IL-2Rα-biased agonist enhances antitumor immunity by invigorating tumor-infiltrating CD25+CD8+ T cells.

To avoid regulatory T cell promotion and vascular toxicity, the interleukin-2 receptor-ß/interleukin-2 receptor-γ (IL-2Rßγ)-biased approach is used by most IL-2 analogs in immuno-oncology. However, recent clinical disappointments in these IL-2 agonists have questioned this strategy. Here we show that both wild-type (IL-2wt) and IL-2Rßγ-attenuated (IL-2α-bias) agonists that preserve IL-2Rα (CD25) activities can effectively expand tumor-specific CD8+ T cells (TSTs) and exhibit better antitumor efficacy and safety than the 'non-α' counterpart (IL-2nα). Mechanistically, TSTs coexpress elevated CD25 and PD-1 and are more susceptible to stimulation by IL-2Rα-proficient agonists. Moreover, the antitumor efficacy of anti-PD-1 depends on activation of PD-1+CD25+ TSTs through autocrine IL-2-CD25 signaling. In individuals with cancer, a low IL-2 signature correlates with non-responsiveness to anti-PD-1 treatment. In mouse models, IL-2α-bias, but not IL-2nα, restores the IL-2 signature and synergizes with anti-PD-1 to eradicate large established tumors. These findings underscore the indispensable function of CD25 in IL-2-based immunotherapy and provide rationales for evaluating IL-2Rα-biased agonists in individuals with cancer.

Public Data Set of Protein-Ligand Dissociation Kinetic Constants for Quantitative Structure-Kinetics Relationship Studies.

Protein-ligand binding affinity reflects the equilibrium thermodynamics of the protein-ligand binding process. Binding/unbinding kinetics is the other side of the coin. Computational models for interpreting the quantitative structure-kinetics relationship (QSKR) aim at predicting protein-ligand binding/unbinding kinetics based on protein structure, ligand structure, or their complex structure, which in principle can provide a more rational basis for structure-based drug design. Thus far, most of the public data sets used for deriving such QSKR models are rather limited in sample size and structural diversity. To tackle this problem, we have compiled a set of 680 protein-ligand complexes with experimental dissociation rate constants (k off), which were mainly curated from the references accumulated for updating our PDBbind database. Three-dimensional structure of each protein-ligand complex in this data set was either retrieved from the Protein Data Bank or carefully modeled based on a proper template. The entire data set covers 155 types of protein, with their dissociation kinetic constants (k off) spanning nearly 10 orders of magnitude. To the best of our knowledge, this data set is the largest of its kind reported publicly. Utilizing this data set, we derived a random forest (RF) model based on protein-ligand atom pair descriptors for predicting k off values. We also demonstrated that utilizing modeled structures as additional training samples will benefit the model performance. The RF model with mixed structures can serve as a baseline for testifying other more sophisticated QSKR models. The whole data set, namely, PDBbind-koff-2020, is available for free download at our PDBbind-CN web site (http://www.pdbbind.org.cn/download.php).

Optimal target saturation of ligand-blocking anti-GITR antibody IBI37G5 dictates FcγR-independent GITR agonism and antitumor activity.

Glucocorticoid-induced tumor necrosis factor receptor (GITR) is a co-stimulatory receptor and an important target for cancer immunotherapy. We herein present a potent FcγR-independent GITR agonist IBI37G5 that can effectively activate effector T cells and synergize with anti-programmed death 1 (PD1) antibody to eradicate established tumors. IBI37G5 depends on both antibody bivalency and GITR homo-dimerization for efficient receptor cross-linking. Functional analyses reveal bell-shaped dose responses due to the unique 2:2 antibody-receptor stoichiometry required for GITR activation. Antibody self-competition is observed after concentration exceeded that of 100% receptor occupancy (RO), which leads to antibody monovalent binding and loss of activity. Retrospective pharmacokinetics/pharmacodynamics analysis demonstrates that the maximal efficacy is achieved at medium doses with drug exposure near saturating GITR occupancy during the dosing cycle. Finally, we propose an alternative dose-finding strategy that does not rely on the traditional maximal tolerated dose (MTD)-based paradigm but instead on utilizing the RO-function relations as biomarker to guide the clinical translation of GITR and similar co-stimulatory agonists.

A bispecific antibody targeting GPC3 and CD47 induced enhanced antitumor efficacy against dual antigen-expressing HCC.

Glypican-3 (GPC3) is a well-characterized hepatocellular carcinoma (HCC)-associated antigen, yet anti-GPC3 therapies have achieved only minimal clinical progress. CD47 is a ubiquitously expressed innate immune checkpoint that promotes evasion of tumors from immune surveillance. Given both the specific expression of GPC3 in HCC and the known phagocytosis inhibitory effect of CD47 in liver cancer, we hypothesized that a bispecific antibody (BsAb) that co-engages with GPC3 and CD47 may offer excellent antitumor efficacy with minimal toxicity. Here, we generated a novel BsAb: GPC3/CD47 biAb. With the use of both in vitro and in vivo assays, we found that GPC3/CD47 biAb exerts strong antitumor activity preferentially against dual antigen-expressing tumor cells. In hCD47/human signal regulatory protein alpha (hCD47/hSIRPα) humanized mice, GPC3/CD47 biAb had an extended serum half-life without causing systemic toxicity. Importantly, GPC3/CD47 biAb induced enhanced Fc-mediated effector functions to dual antigen-expressing HCC cells in vitro, and both macrophages and neutrophils are required for its strong efficacy against xenograft HCC tumors. Notably, GPC3/CD47 biAb outperformed monotherapies and a combination therapy with anti-CD47 and anti-GPC3 monoclonal antibodies (mAbs) in a xenograft HCC model. Our study illustrates a strategy for improving HCC treatment by boosting innate immune responses and presents new insights to inform antibody design for the future development of innovative immune therapies.

Novel Abs targeting the N-terminus of fibroblast growth factor 19 inhibit hepatocellular carcinoma growth without bile-acid-related side-effects.

Hepatocellular carcinoma (HCC) is a common and particularly fatal form of cancer for which very few drugs are effective. The fibroblast growth factor 19 (FGF19) has been viewed as a driver of HCC development and a potential Ab target for developing novel HCC therapy. However, a previously developed anti-FGF19 Ab disrupted FGF19's normal regulatory function and caused severe bile-acid-related side-effects despite of having potent antitumor effects in preclinical models. Here, we developed novel human Abs (G1A8 and HS29) that specifically target the N-terminus of FGF19. Both Abs inhibited FGF19-induced HCC cell proliferation in vitro and significantly suppressed HCC tumor growth in mouse models. Importantly, no bile-acid-related side effects were observed in preclinical cynomolgus monkeys. Fundamentally, our study demonstrates that it is possible to target FGF19 for anti-HCC therapies without adversely affecting its normal bile acid regulatory function, and highlights the exciting promise of G1A8 or HS29 as potential therapy for HCC.