Evidence map›Paper›PMID 38312939›Full record

ArticleJournal of lipids2024

Plasma Lipidomics Profiling to Identify the Biomarkers of Diagnosis and Radiotherapy Response for Advanced Non-Small-Cell Lung Cancer Patients.

Minghe Lv, Shali Shao, Yajing Du, Xibing Zhuang, Xiangdong Wang, Tiankui Qiao

Open access · hybridAbstract read
In one paragraph

Article in Journal of lipids, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 21% of its field
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

7 citing papers in PubMed, 6 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Minghe LvCenter for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Jinshan District, Shanghai 201508, China.ORCID https://orcid.org/0000-0001-9342-773X
Shali ShaoCenter for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Jinshan District, Shanghai 201508, China.
Yajing DuCenter for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Jinshan District, Shanghai 201508, China.
Xibing ZhuangCenter for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Jinshan District, Shanghai 201508, China.
Xiangdong WangCenter for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Jinshan District, Shanghai 201508, China.
Tiankui QiaoCenter for Tumor Diagnosis and Therapy, Jinshan Hospital, Fudan University, Jinshan District, Shanghai 201508, China.ORCID https://orcid.org/0000-0002-0454-0616
Jinshan Hospital of Fudan University · CNShanghai University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Advanced lung cancer that contributes to a heavy burden on medical institutions is the leading cause of cancer-related death and is often accompanied by metabolic disorders. In this study, we aimed to explore the biomarkers of diagnosis and radiotherapy response in non-small-cell lung cancer (NSCLC) patients by plasma lipidomics analysis. Method: Using triple-quadrupole mass spectrometer analysis, our research characterized the plasma lipid metabolomics profile of 25 healthy controls and 31 advanced NSCLC patients in each of three different radiotherapy phases. Results: The results showed altered lipid elements and concentrations among NSCLC patients with different radiotherapy phases, NSCLC subtypes, and different radiotherapeutic responses. We found that compared to the healthy controls, myelin-associated glycoprotein (MAG), phosphatidylinositol (PI), and phosphatidylserine (PS) were mainly and significantly altered lipid elements (> twofold, and Conclusion: Our results indicated that plasma lipidomics profiling might have a vital value to uncover the heterogeneity of lipid metabolism in healthy people and advanced NSCLC patients with different radiotherapy phase, and further to screen out radiotherapeutic response-specific biomarkers.

Identifiers

PMID38312939
PMCPMC10838201
OpenAlexW4391276202

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.