Evidence map›Paper›PMID 27994470›Full record

ArticleOncoTargets and therapy2016

Identification of feature genes for smoking-related lung adenocarcinoma based on gene expression profile data.

Ying Liu, Ran Ni, Hui Zhang, Lijun Miao, Jing Wang, Wenqing Jia, Yuanyuan Wang

Abstract read
In one paragraph

Article in OncoTargets and therapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Live or Heat-KilledInternational journal of molecular sciences · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Group 1B phospholipase ABiochimica et biophysica acta. Molecular and cell biology of lipids · 2019
    Review
  9. Article
  10. Article
  11. 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

7 authors.

Ying LiuRespiration Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, People's Republic of China.
Ran NiRespiration Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, People's Republic of China.
Hui ZhangRespiration Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, People's Republic of China.
Lijun MiaoRespiration Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, People's Republic of China.
Jing WangRespiration Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, People's Republic of China.
Wenqing JiaRespiration Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, People's Republic of China.
Yuanyuan WangRespiration Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to identify the genes and pathways associated with smoking-related lung adenocarcinoma. Three lung adenocarcinoma associated datasets (GSE43458, GSE10072, and GSE50081), the subjects of which included smokers and nonsmokers, were downloaded to screen the differentially expressed feature genes between smokers and nonsmokers. Based on the identified feature genes, we constructed the protein-protein interaction (PPI) network and optimized feature genes using closeness centrality (CC) algorithm. Then, the support vector machine (SVM) classification model was constructed based on the feature genes with higher CC values. Finally, pathway enrichment analysis of the feature genes was performed. A total of 213 down-regulated and 83 up-regulated differentially expressed genes were identified. In the constructed PPI network, the top ten nodes with higher degrees and CC values included

Indexed as

feature geneslung adenocarcinomapathwaysupport vector machine (SVM) classification

Identifiers

PMID27994470
PMCPMC5153289

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.