Article in Clinical and translational science, 2026. 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.
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
15 authors.
Lin XuDepartment of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID 0000-0001-5815-4457
Arhanti SadanandDepartment of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID 0000-0002-7780-1688
Evan W NeczyporDepartment of Medicine, University of Chicago Pritzker School of Medicine, Chicago, Illinois, USA.ORCID 0000-0002-2969-3758
Yen-Ting LiuDepartment of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID 0000-0001-5498-5720
Erin ButlerDepartment of Pediatrics, Division of Hematology/Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID 0000-0003-4178-4430
Kelley MooreDivision of Hematology/Oncology, Department of Pediatrics, University of Chicago Pritzker School of Medicine, Chicago, Illinois, USA.ORCID 0009-0002-5970-3096
Flannery BowmanDepartment of Pediatrics, Division of Hematology/Oncology, and Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina, USA.ORCID 0009-0002-7557-8889
Yamin MazumderDepartment of Pediatrics, Division of Hematology/Oncology, and Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina, USA.ORCID 0009-0004-1006-6107
Arlene NaranjoChildren's Oncology Group Statistics and Data Center, Department of Biostatistics, University of Florida, Gainesville, Florida, USA.ORCID 0000-0001-7737-4324
Alexandre ChlenskiDivision of Hematology/Oncology, Department of Pediatrics, University of Chicago Pritzker School of Medicine, Chicago, Illinois, USA.ORCID 0000-0002-9885-4017
Xue XiaoQuantitative Biomedical Research Center, Department of Health Data Science and Biostatistics, Peter O'donnell, Jr., School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID 0000-0003-1384-9954
Lei GuoQuantitative Biomedical Research Center, Department of Health Data Science and Biostatistics, Peter O'donnell, Jr., School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID 0000-0002-6072-2377
Susan L CohnDivision of Hematology/Oncology, Department of Pediatrics, University of Chicago Pritzker School of Medicine, Chicago, Illinois, USA.ORCID 0000-0001-5749-7650
Mark A ApplebaumDivision of Hematology/Oncology, Department of Pediatrics, University of Chicago Pritzker School of Medicine, Chicago, Illinois, USA.ORCID 0000-0001-9766-8477
Stephen X SkapekDepartment of Pediatrics, Division of Hematology/Oncology, and Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina, USA.ORCID 0000-0002-4136-8384
Funding
NCTN BIQSFP ANBL1531 (NRT)U10CA180886 · NCI · PUBLIC HEALTH INSTITUTE · PI Douglas S. Hawkins · 2014 to 2026
$390.6M
COG SDMC - Statistics CoreU10CA180899 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TODD A ALONZO · 2014 to 2026
$132.8M
NCI NIH HHS U10 CA180886NCI NIH HHS U10 CA180899
6 · The paper itself
Abstract
Identifying targetable oncogenic drivers remains a challenge in neuroblastoma, the most common extracranial solid malignancy in children. We applied a Bayesian algorithm for integrative analysis of expression and copy-number, iExCN, to nominate oncogenic drivers in neuroblastoma. The iExCN algorithm found 47 oncogenes from a dataset of 195 neuroblastoma biopsy specimens. The nominated oncogenes included some previously implicated in neuroblastoma, including ALK, MDM2, MYCN, and XPO1, but most have not been linked to this disease. A CRISPR/Cas9-based screen testing those candidates revealed neuroblastoma cell line-specific and shared vulnerabilities in three well-characterized models, and dependencies were confirmed by complementary RNA knockdown. Analysis of more than 30 additional neuroblastoma cell lines using DepMap confirmed statistically significant dependency scores in the iExCN genes. Finally, analysis of two cohorts of children with neuroblastoma revealed a trend toward worse survival in cases in which more iExCN genes showed copy number gains. Our findings uncover multiple, potentially targetable oncogenic drivers that appear to influence neuroblastoma biology, demonstrating a generalizable capacity for iExCN to unmask disease genes and therapeutic targets in cancer.
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.
A Bayesian-Based Integrative Bioinformatics Analysis Nominates Oncogenic Drivers in Neuroblastoma. · full record | OpenQuestion