Evidence map›Paper›PMID 36959566›Full record

ArticleBMC cancer2023

CA916798 predicts poor prognosis and promotes Gefitinib resistance for lung adenocarcinoma.

Jian He, Xi Lan, Xiayan Liu, Caixia Deng, Hu Luo, Yan Wang, Ping Kang, Zhijian Sun, Lintao Zhao, Xiangdong Zhou

Open access · goldFull text read
In one paragraph

Article in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 43% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

10 authors at 2 institutions in 1 country.

Jian He *Department of Respiratory medicine, The First Hospital Affiliated to Army Medical University, 29 Gaotanyan Main Street, Chongqing, 400038, China.
Xi Lan *Department of Respiratory medicine, The First Hospital Affiliated to Army Medical University, 29 Gaotanyan Main Street, Chongqing, 400038, China.
Xiayan Liu *Department of Respiratory medicine, The First Hospital Affiliated to Army Medical University, 29 Gaotanyan Main Street, Chongqing, 400038, China.
Caixia DengDepartment of Respiratory medicine, The First Hospital Affiliated to Army Medical University, 29 Gaotanyan Main Street, Chongqing, 400038, China.
Hu LuoDepartment of Respiratory medicine, The First Hospital Affiliated to Army Medical University, 29 Gaotanyan Main Street, Chongqing, 400038, China.
Yan WangInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China.
Ping KangK2 Oncology Co., Ltd, Beijing, 100176, China.
Zhijian SunK2 Oncology Co., Ltd, Beijing, 100176, China.
Lintao ZhaoDepartment of Respiratory medicine, The First Hospital Affiliated to Army Medical University, 29 Gaotanyan Main Street, Chongqing, 400038, China. zhaolintao72@163.com.
Xiangdong ZhouDepartment of Respiratory medicine, The First Hospital Affiliated to Army Medical University, 29 Gaotanyan Main Street, Chongqing, 400038, China. xiangdongzhou2022@163.com.
Army Medical University · CNSouthwest Hospital · CN

Funding

National Natural Science Foundation of China 81372500
6 · The paper itself

Abstract

backgroundOur previous studies have identified CA916798 as a chemotherapy resistance-associated gene in lung cancer. However, the histopathological relevance and biological function of CA916798 in lung adenocarcinoma (LUAD) remains to be delineated. In this study, we further investigated and explored the clinical and biological significance of CA916798 in LUAD.

methodsThe relationship between CA916798 and clinical features of LUAD was analyzed by tissue array and online database. CCK8 and flow cytometry were used to measure cell proliferation and cell cycle of LUAD after knockdown of CA916798 gene. qRT-PCR and western blotting were used to detect the changes of cell cycle-related genes after knockdown or overexpression of CA916798. The tumorigenesis of LUAD cells was evaluated with or without engineering manipulation of CA916798 gene expression. Response to Gefitinib was evaluated using LUAD cells with forced expression or knockdown of CA916798.

resultsThe analysis on LUAD samples showed that high expression of CA916798 was tightly correlated with pathological progression and poor prognosis of LUAD patients. A critical methylation site in promoter region of CA916798 gene was identified to be related with CA916798 gene expression. Forced expression of CA916798 relieved the inhibitory effects of WEE1 on CDK1 and facilitated cell cycle progression from G2 phase to M phase. However, knockdown of CA916798 enhanced WEE1 function and resulted in G2/M phase arrest. Consistently, chemical suppression of CDK1 dramatically inhibited G2/M phase transition in LUAD cells with high expression of CA916798. Finally, we found that CA916798 was highly expressed in Gefitinib-resistant LUAD cells. Exogenous expression of CA916798 was sufficient to endow Gefitinib resistance with tumor cells, but interference of CA916798 expression largely rescued response of tumor cells to Gefitinib.

conclusionsCA916798 played oncogenic roles and was correlated with the development of Gefitinib resistance in LUAD cells. Therefore, CA916798 could be considered as a promising prognostic marker and a therapeutic target for LUAD.

Indexed as

Adenocarcinoma of LungLung NeoplasmsBlotting, WesternCell Line, TumorCell ProliferationGefitinibGene Expression Regulation, NeoplasticHumansPrognosisGefitinibCA916798CCNB1G2/M phaseGefitinib resistanceLung adenocarcinoma

Identifiers

PMID36959566
PMCPMC10035219
OpenAlexW4360615566

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read37
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.