Evidence map›Paper›PMID 39143582›Full record

ArticleRespiratory research2024

Integrated omics characterization reveals reduced cancer indicators and elevated inflammatory factors after thermal ablation in non-small cell lung cancer patients.

Xinglu Zhang, Shuai Shao, Nan Song, Baolu Yang, Fengjiao Liu, Zhaohui Tong, Feng Wang, Jieqiong Li

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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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. 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

8 authors.

Xinglu Zhang *Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Gongti South Road, Beijing, 100020, Chaoyang District, China.
Shuai Shao *Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Gongti South Road, Beijing, 100020, Chaoyang District, China.
Nan SongMedical Research Center, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Baolu YangDepartment of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Gongti South Road, Beijing, 100020, Chaoyang District, China.
Fengjiao LiuDepartment of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Gongti South Road, Beijing, 100020, Chaoyang District, China.
Zhaohui TongDepartment of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Gongti South Road, Beijing, 100020, Chaoyang District, China. tongzhaohuicy@sina.com.
Feng WangDepartment of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Gongti South Road, Beijing, 100020, Chaoyang District, China. tad2008@hotmail.com.
Jieqiong LiMedical Research Center, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China. jieqiongli2010@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThermal ablation is a minimally invasive treatment for non-small cell lung cancer (NSCLC). Aside from causing an immediate direct tumour cell injury, the effects of thermal ablation on the internal microenvironment are unknown. This study aimed to investigate the effects of thermal ablation on the plasma internal environment in patients with NSCLC.

methods128 plasma samples were collected from 48 NSCLC (pre [LC] and after thermal ablation [LC-T]) patients and 32 healthy controls (HCs). Olink proteomics and metabolomics were utilized to construct an integrated landscape of the cancer-related immune and inflammatory responses after ablation.

resultsCompared with HCs, LC patients exhibited 58 differentially expressed proteins (DEPs) and 479 differentially expressed metabolites (DEMs), which might participate in tumour progression and metastasis. Moreover, 75 DEPs were identified among the HC, LC, and LC-T groups. Forty-eight highly expressed DEPs (eg, programmed death-ligand 1 [PD-L1]) in the LC group were found to be downregulated after thermal ablation. These DEPs had significant impacts on pathways such as angiogenesis, immune checkpoint blockade, and pro-tumour chemotaxis. Metabolites involved in tumour cell survival were associated with these proteins at the expression and functional levels. In contrast, 19 elevated proteins (eg, interleukin [IL]-6) were identified after thermal ablation. These proteins were mainly associated with inflammatory response pathways (NF-κB signalling and tumour necrosis factor signalling) and immune cell activation.

conclusionsThermal ablation-induced changes in the host plasma microenvironment contribute to anti-tumour immunity in NSCLC, offering new insights into tumour ablation combined with immunotherapy. Trial registration This study was registered on the Chinese Clinical Trial Registry ( https://www.chictr.org.cn/index.html ). ID: ChiCTR2300076517. Registration Date: 2023-10-11.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsAgedBiomarkers, TumorFemaleHumansInflammation MediatorsMaleMetabolomicsMiddle AgedProteomicsTreatment OutcomeTumor MicroenvironmentBiomarkers, TumorInflammation MediatorsImmune responseLung cancerMetabolomicProteomicThermal ablation

Identifiers

PMID39143582
PMCPMC11325606

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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.