Evidence map›Paper›PMID 32690943›Full record

ArticleNature chemical biology2020

A mass spectrometry-based proteome map of drug action in lung cancer cell lines.

Benjamin Ruprecht, Julie Di Bernardo, Zhao Wang, Xuan Mo, Oleg Ursu, Matthew Christopher, Rafael B Fernandez, Li Zheng, Brian D Dill, Huijun Wang and 10 more

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Nature chemical biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
3.7field-weighted citation impact, top 5% 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

28 citing papers in PubMed, 54 citations in OpenAlex.

  1. Article
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  5. Leveraging HILIC/ERLIC separations for online nanoscale LC-MS/MS analysis of phosphopeptide isoforms from RNA polymerase II C-terminal domain.Journal of chromatography. B, Analytical technologies in the biomedical and life sciences · 2025
    Article
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  10. Memory effects of prior subculture may impact the quality of multiomic perturbation profiles.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. [Deciphering cellular processes responding to lethality of 17Se pu = Chinese journal of chromatography · 2024
    Article
  12. High-resolution transcriptomics analysis of CXCL13Journal of thoracic disease · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors at 1 institution in 1 country.

Benjamin RuprechtChemical Biology, Merck, Boston, MA, USA. benjamin.ruprecht@merck.com.ORCID http://orcid.org/0000-0001-9807-5825
Julie Di BernardoChemical Biology, Merck, Boston, MA, USA.
Zhao WangChemical Biology, Merck, Boston, MA, USA.
Xuan MoChemical Biology, Merck, Boston, MA, USA.ORCID http://orcid.org/0000-0001-8638-6482
Oleg UrsuChemoinformatics, Merck, Boston, MA, USA.
Matthew ChristopherChemical Biology, Merck, Boston, MA, USA.
Rafael B FernandezPharmacology, Merck, Boston, MA, USA.
Li ZhengChemical Biology, Merck, Boston, MA, USA.
Brian D DillChemical Biology, Merck, Boston, MA, USA.ORCID http://orcid.org/0000-0002-4532-3044
Huijun WangChemoinformatics, Merck, Kenilworth, NJ, USA.
Yuting XuBiometrics Research, Merck, Rahway, NJ, USA.ORCID http://orcid.org/0000-0003-2091-3854
Andy LiawBiometrics Research, Merck, Rahway, NJ, USA.
Jonathan D MortisonChemical Biology, Merck, Boston, MA, USA.
Nirodhini SiriwardanaChemical Biology, Merck, Boston, MA, USA.
Brian AndresenChemical Biology, Merck, Boston, MA, USA.
Meir GlickChemoinformatics, Merck, Boston, MA, USA.
James R TataChemical Biology, Merck, Kenilworth, NJ, USA.
Victoria KutilekChemical Biology, Merck, Boston, MA, USA.
Ivan Cornella-TaracidoChemical Biology, Merck, Boston, MA, USA.
An ChiChemical Biology, Merck, Boston, MA, USA. an_chi@merck.com.ORCID http://orcid.org/0000-0002-8213-1826
Merck & Co., Inc., Rahway, NJ, USA (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mass spectrometry-based discovery proteomics is an essential tool for the proximal readout of cellular drug action. Here, we apply a robust proteomic workflow to rapidly profile the proteomes of five lung cancer cell lines in response to more than 50 drugs. Integration of millions of quantitative protein-drug associations substantially improved the mechanism of action (MoA) deconvolution of single compounds. For example, MoA specificity increased after removal of proteins that frequently responded to drugs and the aggregation of proteome changes across cell lines resolved compound effects on proteostasis. We leveraged these findings to demonstrate efficient target identification of chemical protein degraders. Aggregating drug response across cell lines also revealed that one-quarter of compounds modulated the abundance of one of their known protein targets. Finally, the proteomic data led us to discover that inhibition of mitochondrial function is an off-target mechanism of the MAP2K1/2 inhibitor PD184352 and that the ALK inhibitor ceritinib modulates autophagy.

Indexed as

Antineoplastic AgentsCell Line, TumorGene Expression Regulation, NeoplasticHumansLung NeoplasmsMass SpectrometryProteomeProteomicsAntineoplastic AgentsProteome

Identifiers

PMID32690943
OpenAlexW3043124935

What OpenQuestion holds

Textmetadata
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.