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Updated: May 13, 2025
Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
Published on: August 4, 2016
Detecting known neoepitopes, gene fusions, transposable elements, and circular RNAs in cell-free RNA
Mayank Mahajan1, Martin Hemberg1
1Gene Lay Institute of Immunology and Inflammation, Brigham and Women's Hospital, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, United States.
Motivation:
Cancer is the second leading cause of death worldwide, and although there have been advances in treatments, including immunotherapies, these often require biopsies which can be costly and invasive to obtain. Due to lack of pre-emptive cancer detection methods, many cases of cancer are detected at a late stage when the definitive symptoms appear. Plasma samples are relatively easy to obtain, and they can be used to monitor the molecular signatures of ongoing processes in the body. Profiling cell-free DNA is a popular method for monitoring cancer, but only a few studies have explored the use of cell-free RNA (cfRNA), which shows the recent footprint of systemic transcription.
Results:
Here, we developed FastNeo, a computational method for detecting known neoepitopes in human cfRNA. We show that neoepitopes and other biomarkers detected in cfRNA can discern Hepatocellular carcinoma patients from the healthy patients with a sensitivity of 0.84 and a specificity of 0.79. For colorectal cancer we achieve a sensitivity of 0.87 and a specificity of 0.8. An important advantage of our cfRNA based approach is that it also reports putative neoepitopes which are important for therapeutic purposes.
Availability And Implementation:
The FastNeo package is available at https://github.com/yashumayank/FastNeo and https://zenodo.org/records/11521368. The benchmark pipelines to detect Immune Epitope database and Tumor-Specific Neoantigen database neoepitopes using HaplotypeCaller, bcftools, and Lofreq, and to run FastNeo with STAR instead of Bowtie2 are also available in the above github repository.
Insights
This study introduces FastNeo, a novel computational method for detecting neoepitopes in cell-free RNA (cfRNA). FastNeo accurately identifies cancer biomarkers in cfRNA, enabling early detection and therapeutic insights for hepatocellular and colorectal cancers.
Area of Science:
- Biochemistry
- Computational Biology
- Oncology
Background:
- Cancer remains a leading cause of death globally, often diagnosed late due to invasive biopsy requirements and lack of early detection methods.
- Plasma samples offer a minimally invasive source for monitoring systemic molecular signatures, with cell-free DNA (cfDNA) being a popular biomarker.
- Cell-free RNA (cfRNA) analysis is an emerging field, providing insights into recent systemic transcriptional activity.
Purpose of the Study:
- To develop a computational method, FastNeo, for detecting neoepitopes in human cfRNA.
- To assess the efficacy of cfRNA-based biomarkers for cancer detection.
- To identify neoepitopes for potential therapeutic applications.
Main Methods:
- Development of the FastNeo computational package for neoepitope detection in cfRNA.
- Utilized established bioinformatics pipelines for neoepitope identification.
- Benchmarking FastNeo against standard tools like HaplotypeCaller, bcftools, and Lofreq.
Main Results:
- FastNeo successfully detected neoepitopes and other biomarkers in cfRNA.
- The cfRNA approach distinguished hepatocellular carcinoma patients from healthy individuals with 84% sensitivity and 79% specificity.
- Colorectal cancer detection achieved 87% sensitivity and 80% specificity using cfRNA biomarkers.
Conclusions:
- cfRNA analysis, powered by FastNeo, offers a promising non-invasive strategy for early cancer detection.
- The method identifies specific neoepitopes, crucial for guiding targeted immunotherapies.
- FastNeo enhances the utility of cfRNA as a diagnostic and therapeutic tool in oncology.
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