Evidence map›Paper›PMID 34686201›Full record

ArticleJournal of ovarian research2021

Molecular response to PARP1 inhibition in ovarian cancer cells as determined by mass spectrometry based proteomics.

Alexandra Franz, Fabian Coscia, Ciyue Shen, Lea Charaoui, Matthias Mann, Chris Sander

Open access · goldAbstract read
In one paragraph

Article in Journal of ovarian research, 2021. 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
1.0field-weighted citation impact, top 21% 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, 22 citations in OpenAlex.

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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

6 authors at 3 institutions in 3 countries.

Alexandra FranzDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA. afranz@ds.dfci.harvard.edu.
Fabian CosciaProteomics Program, NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen, Denmark.
Ciyue ShenDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA.
Lea CharaouiDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA.
Matthias MannProteomics Program, NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen, Denmark.
Chris SanderDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA, 02115, USA. sander.research@gmail.com.ORCID http://orcid.org/0000-0001-6059-6270
Broad Institute · USUniversity of Copenhagen · DKHarvard University · US

Funding

TR&D 3 - Network Guided Machine LearningP41GM103504 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2012 to 2024
$17.3M
h2020 marie skłodowska-curie actions 846795national resource center for network biology P41GM103504NIGMS NIH HHS P41 GM103504novo nordisk foundation NNF14CC0001novo nordisk foundation NNF15CC0001
6 · The paper itself

Abstract

backgroundPoly (ADP)-ribose polymerase (PARP) inhibitors have entered routine clinical practice for the treatment of high-grade serous ovarian cancer (HGSOC), yet the molecular mechanisms underlying treatment response to PARP1 inhibition (PARP1i) are not fully understood.

methodsHere, we used unbiased mass spectrometry based proteomics with data-driven protein network analysis to systematically characterize how HGSOC cells respond to PARP1i treatment.

resultsWe found that PARP1i leads to pronounced proteomic changes in a diverse set of cellular processes in HGSOC cancer cells, consistent with transcript changes in an independent perturbation dataset. We interpret decreases in the levels of the pro-proliferative transcription factors SP1 and β-catenin and in growth factor signaling as reflecting the anti-proliferative effect of PARP1i; and the strong activation of pro-survival processes NF-κB signaling and lipid metabolism as PARPi-induced adaptive resistance mechanisms. Based on these observations, we nominate several protein targets for therapeutic inhibition in combination with PARP1i. When tested experimentally, the combination of PARPi with an inhibitor of fatty acid synthase (TVB-2640) has a 3-fold synergistic effect and is therefore of particular pre-clinical interest.

conclusionOur study improves the current understanding of PARP1 function, highlights the potential that the anti-tumor efficacy of PARP1i may not only rely on DNA damage repair mechanisms and informs on the rational design of PARP1i combination therapies in ovarian cancer.

Indexed as

FemaleHumansMass SpectrometryOvarian NeoplasmsPoly(ADP-ribose) Polymerase InhibitorsProteomicsPoly(ADP-ribose) Polymerase InhibitorsCombination therapyData-driven protein module discoveryHigh-grade serous ovarian cancerMass spectrometry based proteomicsMolecular response profilingMolecular signaling pathwaysPARP inhibitor resistancePARP inhibitorsPathway analysis

Identifiers

PMID34686201
PMCPMC8539835
OpenAlexW3206760576

What Socratic 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 Socratic graph.