Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations

In precision medicine, DNA-based assays are currently necessary but not always sufficient for predicting therapeutic efficacy of cancer drugs based on the mutational findings in a patient's tumor specimen. Most drugs target proteins, but it is challenging and not yet cost-effective to perform high-throughput proteomics profiling, including mutational analysis, on cancer specimens. RNA may be an effective mediator for bridging the "DNA to protein divide" and provide more clarity and therapeutic predictability for precision oncology. While RNA sequencing (RNA-seq) has been increasingly used alongside DNA cancer mutation screening panels to assess the impact of variants on gene transcript expression and splicing, comprehensive evaluations of RNA panels and the integration of expressed mutation data analytics to supplement DNA panels are still limited. In this study, we conducted targeted RNA-seq on a reference sample set for expressed variant detection to explore its potential capability to complement DNA variant results or detect variants independently. The results indicated that, with a carefully controlled false positive rate ensuring high accuracy, RNA-seq uniquely identified variants with significant pathological relevance that were missed by DNA-seq, demonstrating its potential to uncover clinically actionable mutations. On the other hand, while some variants were detected by both approaches, others were missed by one or the other, reflecting either the nature of these variants or limitations of the bioinformatics tools used. Variants missed by RNA-seq are often not expressed or expressed at very low levels, suggesting they may be of lower clinical relevance. Incorporating RNA-seq into clinical biomarker panels will ultimately advance precision medicine and improve patient outcomes by improving the strength and reliability of somatic mutation findings for clinical diagnosis, prognosis and prediction of therapeutic efficacy.

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Publication Details

Journal
npj Precision Oncology
Published
2025-06-13
DOI
https://doi.org/10.1038/s41698-025-00993-8
Citations
4
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
3.22

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article

Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations

Rebecca Kusko, Andreas Scherer, Roberta Maestro, Carlos Pabón-Peña et al.
4 citations
npj Precision Oncology
RNA modifications and cancer
3.22
article

Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations

Rebecca Kusko, Andreas Scherer, Roberta Maestro, Carlos Pabón-Peña, Paweł P. Łabaj, Sayed Mohammad Ebrahim Sahraeian, Pierre R. Bushel, Anne Bergstrom Lucas, Christopher Mozsary, Binsheng Gong, Guangchun Chen, Donald J. Johann, Bohu Pan, Wendell Jones, Hagen Tilgner, Todd Richmond, Jonathan Foox, David P. Kreil, Dan Li, Natalia Novoradovskaya, Daniel Butler, Christopher E. Mason, Jianying Li, James C. Willey, Joshua Xu
article en
4 citations

Abstract

In precision medicine, DNA-based assays are currently necessary but not always sufficient for predicting therapeutic efficacy of cancer drugs based on the mutational findings in a patient's tumor specimen. Most drugs target proteins, but it is challenging and not yet cost-effective to perform high-throughput proteomics profiling, including mutational analysis, on cancer specimens. RNA may be an effective mediator for bridging the "DNA to protein divide" and provide more clarity and therapeutic predictability for precision oncology. While RNA sequencing (RNA-seq) has been increasingly used alongside DNA cancer mutation screening panels to assess the impact of variants on gene transcript expression and splicing, comprehensive evaluations of RNA panels and the integration of expressed mutation data analytics to supplement DNA panels are still limited. In this study, we conducted targeted RNA-seq on a reference sample set for expressed variant detection to explore its potential capability to complement DNA variant results or detect variants independently. The results indicated that, with a carefully controlled false positive rate ensuring high accuracy, RNA-seq uniquely identified variants with significant pathological relevance that were missed by DNA-seq, demonstrating its potential to uncover clinically actionable mutations. On the other hand, while some variants were detected by both approaches, others were missed by one or the other, reflecting either the nature of these variants or limitations of the bioinformatics tools used. Variants missed by RNA-seq are often not expressed or expressed at very low levels, suggesting they may be of lower clinical relevance. Incorporating RNA-seq into clinical biomarker panels will ultimately advance precision medicine and improve patient outcomes by improving the strength and reliability of somatic mutation findings for clinical diagnosis, prognosis and prediction of therapeutic efficacy.

npj Precision OncologyVol. 9(1)
Jagiellonian University (PL), National Center for Toxicological Research (US), United States Food and Drug Administration (US), University of Helsinki (FI), Agilent Technologies (United States) (US), Cornell University (US), National Institute of Environmental Health Sciences (US), MIND Research Institute (US), Center for Neuro-Oncology (US), IQVIA (United States) (US), Centro di Riferimento Oncologico (IT), Winthrop Rockefeller Foundation (US), Institute for Molecular Medicine Finland (FI), Computational Physics (United States) (US), Weill Cornell Medicine (US), University of Arkansas for Medical Sciences (US), The University of Texas Southwestern Medical Center (US), University of Toledo (US), Kelly Services (United States) (US), BOKU University (AT)
National Institutes of Health, U.S. Food and Drug Administration, National Institute of Environmental Health Sciences
Openalex Percentile: Top 8%
RNA modifications and cancer
3.22
DOIOpen Access PDFOpenAlex
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