Evidence map›Paper›PMID 36909587›Full record

ArticlebioRxiv : the preprint server for biology2023

Genetic Predisposition to Neuroblastoma Results from a Regulatory Polymorphism that Promotes the Adrenergic Cell State.

Nina Weichert-Leahey, Hui Shi, Ting Tao, Derek A Oldridge, Adam D Durbin, Brian J Abraham, Mark W Zimmerman, Shizhen Zhu, Andrew C Wood, Deepak Reyon and 5 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 7 institutions in 3 countries.

Nina Weichert-LeaheyORCID 0000-0002-0351-3018
Hui Shi
Derek A Oldridge
Adam D Durbin
Brian J Abraham
Mark W Zimmerman
Shizhen Zhu
Andrew C Wood
Deepak Reyon
J Keith Joung
Richard A Young
Sharon J Diskin
John M Maris
A Thomas Look
Harvard University · USChildren's Hospital of Philadelphia · USBoston Children's Hospital · USSt. Jude Children's Research Hospital · USBroad Institute · USMayo Clinic · USUniversity of Auckland · NZ

Funding

Targeting EP300, a selective dependency in neuroblastomaK08CA245251 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI DURBIN, ADAM DAVID · 2020 to 2024
$1.3M
NCI NIH HHS K08 CA245251
6 · The paper itself

Abstract

Childhood neuroblastomas exhibit plasticity between an undifferentiated neural crest-like "mesenchymal" cell state and a more differentiated sympathetic "adrenergic" cell state. These cell states are governed by autoregulatory transcriptional loops called core regulatory circuitries (CRCs), which drive the early development of sympathetic neuronal progenitors from migratory neural crest cells during embryogenesis. The adrenergic cell identity of neuroblastoma requires LMO1 as a transcriptional co-factor. Both LMO1 expression levels and the risk of developing neuroblastoma in children are associated with a single nucleotide polymorphism G/T that affects a G ATA motif in the first intron of LMO1. Here we show that wild-type zebrafish with the G ATA genotype develop adrenergic neuroblastoma, while knock-in of the protective T ATA allele at this locus reduces the penetrance of MYCN-driven tumors, which are restricted to the mesenchymal cell state. Whole genome sequencing of childhood neuroblastomas demonstrates that T ATA/ T ATA tumors also exhibit a mesenchymal cell state and are low risk at diagnosis. Thus, conversion of the regulatory G ATA to a T ATA allele in the first intron of

Identifiers

PMID36909587
PMCPMC10002714
OpenAlexW4323047131

What OpenQuestion holds

Textmetadata
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.