Evidence map›Paper›PMID 34745947›Full record

ArticleFrontiers in oncology2021

Identification of a Three-Gene Signature Based on Epithelial-Mesenchymal Transition of Lung Adenocarcinoma Through Construction and Validation of a Risk-Prediction Model.

Jianguang Shi, Zishan Wang, Jing Guo, Yingqi Chen, Changyong Tong, Jingjie Tong, Wentao Hu, Chenwei Li, Xinjian Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 42% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Factors Determining Epithelial-Mesenchymal Transition in Cancer Progression.International journal of molecular sciences · 2024
    Review
  4. Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Jianguang ShiThoracic Surgery Department, Ningbo First Hospital, Ningbo, China.
Zishan WangThoracic Surgery Department, Ningbo First Hospital, Ningbo, China.
Jing GuoThoracic Surgery Department, Ningbo First Hospital, Ningbo, China.
Yingqi ChenThoracic Surgery Department, Ningbo First Hospital, Ningbo, China.
Changyong TongThoracic Surgery Department, Ningbo First Hospital, Ningbo, China.
Jingjie TongThoracic Surgery Department, Ningbo First Hospital, Ningbo, China.
Wentao HuThoracic Surgery Department, Ningbo First Hospital, Ningbo, China.
Chenwei LiThoracic Surgery Department, Ningbo First Hospital, Ningbo, China.
Xinjian LiThoracic Surgery Department, Ningbo First Hospital, Ningbo, China.
Ningbo First Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial-mesenchymal transition (EMT) process, which is regulated by genes of inducible factors and transcription factor family of signaling pathways, transforms epithelial cells into mesenchymal cells and is involved in tumor invasion and progression and increases tumor tolerance to clinical interventions. This study constructed a multigene marker for lung predicting the prognosis of lung adenocarcinoma (LUAD) patients by bioinformatic analysis based on EMT-related genes. Gene sets associated with EMT were downloaded from the EMT-gene database, and RNA-seq of LUAD and clinical information of patients were downloaded from the TCGA database. Differentially expressed genes were screened by difference analysis. Survival analysis was performed to identify genes associated with LUAD prognosis, and overlapping genes were taken for all the three. Prognosis-related genes were further determined by combining LASSO regression analysis for establishing a prediction signature, and the risk score equation for the prognostic model was established using multifactorial COX regression analysis to construct a survival prognostic model. The model accuracy was evaluated using subject working characteristic curves. According to the median value of risk score, samples were divided into a high-risk group and low-risk group to observe the correlation with the clinicopathological characteristics of patients. Combined with the results of one-way COX regression analysis, HGF, PTX3, and S100P were considered as independent predictors of LUAD prognosis. In lung cancer tissues, HGF and PTX3 expression was downregulated and S100P expression was upregulated. Kaplan-Meier, COX regression analysis showed that HGF, PTX3, and S100P were prognostic independent predictors of LUAD, and high expressions of all the three were all significantly associated with immune cell infiltration. The present study provided potential prognostic predictive biological markers for LUAD patients, and confirmed EMT as a key mechanism in LUAD progression.

Indexed as

epithelial-mesenchymal transitionLASSOlung adenocarcinomaprognosisrisk score

Identifiers

PMID34745947
PMCPMC8567015
OpenAlexW3209667008

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.