Evidence map›Paper›PMID 37410292›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Visualization of Small Intact Proteins in Breast Cancer FFPE Tissue.

Marco Giampà, Maria K Andersen, Sebastian Krossa, Vanna Denti, Andrew Smith, Siver Andreas Moestue

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Marco GiampàDepartment of Clinical and Molecular Medicine, NTNU - Norwegian University of Science and Technology, Trondheim, Norway. marco.giampa@kuleuven.be.
Maria K AndersenDepartment of Circulation and Medical Imaging, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.
Sebastian KrossaDepartment of Circulation and Medical Imaging, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.
Vanna DentiProteomics and Metabolomics Unit, Department of Medicine and Surgery, Vedano al Lambro, Italy.
Andrew SmithProteomics and Metabolomics Unit, Department of Medicine and Surgery, Vedano al Lambro, Italy.
Siver Andreas MoestueDepartment of Clinical and Molecular Medicine, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular visualization of metabolites, lipids, and proteins by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is becoming an in-demand analytical approach to aid the histopathological analysis of breast cancer. Particularly, proteins seem to play a role in cancer progression, and specific proteins are currently used in the clinic for staging. Formalin-fixed paraffin-embedded (FFPE) tissues are ideal for correlating the molecular markers with clinical outcomes due to their long-term storage. So far, to obtain proteomic information by MSI from this kind of tissue, antigen retrieval and tryptic digestion steps are required. In this chapter, we present a protocol to spatially detect small proteins in tumor and necrotic regions of patient-derived breast cancer xenograft FFPE tissues without employing any on-tissue digestion. This protocol can be used for other kinds of FFPE tissue following specific optimization of the sample preparation phases.

Indexed as

Breast NeoplasmsFemaleFormaldehydeHumansParaffin EmbeddingProteinsProteomicsSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationTissue FixationFormaldehydeProteinsBreast cancerFFPE tissueMALDI MSIProtein

Identifiers

PMID37410292

What OpenQuestion holds

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Registered trials

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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.