Abstract P4-12-08: Use of an aptamer library based next generation omics platform for the development of a novel trastuzumab predictive assay
Authors: Spetzler D , Domenyuk V , Santhanam R , Wei X , Stark A , Wang J , Gatalica Z , Miglarese M , Vidal G , Schwartzberg LS 
Published: March 2017

Abstract
Introduction: Previous attempts to use individual aptamers as diagnostic reagents have failed to consistently achieve performance comparable to antibodies. Here we report a novel systems biology approach using poly-ligand aptamer libraries to identify responders and non-responders to traztuzumab-based regimens in metastatic breast cancer.
Methods: To overcome the fundamental limitation of the individual aptamer binding affinities, large libraries (106 species) were created so that potentially thousands of aptamers could bind to each of a multitude of targets related to the whole cellular changes in response to trastuzumab therapy. A set of breast cancer patients, which received trastuzumab mono- or combined therapy for at least 7 months were classified as “Responders” (R); cases with particular regimen discontinued in the period not exceeding 5 months were classified as “Non-Responders”(NR). A library of 2x1012 unique 90-mer ssDNA oligodeoxynucleotides (ssODN) was trained on FFPE tissue of both R and NR patients. Partitioning of aptamer libraries was done by microdissection of the tumor tissue, after incubation of aptamer library with the entire tissue section, to drive selection pressure toward cancer cells. A total of 10 cases of R and NR, 6 Her2+ cases each, were used to train separate aptamer libraries, with 1 positive and 2 counter selection cases per enrichment. Enriched libraries were screened on 20 R and 20 NR cases (11 Her2+ cases each) by adopting modified immunohistochemistry protocol. Each library was used as an independent reagent (similar to an antibody in IHC) across all 40 cases to evaluate the efficacy of the aptamer library to distinguish differences between the R and NR groups. Staining (DAB chromogen) profiles were scored from 0 to 3+ (nuclear and cytoplasmic staining) by a pathologist without any knowledge of the clinical outcomes. Initial validation was done by t-test using raw histological scores. Four libraries showed significant p-values between groups of responders and non-responders, a classification algorithm was constructed and evaluated using area under the receiver-operator characteristic curve (AUC). The datasets of two best-performing libraries were combined into one model using logistic regression to further improved the classifier performance.
Results: Of seventeen trained libraries, eight were evaluated and four showed significant correlation to clinical benefit with a minimum accuracy of 75% for each library when evaluated independently. Furthermore, two libraries showed exceptional performance (ROC curve AUC of 0.86 and 0.77). Combination of the profiling data from these two libraries using logistic regression resulted in an AUC of 0.985. A prospective validation of aptamer histochemical theranostic testing has been initiated.
Summary: Enriched aptamer libraries appear to distinguish trastuzumab responsiveness in metastatic breast cancer. This technology could be used as an additional technique beyond FISH testing to determine sensitivity to anti-HER2 agents. The demonstrated platform is applicable to virtually any disease where the safe and effective use of corresponding drug is yet to be improved.
Citation Format: Spetzler D, Domenyuk V, Santhanam R, Wei X, Stark A, Wang J, Gatalica Z, Miglarese M, Vidal G, Schwartzberg LS. Use of an aptamer library based next generation omics platform for the development of a novel trastuzumab predictive assay [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-12-08.