Abstract B42: Identification of nucleic acid aptamers for ovarian cancer biomarkers using multiple selection modes and high-throughput sequencing.

Nucleic acid-based affinity probes that specifically recognize ovarian cancer biomarkers in serum may serve as the basis of novel blood tests, whereas use of these affinity probes to direct payloads to tumor-associated markers may enable theranostic and imaging applications. Herein, we report our ongoing efforts to identify nucleic acid aptamers through the SELEX (Systematic Evolution of Ligands by Exponential Enrichment) process. We use the cell-SELEX method to identify single-stranded DNA aptamers to serve as affinity probes for the ovarian cancer markers MUC16 and mesothelin, using cell lines that express these proteins as the target. Further, we have conducted in-vitro selection using purified CA125 and HE4, in separate experiments, as the targets. In all cases, selective pressures are introduced to evolve the initially randomized population of oligonucleotides into a selected sub-population with affinity for the target of interest. The process concludes with sequencing of the oligonucleotides comprising the selected population on an Illumina platform, a high-throughput technology that reveals the sequence information of tens of millions of oligonucleotides, a dramatic improvement over the 10s to 100s of sequences identified by conventional cloning and sequencing. Mining this abundant sequence information has required the development of bioinformatics tools that identify the most promising aptamers for subsequent testing. We have generated a bioinformatics pipeline, using a combination of existing open-source computational tools and a new script to calculate enrichment. We have made this script available through GitHub. Concluding the aptamer selection process with high-throughput sequencing enables the entirety of the selection process, and not only its endpoint, to be characterized. This characterization enabled us to test the following hypotheses: (1) Enrichment of sequences in response to the selective pressures is more important than the abundance of sequences, particularly if the initial “random” pool is sub-optimally randomized; (2) Aptamers belonging to sequence clusters are more likely to display affinity for their targets than “orphan” sequences; (3) An aptamer that is selected against—decreasing its abundance in response to selective pressure—is an effective negative control. We find that biases in as-synthesized “random” libraries can be significant, both in nucleotide abundance and in sequence over-representation. Enriched sequences are more likely to be effective target binders than abundant sequences that result from synthesis or amplification bias. Sequences that are selected against do not display affinity for the target and therefore are effective controls. We acknowledge support from the National Institutes of Health. Citation Format: Rebecca J. Whelan, Arvinder Kapur, Mildred Felder, Jamie Shallcross, Manish S. Patankar. Identification of nucleic acid aptamers for ovarian cancer biomarkers using multiple selection modes and high-throughput sequencing. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr B42.