AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers.

Aptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative Systematic Evolution of Ligands by EXponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Herein we present AptamerRunner, an aptamer clustering algorithm that generates visual networks of aptamers that are related by sequence and/or structure. These networks can then be overlayed with ranking data, such as fold enrichment or data from scoring algorithms. The ability to visually integrate data using AptamerRunner represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner has broad-reaching implications for aptamer researchers across a wide range of disciplines.

Selection of a novel cell-internalizing RNA aptamer specific for CD22 antigen in B cell acute lymphoblastic leukemia.

Despite improvements in B cell acute lymphoblastic leukemia (B-ALL) treatment, a significant number of patients experience relapse of the disease, resulting in poor prognosis and high mortality. One of the drawbacks of current B-ALL treatments is the high toxicity associated with the non-specificity of chemotherapeutic drugs. Targeted therapy is an appealing strategy to treat B-ALL to mitigate these toxic off-target effects. One such target is the B cell surface protein CD22. The restricted expression of CD22 on the B-cell lineage and its ligand-induced internalizing properties make it an attractive target in cases of B cell malignancies. To target B-ALL and the CD22 protein, we performed cell internalization SELEX (Systematic Evolution of Ligands by EXponential enrichment) followed by molecular docking to identify internalizing aptamers specific for B-ALL cells that bind the CD22 cell-surface receptor. We identified two RNA aptamers, B-ALL1 and B-ALL2, that target human malignant B cells, with B-ALL1 the first documented RNA aptamer interacting with the CD22 antigen. These B-ALL-specific aptamers represent an important first step toward developing novel targeted therapies for B cell malignancy treatments.

Aptamers as Diagnostic Tools in Cancer.

Cancer is the second leading cause of death worldwide. Researchers have been working hard on investigating not only improved therapeutics but also on early detection methods, both critical to increasing treatment efficacy, and developing methods for disease prevention. The use of nucleic acids, or aptamers, has emerged as more specific and accurate cancer diagnostic and therapeutic tools. Aptamers are single-stranded DNA or RNA molecules that recognize specific targets based on unique three-dimensional conformations. Despite the fact aptamer development has been mainly restricted to laboratory settings, the unique attributes of these molecules suggest their high potential for clinical advances in cancer detection. Aptamers can be selected for a wide range of targets, and also linked with an extensive variety of diagnostic agents, via physical or chemical conjugation, to improve previously-established detection methods or to be used as novel biosensors for cancer diagnosis. Consequently, herein we review the principal considerations and recent updates in cancer detection and imaging through aptamer-based molecules.