Purpose: Pediatric high-grade glioma (pHGG) diagnosis portends poor prognosis and therapeutic monitoring remains difficult. Tumors release cell-free tumor DNA (cf-tDNA) into cerebrospinal fluid (CSF), allowing for potential detection of tumor-associated mutations by CSF sampling. We hypothesized that direct, electronic analysis of cf-tDNA with a handheld platform (Oxford Nanopore MinION) could quantify patient-specific CSF cf-tDNA variant allele fraction (VAF) with improved speed and limit of detection compared with established methods. Experimental Design: We performed ultra-short fragment (100–200 bp) PCR amplification of cf-tDNA for clinically actionable alterations in CSF and tumor samples from patients with pHGG (n = 12) alongside nontumor CSF (n = 6). PCR products underwent rapid amplicon-based sequencing by Oxford Nanopore Technology (Nanopore) with quantification of VAF. Additional comparison to next-generation sequencing (NGS) and droplet digital PCR (ddPCR) was performed. Results: Nanopore demonstrated 85% sensitivity and 100% specificity in CSF samples (n = 127 replicates) with 0.1 femtomole DNA limit of detection and 12-hour results, all of which compared favorably with NGS. Multiplexed analysis provided concurrent analysis of H3.3A (H3F3A) and H3C2 (HIST1H3B) mutations in a nonbiopsied patient and results were confirmed by ddPCR. Serial CSF cf-tDNA sequencing by Nanopore demonstrated correlation of radiological response on a clinical trial, with one patient showing dramatic multi-gene molecular response that predicted long-term clinical response. Conclusions: Nanopore sequencing of ultra-short pHGG CSF cf-tDNA fragments is feasible, efficient, and sensitive with low-input samples thus overcoming many of the barriers restricting wider use of CSF cf-tDNA diagnosis and monitoring in this patient population.
The ongoing pandemic of coronavirus disease 2019 (COVID-19), which results from the rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a significant global public health threat, with molecular mechanisms underlying its pathogenesis largely unknown. In the context of viral infections, small non-coding RNAs (sncRNAs) are known to play important roles in regulating the host responses, viral replication, and host-virus interaction. Compared with other subfamilies of sncRNAs, including microRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs), tRNA-derived RNA fragments (tRFs) are relatively new and emerge as a significant regulator of host-virus interactions. Using T4 PNK‐RNA‐seq, a modified next-generation sequencing (NGS), we found that sncRNA profiles in human nasopharyngeal swabs (NPS) samples are significantly impacted by SARS-CoV-2. Among impacted sncRNAs, tRFs are the most significantly affected and most of them are derived from the 5′-end of tRNAs (tRF5). Such a change was also observed in SARS-CoV-2-infected airway epithelial cells. In addition to host-derived ncRNAs, we also identified several small virus-derived ncRNAs (svRNAs), among which a svRNA derived from CoV2 genomic site 346 to 382 (sv-CoV2-346) has the highest expression. The induction of both tRFs and sv-CoV2-346 has not been reported previously, as the lack of the 3′-OH ends of these sncRNAs prevents them to be detected by routine NGS. In summary, our studies demonstrated the involvement of tRFs in COVID-19 and revealed new CoV2 svRNAs.
Given the diverse molecular pathways involved in tumorigenesis, identifying subgroups among cancer patients is crucial in precision medicine. While most targeted therapies rely on DNA mutation status in tumors, responses to such therapies vary due to the many molecular processes involved in propagating DNA changes to proteins (which constitute the usual drug targets). Though RNA expressions have been extensively used to categorize tumors, identifying clinically important subgroups remains challenging given the difficulty of discerning subgroups within all possible RNA-RNA networks. It is thus essential to incorporate multiple types of data. Recently, RNA was found to regulate other RNA through a common microRNA (miR). These regulating and regulated RNAs are referred to as competing endogenous RNAs (ceRNAs). However, global correlations between mRNA and miR expressions across all samples have not reliably yielded ceRNAs. In this study, we developed a ceRNA-based method to identify subgroups of cancer patients combining DNA copy number variation, mRNA expression, and microRNA (miR) expression data with biological knowledge. Clinical data is used to validate identified subgroups and ceRNAs. Since ceRNAs are causal, ceRNA-based subgroups may present clinical relevance. Using lung adenocarcinoma data from The Cancer Genome Atlas (TCGA) as an example, we focused on EGFR amplification status, since a targeted therapy for EGFR exists. We hypothesized that global correlations between mRNA and miR expressions across all patients would not reveal important subgroups and that clustering of potential ceRNAs might define molecular pathway-relevant subgroups. Using experimentally validated miR-target pairs, we identified EGFR and MET as potential ceRNAs for miR-133b in lung adenocarcinoma. The EGFR-MET up and miR-133b down subgroup showed a higher death rate than the EGFR-MET down and miR-133b up subgroup. Although transactivation between MET and EGFR has been identified previously, our result is the first to propose ceRNA as one of its underlying mechanisms. Furthermore, since MET amplification was seen in the case of resistance to EGFR-targeted therapy, the EGFR-MET up and miR-133b down subgroup may fall into the drug non-response group and thus preclude EGFR target therapy.
The ongoing pandemic of coronavirus disease 2019 (COVID-19), which results from the rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a significant global public health threat, with molecular mechanisms underlying its pathogenesis largely unknown. Small non-coding RNAs (sncRNAs) are known to play important roles in almost all biological processes. In the context of viral infections, sncRNAs have been shown to regulate the host responses, viral replication, and host-virus interaction. Compared with other subfamilies of sncRNAs, including microRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs), tRNA-derived RNA fragments (tRFs) are relatively new and emerge as a significant regulator of host-virus interactions. Using T4 PNK-RNA-seq, a modified next-generation sequencing (NGS), we recently found that nasopharyngeal swabs (NPS) samples from SARS-CoV-2 positive and negative subjects show a significant difference in sncRNA profiles. There are about 166 SARS-CoV-2-impacted sncRNAs. Among them, tRFs are the most significantly affected and almost all impacted tRFs are derived from the 5'-end of tRNAs (tRF5). Using a modified qRT-PCR, which was recently developed to specifically quantify tRF5s by isolating the tRF signals from its corresponding parent tRNA signals, we validated that tRF5s derived from tRNA GluCTC (tRF5-GluCTC), LysCTT (tRF5-LysCTT), ValCAC (tRF5-ValCAC), CysGCA (tRF5-CysGCA) and GlnCTG (tRF5-GlnCTG) are enhanced in NPS samples of SARS-CoV2 patients and SARS41 CoV2-infected airway epithelial cells. In addition to host-derived ncRNAs, we also identified several sncRNAs derived from the virus (svRNAs), among which a svRNA derived from CoV2 genomic site 346 to 382 (sv-CoV2-346) has the highest expression. The induction of both tRFs and sv-CoV2-346 has not been reported previously, as the lack of the 3'-OH ends of these sncRNAs prevents them to be detected by routine NGS. In summary, our studies demonstrated the involvement of tRFs in COVID-19 and revealed new CoV2 svRNAs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.