Evidence map›Paper›PMID 34771455›Full record

ArticleCancers2021

Network-Based Analysis to Identify Drivers of Metastatic Prostate Cancer Using GoNetic.

Louise de Schaetzen van Brienen, Giles Miclotte, Maarten Larmuseau, Jimmy Van den Eynden, Kathleen Marchal

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 39% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

5 authors at 1 institution in 1 country.

Louise de Schaetzen van BrienenDepartment of Plant Biotechnology and Bioinformatics, Faculty of Sciences, Ghent University, 9052 Ghent, Belgium.ORCID 0000-0002-5882-9458
Giles MiclotteDepartment of Plant Biotechnology and Bioinformatics, Faculty of Sciences, Ghent University, 9052 Ghent, Belgium.ORCID 0000-0002-9212-3440
Maarten LarmuseauDepartment of Plant Biotechnology and Bioinformatics, Faculty of Sciences, Ghent University, 9052 Ghent, Belgium.ORCID 0000-0003-0466-099X
Jimmy Van den EyndenDepartment of Human Structure and Repair, Faculty of Medicine and Health Sciences, Ghent University, 9000 Ghent, Belgium.ORCID 0000-0003-0002-5614
Kathleen MarchalDepartment of Plant Biotechnology and Bioinformatics, Faculty of Sciences, Ghent University, 9052 Ghent, Belgium.ORCID 0000-0002-2169-4588
Ghent University · BE

Funding

Fonds Wetenschappelijk Onderzoek 3G045620Fonds Wetenschappelijk Onderzoek G.0371.06Fonds Wetenschappelijk Onderzoek G046318
6 · The paper itself

Abstract

Most known driver genes of metastatic prostate cancer are frequently mutated. To dig into the long tail of rarely mutated drivers, we performed network-based driver identification on the Hartwig Medical Foundation metastatic prostate cancer data set (HMF cohort). Hereto, we developed GoNetic, a method based on probabilistic pathfinding, to identify recurrently mutated subnetworks. In contrast to most state-of-the-art network-based methods, GoNetic can leverage sample-specific mutational information and the weights of the underlying prior network. When applied to the HMF cohort, GoNetic successfully recovered known primary and metastatic drivers of prostate cancer that are frequently mutated in the HMF cohort (

Indexed as

driver identificationmetastatic prostate cancernetwork-based cancer data analysissomatic mutations

Identifiers

PMID34771455
PMCPMC8582433
OpenAlexW3206321850

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.