Evidence map›Paper›PMID 34247575›Full record

ArticleBMC cancer2021

A methylation-based nomogram for predicting survival in patients with lung adenocarcinoma.

Xuelong Wang, Bin Zhou, Yuxin Xia, Jianxin Zuo, Yanchao Liu, Xin Bi, Xiong Luo, Chengwei Zhang

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2021. 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
0.6field-weighted citation impact, top 36% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Xuelong Wang *Department of Thoracic Surgery, Capital Medical University Electric Power Teaching Hospital, Beijing, 100073, China.
Bin Zhou *Department of Thoracic Surgery, Capital Medical University Electric Power Teaching Hospital, Beijing, 100073, China.
Yuxin Xia *Department of emergency, Capital Medical University Electric Power Teaching Hospital, Beijing, 100073, China.
Jianxin ZuoDepartment of Thoracic Surgery, Capital Medical University Electric Power Teaching Hospital, Beijing, 100073, China.
Yanchao LiuDepartment of Thoracic Surgery, Capital Medical University Electric Power Teaching Hospital, Beijing, 100073, China.
Xin BiDepartment of Thoracic Surgery, Capital Medical University Electric Power Teaching Hospital, Beijing, 100073, China.
Xiong LuoDepartment of Internal Medicine, Beijing Nuclear Industry Hospital, Beijing, 100822, China.
Chengwei ZhangDepartment of Thoracic Surgery, Capital Medical University Electric Power Teaching Hospital, Beijing, 100073, China. bjdlyyxwk@163.com.ORCID http://orcid.org/0000-0003-1620-4510
Capital Medical University · CNChina National Nuclear Corporation · CNNorth China Electric Power University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDNA methylation alteration is frequently observed in Lung adenocarcinoma (LUAD) and may play important roles in carcinogenesis, diagnosis, and prognosis. Thus, this study aimed to construct a reliable methylation-based nomogram, guiding prognostic classification screening and personalized medicine for LUAD patients.

methodThe DNA methylation data, gene expression data and corresponding clinical information of lung adenocarcinoma samples were extracted from The Cancer Genome Atlas (TCGA) database. Differentially methylated sites (DMSs) and differentially expressed genes (DEGs) were obtained and then calculated correlation by pearson correlation coefficient. Functional enrichment analysis and Protein-protein interaction network were used to explore the biological roles of aberrant methylation genes. A prognostic risk score model was constructed using univariate Cox and LASSO analysis and was assessed in an independent cohort. A methylation-based nomogram that included the risk score and the clinical risk factors was developed, which was evaluated by concordance index and calibration curves.

resultWe identified a total of 1362 DMSs corresponding to 471 DEGs with significant negative correlation, including 752 hypermethylation sites and 610 hypomethylation sites. Univariate cox regression analysis showed that 59 DMSs were significantly associated with overall survival. Using LASSO method, we constructed a three-DMSs signature that was independent predictive of prognosis in the training cohort. Patients in high-risk group had a significant shorter overall survival than patients in low-risk group classified by three-DMSs signature (log-rank p = 1.9E-04). Multivariate cox regression analysis proved that the three-DMSs signature was an independent prognostic factor for LUAD in TCGA-LUAD cohort (HR = 2.29, 95%CI: 1.47-3.57, P = 2.36E-04) and GSE56044 cohort (HR = 2.16, 95%CI: 1.19-3.91, P = 0.011). Furthermore, a nomogram, combining the risk score with clinical risk factors, was developed with C-indexes of 0.71 and 0.70 in TCGA-LUAD and GSE56044 respectively.

conclusionsThe present study established a robust three-DMSs signature for the prediction of overall survival and further developed a nomogram that could be a clinically available guide for personalized treatment of LUAD patients.

Indexed as

NomogramsAdenocarcinoma of LungDNA MethylationFemaleHumansLung NeoplasmsMalePrognosisSurvival AnalysisDifferentially methylated sitesDNA methylationLung adenocarcinomaPrognosisSignature

Identifiers

PMID34247575
PMCPMC8273993
OpenAlexW3143870285

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LicenceCC BY
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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.