Evidence map›Paper›PMID 40022167›Full record

ArticleGenome biology2025

PRODE recovers essential and context-essential genes through neighborhood-informed scores.

Thomas Cantore, Paola Gasperini, Riccardo Bevilacqua, Yari Ciani, Sanju Sinha, Eytan Ruppin, Francesca Demichelis

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

7 authors.

Thomas CantoreLaboratory of Computational and Functional Oncology, Department of Cellular, Computational, and Integrative Biology, University of Trento, Via Sommarive 9, Trento, 38123, Italy.
Paola GasperiniLaboratory of Computational and Functional Oncology, Department of Cellular, Computational, and Integrative Biology, University of Trento, Via Sommarive 9, Trento, 38123, Italy.
Riccardo BevilacquaLaboratory of Computational and Functional Oncology, Department of Cellular, Computational, and Integrative Biology, University of Trento, Via Sommarive 9, Trento, 38123, Italy.
Yari CianiLaboratory of Computational and Functional Oncology, Department of Cellular, Computational, and Integrative Biology, University of Trento, Via Sommarive 9, Trento, 38123, Italy.
Sanju SinhaCancer Data Science Laboratory (CDSL), Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA.
Eytan RuppinCancer Data Science Laboratory (CDSL), Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD, USA.
Francesca DemichelisLaboratory of Computational and Functional Oncology, Department of Cellular, Computational, and Integrative Biology, University of Trento, Via Sommarive 9, Trento, 38123, Italy. f.demichelis@unitn.it.ORCID http://orcid.org/0000-0002-8266-8631

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene context-essentiality assessment supports precision oncology opportunities. The variability of gene effects inference from loss-of-function screenings across models and technologies limits identifying robust hits. We propose a computational framework named PRODE that integrates gene effects with protein-protein interactions to generate neighborhood-informed essential (NIE) and neighborhood-informed context essential (NICE) scores. It outperforms the canonical gene effect approach in recovering missed essential genes in shRNA screens and prioritizing context-essential hits from CRISPR-KO screens, as supported by in vitro validations. Applied to Her2 + breast cancer tumor samples, PRODE identifies oxidative phosphorylation genes as vulnerabilities with prognostic value, highlighting new therapeutic opportunities.

Indexed as

Breast NeoplasmsComputational BiologyGenes, EssentialErb-b2 Receptor Tyrosine KinasesFemaleHumansOxidative PhosphorylationERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesCancerCancer vulnerabilitiesContext-essentialityEssentialityGene effectNeighborhood-informed scoresOncologyPPISynthetic lethality

Identifiers

PMID40022167
PMCPMC11869679

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.