Targeted cancer radioimaging and radiotherapy and the development of tumor-avid molecules using phage display
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Prostate cancer (PCa) is the second leading cause of cancer death in men and new biomarkers are needed to improve diagnostic and therapeutic approaches in aggressive forms of this disease. CD44v6, a splice variant of the transmembrane glycoprotein CD44, has emerged as a promising biomarker for aggressive PCa and has been shown to be strongly correlated with chemo- and radio-resistant PCa. Here, we hypothesized that aggressive PCa could be radioimaged in vivo by targeting CD44v6 with a CD44v6 specific antibody (Ab). We employed three separate imaging strategies using 67Ga as the radiotracer: a direct-labeled Ab approach, a two-step pre-targeting approach, and a three-step pre-targeting approach. All three strategies were able to image PCa in vivo with varying degrees of success. Tumor uptake in the direct-labeled approach reached 6.61 percent ID/g but had tumor/liver and tumor/spleen uptake ratios of 0.19 and 0.33, respectively. The two-step pre-targeting approach lead to improved uptake levels in non-target organs; however, the SPECT/CT images did not improve. Lastly, the three-step pre-targeting approach led to a two-fold increase in tumor/blood uptake ratios compared to the two-step pre-targeting approach, which resulted in greatly improved SPECT/CT images. These results show that CD44v6 is a viable target for imaging PCa in vivo and could be used as a potential therapeutic target. Additionally, these results demonstrate how pre-targeting strategies can overcome poor Ab pharmacokinetic properties. Melanoma is an extremely aggressive cancer and is projected to be one of the deadliest in the United States in 2020. Checkpoint blockade immunotherapy using anti-PD-1 and anti-CTLA-4 antibodies has become the gold standard treatment for metastatic melanoma. However, these current therapeutic strategies suffer from off-target toxicities and resistance. The melanocortin 1 receptor has long been a target of interest in targeted melanoma therapies. Radiolabeled [alpha]-melanocyte stimulating hormone ([alpha]-MSH) peptide derivatives have shown success as imaging and therapeutic agents in pre-clinical trials; however, the high renal uptake limits clinical translation. Conjugation of [alpha]-MSH peptides to ultrasmall, silica-based nanoparticles (C' dots) have greatly improved the pharmacokinetic properties of [alpha]-MSH peptides. 225Ac and 177Lu labeled [alpha]-MSH-C' dots have prolonged survival in melanoma mouse models while also reducing tumor size. These radiolabeled C' dots are also able to initiate an immune response at the tumor suggesting a synergistic effect could be seen using a combination of targeted radiotherapy and immunotherapy. In this study, we evaluated the therapeutic efficacy of a combination of 177Lu-DOTA-[alpha]-MSH-PEG-Cy5-C' dots and a cocktail of anti-PD-1 and anti-CTLA4 antibodies. The combination therapy improved median survival to 21 days compared to 14 days of the PBS control. Additionally, the combination provided a more robust therapeutic response than each method individually. This combination therapy demonstrated a clear survival benefit in mouse melanoma models that supports further clinical translation. Biomarkers found in multiple cancers are appealing targets for drug development as the same drugs could potentially be used to treat a variety of cancers. Mesothelin (MSLN) and Mucin-1 (MUC1) are two transmembrane proteins that are present in a multitude of cancers. MSLN overexpression has been correlated with advanced cancers and poor prognosis. Additionally, MSLN is involved in cancer spread and invasiveness. Like MSLN, MUC1 is heavily involved in signaling pathways that lead to metastasis. MUC1 has also been implicated in chemotherapy resistance. Because of these properties, both MSLN and MUC1 are attractive targets for cancer imaging and therapy applications. We performed two rounds of phage display selection with the McCafferty scFv phage display library and isolated scFvs specific for MSLN and MUC1. The selected clones were able to be expressed and purified from E. coli and bound to pure MSLN and MUC1 protein in ELISAs. Flow cytometry and confocal studies also demonstrated the selected scFvs' ability to recognize MSLN and MUC1 expressed on ovarian, pancreatic, breast, and lung cancer cells. The data from this study laid the foundation for future work in MSLN and MUC1 targeted radioimaging and radiotherapy studies. In phage display selections, only a handful of clones can be analyzed and sequenced by standard Sanger sequencing methods. Next generation sequencing (NGS) technologies have allowed for a much more extensive sequence analysis of phage display selections with the ability to obtain millions of reads in a single run. Several laboratories have analyzed NGS data from phage display selections; however, each group has taken their own unique approach for data analysis. We developed a computational pipeline that can analyze NGS data from any phage display selection regardless of the library used or target selected against with hopes to provide a more common approach to NGS data analysis. The pipeline is able to read FASTQ files generated from an Illumina Sequencer, trim flanking sequences around the randomized inserts of the phage library, translate the nucleic acid sequences into amino acids, count and normalize each sequence, and compare sequence frequencies between a target and a negative control selection. Here we report the successful analysis of NGS data from 3 separate phage display selections using the NEB PhD C7C peptide library, the fuse5 15-mer peptide library, and the McCafferty scFv library. Each analysis provided a ranking of sequences based on log2 ratio values between target and negative selections and produced scatterplots to visualize comparisons. Top sequences were further tested for their ability to bind the targets they were selected against. This computational pipeline is the first of its kind in its ability to analyze NGS data from various phage display selections.
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Ph. D.