Evidence map›Paper›PMID 27835911›Full record

ArticleOncotarget2016

Prognostic and predictive values of CDK1 and MAD2L1 in lung adenocarcinoma.

Yuan-Xiang Shi, Tao Zhu, Ting Zou, Wei Zhuo, Yi-Xin Chen, Ma-Sha Huang, Wei Zheng, Chen-Jing Wang, Xi Li, Xiao-Yuan Mao and 4 more

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed
10.8field-weighted citation impact, top 1% 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

71 citing papers in PubMed, 106 citations in OpenAlex.

  1. Article
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  4. Combining serum CDK1 with tumor markers for the diagnosis of small cell lung cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Article
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  8. [Progress in the Study of Spindle Assembly Checkpoint in Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2023
    Article
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11 more citing papers are in PubMed but not listed here.

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

14 authors at 2 institutions in 1 country.

Yuan-Xiang ShiDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Tao ZhuDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Ting ZouDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Wei ZhuoDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Yi-Xin ChenDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Ma-Sha HuangDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Wei ZhengDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Chen-Jing WangDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Xi LiDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Xiao-Yuan MaoDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Wei ZhangDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Hong-Hao ZhouDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Ji-Ye YinDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Zhao-Qian LiuDepartment of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China.
Xiangya Hospital Central South University · CNCentral South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer remains as the leading cause of cancer-related death worldwide, and lung adenocarcinoma (LUAD) is the most common histological subtype. This study aims to investigate biomarkers associated with cancer progression and prognosis of LUAD. We integrated expression profiles of 668 lung cancer patients in five datasets from the Gene Expression Omnibus (GEO) and identified a panel of differentially expressed genes (DEGs). Function enrichment analysis highlighted that these genes were closely associated with the carcinogenesis of LUAD, such as cell cycle, ECM-receptor interaction and p53 signaling pathway. Cyclin-dependent kinase 1 (CDK1) and MAD2 mitotic arrest deficient-like 1 (MAD2L1), two critical mitotic checkpoint genes, were selected for further study. Elevated expression of CDK1 and MAD2L1 was validated in an independent LUAD cohort. Kaplan-Meier analysis revealed that CDK1 and MAD2L1 expression was negatively correlated with both overall survival (OS) and relapse-free survival (RFS). In conclusion, CDK1 and MAD2L1 were adverse prognostic biomarkers for LUAD whose increased expression could render patients with LUAD a high risk of cancer recurrence and poor survival, suggesting that they might be applied as potential targets for LUAD treatment.

Indexed as

AdenocarcinomaAgedBiomarkers, TumorCarcinogenesisCDC2 Protein KinaseDatasets as TopicFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLung NeoplasmsMad2 ProteinsMaleMitosisPredictive Value of TestsPrognosisBiomarkers, TumorCDC2 Protein KinaseCDK1 protein, humanMAD2L1 protein, humanMad2 ProteinsTumor Suppressor Protein p53biomarkerCDK1lung cancerMAD2L1prognosis

Identifiers

PMID27835911
PMCPMC5356732
OpenAlexW2551814309

What OpenQuestion holds

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LicenceCC BY
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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.