Evidence map›Paper›PMID 28356110›Full record

ReviewCell communication and signaling : CCS2017

Understanding cell signaling in cancer stem cells for targeted therapy - can phosphoproteomics help to reveal the secrets?

Wolfgang Gruber, Tamara Scheidt, Fritz Aberger, Christian G Huber

Open access · goldAbstract readReview
In one paragraph

Review in Cell communication and signaling : CCS, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.2field-weighted citation impact, top 10% 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

10 citing papers in PubMed, 29 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Metabolic Adaptations in Cancer Stem Cells.Frontiers in oncology · 2020
    Review
  6. Article
  7. Molecular Targeted Therapy Approach to Musculoskeletal Tumors.Techniques in orthopaedics (Rockville, Md.) · 2018
    Article
  8. Article
  9. Article
  10. 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

4 authors at 1 institution in 1 country.

Wolfgang GruberDepartment of Molecular Biology, Cancer Cluster Salzburg, Paris-Lodron University of Salzburg, Hellbrunner Strasse 34, 5020, Salzburg, Austria.
Tamara ScheidtDepartment of Molecular Biology, Cancer Cluster Salzburg, Paris-Lodron University of Salzburg, Hellbrunner Strasse 34, 5020, Salzburg, Austria.
Fritz AbergerDepartment of Molecular Biology, Cancer Cluster Salzburg, Paris-Lodron University of Salzburg, Hellbrunner Strasse 34, 5020, Salzburg, Austria. fritz.aberger@sbg.ac.at.ORCID http://orcid.org/0000-0003-2009-6305
Christian G HuberDepartment of Molecular Biology, Cancer Cluster Salzburg, Paris-Lodron University of Salzburg, Hellbrunner Strasse 34, 5020, Salzburg, Austria. c.huber@sbg.ac.at.
University of Salzburg · AT

Funding

Austrian Science Fund FWF P 25629
6 · The paper itself

Abstract

backgroundCancer represents heterogeneous and aberrantly proliferative manifestations composed of (epi)genetically and phenotypically distinct cells with a common clonal origin. Cancer stem cells (CSC) make up a rare subpopulation with the remarkable capacity to initiate, propagate and spread a malignant disease. Furthermore, CSC show increased therapy resistance, thereby contributing to disease relapse. Elimination of CSC, therefore, is a crucial aim to design efficacious treatments for long-term survival of cancer patients. In this article, we highlight the nature of CSC and propose that phosphoproteomics based on unbiased high-performance liquid chromatography-mass spectrometry provides a powerful tool to decipher the molecular CSC programs. Detailed knowledge about the regulation of signaling processes in CSC is a prerequisite for the development of patient-tailored multi-modal treatments including the elimination of rare CSC. MAIN BODY: Phosphorylation is a crucial post-translational modification regulating a plethora of both intra- and intercellular communication processes in normal and malignant cells. Small-molecule targeting of kinases has proven successful in the therapy, but the high rates of relapse and failure to stem malignant spread suggest that these kinase inhibitors largely spare CSC. Studying the kinetics of global phosphorylation patterns in an unbiased manner is, therefore, required to improve strategies and successful treatments within multi-modal therapeutic regimens by targeting the malignant behavior of CSC. The phosphoproteome comprises all phosphoproteins within a cell population that can be analyzed by phosphoproteomics, allowing the investigation of thousands of phosphorylation events. One major aspect is the perception of events underlying the activation and deactivation of kinases and phosphatases in oncogenic signaling pathways. Thus, not only can this tool be harnessed to better understand cellular processes such as those controlling CSC, but also applied to identify novel drug targets for targeted anti-CSC therapy.

conclusionState-of-the-art phosphoproteomics approaches focusing on single cell analysis have the potential to better understand oncogenic signaling in heterogeneous cell populations including rare, yet highly malignant CSC. By eliminating the influence of heterogeneity of populations, single-cell studies will reveal novel insights also into the inter- and intratumoral communication processes controlling malignant CSC and disease progression, laying the basis for improved rational combination treatments.

Indexed as

Molecular Targeted TherapySignal TransductionHumansNeoplastic Stem CellsPhosphoproteinsProteomeProteomicsPhosphoproteinsProteomeCancer stem cellsKinasesPhosphoproteomicsPhospho-signalingTumor cell heterogeneity

Identifiers

PMID28356110
PMCPMC5372284
OpenAlexW2600098802

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.