Evidence map›Paper›PMID 25867170›Full record

ArticleJournal of visualized experiments : JoVE2015

Quantitative mass spectrometric profiling of cancer-cell proteomes derived from liquid and solid tumors.

Hanibal Bohnenberger, Philipp Ströbel, Sebastian Mohr, Jasmin Corso, Tobias Berg, Henning Urlaub, Christof Lenz, Hubert Serve, Thomas Oellerich

Open access · greenAbstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS.Journal of the American Society for Mass Spectrometry · 2018
    Article
  4. Observational
  5. 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

9 authors at 5 institutions in 1 country.

Hanibal BohnenbergerInstitute of Pathology, University Medical Center, Göttingen; Hanibal.bohnenberger@med.uni-goettingen.de.
Philipp StröbelInstitute of Pathology, University Medical Center, Göttingen.
Sebastian MohrDepartment of Hematology/Oncology, Goethe University of Frankfurt.
Jasmin CorsoBioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry.
Tobias BergDepartment of Hematology/Oncology, Goethe University of Frankfurt.
Henning UrlaubBioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry; Bioanalytics, Institute of Clinical Chemistry, University Medical Center, Göttingen.
Christof LenzBioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry; Bioanalytics, Institute of Clinical Chemistry, University Medical Center, Göttingen.
Hubert ServeDepartment of Hematology/Oncology, Goethe University of Frankfurt; German Cancer Consortium; German Cancer Research Center.
Thomas OellerichDepartment of Hematology/Oncology, Goethe University of Frankfurt; German Cancer Consortium; German Cancer Research Center; Thomas.Oellerich@kgu.de.
Goethe University Frankfurt · DEMax Planck Institute for Biophysical Chemistry · DEUniversitätsmedizin Göttingen · DEDeutschen Konsortium für Translationale Krebsforschung · DEUniversity of Göttingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic biomarkers. However, methods for quantitative proteomic characterization of patient-derived tumors and in particular their cellular subpopulations are largely lacking. Here we describe an experimental set-up that allows quantitative analysis of proteomes of cancer cell subpopulations derived from either liquid or solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry followed by bioinformatic data analysis. To enrich specific cellular subsets, liquid tumors are first immunophenotyped by flow cytometry followed by FACS-sorting; for solid tumors, laser-capture microdissection is used to purify specific cellular subpopulations. In a second step, proteins are extracted from the purified cells and subsequently combined with a tumor-specific, SILAC-labeled spike-in standard that enables protein quantification. The resulting protein mixture is subjected to either gel electrophoresis or Filter Aided Sample Preparation (FASP) followed by tryptic digestion. Finally, tryptic peptides are analyzed using a hybrid quadrupole-orbitrap mass spectrometer, and the data obtained are processed with bioinformatic software suites including MaxQuant. By means of the workflow presented here, up to 8,000 proteins can be identified and quantified in patient-derived samples, and the resulting protein expression profiles can be compared among patients to identify diagnostic proteomic signatures or potential drug targets.

Indexed as

Chromatography, LiquidFlow CytometryHumansLaser Capture MicrodissectionMass SpectrometryNeoplasmsProteomeProteomicsProteome

Identifiers

PMID25867170
PMCPMC4401153
OpenAlexW1968130772

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.