5 research outputs found

    Phospho‐RNA‐seq: a modified small RNA‐seq method that reveals circulating mRNA and lncRNA fragments as potential biomarkers in human plasma

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    Extracellular RNAs (exRNAs) in biofluids have attracted great interest as potential biomarkers. Although extracellular microRNAs in blood plasma are extensively characterized, extracellular messenger RNA (mRNA) and long non‐coding RNA (lncRNA) studies are limited. We report that plasma contains fragmented mRNAs and lncRNAs that are missed by standard small RNA‐seq protocols due to lack of 5′ phosphate or presence of 3′ phosphate. These fragments were revealed using a modified protocol (“phospho‐RNA‐seq”) incorporating RNA treatment with T4‐polynucleotide kinase, which we compared with standard small RNA‐seq for sequencing synthetic RNAs with varied 5′ and 3′ ends, as well as human plasma exRNA. Analyzing phospho‐RNA‐seq data using a custom, high‐stringency bioinformatic pipeline, we identified mRNA/lncRNA transcriptome fingerprints in plasma, including tissue‐specific gene sets. In a longitudinal study of hematopoietic stem cell transplant patients, bone marrow‐ and liver‐enriched exRNA genes were tracked with bone marrow recovery and liver injury, respectively, providing proof‐of‐concept validation as a biomarker approach. By enabling access to an unexplored realm of mRNA and lncRNA fragments, phospho‐RNA‐seq opens up new possibilities for plasma transcriptomic biomarker development.SynopsisA modified RNA‐seq method (Phospho‐RNA‐seq) revealed a new population of mRNA/lncRNA fragments in plasma, including ones that track with disease. This opens up new possibilities for disease detection via RNA profiling of plasma and other biofluids.Phospho‐RNA‐seq reveals a large population of mRNA and long non‐coding RNA fragments in human plasma, which are missed by standard small RNA‐seq protocols that depend on target RNAs having a 5′ P and 3′ OH.Accurate detection of plasma mRNA and lncRNA fragments requires a stringent bioinformatic analysis pipeline to avoid false positive alignments to mRNA and lncRNA genes.Phospho‐RNA‐seq identified ensembles of tissue‐specific transcripts in plasma of hematopoietic stem cell transplant patients, which show co‐expression patterns that vary dynamically and track with pathophysiological processes.By enabling access to an unexplored space of extracellular mRNA and lncRNA fragments, phospho‐RNA‐seq opens up new possibilities for monitoring health and disease via transcriptome fragment profiling of plasma and potentially other biofluids.A modified RNA‐seq method reveals a large population of mRNA/lncRNA fragments in plasma that are missed by standard small RNA‐seq protocols including ones that are associated with disease.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149518/1/embj2019101695_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149518/2/embj2019101695-sup-0002-EVFigs.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149518/3/embj2019101695.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149518/4/embj2019101695-sup-0001-Appendix.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149518/5/embj2019101695.reviewer_comments.pd

    Rapid, ultra low coverage copy number profiling of cell-free DNA as a precision oncology screening strategy.

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    Current cell-free DNA (cfDNA) next generation sequencing (NGS) precision oncology workflows are typically limited to targeted and/or disease-specific applications. In advanced cancer, disease burden and cfDNA tumor content are often elevated, yielding unique precision oncology opportunities. We sought to demonstrate the utility of a pan-cancer, rapid, inexpensive, whole genome NGS of cfDNA approach (PRINCe) as a precision oncology screening strategy via ultra-low coverage (~0.01x) tumor content determination through genome-wide copy number alteration (CNA) profiling. We applied PRINCe to a retrospective cohort of 124 cfDNA samples from 100 patients with advanced cancers, including 76 men with metastatic castration-resistant prostate cancer (mCRPC), enabling cfDNA tumor content approximation and actionable focal CNA detection, while facilitating concordance analyses between cfDNA and tissue-based NGS profiles and assessment of cfDNA alteration associations with mCRPC treatment outcomes. Therapeutically relevant focal CNAs were present in 42 (34%) cfDNA samples, including 36 of 93 (39%) mCRPC patient samples harboring AR amplification. PRINCe identified pre-treatment cfDNA CNA profiles facilitating disease monitoring. Combining PRINCe with routine targeted NGS of cfDNA enabled mutation and CNA assessment with coverages tuned to cfDNA tumor content. In mCRPC, genome-wide PRINCe cfDNA and matched tissue CNA profiles showed high concordance (median Pearson correlation = 0.87), and PRINCe detectable AR amplifications predicted reduced time on therapy, independent of therapy type (Kaplan-Meier log-rank test, chi-square = 24.9, p < 0.0001). Our screening approach enables robust, broadly applicable cfDNA-based precision oncology for patients with advanced cancer through scalable identification of therapeutically relevant CNAs and pre-/post-treatment genomic profiles, enabling cfDNA- or tissue-based precision oncology workflow optimization
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