Evidence map›Paper›PMID 41093603›Full record

ArticleAnnals of laboratory medicine2026

Detection of Fusion Genes Using RNA Sequencing in Acute Leukemia.

Hyun-Young Kim, Boram Kim, Min-Seung Park, Jong-Ho Park, Hee Young Ju, Keon Hee Yoo, Jun Ho Jang, Chul Won Jung, Hee-Jin Kim

Abstract read
In one paragraph

Article in Annals of laboratory medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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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

9 authors.

Hyun-Young KimDepartment of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-0553-7096
Boram KimDepartment of Laboratory Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-5695-8902
Min-Seung ParkDepartment of Laboratory Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-4482-3098
Jong-Ho ParkPrecision Medicine Center, Seoul National University Bundang Hospital, Seongnam, Korea.ORCID https://orcid.org/0000-0001-5883-8322
Hee Young JuDepartment of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-6744-0412
Keon Hee YooDepartment of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-5980-7912
Jun Ho JangDivision of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-7423-4676
Chul Won JungDivision of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-5474-6807
Hee-Jin KimDepartment of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-3741-4613

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Fusion genes are major drivers of acute leukemia. Conventional diagnostics are limited in detecting the diverse fusions included in recently updated acute leukemia classifications. We evaluated the fusion detection performance of RNA sequencing (RNA-seq) compared with that of conventional diagnostics in patients with acute leukemia. Methods: We retrospectively obtained the data of 101 patients with acute leukemia who underwent conventional diagnostics (i.e., karyotyping, FISH, or multiplex reverse transcription PCR) at diagnosis at Samsung Medical Center, Seoul, Korea, between September 2022 and September 2023. Whole RNA-seq was performed using the Illumina Stranded mRNA Prep kit (Illumina, San Diego, CA, USA). The concordance, sensitivity, and specificity of RNA-seq for fusion gene detection were compared with those of conventional diagnostics. Results: RNA-seq helped identify 52 fusion genes in 51 (50.5%) of 101 patients, with detection rates of 40.7%, 70.3%, 37.5%, and 50% in acute myeloid leukemia, B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia, and mixed-phenotype acute leukemia, respectively. RNA-seq showed 83.3% sensitivity and 80.8% concordance with conventional diagnostics; it missed eight fusions, likely because of low transcript abundance or enhancer hijacking. RNA-seq also helped clarify three previously unspecified rearrangements and detected 12 fusions (21.4%) in 56 cases that tested negative with conventional diagnostics, including four novel ( Conclusions: This was the first study to evaluate the performance of whole RNA-seq in fusion detection in patients with acute leukemia in Korea. Incorporating RNA-seq into diagnostic workflows may facilitate earlier and more precise therapeutic decisions and improve prognostic assessment in patients with acute leukemia.

Indexed as

LeukemiaOncogene Proteins, FusionSequence Analysis, RNAAdolescentAdultAgedAged, 80 and overChildChild, PreschoolFemaleHumansLeukemia, Myeloid, AcuteMaleMiddle AgedPrecursor Cell Lymphoblastic Leukemia-LymphomaRetrospective StudiesOncogene Proteins, FusionAcute lymphoblastic leukemiaAcute myeloid leukemiaFISHGene fusionKaryotypingReverse transcription PCRRNA sequencing

Identifiers

PMID41093603
PMCPMC13071280

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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.