Evidence map›Paper›PMID 40904101›Full record

ArticleProteomics2025

SLB-msSIM: A Spectral Library-Based Multiplex Segmented SIM Platform for Single-Cell Proteomic Analysis.

Lakmini Senavirathna, Cheng Ma, Van-An Duong, Hong-Yuan Tsai, Ru Chen, Sheng Pan

Abstract read
In one paragraph

Article in Proteomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Lakmini SenavirathnaThe Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, USA.ORCID 0000-0003-0911-7320
Cheng MaThe Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, USA.
Van-An DuongThe Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, USA.ORCID 0000-0002-4676-1804
Hong-Yuan TsaiDepartment of Medicine, Baylor College of Medicine, Houston, Texas, USA.
Ru ChenDepartment of Medicine, Baylor College of Medicine, Houston, Texas, USA.
Sheng PanThe Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, USA.

Funding

Early detection of pancreatic cancer in diabeticsR01CA180949 · NCI · UNIVERSITY OF WASHINGTON · PI CHEN, RU, PAN, SHENG · 2014 to 2018
$2.9M
Elucidating the role of gut microbiota in colitis-associated colorectal cancerR01CA276173 · NCI · BAYLOR COLLEGE OF MEDICINE · PI Ru Chen, Sheng Pan · 2023 to 2026
$2.5M
Cancer Prevention & Research Institute of Texas (CPRIT) RP210111National Institutes of Health (NIH) R01CA180949National Institutes of Health (NIH) R01CA276173NCI NIH HHS R01 CA180949NCI NIH HHS R01 CA276173
6 · The paper itself

Abstract

Mass spectrometry (MS)-based single-cell proteomics, while highly challenging, offers unique potential for a wide range of applications to interrogate cellular heterogeneity, trajectories, and phenotypes at a functional level. We report here the development of the spectral library-based multiplex segmented selected ion monitoring (SLB-msSIM) method, a conceptually unique approach with significantly enhanced sensitivity and robustness for single-cell analysis. The single-cell MS data is acquired by a multiplex segmented selected ion monitoring (msSIM) technique, which sequentially applies multiple isolation cycles with the quadrupole using a wide isolation window in each cycle to accumulate and store precursor ions in the C-trap for a single scan in the Orbitrap. Proteomic identification is achieved through spectral matching using a well-defined spectral library. We applied the SLB-msSIM method to interrogate cellular heterogeneity in various pancreatic cancer cell lines, revealing common and distinct functional traits among PANC-1, MIA-PaCa2, AsPc-1, HPAF, and normal HPDE cells. Furthermore, for the first time, our novel data revealed the diverse cell trajectories of individual PANC-1 cells during the induction and reversal of epithelial-mesenchymal transition (EMT). Collectively, our results demonstrate that SLB-msSIM is a highly sensitive and robust platform, applicable to a wide range of instruments for single-cell proteomic studies. SUMMARY: We present the SLB-msSIM method, a conceptually unique approach in mass spectrometry-based single-cell proteomics that significantly enhances sensitivity and robustness. This innovative platform enables detailed analysis of the proteome landscape, capturing cellular heterogeneity, trajectories, and phenotypes at a single-cell resolution. Utilizing the SLB-msSIM technique, we identified both common and distinct functional traits among various pancreatic cancer cell lines and normal cells. Moreover, our study unveiled new insights into the diverse cell trajectories of individual cancer cells during the induction and reversal of epithelial-mesenchymal transition (EMT). In summary, the SLB-msSIM method offers a highly sensitive and robust platform for single-cell proteomic studies, with broad applicability across different instruments.

Indexed as

Mass SpectrometryPancreatic NeoplasmsProteomeProteomicsSingle-Cell AnalysisCell Line, TumorHumansProteomecancer cell heterogeneityepithelial‐mesenchymal transition (EMT)mass spectrometryproteomicssingle‐cell proteomicsspectral library‐based multiplex segmented selected ion monitoring (SLB‐msSIM)

Identifiers

PMID40904101
PMCPMC12491930

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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.