was significantly reduced as compared to that in the normal pancreatic tissues. The clinical analysis revealed that a low expression of miR-153 was closely associated with poor prognostic features and shorter long-term survival of PDAC patients. Furthermore, univariate and multivariate Cox regression analyses showed that miR-153 was an independent prognostic factor for predicting survival in PDAC patients. In vitro studies demonstrated that the upregulation of miR-153 inhibited migration and invasion in MIAPaCa-2 cells. By contrast, the downregulation of miR-153 increased the number of migrated and invaded AsPC-1 cells. miR-153 inversely regulated SNAI1 abundance in MIAPaCa-2 cells. Notably, SNAI1 was identified as a direct target of miR-153 in PDAC. Furthermore, an inverse correlation between miR-153 and SNAI1 expression was observed in PDAC tissues. In conclusion, the results showed miR-153 is an independent prognostic marker for predicting survival in PDAC patients and inhibits cell migration and invasion by targeting SNAI1.

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.

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 score0.054
Threshold uncertainty score0.648

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 head0.011
GPT teacher head0.247
Teacher spread0.237 · 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