Abstract 1895: Improving capability for biomarker discovery of glioblastoma-enriched poly-ligand profiling library using aptamer capture microarrays

Abstract Adaptive dynamic artificial poly-ligand targeting (ADAPT) biotargeting system is an innovative aptamer-based poly-ligand profiling and therapeutic target discovery platform employed to uncover the complexity of cancer in various sample types including Formalin-fixed paraffin-embedded tissue (FFPE). The enrichment process, selective evolution of ligands by exponential enrichment (SELEX), selects single-stranded oligodeoxynucleotides (ssODNs) from a diverse starting pool of ssODNs, which are supposed to preferentially bind to markers expressed in cancer tissues. In practice, the biological and technical complexity of sequence selection leads to an enriched library of ssODNs that contains many persistent sequences with poor differential binding between cancer and normal control tissues. Traditionally SELEX is performed to enrich a library from which the top performing candidates are synthesized and characterized, leading to indistinctive sequences being screened out through this time-consuming and expensive process. ADAPT, on the other hand, is predicated on many thousands of unknown interactions between the sequences in the enriched library and their cognate markers in the FFPE tissues. Consequently, the performance of an enriched library for ADAPT is susceptible to the abundance of indiscriminate ssODN sequences. In this work, after identifying potential binder sequences from an enriched library against glioblastoma (GBM) FFPE tissue, we proposed using Aptamer Capture Microarrays (ACM) to isolate sub-pools of sequences of interest and remove indiscriminate ssODNs from the library. Clinical GBM patient and normal control FFPE tissues were stained with a GBM-enriched ADAPT library. The bound libraries were recovered and sequenced with next generation sequencing (NGS). Different analytical strategies were used to identify sub-pools of sequences that potentially bind preferentially to GBM tissues. By designing microarray probes to capture selected sequences, and then eluting these targeted sequences from the microarray, the percentage of sample reads of the selected sequences were increased from a less than 5% in original enriched library to more than 80% in final cleaned up library. Our results show enhanced discrimination of GBM and normal tissues through FFPE tissue staining. This novel application of microarray capture is a highly cost-effective alternative to oligo pool synthesis, affording multiple partitions of a library to test varied ssODN selection methodologies. Libraries optimized by this method is expected to improve our ability to identify biomarkers. Citation Format: Xixi Wei, Justin Saul, Daniel Martin, Alexis Rodin, Anna Walton, Danielle Richard, Tassilo Hornung. Improving capability for biomarker discovery of glioblastoma-enriched poly-ligand profiling library using aptamer capture microarrays [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1895.