Evidence map›Paper›PMID 36388454›Full record

ArticleMaterials today. Bio2022

Serum amino acids quantification by plasmonic colloidosome-coupled MALDI-TOF MS for triple-negative breast cancer diagnosis.

Xinyue Han, Dandan Li, Shurong Wang, Yuxiang Lin, Yun Liu, Ling Lin, Liang Qiao

Open access · goldAbstract read
In one paragraph

Article in Materials today. Bio, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

9 citing papers in PubMed, 18 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

7 authors at 2 institutions in 1 country.

Xinyue HanDepartment of Chemistry, Shanghai Stomatological Hospital, and Zhongshan Hospital, Fudan University, Shanghai, 200000, China.
Dandan LiDepartment of Chemistry, Shanghai Stomatological Hospital, and Zhongshan Hospital, Fudan University, Shanghai, 200000, China.
Shurong WangDepartment of Chemistry, Shanghai Stomatological Hospital, and Zhongshan Hospital, Fudan University, Shanghai, 200000, China.
Yuxiang LinDepartment of Breast Surgery, Affiliated Union Hospital of Fujian Medical University, Fuzhou, 350001, China.
Yun LiuDepartment of Chemistry, Shanghai Stomatological Hospital, and Zhongshan Hospital, Fudan University, Shanghai, 200000, China.
Ling LinDepartment of Chemistry, Shanghai Stomatological Hospital, and Zhongshan Hospital, Fudan University, Shanghai, 200000, China.
Liang QiaoDepartment of Chemistry, Shanghai Stomatological Hospital, and Zhongshan Hospital, Fudan University, Shanghai, 200000, China.
Fudan University · CNFujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) is characterized with high diffusion, metastasis and recurrence. The early treatment and early diagnosis of TNBC are highly important for the survival of TNBC patients. Nevertheless, traditional methods for TNBC diagnosis, i.e. imaging examinations and tissue biopsy, cannot achieve early diagnosis, are invasive and associated with the risk of arousing tumor spreading. Herein, we developed colloidosomes-coupled matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to quantify free serum amino acids for the diagnosis of TNBC. Gold nanoparticles (AuNPs) were used to form water-in-oil colloidosomes and to encapsulate deproteinated serum for MALDI-TOF MS analysis. With small sample spot size (200-300 μm) and densely packed AuNPs monolayer, the dried sample spot from colloidosomes can facilitate MALDI-TOF MS analysis of small molecule metabolites with high sensitivity, high reproducibility and good quantification performance. We used the method to quantify free amino acids in human serum. A cohort of 30 TNBC patients, 30 breast lump patients and 30 healthy controls were recruited for the study. It was found that the concentrations of free amino acids in TNBC patients were significantly lower than that of heathy controls, and the concentrations were also significantly different from that of breast lump patients. Based on the quantities of serum free amino acids, we have built a machine learning-based classification model to differentiate TNBC patients from the controls, including healthy controls and breast lump patients, and the sensitivity, specificity and accuracy were 95%, 100% and 97%, respectively. The assay consumes less than 1 ​μL serum per analysis, and takes only minutes to analyze a sample. With the advantages of low cost, low sample consumption, high throughput in analysis and high accuracy in identification, the non-invasive liquid biopsy method is promising to be applied to clinical diagnosis of TNBC.

Indexed as

Amino acid quantificationLiquid biopsyMALDI-TOF MSPlasmonic colloidosomeTriple-negative breast cancer

Identifiers

PMID36388454
PMCPMC9647586
OpenAlexW4308261160

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.