Evidence map›Paper›PMID 41457639›Full record

ArticleCancer science2026

Precision Oncology for Pediatric Solid Tumors Using In-Hospital Pediatric/AYA Malignancy-Specific Panel Sequencing.

Masato Kojima, Sho Kurihara, Isamu Saeki, Ryo Touge, Keigo Nakashima, Shuhei Karakawa, Fumiyuki Yamasaki, Satoshi Okada, Eiso Hiyama

Abstract read
In one paragraph

Article in Cancer science, 2026. 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
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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.

No citing paper in PubMed yet.

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

9 authors.

Masato KojimaDepartment of Pediatric Surgery, Hiroshima University Hospital, Hiroshima, Japan.ORCID https://orcid.org/0000-0001-7783-0289
Sho KuriharaDepartment of Pediatric Surgery, Hiroshima University Hospital, Hiroshima, Japan.ORCID https://orcid.org/0000-0001-7021-4707
Isamu SaekiDepartment of Pediatric Surgery, Hiroshima University Hospital, Hiroshima, Japan.ORCID https://orcid.org/0000-0003-2861-0225
Ryo TougeDepartment of Pediatric Surgery, Hiroshima University Hospital, Hiroshima, Japan.ORCID https://orcid.org/0009-0008-0578-8059
Keigo NakashimaDepartment of Pediatric Surgery, Hiroshima University Hospital, Hiroshima, Japan.
Shuhei KarakawaDepartment of Pediatrics, Hiroshima University Hospital, Hiroshima, Japan.ORCID https://orcid.org/0000-0003-1853-4759
Fumiyuki YamasakiDepartment of Neurosurgery, Hiroshima University Hospital, Hiroshima, Japan.ORCID https://orcid.org/0000-0003-0164-6295
Satoshi OkadaDepartment of Pediatrics, Hiroshima University Hospital, Hiroshima, Japan.ORCID https://orcid.org/0000-0002-4622-5657
Eiso HiyamaDepartment of Biomedical Science, Natural Science Center for Basic Research and Development (N-BARD), Hiroshima University, Hiroshima, Japan.ORCID https://orcid.org/0000-0001-9179-5037

Funding

Japan Agency for Medical Research and Development JP18CK0106332Japan Agency for Medical Research and Development JP18LK0201066Japan Agency for Medical Research and Development JP19cm0106502Japan Agency for Medical Research and Development JP20ck0106609Japan Agency for Medical Research and Development JP22ama221403Japan Agency for Medical Research and Development JP23ck0106854Japan Agency for Medical Research and Development P-DIRECTMinistry of Education, Culture, Sports, Science and Technology 15H02567Ministry of Education, Culture, Sports, Science and Technology 16H02778Ministry of Education, Culture, Sports, Science and Technology 19H01056Ministry of Education, Culture, Sports, Science and Technology 22H03135Ministry of Education, Culture, Sports, Science and Technology 23K24394
6 · The paper itself

Abstract

Precision oncology, based on the genomic profile of tumors, is increasing in cancer treatment. It is important in pediatric and adolescent and young adult (AYA) malignancies, a group of rare cancers that are difficult to diagnose and progress quickly. We evaluated the usefulness of in-hospital molecular profiling using a specific sequencing panel for pediatric and AYA malignancies in clarifying the diagnosis, predicting the prognosis, and identifying therapeutic targets. We evaluated the Oncomine Childhood Cancer Research Assay (203 genes, 1700 fusions) and analyzed 153 samples at diagnosis and 34 samples at relapse or refractory from 165 pediatric and AYA patients with various solid malignancies, including neuroblastoma, hepatoblastoma, brain tumor, and sarcoma. We simulated in-hospital molecular profiling. In total, 320 reportable variants were identified in 153 samples (81.8%). Variants with clinical significance were identified in 62 samples (33.1%), including diagnostic variants in 26 (13.9%), prognostic variants in 17 (9%), targetable variants in 41 (21.9%), and variants with drug resistance in 18 (9.6%). Additionally, 62.0% and 94.1% of identified diagnostic and prognostic variants, respectively, had high levels of evidence. In five patients with cancer predisposition syndromes, all pathogenic germline mutations were validated. The turnaround time (TAT) from sample collection to reporting of the molecular profile was within seven working days. In-hospital molecular profiling using a sequencing panel specified tailored for pediatric and AYA malignancies has a high rate of identifying reportable variants and enables accurate diagnosis, malignancy grading, and treatment selection, as well as cancer predisposition syndromes with a short TAT.

Indexed as

NeoplasmsPrecision MedicineAdolescentAdultBiomarkers, TumorChildChild, PreschoolFemaleHigh-Throughput Nucleotide SequencingHumansInfantMaleNeuroblastomaPrognosisYoung AdultBiomarkers, Tumoradolescentin‐hospital sequencingmolecular profilingpediatricprecision oncologytargeted sequencing panelyoung adult

Identifiers

PMID41457639
PMCPMC12951107

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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.