Evidence map›Paper›PMID 36061963›Full record

ArticleInternational journal of general medicine2022

AC099850.3/NCAPG Axis Predicts Poor Prognosis and is Associated with Resistance to EGFR Tyrosine-Kinase Inhibitors in Lung Adenocarcinoma.

Jiaqi Bao, Yanlong Wu, Kun Zhang, Huijuan Qi

Abstract read
In one paragraph

Article in International journal of general medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. 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

4 authors.

Jiaqi Bao *Department of Thoracic Surgery, Affiliated Hospital of Chifeng University, Chifeng, People's Republic of China.
Yanlong Wu *Department of Urology, Affiliated Hospital of Chifeng University, Chifeng, People's Republic of China.
Kun ZhangDepartment of Radiology, Huhhot First Hospital, Huhhot, People's Republic of China.
Huijuan QiDepartment of Gynecology, Affiliated Hospital of Chifeng University, Chifeng, People's Republic of China.ORCID 0000-0002-6859-9959

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: TKI-acquired resistance markedly interferes with treatment of lung cancer patients with EGFR mutant features. Long non-coding RNAs (lncRNAs) modify EGFR-TKI resistance during tumor progression. Non-structural maintenance of chromosomes condensin I complex subunit G (NCAPG) is a mitosis-related protein that is involved in tumorigenesis. We investigated the potential regulatory lncRNAs of NCAPG in lung adenocarcinoma (LUAD) and assessed their roles in EGFR-TKI resistance. Methods: Data for 1678 lung cancer patients were retrieved from TCGA and GEO databases and used to evaluate NCAPG and lncRNAs expressions, as well as their prognostic significance in LUAD. Protein levels of NCAPG in LUAD were validated by immuno-histochemistry. To assess the relationship between NCAPG levels and EGFR-TKIs sensitivity, a cohort of 57 LUAD patients administered with EGFR-TKIs was used. Results: Both NCAPG and lncRNA AC099850.3 were over-expressed in LUAD tissues, and correlated with tumor progression and poor prognosis in LUAD. LncRNA AC099850.3 was identified as a potential regulator of NCAPG expressions. The AC099850.3/NCAGP axis was markedly correlated with EGFR mutations and IC Conclusion: The AC099850.3/NCAPG axis is a potential prognostic predictor and therapeutic biomarker for EGFR-TKIs in LUAD.

Indexed as

biomarkerEGFRlncRNAlung cancerNCAPG

Identifiers

PMID36061963
PMCPMC9439153

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.