Evidence map›Paper›PMID 34607525›Full record

ReviewExpert review of proteomics2021

Laser Capture Proteomics: spatial tissue molecular profiling from the bench to personalized medicine.

Lance A Liotta, Philip A Pappalardo, Alan Carpino, Amanda Haymond, Marissa Howard, Virginia Espina, Julie Wulfkuhle, Emanuel Petricoin

Open access · bronzeAbstract readReview
In one paragraph

Review in Expert review of proteomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

27 citing papers in PubMed, 38 citations in OpenAlex.

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  11. Laser capture microdissection.Nature reviews. Methods primers · 2025
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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 at 1 institution in 1 country.

Lance A LiottaCenter For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA.
Philip A PappalardoCenter For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA.
Alan CarpinoFluidigm Corporation, South San Francisco, CA, USA.
Amanda HaymondCenter For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA.
Marissa HowardCenter For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA.
Virginia EspinaCenter For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA.ORCID 0000-0001-5080-5972
Julie WulfkuhleCenter For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA.
Emanuel PetricoinCenter For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA.
George Mason University · US

Funding

Probes to target the 3-way hotspot of IL1RacP to abolish aberrant interleukin inflammationR01AR068436 · NIAMS · GEORGE MASON UNIVERSITY · PI LIOTTA, LANCE ALLEN · 2015 to 2017
$1.7M
Protein painting identifies therapeutic targets at protein-protein interfacesR33CA206937 · NCI · GEORGE MASON UNIVERSITY · PI LIOTTA, LANCE ALLEN · 2016 to 2018
$1.2M
Protein Painting reveals hidden protein-protein interaction domainsR21CA177535 · NCI · GEORGE MASON UNIVERSITY · PI LIOTTA, LANCE ALLEN · 2013 to 2014
$482k
Surrogate and Sentinal Technologies to Monitor Stability of Cancer PhosphoproteinR21CA125698 · NCI · GEORGE MASON UNIVERSITY · PI LIOTTA, LANCE ALLEN · 2008 to 2009
$330k
NCI NIH HHS R21 CA125698NCI NIH HHS R21 CA177535NCI NIH HHS R33 CA206937NIAMS NIH HHS R01 AR068436
6 · The paper itself

Abstract

introductionLaser Capture Microdissection (LCM) uses a laser to isolate, or capture, specific cells of interest in a complex heterogeneous tissue section, under direct microscopic visualization. Recently, there has been a surge of publications using LCM for tissue spatial molecular profiling relevant to a wide range of research topics. AREAS COVERED: We summarize the many advances in tissue Laser Capture Proteomics (LCP) using mass spectrometry for discovery, and protein arrays for signal pathway network mapping. This review emphasizes: a) transition of LCM phosphoproteomics from the lab to the clinic for individualized cancer therapy, and b) the emerging frontier of LCM single cell molecular analysis combining proteomics with genomic, and transcriptomic analysis. The search strategy was based on the combination of MeSH terms with expert refinement. EXPERT OPINION: LCM is complemented by a rich set of instruments, methodology protocols, and analytical A.I. (artificial intelligence) software for basic and translational research. Resolution is advancing to the tissue single cell level. A vision for the future evolution of LCM is presented. Emerging LCM technology is combining digital and AI guided remote imaging with automation, and telepathology, to a achieve multi-omic profiling that was not previously possible.

Indexed as

Precision MedicineProteomicsArtificial IntelligenceLaser Capture MicrodissectionLasersDCIS (Ductal Carcinoma in Situ)ERBB (Epidermal growth factor receptor family)kinase signalingLaser Capture Microdissectionmass spectrometryneoadjuvant therapyphosphoproteinproteomicstissue spatial profilingtumor-host microenvironment

Identifiers

PMID34607525
PMCPMC10720974
OpenAlexW3203331740

What OpenQuestion 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 OpenQuestion graph.