RESUMEN
Body fluids in the context of cancer diagnosis are the primary source of liquid biopsy, i.e., biomarker detection that includes blood and serum, urine, and saliva. RNA represents a particular class of biomarkers because it is thought to monitor the current status of gene expression in humans, in organs, and if present, also in tumors. In case of bladder cancer, we developed a scheme that describes, in detail, all steps from the collection of urine samples from patients, stabilization of samples, their transportation, storage, and marker analysis by qPCR-based technology. We find that urine samples prepared according to this protocol show stability of RNA over more than 10 days at unchilled temperatures during shipping. A specific procedure of primer design and amplicon evaluation allows a specific assignment of PCR products to human genomics and transcriptomics data collections. In summary, we describe a technical option for the robust acquisition of urine samples and the quantitative detection of RNA-based tumor markers in case of bladder cancer patients. This protocol is for general use, and we describe that it works for any RNA-based tumor marker in urine of cancer patients.
RESUMEN
The discovery of RNA interference (RNAi) gave rise to the development of new nucleic acid-based technologies as powerful investigational tools and potential therapeutics. Mechanistic key details of RNAi in humans need to be deciphered yet, before such approaches take root in biomedicine and molecular therapy. We developed and validated an in silico-based model of siRNA-mediated RNAi in human cells in order to link in vitro-derived pre-steady state kinetic data with a quantitative and time-resolved understanding of RNAi on the cellular level. The observation that product release by Argonaute 2 is accelerated in the presence of an excess of target RNA in vitro inspired us to suggest an associative mechanism for the RNA slicer reaction where incoming target mRNAs actively promote dissociation of cleaved mRNA fragments. This novel associative model is compatible with high multiple turnover rates of RNAi-based gene silencing in living cells and accounts for target mRNA concentration-dependent enhancement of the RNAi machinery.
Asunto(s)
Interferencia de ARN , ARN Mensajero/metabolismo , Proteínas Argonautas/metabolismo , Simulación por Computador , Células HeLa , Humanos , Cinética , Modelos Genéticos , ARN Interferente Pequeño/metabolismoRESUMEN
A number of theoretical and experimental approaches to design biologically active antisense oligonucleotides (AS-ON) have proven their usefulness. This includes systematic computational strategies that are based on the understanding of antisense mechanisms. Here, we investigate in detail the relationship between computational parameters of the local target search for the theoretical design of AS-ON and the hit rate, that is, the biologic efficacy of AS-ON in cell culture. The computational design of AS-ON studied in this work is based on an established algorithm to predict structurally favorable local target sites along a given target RNA against which AS-ON are directed. Briefly, a sequence segment of a certain length (window) is used to predict a group of lowest-energy RNA secondary structures. Subsequently, this window is shifted along the target sequence by a certain step width. To date, those technical parameters of the systematic structural target analysis have been chosen arbitrarily. Here, we investigate their role for the successful design of AS-ON and suggest an optimized computer-based protocol for the selection of favorable local target sequences and, hence, an improved design of active AS-ON. Further, this study provides systematic insights into the structure- function relationship of AS-ON.