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Peer-reviewedCC BYScientific Reports

Integration of gene expression and alternative splicing enhances IGHV mutation status and survival risk prediction in chronic lymphocytic leukemia

  • Lei Yu1
  • Ruidong Li1
  • Meiling Jin2
  • Weier Guo3
  • Stacey M. Fernandes4
  • Jennifer R. Brown4
  • Lili Wang5
  • Zhenyu Jia1
5 affiliations
  1. 1Department of Botany and Plant Sciences, University of California, Riverside
  2. 2Department of Systems Biology, Beckman Research Institute
  3. 3Department of Plant Sciences, University of California, Davis
  4. 4Department of Medical Oncology, Dana Farber Cancer Institute
  5. 5Division of Hematology and Oncology, Department of Medicine, Columbia University Irving Medical Center
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Abstract

The immunoglobulin heavy chain variable region (IGHV) mutation status is a key prognostic marker in chronic lymphocytic leukemia (CLL), shaping disease progression and therapeutic response. Current IGHV testing relies on molecular genomic analyses and requires specific laboratory tests, limiting its accessibility. Here, we developed an unbiased computational approach to accurately predict IGHV mutation status based on gene expression and alternative splicing profiles derived from transcriptome data. We showed that predicted IGHV status had a superior predictive power for overall and failure-free survival compared to conventional IGHV testing methods. Moreover, we identified significant novel associations between key transcriptomic features and genetic lesions, indicating potential but unexplored roles in CLL pathogenesis. Our results thus highlight a novel strategy for integrating molecular features to improve CLL prognosis, underscoring the prognostic value of RNA alternative splicing in CLL biology.

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Cite

BibTeXRIS
BibTeX
@article{yu2026integration,
  title = {{Integration of gene expression and alternative splicing enhances IGHV mutation status and survival risk prediction in chronic lymphocytic leukemia}},
  author = {Lei Yu and Ruidong Li and Meiling Jin and Weier Guo and Stacey M. Fernandes and Jennifer R. Brown and Lili Wang and Zhenyu Jia},
  journal = {Scientific Reports},
  year = {2026},
  month = jul,
  doi = {10.1038/s41598-026-62824-5},
  url = {https://doi.org/10.1038/s41598-026-62824-5},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Integration of gene expression and alternative splicing enhances IGHV mutation status and survival risk prediction in chronic lymphocytic leukemia
AU  - Lei Yu
AU  - Ruidong Li
AU  - Meiling Jin
AU  - Weier Guo
AU  - Stacey M. Fernandes
AU  - Jennifer R. Brown
AU  - Lili Wang
AU  - Zhenyu Jia
PY  - 2026
DA  - 2026/07/01
JO  - Scientific Reports
DO  - 10.1038/s41598-026-62824-5
UR  - https://doi.org/10.1038/s41598-026-62824-5
AB  - The immunoglobulin heavy chain variable region (IGHV) mutation status is a key prognostic marker in chronic lymphocytic leukemia (CLL), shaping disease progression and therapeutic response. Current IGHV testing relies on molecular genomic analyses and requires specific laboratory tests, limiting its accessibility. Here, we developed an unbiased computational approach to accurately predict IGHV mutation status based on gene expression and alternative splicing profiles derived from transcriptome data. We showed that predicted IGHV status had a superior predictive power for overall and failure-free survival compared to conventional IGHV testing methods. Moreover, we identified significant novel associations between key transcriptomic features and genetic lesions, indicating potential but unexplored roles in CLL pathogenesis. Our results thus highlight a novel strategy for integrating molecular features to improve CLL prognosis, underscoring the prognostic value of RNA alternative splicing in CLL biology.
SN  - 2045-2322
ER  -