Dataset Information

Detection of extracellular RNAs in cancer and viral infection via tethered cationic lipoplex nanoparticles containing molecular beacons.

ABSTRACT: Noninvasive early detection methods have the potential to reduce mortality rates of both cancer and infectious diseases. Here, we present a novel assay by which tethered cationic lipoplex nanoparticles containing molecular beacons (MBs) can capture cancer cell-derived exosomes or viruses and identify encapsulated RNAs in a single step. A series of ultracentrifugation and Exoquick isolation kit were first used to isolate exosomes from the cell culture medium and human serum, respectively. Cationic lipoplex nanoparticles linked onto the surface of a thin glass plate capture negatively charged viruses or cell-secreted exosomes by electrostatic interactions to form larger nanoscale complexes. Lipoplex/virus or lipoplex/exosome fusion leads to the mixing of viral/exosomal RNAs and MBs within the lipoplexes. After the target RNAs specially bind to the MBs, exosomes enriched in target RNAs are readily identified by the fluorescence signals of MBs. The in situ detection of target extracellular RNAs without diluting the samples leads to high detection sensitivity not achievable by existing methods, e.g., quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Here we demonstrate this concept using lentivirus and serum from lung cancer patients.

SUBMITTER: Wu Y

PROVIDER: S-EPMC4121114 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Detection of extracellular RNAs in cancer and viral infection via tethered cationic lipoplex nanoparticles containing molecular beacons.

Wu Yun Y Kwak Kwang Joo KJ Agarwal Kitty K Marras Alexander A Wang Chao C Mao Yicheng Y Huang Xiaomeng X Ma Junyu J Yu Bo B Lee Robert R Vachani Anil A Marcucci Guido G Byrd John C JC Muthusamy Natarajan N Otterson Gregory G Huang Kun K Castro Carlos E CE Paulaitis Michael M Nana-Sinkam Serge P SP Lee L James LJ

Analytical chemistry 20131113 23

Noninvasive early detection methods have the potential to reduce mortality rates of both cancer and infectious diseases. Here, we present a novel assay by which tethered cationic lipoplex nanoparticles containing molecular beacons (MBs) can capture cancer cell-derived exosomes or viruses and identify encapsulated RNAs in a single step. A series of ultracentrifugation and Exoquick isolation kit were first used to isolate exosomes from the cell culture medium and human serum, respectively. Cationi ...[more]

PMID: 24102152

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Project description:Rationale: Long extracellular RNAs (exRNAs) in plasma can be profiled by new sequencing technologies, even with low abundance. However, cancer-related exRNAs and their variations remain understudied. Methods: We investigated different variations (i.e. differential expression, alternative splicing, alternative polyadenylation, and differential editing) in diverse long exRNA species (e.g. long noncoding RNAs and circular RNAs) using 79 plasma exosomal RNA-seq (exoRNA-seq) datasets of multiple cancer types. We then integrated 53 exoRNA-seq datasets and 65 self-profiled cell-free RNA-seq (cfRNA-seq) datasets to identify recurrent variations in liver cancer patients. We further combined TCGA tissue RNA-seq datasets and validated biomarker candidates by RT-qPCR in an individual cohort of more than 100 plasma samples. Finally, we used machine learning models to identify a signature of 3 noncoding RNAs for the detection of liver cancer. Results: We found that different types of RNA variations identified from exoRNA-seq data were enriched in pathways related to tumorigenesis and metastasis, immune, and metabolism, suggesting that cancer signals can be detected from long exRNAs. Subsequently, we identified more than 100 recurrent variations in plasma from liver cancer patients by integrating exoRNA-seq and cfRNA-seq datasets. From these datasets, 5 significantly up-regulated long exRNAs were confirmed by TCGA data and validated by RT-qPCR in an independent cohort. When using machine learning models to combine two of these validated circular and structured RNAs (SNORD3B-1, circ-0080695) with a miRNA (miR-122) as a panel to classify liver cancer patients from healthy donors, the average AUROC of the cross-validation was 89.4%. The selected 3-RNA panel successfully detected 79.2% AFP-negative samples and 77.1% early-stage liver cancer samples in the testing and validation sets. Conclusions: Our study revealed that different types of RNA variations related to cancer can be detected in plasma and identified a 3-RNA detection panel for liver cancer, especially for AFP-negative and early-stage patients.

Dataset Information

Detection of extracellular RNAs in cancer and viral infection via tethered cationic lipoplex nanoparticles containing molecular beacons.

Publications

Detection of extracellular RNAs in cancer and viral infection via tethered cationic lipoplex nanoparticles containing molecular beacons.

Similar Datasets

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