Evidence map›Paper›PMID 35406537›Full record

ArticleCancers2022

MALDI Mass Spectrometry Imaging-Prognostic Pathways and Metabolites for Renal Cell Carcinomas.

Franziska Erlmeier, Na Sun, Jian Shen, Annette Feuchtinger, Achim Buck, Verena M Prade, Thomas Kunzke, Peter Schraml, Holger Moch, Michael Autenrieth and 3 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.7field-weighted citation impact, top 18% 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

12 citing papers in PubMed, 18 citations in OpenAlex.

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  8. Sample Preparation for Metabolite Detection in Mass Spectrometry Imaging.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
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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

13 authors at 5 institutions in 2 countries.

Franziska ErlmeierInstitute of Pathology, University Hospital Erlangen-Nuremberg, 91054 Erlangen, Germany.
Na SunResearch Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany.
Jian ShenResearch Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany.
Annette FeuchtingerResearch Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany.
Achim BuckResearch Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany.
Verena M PradeResearch Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany.
Thomas KunzkeResearch Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany.
Peter SchramlDepartment of Pathology and Molecular Pathology, University Hospital Zurich, 8091 Zurich, Switzerland.
Holger MochDepartment of Pathology and Molecular Pathology, University Hospital Zurich, 8091 Zurich, Switzerland.ORCID 0000-0002-7986-2839
Michael AutenriethDepartment of Urology, Rechts der Isar Medical Center, Technical University of Munich, 81675 Munich, Germany.
Wilko WeichertInstitute of Pathology, Technical University Munich, 81675 Munich, Germany.
Arndt HartmannInstitute of Pathology, University Hospital Erlangen-Nuremberg, 91054 Erlangen, Germany.
Axel WalchResearch Unit Analytical Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany.
Helmholtz Zentrum München · DEUniversitätsklinikum Erlangen · DEUniversity Hospital of Zurich · CHTechnical University of Munich · DETUM Klinikum · DE

Funding

Deutsche Forschungsgemeinschaft ER 795/1-1Deutsche Forschungsgemeinschaft SFB 205 / S01Swiss National Science Foundation 31003A-160126; and 310030_166391/1
6 · The paper itself

Abstract

High mass resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a suitable method for biomarker detection for several tumor entities. Renal cell carcinoma (RCC) is the seventh most common cancer type and accounts for more than 80% of all renal tumors. Prognostic biomarkers for RCC are still missing. Therefore, we analyzed a large, multicenter cohort including the three most common RCC subtypes (clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC)) by MALDI for prognostic biomarker detection. MALDI-Fourier-transform ion cyclotron resonance (FT-ICR)-MSI analysis was performed for renal carcinoma tissue sections from 782 patients. SPACiAL pipeline was integrated for automated co-registration of histological and molecular features. Kaplan-Meier analyses with overall survival as endpoint were executed to determine the metabolic features associated with clinical outcome. We detected several pathways and metabolites with prognostic power for RCC in general and also for different RCC subtypes.

Indexed as

chromophobe renal cell carcinomaclear-cell renal cell carcinomamass spectrometry imagingmetabolomicspapillary renal cell carcinoma

Identifiers

PMID35406537
PMCPMC8996951
OpenAlexW4221085866

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.