Evidence map›Paper›PMID 39107932›Full record

ArticleThe clinical respiratory journal2024

Identification of Biomarkers for Lung Adenocarcinoma With Qi Deficiency and Phlegm Dampness.

Jiabin Chen, Sheng Wang, Qiaolei Yang, Yongjun Zhang, Jianfei Shen, Kequn Chai

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Article in The clinical respiratory journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Jiabin ChenDepartment of Oncology, Tongde Hospital of Zhejiang, affiliated to Zhejiang Chinese Medicine University, Hangzhou, China.
Sheng WangDepartment of Respiratory, Jinhua Guangfu Hospital, Jinhua, China.
Qiaolei YangInstitute of Pharmaceutical Biotechnology, Faculty of Medicine, Zhejiang University, Hangzhou, China.
Yongjun ZhangDepartment of Integrated Chinese and Western Medicine, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, China.ORCID https://orcid.org/0000-0002-2326-7870
Jianfei ShenDepartment of Thoracic Surgery, Taizhou Hospital, Taizhou, China.ORCID https://orcid.org/0000-0001-6123-0959
Kequn ChaiDepartment of Oncology, Tongde Hospital of Zhejiang, affiliated to Zhejiang Chinese Medicine University, Hangzhou, China.ORCID https://orcid.org/0000-0001-5997-9733

Funding

Key R & D plan of Zhejiang Province 2022C03152Key research project of TCM in Zhejiang Province 2022ZZ006National Natural Science Foundation of China 82274322
6 · The paper itself

Abstract

backgroundQi deficiency and phlegm dampness (QPD) is one of the most common traditional Chinese medicine (TCM) syndromes in lung adenocarcinoma (LUAD). This study aimed to identify syndrome-specific biomarkers for LUAD with QPD syndrome.

methodsPeripheral blood mononuclear cells (PBMCs) from LUAD patients with QPD, LUAD patients with non-QPD (N-QPD), and healthy control (H) were collected and analyzed with RNA-seq to identify differentially expressed genes (DEGs). The area under the receiver operator characteristic curve (AUC) of each DEG was calculated, and the top 10 highest AUC DEGs were validated by qRT-PCR. Logistic regression analysis was used to develop a diagnostic model evaluated with AUC.

resultsA total of 135 individuals were enrolled in this study (training set: 15 QPD, 15 N-QPD, 15 H; validation set: 30 QPD, 30 N-QPD, 30 H). A total of 1480 DEGs were identified between QPD and N-QPD. The qRT-PCR results showed that the expression of DDR2 was downregulated, and PPARG was upregulated, which was in line with the finding of the training set. We developed a diagnostic model with these two genes. The AUC of the diagnostic model in the training cohort and validation cohort was 0.891 and 0.777, respectively.

conclusionsWe identified the two genes (DDR2 and PPARG) as syndrome-specific biomarkers for LUAD with QPD syndrome and developed a novel diagnostic model, which may help to improve the accuracy and sensibility of clinical diagnosis and provide a new target for natural drug treatment of LUAD.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorLung NeoplasmsMedicine, Chinese TraditionalAgedCase-Control StudiesFemaleHumansLeukocytes, MononuclearMaleMiddle AgedPPAR gammaQiROC CurveBiomarkers, TumorPPAR gammaPPARG protein, humanbiomarkerlung adenocarcinomaQi deficiency and phlegm dampnessRNA‐seqtraditional Chinese medicine

Identifiers

PMID39107932
PMCPMC11303266

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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 Socratic graph.