Liposome-Encapsulated Eribulin Shows Enhanced Antitumor Activity over Eribulin for Combination Therapy with Anti-PD-1 Antibody.

Eribulin is a microtubule dynamics inhibitor with tumor microenvironment modulation activity such as vascular remodeling activity. Here, we investigated antitumor and immunomodulatory activities of eribulin and its liposomal formulation (eribulin-LF) as monotherapies or in combination with anti-programmed death 1 (PD-1) Ab. The antitumor activity of eribulin or eribulin-LF as monotherapy or in combination with anti-PD-1 Ab was examined in a P-glycoprotein-knockout 4T1 model. Eribulin and eribulin-LF showed stronger antitumor activity in immunocompetent mice compared with immunodeficient mice, indicating that they have immunomodulatory activity that underlies its antitumor activity. Combination therapy of eribulin and eribulin-LF with anti-PD-1 Ab showed antitumor activity, and the combination activity of eribulin-LF with anti-PD-1 Ab was observed at a lower dose and longer interval of administration compared with that using eribulin. To examine the immunomodulatory activity of eribulin and eribulin-LF and its underlying mechanisms, we performed flow cytometry, IHC, and gene expression profiling. IHC and flow cytometry revealed that eribulin-LF increased microvessel density and intratumoral populations of cytotoxic T cells and natural killer cells rather than eribulin. Gene expression profiling demonstrated that eribulin-LF induces IFNγ signaling. Furthermore, IHC also showed that eribulin-LF increased infiltration of CD8-positive cells together with increased CD31-positive cells. Eribulin-LF also increased ICAM-1 expression, which is essential for lymphocyte adhesion to vascular endothelial cells. In conclusion, eribulin showed combination antitumor activity with anti-PD-1 Ab via immunomodulation due to its vascular remodeling activity, and the liposomal formulation showed improved antitumor activity over the standard formulation.

HT-SELEX-based identification of binding pre-miRNA hairpin-motif for small molecules.

Selective targeting of biologically relevant RNAs with small molecules is a long-standing challenge due to the lack of clear understanding of the binding RNA motifs for small molecules. The standard SELEX procedure allows the identification of specific RNA binders (aptamers) for the target of interest. However, more effort is needed to identify and characterize the sequence-structure motifs in the aptamers important for binding to the target. Herein, we described a strategy integrating high-throughput (HT) sequencing with conventional SELEX followed by bioinformatic analysis to identify aptamers with high binding affinity and target specificity to unravel the sequence-structure motifs of pre-miRNA, which is essential for binding to the recently developed new water-soluble small-molecule CMBL3aL. To confirm the fidelity of this approach, we investigated the binding of CMBL3aL to the identified motifs by surface plasmon resonance (SPR) spectroscopy and its potential regulatory activity on dicer-mediated cleavage of the obtained aptamers and endogenous pre-miRNAs comprising the identified motif in its hairpin loop. This new approach would significantly accelerate the identification process of binding sequence-structure motifs of pre-miRNA for the compound of interest and would contribute to increase the spectrum of biomedical application.

RaptRanker: in silico RNA aptamer selection from HT-SELEX experiment based on local sequence and structure information.

Aptamers are short single-stranded RNA/DNA molecules that bind to specific target molecules. Aptamers with high binding-affinity and target specificity are identified using an in vitro procedure called high throughput systematic evolution of ligands by exponential enrichment (HT-SELEX). However, the development of aptamer affinity reagents takes a considerable amount of time and is costly because HT-SELEX produces a large dataset of candidate sequences, some of which have insufficient binding-affinity. Here, we present RNA aptamer Ranker (RaptRanker), a novel in silico method for identifying high binding-affinity aptamers from HT-SELEX data by scoring and ranking. RaptRanker analyzes HT-SELEX data by evaluating the nucleotide sequence and secondary structure simultaneously, and by ranking according to scores reflecting local structure and sequence frequencies. To evaluate the performance of RaptRanker, we performed two new HT-SELEX experiments, and evaluated binding affinities of a part of sequences that include aptamers with low binding-affinity. In both datasets, the performance of RaptRanker was superior to Frequency, Enrichment and MPBind. We also confirmed that the consideration of secondary structures is effective in HT-SELEX data analysis, and that RaptRanker successfully predicted the essential subsequence motifs in each identified sequence.