Evidence map›Paper›PMID 41272619›Full record

ArticleBMC pulmonary medicine2025

Research on tracheal stenosis based on molecular biomarkers.

Shuxian Ma, Haitao Li, Pei Zhang, Yanjie Yang, Shuangna He, Xuze Li, Zhangnan Sun, Zhigang Cai, Lining Huang

Abstract read
In one paragraph

Article in BMC pulmonary medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

9 authors.

Shuxian MaDepartment of Anesthesiology, The Second Hospital of Hebei Medical University, No. 215 West Heping Road Xinhua District, Shijiazhuang, 050000, Shijiazhuang, China.
Haitao LiDepartment of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Pei ZhangIntensive Care Unit of Department of Anesthesiology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yanjie YangDepartment of Anesthesiology, The Second Hospital of Hebei Medical University, No. 215 West Heping Road Xinhua District, Shijiazhuang, 050000, Shijiazhuang, China.
Shuangna HeDepartment of Anesthesiology, The Second Hospital of Hebei Medical University, No. 215 West Heping Road Xinhua District, Shijiazhuang, 050000, Shijiazhuang, China.
Xuze LiDepartment of Anesthesiology, The Second Hospital of Hebei Medical University, No. 215 West Heping Road Xinhua District, Shijiazhuang, 050000, Shijiazhuang, China.
Zhangnan SunDepartment of Anesthesiology, The Second Hospital of Hebei Medical University, No. 215 West Heping Road Xinhua District, Shijiazhuang, 050000, Shijiazhuang, China.
Zhigang CaiDepartment of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Lining HuangDepartment of Anesthesiology, The Second Hospital of Hebei Medical University, No. 215 West Heping Road Xinhua District, Shijiazhuang, 050000, Shijiazhuang, China. 27701226@hebmu.edu.cn.

Funding

Medical Science Research Program of Hebei Health Commission 20230051
6 · The paper itself

Abstract

backgroundTracheal stenosis is a common respiratory disease characterized by abnormal narrowing of the tracheal lumen, which restricts airflow and can lead to symptoms such as dyspnea and even asphyxiation. Although the widespread use of imaging and bronchoscopy has improved diagnostic efficiency, the molecular mechanisms underlying tracheal stenosis remain unclear, particularly regarding the identification of predictive molecular markers.

methodsThis was a retrospective study involving 43 patient samples. A range of statistical methods-including Spearman correlation analysis, multivariable logistic regression, LASSO regression, and ROC curve validation-were employed to systematically screen for molecular targets associated with tracheal stenosis and assess their potential for risk prediction. The study also investigated the roles of ion channels and cell cycle-related molecules through literature analysis. Additionally, a tracheal stenosis animal model was constructed, and RT-qPCR was used to detect differences in mRNA expression levels of candidate molecules (CACNA1D, MKI67, CCNB2, CDKL5, and VAMP2).

resultsRespiratory failure and scar diathesis were significantly associated with the occurrence of tracheal stenosis (P < 0.05). Patients with respiratory failure had a notably higher risk of developing tracheal stenosis (P < 0.001), while those with scar diathesis also showed increased susceptibility (P = 0.009). Other clinical characteristics, including age, sex, hypertension, and diabetes, were not significantly associated with stenosis risk (P > 0.05). Regarding molecular markers, positively correlated genes-such as CACNA1D, AMPH, and PTPRD-were expressed at significantly higher levels in patients with tracheal stenosis (P < 0.001), suggesting their role in promoting cell proliferation or ion channel dysfunction. In contrast, negatively correlated markers-such as CALML4, CDKL5, and VAMP2-were expressed at lower levels (P < 0.001), potentially exerting protective effects through inhibition of cell proliferation or maintenance of cellular structure. LASSO regression identified CCNB2, PTPRD, and CACNA1D as positively associated with stenosis risk, whereas VAMP2 and CDKL5 were negatively associated. ROC curve analysis demonstrated excellent model performance (AUC = 0.91), indicating strong predictive capacity of the selected biomarkers. Subgroup analysis showed that elevated MKI67 expression was significantly associated with stenosis risk in patients with respiratory failure, but not in those without. Experimental validation using a tracheal stenosis animal model confirmed the differential expression trends observed in clinical samples: upregulation of CACNA1D, MKI67, and CCNB2, and downregulation of CDKL5 and VAMP2.

conclusionsThis study, for the first time, identified several key molecular targets associated with tracheal stenosis through integrated clinical, computational, and experimental analyses. Dysregulation of ion channel-related genes (e.g., CACNA1D) and cell cycle regulators (e.g., MKI67, CCNB1, CCNB2) may contribute to stenosis by promoting airway smooth muscle proliferation and calcium signaling disturbances. Conversely, protective markers such as CALML4 and CDKL5 may inhibit proliferation and preserve cellular homeostasis. Notably, respiratory failure may amplify the pro-stenotic effects of MKI67 via enhanced inflammation or oxidative stress. The identified markers (e.g., CACNA1D, MKI67) show promise as early predictors for tracheal stenosis, facilitating early screening and risk stratification. Furthermore, targeted therapies-such as calcium channel blockers-against high-risk markers may offer novel treatment options. However, further studies with larger cohorts and mechanistic experiments are warranted to confirm these findings and explore clinical translation.

Indexed as

Tracheal StenosisAdultAgedAnimalsBiomarkersDisease Models, AnimalFemaleHumansLogistic ModelsMaleMiddle AgedRespiratory InsufficiencyRetrospective StudiesBiomarkersCACNA1DIon channelsLASSO regressionMolecular markersROC curveTracheal stenosis

Identifiers

PMID41272619
PMCPMC12751125

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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.