Evidence map›Paper›PMID 31253832›Full record

ArticleScientific reports2019

Label propagation defines signaling networks associated with recurrently mutated cancer genes.

Merve Cakir, Sayan Mukherjee, Kris C Wood

Abstract read
In one paragraph

Article in Scientific reports, 2019. 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

3 authors.

Merve CakirProgram in Computational Biology and Bioinformatics, Duke University, Durham, NC, 27708, USA.
Sayan MukherjeeDepartments of Statistical Science, Mathematics, Computer Science, Biostatistics & Bioinformatics, Duke University, Durham, NC, 27708, USA. sayan@stat.duke.edu.
Kris C WoodDepartment of Pharmacology and Cancer Biology, Duke University, Durham, NC, 27710, USA. kris.wood@duke.edu.ORCID http://orcid.org/0000-0002-5887-2253

Funding

Selectively targeting apoptosis in PIK3CA mutant colorectal cancersR01CA207083 · NCI · DUKE UNIVERSITY · PI WOOD, KRIS C. · 2016 to 2020
$1.8M
NCI NIH HHS R01 CA207083
6 · The paper itself

Abstract

Human tumors have distinct profiles of genomic alterations, and each of these alterations has the potential to cause unique changes to cellular homeostasis. Detailed analyses of these changes could reveal downstream effects of genomic alterations, contributing to our understanding of their roles in tumor development and progression. Across a range of tumor types, including bladder, lung, and endometrial carcinoma, we determined genes that are frequently altered in The Cancer Genome Atlas patient populations, then examined the effects of these alterations on signaling and regulatory pathways. To achieve this, we used a label propagation-based methodology to generate networks from gene expression signatures associated with defined mutations. Individual networks offered a large-scale view of signaling changes represented by gene signatures, which in turn reflected the scope of molecular events that are perturbed in the presence of a given genomic alteration. Comparing different networks to one another revealed common biological pathways impacted by distinct genomic alterations, highlighting the concept that tumors can dysregulate key pathways through multiple, seemingly unrelated mechanisms. Finally, altered genes inducing common changes to the signaling network were used to search for genomic markers of drug response, connecting shared perturbations to differential drug sensitivity.

Indexed as

Genes, NeoplasmMutationSignal TransductionBiomarkers, TumorComputational BiologyDisease ProgressionGene Expression ProfilingGene Regulatory NetworksGenomicsHumansNeoplasmsRecurrenceSystems BiologyBiomarkers, Tumor

Identifiers

PMID31253832
PMCPMC6599034

What OpenQuestion holds

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Registered trials

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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.