Evidence map›Paper›PMID 38491375›Full record

ArticleRespiratory research2024

Identifying a survival-associated cell type based on multi-level transcriptome analysis in idiopathic pulmonary fibrosis.

Fei Xu, Yun Tong, Wenjun Yang, Yiyang Cai, Meini Yu, Lei Liu, Qingkang Meng

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Article in Respiratory research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Fei XuDepartment of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yun TongDepartment of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Wenjun YangDepartment of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Yiyang CaiDepartment of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Meini YuDepartment of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Lei LiuDepartment of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China. liulei@ems.hrbmu.edu.cn.
Qingkang MengDepartment of Pharmacogenomics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China. mqk@hrbmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIdiopathic pulmonary fibrosis (IPF) is a progressive disease with a five-year survival rate of less than 40%. There is significant variability in survival time among IPF patients, but the underlying mechanisms for this are not clear yet. METHODS AND

resultsWe collected single-cell RNA sequence data of 13,223 epithelial cells taken from 32 IPF patients and bulk RNA sequence data from 456 IPF patients in GEO. Based on unsupervised clustering analysis at the single-cell level and deconvolution algorithm at bulk RNA sequence data, we discovered a special alveolar type 2 cell subtype characterized by high expression of CCL20 (referred to as ATII-CCL20), and found that IPF patients with a higher proportion of ATII-CCL20 had worse prognoses. Furthermore, we uncovered the upregulation of immune cell infiltration and metabolic functions in IPF patients with a higher proportion of ATII-CCL20. Finally, the comprehensive decision tree and nomogram were constructed to optimize the risk stratification of IPF patients and provide a reference for accurate prognosis evaluation.

conclusionsOur study by integrating single-cell and bulk RNA sequence data from IPF patients identified a special subtype of ATII cells, ATII-CCL20, which was found to be a risk cell subtype associated with poor prognosis in IPF patients. More importantly, the ATII-CCL20 cell subtype was linked with metabolic functions and immune infiltration.

Indexed as

Idiopathic Pulmonary FibrosisAlveolar Epithelial CellsEpithelial CellsGene Expression ProfilingHumansPrognosisTranscriptome

Identifiers

PMID38491375
PMCPMC10941445

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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.