Evidence map›Paper›PMID 32098059›Full record

ArticleGenes2020

Integrative Analysis Identifies Candidate Tumor Microenvironment and Intracellular Signaling Pathways that Define Tumor Heterogeneity in NF1.

Jineta Banerjee, Robert J Allaway, Jaclyn N Taroni, Aaron Baker, Xiaochun Zhang, Chang In Moon, Christine A Pratilas, Jaishri O Blakeley, Justin Guinney, Angela Hirbe and 2 more

Abstract read
In one paragraph

Article in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Review
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  6. Article
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  10. Review
  11. Machine learning in rare disease.Nature methods · 2023
    Review
  12. Article
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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

12 authors.

Jineta BanerjeeComputational Oncology, Sage Bionetworks, Seattle, WA 98121, USA.
Robert J AllawayComputational Oncology, Sage Bionetworks, Seattle, WA 98121, USA.ORCID 0000-0003-3573-3565
Jaclyn N TaroniChildhood Cancer Data Lab, Alex's Lemonade Stand Foundation, Philadelphia, PA 19102, USA.
Aaron BakerComputational Oncology, Sage Bionetworks, Seattle, WA 98121, USA.
Xiaochun ZhangDivision of Oncology, Washington University Medical School, St. Louis, MO 63110, USA.
Chang In MoonDivision of Oncology, Washington University Medical School, St. Louis, MO 63110, USA.
Christine A PratilasSidney Kimmel Comprehensive Cancer Center and Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Jaishri O BlakeleySidney Kimmel Comprehensive Cancer Center and Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
Justin GuinneyComputational Oncology, Sage Bionetworks, Seattle, WA 98121, USA.
Angela HirbeDivision of Oncology, Washington University Medical School, St. Louis, MO 63110, USA.ORCID 0000-0003-1719-0771
Casey S GreeneChildhood Cancer Data Lab, Alex's Lemonade Stand Foundation, Philadelphia, PA 19102, USA.ORCID 0000-0001-8713-9213
Sara Jc GoslineComputational Oncology, Sage Bionetworks, Seattle, WA 98121, USA.ORCID 0000-0002-6534-4774

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurofibromatosis type 1 (NF1) is a monogenic syndrome that gives rise to numerous symptoms including cognitive impairment, skeletal abnormalities, and growth of benign nerve sheath tumors. Nearly all NF1 patients develop cutaneous neurofibromas (cNFs), which occur on the skin surface, whereas 40-60% of patients develop plexiform neurofibromas (pNFs), which are deeply embedded in the peripheral nerves. Patients with pNFs have a ~10% lifetime chance of these tumors becoming malignant peripheral nerve sheath tumors (MPNSTs). These tumors have a severe prognosis and few treatment options other than surgery. Given the lack of therapeutic options available to patients with these tumors, identification of druggable pathways or other key molecular features could aid ongoing therapeutic discovery studies. In this work, we used statistical and machine learning methods to analyze 77 NF1 tumors with genomic data to characterize key signaling pathways that distinguish these tumors and identify candidates for drug development. We identified subsets of latent gene expression variables that may be important in the identification and etiology of cNFs, pNFs, other neurofibromas, and MPNSTs. Furthermore, we characterized the association between these latent variables and genetic variants, immune deconvolution predictions, and protein activity predictions.

Indexed as

Databases, GeneticHumansMachine LearningModels, StatisticalNerve Sheath NeoplasmsNeurofibromaNeurofibroma, PlexiformNeurofibromatosis 1Peripheral NervesPrognosisSequence Analysis, DNASignal TransductionTumor Microenvironmentcancerlatent variablesmachine learningmetaVIPERnerve sheath tumorneurofibromatosis type 1random forestsupervised learningtransfer learningtumor deconvolution

Identifiers

PMID32098059
PMCPMC7073563

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.