Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations
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 perfo...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-06-01
|
| Series: | npj Precision Oncology |
| Online Access: | https://doi.org/10.1038/s41698-025-00993-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849335633768611840 |
|---|---|
| author | Dan Li Jianying Li Donald J. Johann Daniel Butler Guangchun Chen Jonathan Foox Binsheng Gong Wendell Jones David P. Kreil Rebecca Kusko Paweł P. Łabaj Anne Bergstrom Lucas Christopher E. Mason Christopher Mozsary Natalia Novoradovskaya Carlos Pabón-Peña Bohu Pan Todd A. Richmond Roberta Maestro Sayed Mohammad Ebrahim Sahraeian Andreas Scherer Hagen U. Tilgner James C. Willey Pierre R. Bushel Joshua Xu |
| author_facet | Dan Li Jianying Li Donald J. Johann Daniel Butler Guangchun Chen Jonathan Foox Binsheng Gong Wendell Jones David P. Kreil Rebecca Kusko Paweł P. Łabaj Anne Bergstrom Lucas Christopher E. Mason Christopher Mozsary Natalia Novoradovskaya Carlos Pabón-Peña Bohu Pan Todd A. Richmond Roberta Maestro Sayed Mohammad Ebrahim Sahraeian Andreas Scherer Hagen U. Tilgner James C. Willey Pierre R. Bushel Joshua Xu |
| author_sort | Dan Li |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d81e503dde634208a5bf697450b6bd2c |
| institution | Kabale University |
| issn | 2397-768X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Precision Oncology |
| spelling | doaj-art-d81e503dde634208a5bf697450b6bd2c2025-08-20T03:45:11ZengNature Portfolionpj Precision Oncology2397-768X2025-06-019111210.1038/s41698-025-00993-8Augmenting precision medicine via targeted RNA-Seq detection of expressed mutationsDan Li0Jianying Li1Donald J. Johann2Daniel Butler3Guangchun Chen4Jonathan Foox5Binsheng Gong6Wendell Jones7David P. Kreil8Rebecca Kusko9Paweł P. Łabaj10Anne Bergstrom Lucas11Christopher E. Mason12Christopher Mozsary13Natalia Novoradovskaya14Carlos Pabón-Peña15Bohu Pan16Todd A. Richmond17Roberta Maestro18Sayed Mohammad Ebrahim Sahraeian19Andreas Scherer20Hagen U. Tilgner21James C. Willey22Pierre R. Bushel23Joshua Xu24Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug AdministrationIntegrative Bioinformatics Support Group, Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle ParkWinthrop P Rockefeller Cancer Institute, University of Arkansas for Medical SciencesDepartment of Physiology and Biophysics, Weill Cornell Medicine, Cornell UniversityDepartment of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical CenterDepartment of Physiology and Biophysics, Weill Cornell Medicine, Cornell UniversityDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug AdministrationIQVIA LaboratoriesBoku University ViennaCellino BiotechMałopolska Centre of Biotechnology, Jagiellonian UniversityAgilent TechnologiesDepartment of Physiology and Biophysics, Weill Cornell Medicine, Cornell UniversityDepartment of Physiology and Biophysics, Weill Cornell Medicine, Cornell UniversityAgilent TechnologiesAgilent TechnologiesDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug AdministrationComputational Biology and Molecular Lab Applications, Roche Sequencing Solutions Inc.Unit of Oncogenetics and Functional Oncogenomics, Centro di Riferimento Oncologico di Aviano (CRO Aviano) IRCCSRoche Sequencing SolutionsEATRIS ERICBrain and Mind Research Institute, Weill Cornell MedicineDepartments of Medicine, Pathology, and Cancer Biology, College of Medicine and Life Sciences, University of Toledo Health Sciences CampusBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle ParkDivision of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug AdministrationAbstract 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.https://doi.org/10.1038/s41698-025-00993-8 |
| spellingShingle | Dan Li Jianying Li Donald J. Johann Daniel Butler Guangchun Chen Jonathan Foox Binsheng Gong Wendell Jones David P. Kreil Rebecca Kusko Paweł P. Łabaj Anne Bergstrom Lucas Christopher E. Mason Christopher Mozsary Natalia Novoradovskaya Carlos Pabón-Peña Bohu Pan Todd A. Richmond Roberta Maestro Sayed Mohammad Ebrahim Sahraeian Andreas Scherer Hagen U. Tilgner James C. Willey Pierre R. Bushel Joshua Xu Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations npj Precision Oncology |
| title | Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations |
| title_full | Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations |
| title_fullStr | Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations |
| title_full_unstemmed | Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations |
| title_short | Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations |
| title_sort | augmenting precision medicine via targeted rna seq detection of expressed mutations |
| url | https://doi.org/10.1038/s41698-025-00993-8 |
| work_keys_str_mv | AT danli augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT jianyingli augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT donaldjjohann augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT danielbutler augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT guangchunchen augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT jonathanfoox augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT binshenggong augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT wendelljones augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT davidpkreil augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT rebeccakusko augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT pawełpłabaj augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT annebergstromlucas augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT christopheremason augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT christophermozsary augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT natalianovoradovskaya augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT carlospabonpena augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT bohupan augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT toddarichmond augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT robertamaestro augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT sayedmohammadebrahimsahraeian augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT andreasscherer augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT hagenutilgner augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT jamescwilley augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT pierrerbushel augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations AT joshuaxu augmentingprecisionmedicineviatargetedrnaseqdetectionofexpressedmutations |