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Neuroblastoma (NB) is the most common extracranial solid tumor in children. The outcomes for aggressive forms of NB remain poor. The aim of this study was to develop a new molecular-targeted therapy for NB using an antisense oligonucleotide (ASO) and superparamagnetic iron oxide (SPIO) nanoparticles (NPs), as a delivery vehicle, targeting the transcription regulator MAX dimerization protein 3 (MXD3). We previously discovered that MXD3 was highly expressed in high-risk NB, acting as an anti-apoptotic factor; therefore, it can be a good therapeutic target. In this study, we developed two ASO-NP complexes using electrostatic conjugation to polyethylenimine-coated SPIO NPs and chemical conjugation to amphiphilic polymers on amine-functionalized SPIO NPs. Both ASO-NP complexes demonstrated MXD3 knockdown, which resulted in apoptosis in NB cells. ASO chemically-conjugated NP complexes have the potential to be used in the clinic as they showed great efficacy with minimum NP-associated cytotoxicity.

RNA molecules can perform a myriad of functions, from the regulation of gene expression to providing the genetic blueprint for protein synthesis. Characterizing RNA expression dynamics, in a cell-specific manner, still remains a great challenge in biology. Herein we present a new set of protected alkynyl nucleosides for cell-specific metabolic labeling of RNA. We anticipate these analogs will find wide spread utility toward the goal of understanding RNA expression in complex cellular and tissue environments, even within living animals.

The cellular RNA pool in animals arises from two separate genomes stored in the nucleus and multiple mitochondria. Chemical methods to track nascent RNA synthesis are unable to distinguish between these two with stringency. Herein, we report that spatially restricting bioorthogonal nucleoside biosynthesis enables, for the first time, selective metabolic labeling of the RNA transcribed in the mitochondria. We envision that this approach could open the door for heretofore-impossible analyses of mitochondrial RNA. Beyond our results revealed herein, our approach provides a roadmap for researchers to begin to design strategies to examine biomolecules within subcellular compartments.

Purification of cell type-specific RNAs remains a significant challenge. One solution involves biosynthetic tagging of target RNAs. RNA tagging via incorporation of 4-thiouracil (TU) in cells expressing transgenic uracil phosphoribosyltransferase (UPRT), a method known as TU-tagging, has been used in multiple systems but can have limited specificity due to endogenous pathways of TU incorporation. Here, we describe an alternative method that requires the activity of two enzymes: cytosine deaminase (CD) and UPRT. We found that the sequential activity of these enzymes converts 5-ethynylcytosine (EC) to 5-ethynyluridine monophosphate that is subsequently incorporated into nascent RNAs. The ethynyl group allows efficient detection and purification of tagged RNAs. We show that 'EC-tagging' occurs in tissue culture cells and Drosophila engineered to express CD and UPRT. Additional control can be achieved through a split-CD approach in which functional CD is reconstituted from independently expressed fragments. We demonstrate the sensitivity and specificity of EC-tagging by obtaining cell type-specific gene expression data from intact Drosophila larvae, including transcriptome measurements from a small population of central brain neurons. EC-tagging provides several advantages over existing techniques and should be broadly useful for investigating the role of differential RNA expression in cell identity, physiology and pathology.

Real-time tracking of RNA expression can provide insight into the mechanisms used to generate cellular diversity, as well as help determine the underlying causes of disease. Here we present the exploration of azide-modified nucleoside analogues and their ability to be metabolically incorporated into cellular RNA. We report robust incorporation of adenosine analogues bearing azide handles at both the 2'- and N6-positions; 5-methylazidouridine was not incorporated into cellular RNA. We further demonstrate selectivity of our adenosine analogues for transcription and polyadenylation. We predict that azidonucleosides will find widespread utility in examining RNA functions inside living cells, as well as in more complex systems such as tissues and living animals.

Background: There is a need to improve prognostic accuracy for patients with cutaneous melanoma. A 31-gene expression profile (31-GEP) test uses the molecular biology of primary tumors to identify individual patient metastatic risk.Objective: Develop a nomogram incorporating 31-GEP with relevant clinical factors to improve prognostic accuracy.Methods: In an IRB-approved study, 1124 patients from 9 Mohs micrographic surgery centers were prospectively enrolled, treated with Mohs micrographic surgery, and underwent 31-GEP testing. Data from 684 of those patients with at least 1-year follow-up or a metastatic event were included in nomogram development to predict metastatic risk.Results: Logistic regression modeling of 31-GEP results and T stage provided the simplest nomogram with the lowest Bayesian information criteria score. Validation in an archival cohort (n = 901) demonstrated a significant linear correlation between observed and nomogram-predicted risk of metastasis. The resulting nomogram more accurately predicts the risk for cutaneous melanoma metastasis than T stage or 31-GEP alone.Limitations: The patient population is representative of Mohs micrographic surgery centers. Sentinel lymph node biopsy was not performed for most patients and could not be used in the nomogram.Conclusions: Integration of 31-GEP and T stage can gain clinically useful prognostic information from data obtained noninvasively. [ABSTRACT FROM AUTHOR]

Stringent chemical methods to profile RNA expression within discrete cellular populations remains a key challenge in biology. To address this issue, we developed a chemical-genetic strategy for metabolic labeling of RNA. Cell-specific labeling of RNA can be profiled and imaged using bioorthogonal chemistry. We anticipate that this platform will provide the community with a much-needed chemical toolset for cell-type specific profiling of cell-specific transcriptomes derived from complex biological systems. [ABSTRACT FROM AUTHOR]