Evidence map›Paper›PMID 38587042›Full record

ArticleThoracic cancer2024

Single-cell RNA sequencing reveals aberrant sphingolipid metabolism in non-small cell lung cancer impacts tumor-associated macrophages and stimulates angiogenesis via macrophage inhibitory factor signaling.

Luyan Shen, Jingtao Liu, Fengling Hu, Yifan Fang, Yaya Wu, Wei Zhao, Shaohua Ma

Abstract read
In one paragraph

Article in Thoracic cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  7. [Plasma lipidomics-based exploration of potential biomarkers of metastasis in pediatric medulloblastoma].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2025
    Article
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  10. Review
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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

7 authors.

Luyan ShenKey Laboratory of Carcinogenesis and Translational Research, Department of Thoracic Surgery I, Peking University Cancer Hospital and Institute, Beijing, China.
Jingtao LiuKey Laboratory of Carcinogenesis and Translational Research, Department of Pharmacology, Peking University Cancer Hospital and Institute, Beijing, China.
Fengling HuKey Laboratory of Carcinogenesis and Translational Research, Department of Thoracic Surgery I, Peking University Cancer Hospital and Institute, Beijing, China.
Yifan FangKey Laboratory of Carcinogenesis and Translational Research, Department of Thoracic Surgery I, Peking University Cancer Hospital and Institute, Beijing, China.
Yaya WuKey Laboratory of Carcinogenesis and Translational Research, Department of Thoracic Surgery I, Peking University Cancer Hospital and Institute, Beijing, China.
Wei ZhaoKey Laboratory of Carcinogenesis and Translational Research, Department of Clinical Laboratory, Peking University Cancer Hospital and Institute, Beijing, China.
Shaohua MaState Key Laboratory of Molecular Oncology, Beijing, Key Laboratory of Carcinogenesis and Translational Research, Department of Thoracic Surgery I, Peking University Cancer Hospital and Institute, Beijing, China.ORCID 0000-0002-7399-6975

Funding

National Key Research and Development Program of China 2021YFC2500902National Natural Science Foundation of China 82373247Science Foundation of Peking University Cancer Hospital BJCH2024GG01Science Foundation of Peking University Cancer Hospital PY202334
6 · The paper itself

Abstract

backgroundSphingolipids not only serve as structural components for maintaining cell membrane fluidity but also function as bioactive molecules involved in cell signaling and the regulation of various biological processes. Their pivotal role in cancer cell development, encompassing cancer cell proliferation, migration, angiogenesis, and metastasis, has been a focal point for decades. However, the contribution of sphingolipids to the complexity of tumor microenvironment promoting cancer progression has been rarely investigated.

methodsThrough the integration of publicly available bulk RNA-seq and single-cell RNA-seq data, we conducted a comprehensive analysis to compare the transcriptomic features between tumors and adjacent normal tissues, thus elucidating the intricacies of the tumor microenvironment (TME).

resultsDisparities in sphingolipid metabolism (SLM)-associated genes were observed between normal and cancerous tissues, with the TME characterized by the enrichment of sphingolipid signaling in macrophages. Cellular interaction analysis revealed robust communication between macrophages and cancer cells exhibiting low SLM, identifying the crucial ligand-receptor pair, macrophage inhibitory factor (MIF)-CD74. Pseudo-time analysis unveiled the involvement of SLM in modulating macrophage polarization towards either M1 or M2 phenotypes. Categorizing macrophages into six subclusters based on gene expression patterns and function, the SPP1+ cluster, RGS1+ cluster, and CXCL10+ cluster were likely implicated in sphingolipid-induced M2 macrophage polarization. Additionally, the CXCL10+, AGER+, and FABP4+ clusters were likely to be involved in angiogenesis through their interaction with endothelial cells.

conclusionBased on multiple scRNA-seq datasets, we propose that a MIF-targeted strategy could potentially impede the polarization from M1 to M2 and impair tumor angiogenesis in low-SLM non-small cell lung cancer (NSCLC), demonstrating its potent antitumor efficacy.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsNeovascularization, PathologicSphingolipidsTumor-Associated MacrophagesAngiogenesisAnimalsHumansMacrophage Migration-Inhibitory FactorsMiceSequence Analysis, RNASignal TransductionSingle-Cell AnalysisTumor MicroenvironmentMacrophage Migration-Inhibitory FactorsSphingolipidsmacrophage polarizationMIFNSCLCScRNA‐sequencesphingolipid metabolism

Identifiers

PMID38587042
PMCPMC11091791

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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.