Evidence map›Paper›PMID 37218922›Full record

ReviewProteomes2023

Spatial Proteomics for the Molecular Characterization of Breast Cancer.

Klára Brožová, Brigitte Hantusch, Lukas Kenner, Klaus Kratochwill

Open access · goldAbstract readReview
In one paragraph

Review in Proteomes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.8field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. MR-SPJournal of proteome research · 2026
    Article
  5. Review
  6. Article
  7. Review
  8. Review
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

4 authors at 2 institutions in 1 country.

Klára BrožováCore Facility Proteomics, Medical University of Vienna, 1090 Vienna, Austria.
Brigitte HantuschDepartment of Pathology, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-9126-003X
Lukas KennerDepartment of Pathology, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0003-2184-1338
Klaus KratochwillCore Facility Proteomics, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0003-0803-614X
Medical University of Vienna · ATUniversity of Veterinary Medicine Vienna · AT

Funding

Austrian Science Fund FWF P 26011Austrian Science Fund FWF P 29251Austrian Science Fund FWF P 34781
6 · The paper itself

Abstract

Breast cancer (BC) is a major global health issue, affecting a significant proportion of the female population and contributing to high rates of mortality. One of the primary challenges in the treatment of BC is the disease's heterogeneity, which can lead to ineffective therapies and poor patient outcomes. Spatial proteomics, which involves the study of protein localization within cells, offers a promising approach for understanding the biological processes that contribute to cellular heterogeneity within BC tissue. To fully leverage the potential of spatial proteomics, it is critical to identify early diagnostic biomarkers and therapeutic targets, and to understand protein expression levels and modifications. The subcellular localization of proteins is a key factor in their physiological function, making the study of subcellular localization a major challenge in cell biology. Achieving high resolution at the cellular and subcellular level is essential for obtaining an accurate spatial distribution of proteins, which in turn can enable the application of proteomics in clinical research. In this review, we present a comparison of current methods of spatial proteomics in BC, including untargeted and targeted strategies. Untargeted strategies enable the detection and analysis of proteins and peptides without a predetermined molecular focus, whereas targeted strategies allow the investigation of a predefined set of proteins or peptides of interest, overcoming the limitations associated with the stochastic nature of untargeted proteomics. By directly comparing these methods, we aim to provide insights into their strengths and limitations and their potential applications in BC research.

Indexed as

breast cancerMALDI imagingmass spectrometry imagingproteomics

Identifiers

PMID37218922
PMCPMC10204503
OpenAlexW4377563848

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.