Evidence map›Paper›PMID 40891213›Full record

ArticleAnalytical chemistry2025

Liquid Chromatographic and Mass Spectrometric Methods for Quantitative Proteomic Analysis from Single-Cell and Nanogram-Level Samples.

Yuefan Wang, Jongmin Woo, Zhenyu Sun, Diego Assis, Zachary Kirsch, Matthew Willetts, Matthew Albano, Hongyi Liu, Kenneth J Pienta, Sarah R Amend and 1 more

Abstract read
In one paragraph

Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Yuefan WangDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States.ORCID 0000-0001-5731-6143
Jongmin WooDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States.
Zhenyu SunDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States.ORCID 0009-0002-5004-5904
Diego AssisBruker Scientific, Billerica, Massachusetts 01821, United States.
Zachary KirschBruker Scientific, Billerica, Massachusetts 01821, United States.
Matthew WillettsBruker Scientific, Billerica, Massachusetts 01821, United States.
Matthew AlbanoBruker Scientific, Billerica, Massachusetts 01821, United States.
Hongyi LiuDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States.ORCID 0000-0002-9444-3632
Kenneth J PientaCancer Ecology Center, James Buchanan Brady Urological Institute, Johns Hopkins University, Baltimore, Maryland 21287, United States.
Sarah R AmendCancer Ecology Center, James Buchanan Brady Urological Institute, Johns Hopkins University, Baltimore, Maryland 21287, United States.
Hui ZhangDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States.ORCID 0000-0001-8726-7098

Funding

Proteogenomic Characterization of Tumor Tissues and Preclinical Models with High PrecisionU24CA271079 · NCI · JOHNS HOPKINS UNIVERSITY · PI DANIEL Wanyui CHAN, Hui Zhang · 2022 to 2026
$6.6M
Biomarker Reference LaboratoryU2CCA271895 · NCI · JOHNS HOPKINS UNIVERSITY · PI DANIEL Wanyui CHAN · 2023 to 2026
$4.6M
Development of a panel of multiplex biomarkers for the early detection of pancreatic ductal adenocarcinoma and high-risk lesionsU01CA274514 · NCI · JOHNS HOPKINS UNIVERSITY · PI Randall Brand, DANIEL Wanyui CHAN · 2023 to 2026
$3.2M
NCI NIH HHS U01 CA274514NCI NIH HHS U24 CA271079NCI NIH HHS U2C CA271895
6 · The paper itself

Abstract

Liquid chromatography (LC) and mass spectrometry (MS) are two critical components in proteomics. Advances in methods for both LC and MS have significantly enhanced protein identification and quantifications of limited amounts of proteins, particularly at the picogram-to-nanogram level of proteins. In this study, we explored various LC conditions and MS platforms to optimize protein identification and quantification using data-independent acquisition (DIA). Our investigation focused on evaluating the sensitivity for protein identification, reproducibility of quantification, and robustness across multiple models, specifically focused on analyzing proteins at pico- to nanogram levels, with an emphasis on single-cell proteomics. We further applied our approach for the proteomic analysis of HeLa single cells. Overall, we identified and quantified over 6300 proteins at the single-cell level amount of peptides with a coefficient of variation (CV) of less than 20%, and detected up to 5000 proteins from isolated single HeLa cell samples. Finally, we analyzed docetaxel-treated and nontreated PC3 cells to reveal proteome changes at the single-cell level. This study provides a comprehensive technical evaluation for LC-MS methods in protein identification and quantification for analytical applications involving single-cell proteomics from the picogram to nanogram level of proteins.

Indexed as

Mass SpectrometryProteomeProteomicsSingle-Cell AnalysisChromatography, LiquidHeLa CellsHumansProteome

Identifiers

PMID40891213
PMCPMC12405731

What OpenQuestion holds

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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 OpenQuestion graph.