Evidence map›Paper›PMID 29363612›Full record

ArticleMolecular & cellular proteomics : MCP2018

Spatial Tissue Proteomics Quantifies Inter- and Intratumor Heterogeneity in Hepatocellular Carcinoma (HCC).

Katarzyna Buczak, Alessandro Ori, Joanna M Kirkpatrick, Kerstin Holzer, Daniel Dauch, Stephanie Roessler, Volker Endris, Felix Lasitschka, Luca Parca, Alexander Schmidt and 5 more

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Article
  2. Article
  3. Spatial proteomics: technical evolution and applications in cancer research.Frontiers in cell and developmental biology · 2026
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. The Breast Cancer Proteome and Precision Oncology.Cold Spring Harbor perspectives in medicine · 2023
    Review
  13. Review
  14. Review
  15. Review
  16. Automated Sample Preparation for Mass Spectrometry-Based Clinical Proteomics.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  17. Article
  18. Article
  19. Article
  20. 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

15 authors.

Katarzyna BuczakFrom the ‡European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.
Alessandro OriFrom the ‡European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.
Joanna M Kirkpatrick§Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany.
Kerstin Holzer‖Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.
Daniel Dauch**Department of Internal Medicine VIII, University Hospital Tübingen, 72076 Tübingen, Germany.
Stephanie Roessler‖Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.
Volker Endris‖Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.
Felix Lasitschka‖Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.
Luca ParcaFrom the ‡European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.
Alexander Schmidt¶¶Biozentrum, University of Basel, Basel, Switzerland.
Lars Zender**Department of Internal Medicine VIII, University Hospital Tübingen, 72076 Tübingen, Germany.
Peter Schirmacher‖Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.
Jeroen Krijgsveld¶European Molecular Biology Laboratory, Proteomics Core Facility, Heidelberg, Germany.
Stephan SingerFrom the ‡European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany; martin.beck@embl.de stephan.singer@uni-greifswald.de.
Martin BeckFrom the ‡European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany; martin.beck@embl.de stephan.singer@uni-greifswald.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The interpatient variability of tumor proteomes has been investigated on a large scale but many tumors display also intratumoral heterogeneity regarding morphological and genetic features. It remains largely unknown to what extent the local proteome of tumors intrinsically differs. Here, we used hepatocellular carcinoma as a model system to quantify both inter- and intratumor heterogeneity across human patient specimens with spatial resolution. We defined proteomic features that distinguish neoplastic from the directly adjacent nonneoplastic tissue, such as decreased abundance of NADH dehydrogenase complex I. We then demonstrated the existence of intratumoral variations in protein abundance that re-occur across different patient samples, and affect clinically relevant proteins, even in the absence of obvious morphological differences or genetic alterations. Our work demonstrates the suitability and the benefits of using mass spectrometry-based proteomics to analyze diagnostic tumor specimens with spatial resolution. Data are available via ProteomeXchange with identifier PXD007052.

Indexed as

AdultAgedAged, 80 and overAnimalsCarcinoma, HepatocellularFemaleHumansLiverLiver NeoplasmsMaleMass SpectrometryMiceMiddle AgedNeoplasm ProteinsProteomicsNeoplasm Proteins

Identifiers

PMID29363612
PMCPMC5880102

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.