Structure and interactions of the human programmed cell death 1 receptor

Mathematical modeling and analysis of cancer treatment with radiation and anti-PD-L1

In cancer treatment, radiation therapy (RT) induces direct tumor cell death due to DNA damage, but it also enhances the deaths of radiosensitive immune cells and is followed by local relapse and up-regulation of immune checkpoint ligand PD-L1. Since the binding between PD-1 and PD-L1 curtails anti-tumor immunities, combining RT and PD-L1 inhibitor, anti-PD-L1, is a potential method to improve the treatment efficacy by RT. Some experiments support this hypothesis by showing that the combination of ionizing irradiation (IR) and anti-PD-L1 improves tumor reduction comparing to the monotherapy of IR or anti-PD-L1. In this work, we create a simplified ODE model to study the order of tumor growths under treatments of IR and anti-PD-L1. Our synergy analysis indicates that both IR and anti-PD-L1 improve the tumor reduction of each other, when IR and anti-PD-L1 are given simultaneously. When giving IR and anti-PD-L1 separately, a high dosage of IR should be given first to efficiently reduce tumor load and then followed by anti-PD-L1 with strong efficacy to maintain the tumor reduction and slow down the relapse. Increasing the duration of anti-PD-L1 improves the tumor reduction, but it cannot prolong the duration that tumor relapses to the level of the control case. Under some simplification, we also prove that the model has an unstable tumor free equilibrium and a locally asymptotically stable tumor persistent equilibrium. Our bifurcation diagram reveals a transition from tumor elimination to tumor persistence, as the tumor growth rate increases. In the tumor persistent case, both anti-PD-L1 and IR can reduce tumor amount in the long term.

In Search of Better Peptide-(Derived from PD-L2)-Based Immune Checkpoint Inhibitors

Current anti-cancer immune checkpoint therapy relies on antibodies that primarily target the PD-1/PD-L1(-L2) negative regulatory pathway. Although very successful in some cases for certain cancers, these antibodies do not help most patients who, presumably, should benefit from this type of therapy. Therefore, an unmet clinical need for novel, more effective drugs targeting immune checkpoints remains. We have developed a series of high-potency peptide inhibitors interfering with PD-1/PD-L1(-L2) protein-protein interaction. Our best peptide inhibitors are 12 and 14 amino acids long and show sub-micromolar IC50 inhibitory activity in the in vitro assay. The positioning of the peptides within the PD-1 binding site is explored by extensive modeling. It is further supported by 2D NMR studies of PD-1/peptide complexes. These results reflect substantial progress in the development of immune checkpoint inhibitors using peptidomimetics.

Engineering PD-1-targeted small protein variants for in vitro diagnostics and in vivo PET imaging

BACKGROUND

Programmed cell death 1 (PD-1) belongs to immune checkpoint proteins ensuring negative regulation of the immune response. In non-small cell lung cancer (NSCLC), the sensitivity to treatment with anti-PD-1 therapeutics, and its efficacy, mostly correlated with the increase of tumor infiltrating PD-1+ lymphocytes. Due to solid tumor heterogeneity of PD-1+ populations, novel low molecular weight anti-PD-1 high-affinity diagnostic probes can increase the reliability of expression profiling of PD-1+ tumor infiltrating lymphocytes (TILs) in tumor tissue biopsies and in vivo mapping efficiency using immune-PET imaging.

METHODS

We designed a 13 kDa β-sheet Myomedin scaffold combinatorial library by randomization of 12 mutable residues, and in combination with ribosome display, we identified anti-PD-1 Myomedin variants (MBA ligands) that specifically bound to human and murine PD-1-transfected HEK293T cells and human SUP-T1 cells spontaneously overexpressing cell surface PD-1.

RESULTS

Binding affinity to cell-surface expressed human and murine PD-1 on transfected HEK293T cells was measured by fluorescence with LigandTracer and resulted in the selection of most promising variants MBA066 (hPD-1 KD = 6.9 nM; mPD-1 KD = 40.5 nM), MBA197 (hPD-1 KD = 29.7 nM; mPD-1 KD = 21.4 nM) and MBA414 (hPD-1 KD = 8.6 nM; mPD-1 KD = 2.4 nM). The potential of MBA proteins for imaging of PD-1+ populations in vivo was demonstrated using deferoxamine-conjugated MBA labeled with 68Galium isotope. Radiochemical purity of 68Ga-MBA proteins reached values 94.7-99.3% and in vitro stability in human serum after 120 min was in the range 94.6-98.2%. The distribution of 68Ga-MBA proteins in mice was monitored using whole-body positron emission tomography combined with computerized tomography (PET/CT) imaging up to 90 min post-injection and post mortem examined in 12 mouse organs. The specificity of MBA proteins was proven by co-staining frozen sections of human tonsils and NSCLC tissue biopsies with anti-PD-1 antibody, and demonstrated their potential for mapping PD-1+ populations in solid tumors.

CONCLUSIONS

Using directed evolution, we developed a unique set of small binding proteins that can improve PD-1 diagnostics in vitro as well as in vivo using PET/CT imaging.

Emerging therapeutic frontiers in cancer: insights into posttranslational modifications of PD-1/PD-L1 and regulatory pathways

The interaction between programmed cell death ligand 1 (PD-L1), which is expressed on the surface of tumor cells, and programmed cell death 1 (PD-1), which is expressed on T cells, impedes the effective activation of tumor antigen-specific T cells, resulting in the evasion of tumor cells from immune-mediated killing. Blocking the PD-1/PD-L1 signaling pathway has been shown to be effective in preventing tumor immune evasion. PD-1/PD-L1 blocking antibodies have garnered significant attention in recent years within the field of tumor treatments, given the aforementioned mechanism. Furthermore, clinical research has substantiated the efficacy and safety of this immunotherapy across various tumors, offering renewed optimism for patients. However, challenges persist in anti-PD-1/PD-L1 therapies, marked by limited indications and the emergence of drug resistance. Consequently, identifying additional regulatory pathways and molecules associated with PD-1/PD-L1 and implementing judicious combined treatments are imperative for addressing the intricacies of tumor immune mechanisms. This review briefly outlines the structure of the PD-1/PD-L1 molecule, emphasizing the posttranslational modification regulatory mechanisms and related targets. Additionally, a comprehensive overview on the clinical research landscape concerning PD-1/PD-L1 post-translational modifications combined with PD-1/PD-L1 blocking antibodies to enhance outcomes for a broader spectrum of patients is presented based on foundational research.

Peptide-based inhibitors targeting the PD-1/PD-L1 axis: potential immunotherapeutics for cancer

The PD-1/PD-L1 complex belongs to the group of inhibitory immune checkpoints and plays a critical role in immune regulation. The PD-1/PD-L1 axis is also responsible for immune evasion of cancer cells, and this complex is one of the main targets of immunotherapies used in oncology. Treatment using immune checkpoint inhibitors is mainly based on antibodies. This approach has great therapeutic potential; however, it also has major drawbacks and can induce immune-related adverse events. Thus, there is a strong need for alternative, non-antibody-based therapies using small molecules, peptides, or peptidomimetics. In the present study, we designed, synthesized, and evaluated a set of PD-1-targeting peptides based on the sequence and structure of PD-L1. The binding of these peptides to PD-1 was investigated using SPR and ELISA. We also assessed their ability to compete with PD-L1 for binding to PD-1 and their inhibitory properties against the PD-1/PD-L1 complex at the cellular level. The best results were obtained for the peptide PD-L1(111-127)(Y112C-I126C), named (L11), which displaced PD-L1 from binding to PD-1 in the competitive assay and inhibited the formation of the PD-1/PD-L1 complex. The (L11) peptide also exhibited strong affinity for PD-1. NMR studies revealed that (L11) does not form a well-defined secondary structure; however, MD simulation indicated that (L11) binds to PD-1 at the same place as PD-L1. After further optimization of the structure, the peptide inhibitor obtained in this study could also be used as a potential therapeutic compound targeting the PD-1/PD-L1 axis.

Engineering a Programmed Death-Ligand 1-Targeting Monobody Via Directed Evolution for SynNotch-Gated Cell Therapy

Programmed death-ligand 1 (PD-L1) is a promising target for cancer immunotherapy due to its ability to inhibit T cell activation; however, its expression on various noncancer cells may cause on-target off-tumor toxicity when designing PD-L1-targeting Chimeric Antigen Receptor (CAR) T cell therapies. Combining rational design and directed evolution of the human fibronectin-derived monobody scaffold, "PDbody" was engineered to bind to PD-L1 with a preference for a slightly lower pH, which is typical in the tumor microenvironment. PDbody was further utilized as a CAR to target the PD-L1-expressing triple negative MDA-MB-231 breast cancer cell line. To mitigate on-target off-tumor toxicity associated with targeting PD-L1, a Cluster of Differentiation 19 (CD19)-recognizing SynNotch IF THEN gate was integrated into the system. This CD19-SynNotch PDbody-CAR system was then expressed in primary human T cells to target CD19-expressing MDA-MB-231 cancer cells. These CD19-SynNotch PDbody-CAR T cells demonstrated both specificity and efficacy in vitro, accurately eradicating cancer targets in cytotoxicity assays. Moreover, in an in vivo bilateral murine tumor model, they exhibited the capability to effectively restrain tumor growth. Overall, CD19-SynNotch PDbody-CAR T cells represent a distinct development over previously published designs due to their increased efficacy, proliferative capability, and mitigation of off-tumor toxicity for solid tumor treatment.

Transmembrane domain-driven PD-1 dimers mediate T cell inhibition

Programmed cell death-1 (PD-1) is a potent immune checkpoint receptor on T lymphocytes. Upon engagement by its ligands, PD-L1 or PD-L2, PD-1 inhibits T cell activation and can promote immune tolerance. Antagonism of PD-1 signaling has proven effective in cancer immunotherapy, and conversely, agonists of the receptor may have a role in treating autoimmune disease. Some immune receptors function as dimers, but PD-1 has been considered monomeric. Here, we show that PD-1 and its ligands form dimers as a consequence of transmembrane domain interactions and that propensity for dimerization correlates with the ability of PD-1 to inhibit immune responses, antitumor immunity, cytotoxic T cell function, and autoimmune tissue destruction. These observations contribute to our understanding of the PD-1 axis and how it can potentially be manipulated for improved treatment of cancer and autoimmune diseases.

Sokotrasterol Sulfate Suppresses IFN-γ-Induced PD-L1 Expression by Inhibiting JAK Activity

PD-1/PD-L1 monoclonal antibodies exhibit promising therapeutic effectiveness in multiple cancers. However, developing a simple and efficient non-antibody treatment strategy using the PD-1/PD-L1 signaling pathway still remains challenging. In this study, we developed a flow cytometry assay to screen bioactive compounds with PD-L1 inhibitory activity. A total of 409 marine natural products were screened, and sokotrasterol sulfate (SKS) was found to efficiently suppress the IFN-γ-induced PD-L1 expression. SKS sensitizes the tumor cells to antigen-specific T-cell killing in the T cell-tumor cell coculture system. Mechanistically, SKS directly targeted Janus kinase (JAK) to inhibit the downstream activation of signal transducer and activator of transcription (STAT) and the subsequent transcription of PDL1. Our findings highlight the immunological role of SKS that may act as a basis for a potential immunotherapeutic agent.

IL-27 in combination with anti-PD-1 can be anti-cancer or pro-cancer

Interleukin-27 (IL-27) is known to play opposing roles in immunology. The present paper considers, specifically, the role IL-27 plays in cancer immunotherapy when combined with immune checkpoint inhibitor anti-PD-1. We first develop a mathematical model for this combination therapy, by a system of Partial Differential Equations, and show agreement with experimental results in mice injected with melanoma cells. We then proceed to simulate tumor volume with IL-27 injection at a variable dose F and anti-PD-1 at a variable dose g. We show that in some range of "small" values of g, as f increases tumor volume decreases as long as fFc(g), where Fc(g) is a monotone increasing function of g. This demonstrates that IL-27 can be both anti-cancer and pro-cancer, depending on the ranges of both anti-PD-1 and IL-27.

Antibody agonists trigger immune receptor signaling through local exclusion of receptor-type protein tyrosine phosphatases

Antibodies can block immune receptor engagement or trigger the receptor machinery to initiate signaling. We hypothesized that antibody agonists trigger signaling by sterically excluding large receptor-type protein tyrosine phosphatases (RPTPs) such as CD45 from sites of receptor engagement. An agonist targeting the costimulatory receptor CD28 produced signals that depended on antibody immobilization and were sensitive to the sizes of the receptor, the RPTPs, and the antibody itself. Although both the agonist and a non-agonistic anti-CD28 antibody locally excluded CD45, the agonistic antibody was more effective. An anti-PD-1 antibody that bound membrane proximally excluded CD45, triggered Src homology 2 domain-containing phosphatase 2 recruitment, and suppressed systemic lupus erythematosus and delayed-type hypersensitivity in experimental models. Paradoxically, nivolumab and pembrolizumab, anti-PD-1-blocking antibodies used clinically, also excluded CD45 and were agonistic in certain settings. Reducing these agonistic effects using antibody engineering improved PD-1 blockade. These findings establish a framework for developing new and improved therapies for autoimmunity and cancer.

Development and Evaluation of a Quantitative Systems Pharmacology Model for Mechanism Interpretation and Efficacy Prediction of Atezolizumab in Combination with Carboplatin and Nab-Paclitaxel in Patients with Non-Small-Cell Lung Cancer

Immunotherapy has shown clinical benefit in patients with non-small-cell lung cancer (NSCLC). Due to the limited response of monotherapy, combining immune checkpoint inhibitors (ICIs) and chemotherapy is considered a treatment option for advanced NSCLC. However, the mechanism of combined therapy and the potential patient population that could benefit from combined therapy remain undetermined. Here, we developed an NSCLC model based on the published quantitative systems pharmacology (QSP)-immuno-oncology platform by making necessary adjustments. After calibration and validation, the established QSP model could adequately characterise the biological mechanisms of action of the triple combination of atezolizumab, nab-paclitaxel, and carboplatin in patients with NSCLC, and identify predictive biomarkers for precision dosing. The established model could efficiently characterise the objective response rate and duration of response of the IMpower131 trial, reproducing the efficacy of alternative dosing. Furthermore, CD8+ and CD4+ T cell densities in tumours were found to be significantly related to the response status. This significant extension of the QSP model not only broadens its applicability but also more accurately reflects real-world clinical settings. Importantly, it positions the model as a critical foundation for model-informed drug development and the customisation of treatment plans, especially in the context of combining single-agent ICIs with platinum-doublet chemotherapy.

Eliciting the antitumor immune response with a conditionally activated PD-L1 targeting antibody analyzed with a quantitative systems pharmacology model

Conditionally activated molecules, such as Probody therapeutics (PbTx), have recently been investigated to improve antitumoral response while reducing systemic toxicity. PbTx are engineered to be proteolytically activated by proteases that are preferentially active locally in the tumor microenvironment (TME). Here, we perform an exploratory study using our recently published quantitative systems pharmacology model, previously validated for other drugs, to evaluate the effectiveness and targeting specificity of an anti-PD-L1 PbTx compared to the non-modified antibody. We have informed the model using the PbTx dynamics and pharmacokinetics published in the literature for anti-PD-L1 in patients with triple-negative breast cancer (TNBC). Our results suggest masking of the antibody slightly decreases its efficacy, while increasing the localization of active therapeutic component in the TME. We also perform a parameter optimization for the PbTx design and drug dosing regimens to maximize the response rate. Although our results are specific to the case of TNBC, our findings are generalizable to any conditionally activated PbTx molecule in solid tumors and suggest that design of a highly effective and selective PbTx is feasible.

Identification of the functional PD-L1 interface region responsible for PD-1 binding and initiation of PD-1 signaling

The PD-1/PD-L1 checkpoint pathway is important for regulating immune responses and can be targeted by immunomodulatory drugs to treat a variety of immune disorders. However, the precise protein-protein interactions required for the initiation of PD-1/PD-L1 signaling are currently unknown. Previously, we designed a series of first-generation PD-1 targeting peptides based on the native interface region of programmed death ligand 1 (PD-L1) that effectively reduced PD-1/PD-L1 binding. In this work, we further characterized the previously identified lead peptide, MN1.1, to identify key PD-1 binding residues and design an optimized peptide, MN1.4. We show MN1.4 is significantly more stable than MN1.1 in serum and retains the ability to block PD-1/PD-L1 complex formation. We further characterized the immunomodulatory effects of MN1.4 treatment by measuring markers of T cell activation in a co-culture model with ovarian cancer cells and peripheral blood mononuclear cells. We found MN1.4 treatment reduced cytokine secretion and suppressed T cell responses in a similar manner as recombinant PD-L1. Therefore, the PD-L1 interface region used to design MN1.4 appeared sufficient to initiate PD-1 signaling and likely represents the minimum necessary region of PD-L1 required for PD-1 recognition. We propose a peptide agonist for PD-1, such as MN1.4, could have several applications for treating autoimmune disorders caused by PD-1 deficiencies such as type 1 diabetes, inflammatory arthritis, or autoimmune side effects arising from monoclonal antibody-based cancer immunotherapies.

Understanding immune checkpoints and PD-1/PD-L1-mediated immune resistance towards tumour immunotherapy

Immunotherapy has emerged as a transformative approach in the treatment of various cancers, offering new hope for patients previously faced with limited treatment options. A cornerstone of cancer immunotherapy lies in targeting immune checkpoints, particularly the programmed cell death protein-1 (PD-1) and programmed death-ligand 1 (PD-L1) pathway. Immune checkpoints serve as crucial regulators of the immune response, preventing excessive immune activity and maintaining self-tolerance. PD-1, expressed on the surface of T cells, and its ligand PD-L1, expressed on various cell types, including cancer cells and immune cells, play a central role in this regulatory process. Although the success rate associated with these immunotherapies is very promising, most patients still show intrinsic or acquired resistance. Since the mechanisms related to PD-1/PD-L1 resistance are not well understood, an in-depth analysis is necessary to improve the success rate of anti-PD-1/PD-L1 therapy. Hence, here we provide an overview of PD-1, its ligand PD-L1, and the resistance mechanism towards PD-1/PD-L1. Furthermore, we have discussed the plausible solution to increase efficacy and clinical response. For the following research, joint endeavours of clinicians and basic scientists are essential to address the limitation of resistance towards immunotherapy.

Different mechanisms of CD200-CD200R induce diverse outcomes in cancer treatment

The CD200 is a cell membrane protein expressed by tumor cells, and its receptor CD200 receptor (CD200R) is expressed by immune cells including macrophages and dendritic cells. The formation of CD200-CD200R inhibits the cellular functions of the targeted immune cells, so CD200 is one type of the immune checkpoint and blockade CD200-CD200R formation is a potential cancer treatment. However, the CD200 blockade has opposite treatment outcomes in different types of cancers. For instance, the CD200R deficient mice have a higher tumor load than the wild type (WT) mice in melanoma suggesting that CD200-CD200R inhibits melanoma. On the other hand, the antibody anti-CD200 treatment in pancreatic ductal adenocarcinoma (PDAC) and head and neck squamous cell carcinoma (HNSCC) significantly reduces the tumor load indicating that CD200-CD200R promotes PDAC and HNSCC. In this work, we hypothesize that different mechanisms of CD200-CD200R in tumor microenvironment could be one of the reasons for the diverse treatment outcomes of CD200 blockade in different types of cancers. We create one Ordinary Differential Equations (ODEs) model for melanoma including the inhibition of CCL8 and regulatory T cells and the switching from M2 to M1 macrophages by CD200-CD200R to capture the tumor inhibition by CD200-CD200R. We also create another ODEs model for PDAC and HNSCC including the promotion of the polarization and suppressive activities of M2 macrophages by CD200-CD200R to generate the tumor promotion by CD200-CD200R. Furthermore, we use these two models to investigate the treatment efficacy of the combination treatment between the CD200-CD200R blockade and the other immune checkpoint inhibitor, anti-PD-1. Our result shows that different mechanisms of CD200-CD200R can induce different treatment outcomes in combination treatments, namely, only the CD200-CD200R blockade reduces tumor load in melanoma and only the anti-PD-1 and CD200 knockout decrease tumor load in PDAC and HNSCC. Moreover, in melanoma, the CD200-CD200R mainly utilizes the inhibitions on M1 macrophages and dendritic cells to inhibit tumor growth, instead of M2 macrophages.

Development of an Albumin-Masked mutPD-1Ig as a Tumor Lesion-Selective Immune Checkpoint Inhibitor

The antitumor effects elicited by immune checkpoint inhibitors (ICIs) have transformed cancer treatments. However, severe immune-related adverse events (irAEs) resulting from these treatments have restricted the application of ICIs. To overcome the adverse events, we developed a tumor lesion-selective pro-PD-1Ig that is activated by proteases overexpressed in tumors. We genetically linked albumin to the N-terminus of a modified PD-1Ig (termed mutPD-1Ig hereafter) via an MMP substrate sequence to form Alb-hinge-mutPD-1Ig. We demonstrate that the binding activity of nondigested Alb-hinge-mutPD-1Ig is approximately 11-folds lower than mutPD-1Ig. However, digestion by type IV collagenase restored the binding activity of Alb-hinge-mutPD-1Ig to a level comparable to that of native mutPD-1Ig. In order to enhance the masking efficiency of Alb-mutPD-1Ig, we simulated the effects of diverse MMP substrate linkers for connecting albumin and PD-1 at various starting positions by bioinformatics tools. Our validation experiments indicate Alb-hinge-mutPD-1Ig displayed the best masking efficiency among all simulated constructs. Our study suggests that albumin may be best applicable to mask a target protein whose binding motif is centralized and in the proximity of the N-terminus of the protein.

Agent-Based Modelling Reveals the Role of the Tumor Microenvironment on the Short-Term Success of Combination Temozolomide/Immune Checkpoint Blockade to Treat Glioblastoma

Glioblastoma is the most common and deadly primary brain tumor in adults. All glioblastoma patients receiving standard-of-care surgery-radiotherapy-chemotherapy (i.e., temozolomide (TMZ)) recur, with an average survival time of only 15 months. New approaches to the treatment of glioblastoma, including immune checkpoint blockade and oncolytic viruses, offer the possibility of improving glioblastoma outcomes and have as such been under intense study. Unfortunately, these treatment modalities have thus far failed to achieve approval. Recently, in an attempt to bolster efficacy and improve patient outcomes, regimens combining chemotherapy and immune checkpoint inhibitors have been tested in trials. Unfortunately, these efforts have not resulted in significant increases to patient survival. To better understand the various factors impacting treatment outcomes of combined TMZ and immune checkpoint blockade, we developed a systems-level, computational model that describes the interplay between glioblastoma, immune, and stromal cells with this combination treatment. Initializing our model to spatial resection patient samples labeled using imaging mass cytometry, our model's predictions show how the localization of glioblastoma cells, influence therapeutic success. We further validated these predictions in samples of brain metastases from patients given they generally respond better to checkpoint blockade compared with primary glioblastoma. Ultimately, our model provides novel insights into the mechanisms of therapeutic success of immune checkpoint inhibitors in brain tumors and delineates strategies to translate combination immunotherapy regimens more effectively into the clinic. SIGNIFICANCE STATEMENT: Extending survival times for glioblastoma patients remains a critical challenge. Although immunotherapies in combination with chemotherapy hold promise, clinical trials have not shown much success. Here, systems models calibrated to and validated against patient samples can improve preclinical and clinical studies by shedding light on the factors distinguishing responses/failures. By initializing our model with imaging mass cytometry visualization of patient samples, we elucidate how factors such as localization of glioblastoma cells and CD8+ T cell infiltration impact treatment outcomes.

Temporal and spatial dynamics of immune cells in spontaneous liver transplant tolerance

The liver has long been deemed a tolerogenic organ. We employed high-dimensional mass cytometry and immunohistochemistry to depict the temporal and spatial dynamics of immune cells in the spleen and liver in a murine model of spontaneous liver allograft acceptance. We depicted the immune landscape of spontaneous liver tolerance throughout the rejection and acceptance stages after liver transplantation and highlighted several points of importance. Of note, the CD4+/CD8+ T cell ratio remained low, even in the tolerance phase. Furthermore, a PhenoGraph clustering analysis revealed that exhausted CD8+ T cells were the most dominant metacluster in graft-infiltrating lymphocytes (GILs), which highly expressed the costimulatory molecule CD86. The temporal and spatial dynamics of immune cells revealed by high-dimensional analyses enable a fine-grained analysis of GIL subsets, contribute to new insights for the discovery of immunological mechanisms of liver tolerance, and provide potential ways to achieve clinical operational tolerance after liver transplantation.

PD-L1/BTLA Checkpoint Axis Exploited for Bacterial Immune Escape by Restraining CD8+ T Cell-Initiated Adaptive Immunity in Zebrafish

Programmed death-ligand 1/programmed cell death 1 (PD-L1/PD-1) is one of the most important immune checkpoints in humans and other mammalian species. However, the occurrence of the PD-L1/PD-1 checkpoint in evolutionarily ancient vertebrates remains elusive because of the absence of a PD-1 homolog before its appearance in tetrapods. In this article, we identified, to our knowledge, a novel PD-L1/B and T lymphocyte attenuator (BTLA) checkpoint in zebrafish by using an Edwardsiella tarda-induced bacterial infection model. Results showed that zebrafish (Danio rerio) PD-L1 (DrPD-L1) and BTLA (DrBTLA) were differentially upregulated on MHC class II+ macrophages (Mϕs) and CD8+ T cells in response to E. tarda infection. DrPD-L1 has a strong ability to interact with DrBTLA, as shown by the high affinity (KD = 5.68 nM) between DrPD-L1/DrBTLA proteins. Functionally, the breakdown of DrPD-L1/DrBTLA interaction significantly increased the cytotoxicity of CD8+BTLA+ T cells to E. tarda-infected PD-L1+ Mϕ cells and reduced the immune escape of E. tarda from the target Mϕ cells, thereby enhancing the antibacterial immunity of zebrafish against E. tarda infection. Similarly, the engagement of DrPD-L1 by soluble DrBTLA protein diminished the tolerization of CD8+ T cells to E. tarda infection. By contrast, DrBTLA engagement by a soluble DrPD-L1 protein drives aberrant CD8+ T cell responses. These results were finally corroborated in a DrPD-L1-deficient (PD-L1-/-) zebrafish model. This study highlighted a primordial PD-L1/BTLA coinhibitory axis that regulates CD8+ T cell activation in teleost fish and may act as an alternative to the PD-L1/PD-1 axis in mammals. It also revealed a previously unrecognized strategy for E. tarda immune evasion by inducing CD8+ T cell tolerance to target Mϕ cells through eliciting the PD-L1/BTLA checkpoint pathway.

Mechanical force regulates ligand binding and function of PD-1

Immune checkpoint blockade targeting PD-1 shows great success in cancer therapy. However, the mechanism of how ligand binding initiates PD-1 signaling remains unclear. As prognosis markers of multiple cancers, soluble PD-L1 is found in patient sera and can bind PD-1, but fails to suppress T cell function. This and our previous observations that T cells exert endogenous forces on PD-1-PD-L2 bonds prompt the hypothesis that mechanical force might be critical to PD-1 triggering, which is missing in the soluble ligand case due to the lack of mechanical support afforded by surface-anchored ligand. Here we show that PD-1 function is eliminated or reduced when mechanical support on ligand is removed or dampened, respectively. Force spectroscopic analysis reveals that PD-1 forms catch bonds with both PD-Ligands <7 pN where force prolongs bond lifetime, but slip bonds >8 pN where force accelerates dissociation. Steered molecular dynamics finds PD-1-PD-L2 complex very sensitive to force due to the two molecules' "side-to-side" binding via β sheets. Pulling causes relative rotation and translation between the two molecules by stretching and aligning the complex along the force direction, yielding new atomic contacts not observed in the crystal structure. Compared to wild-type, PD-1 mutants targeting the force-induced new interactions maintain the same binding affinity but display lower rupture force, shorter bond lifetime, reduced tension, and most importantly, impaired capacity to suppress T cell activation. Our results uncover a mechanism for cells to probe the mechanical support of PD-1-PD-Ligand bonds using endogenous forces to regulate PD-1 triggering.

Selection of optimal quantile protein biomarkers based on cell-level immunohistochemistry data

BACKGROUND

Protein biomarkers of cancer progression and response to therapy are increasingly important for improving personalized medicine. Advanced quantitative pathology platforms enable measurement of protein expression in tissues at the single-cell level. However, this rich quantitative cell-by-cell biomarker information is most often not exploited. Instead, it is reduced to a single mean across the cells of interest or converted into a simple proportion of binary biomarker-positive or -negative cells.

RESULTS

We investigated the utility of retaining all quantitative information at the single-cell level by considering the values of the quantile function (inverse of the cumulative distribution function) estimated from a sample of cell signal intensity levels in a tumor tissue. An algorithm was developed for selecting optimal cutoffs for dichotomizing cell signal intensity distribution quantiles as predictors of continuous, categorical or survival outcomes. The proposed algorithm was used to select optimal quantile biomarkers of breast cancer progression based on cancer cells' cell signal intensity levels of nuclear protein Ki-67, Proliferating cell nuclear antigen, Programmed cell death 1 ligand 2, and Progesterone receptor. The performance of the resulting optimal quantile biomarkers was validated and compared to the standard cancer compartment mean signal intensity markers using an independent external validation cohort. For Ki-67, the optimal quantile biomarker was also compared to established biomarkers based on percentages of Ki67-positive cells. For proteins significantly associated with PFS in the external validation cohort, the optimal quantile biomarkers yielded either larger or similar effect size (hazard ratio for progression-free survival) as compared to cancer compartment mean signal intensity biomarkers.

CONCLUSION

The optimal quantile protein biomarkers yield generally improved prognostic value as compared to the standard protein expression markers. The proposed methodology has a broad application to single-cell data from genomics, transcriptomics, proteomics, or metabolomics studies at the single cell level.

Probing the origins of programmed death ligand-1 inhibition by implementing machine learning-assisted sequential virtual screening techniques

PD-L1 is a key immunotarget involved in binding to its receptor PD-1. PD-L1/PD-1 interface blocking using antibodies (or small molecules) is the central area of interest for tumor suppression in various cancers. Blocking the PD-L1/PD-1 pathway in the tumor cells results in its immune activation and destruction, and thereby restoring the T-cell proliferation and cytokine production. The active binding site interface residues of PD-L1/PD-1 were experimentally known and proven by structural biology and site-directed mutagenesis studies. Structure-based molecular design technique was employed to identify the inhibitors for blocking the PD-L1/PD-1 interface. Nine hits to leads were identified from the SPECS small molecule database by machine learning, molecular docking, and molecular dynamics simulation techniques. Following this, a machine learning-assisted QSAR modeling approach was implemented using ChEMBL database to gain insights into the inhibitory potential of PD-L1 inhibitors and predict the activity of our previously screened nine hit molecules. The best leads identified in the present study bind strongly with the active sites of PD-L1/PD-1 interface residues, which include A121, M115, I116, S117, I54, Y56, D122, and Y123. These computational leads are considered promising molecules for further in vitro and in vivo analysis to be developed as potential PD-L1 checkpoint inhibitors to cure different types of cancers.

Theoretical and experimental studies on the interaction of biphenyl ligands with human and murine PD-L1: Up-to-date clues for drug design

Today it is widely recognized that the PD-1/PD-L1 axis plays a fundamental role in escaping the immune system in cancers, so that anti-PD-1/PD-L1 antibodies have been evaluated for their antitumor properties in more than 1000 clinical trials. As a result, some of them have entered the market revolutionizing the treatment landscape of specific cancer types. Nonetheless, a new era based on the development of small molecules as anti PD-L1 drugs has begun. There are, however, some limitations to advancing these compounds into clinical stages including the possible difficulty in counteracting the PD-1/PD-L1 interaction in vivo, the discrepancy between the in vitro IC₅₀ (HTFR assay) and cellular EC₅₀ (immune checkpoint blockade co-culture assay), and the differences in ligands' affinity between human and murine PD-L1, which can affect their preclinical evaluation. Here, an extensive theoretical study, assisted by MicroScale Thermophoresis binding assays and NMR experiments, was performed to provide an atomistic picture of the binding event of three representative biphenyl-based compounds in both human and murine PD-L1. Structural determinants of the species' specificity were unraveled, providing unprecedented details useful for the design of next generation anti-PD-L1 molecules.

Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition

Generating realistic virtual patients from a limited amount of patient data is one of the major challenges for quantitative systems pharmacology modeling in immuno-oncology. Quantitative systems pharmacology (QSP) is a mathematical modeling methodology that integrates mechanistic knowledge of biological systems to investigate dynamics in a whole system during disease progression and drug treatment. In the present analysis, we parameterized our previously published QSP model of the cancer-immunity cycle to non-small cell lung cancer (NSCLC) and generated a virtual patient cohort to predict clinical response to PD-L1 inhibition in NSCLC. The virtual patient generation was guided by immunogenomic data from iAtlas portal and population pharmacokinetic data of durvalumab, a PD-L1 inhibitor. With virtual patients generated following the immunogenomic data distribution, our model predicted a response rate of 18.6% (95% bootstrap confidence interval: 13.3-24.2%) and identified CD8/Treg ratio as a potential predictive biomarker in addition to PD-L1 expression and tumor mutational burden. We demonstrated that omics data served as a reliable resource for virtual patient generation techniques in immuno-oncology using QSP models.

The impact of hypoxia on tumor-mediated bypassing anti-PD-(L)1 therapy

Extending the durability of response is the current focus in cancer immunotherapy with immune checkpoint inhibitors (ICIs). However, factors like non-immunogenic tumor microenvironment (TME) along with aberrant angiogenesis and dysregulated metabolic systems are negative contributors. Hypoxia is a key TME condition and a critical promoter of tumor hallmarks. It acts on immune and non-immune cells within TME in order for promoting immune evasion and therapy resistance. Extreme hypoxia is a major promoter of resistance to the programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitor therapy. Hypoxia inducible factor-1 (HIF-1) acts as a key mediator of hypoxia and a critical promoter of resistance to the anti-PD-(L)1. Targeting hypoxia or HIF-1 can thus be an effective strategy for reinvigoration of cellular immunity against cancer. Among various strategies presented so far, the key focus is over vascular normalization, which is an approach highly effective for reducing the rate of hypoxia, increasing drug delivery into the tumor area, and boosting the efficacy of anti-PD-(L)1.

Soluble monomeric human programmed cell death-ligand 1 inhibits the functions of activated T cells

Introduction

The presence of soluble human programmed cell death-ligand 1 (shPD-L1) in the blood of patients with cancer has been reported to be negatively correlated with disease prognosis. However, little information exists about the mechanisms underlying high levels of shPD-L1 for promoting disease progression.

Methods

In this study, we first analyzed the correlations between shPD-L1 and apoptosis of T cells in patients with cancer, then tested the effect of shPD-L1 on T-cell functions and the production of regulatory T cells.

Results

We found that the apoptosis of human peripheral PD-1+CD4+ T cells was significantly elevated in patients with cancer compared with healthy donors and was positively correlated with circulating PD-L1 levels in patients with cancer. In vitro, monomeric shPD-L1 significantly inhibited the proliferation, cytokine secretion, and cancer cell-killing activity of peripheral blood mononuclear cells (PBMCs) activated by either agonist antibodies or HATac (high-affinity T cell activation core)-NYE (NY-ESO-1 antigen). It also promoted CD4+ T cells to express forkhead family transcription factor 3 (FoxP3) for the conversion of induced T regulatory cells, which was more significant than that mediated by soluble human PD-L1 fusion protein (shPD-L1-Fc).

Discussion

These results confirm that soluble PD-L1 could be a candidate for inhibiting the functions of activated T cells, promoting peripheral tolerance to tumor cells, and implicating in system tumor immune escape in addition to the tumor microenvironment. This is an important mechanism explaining the negative correlation between peripheral blood PD-L1 levels and cancer prognosis. Therefore, understanding the roles of hPD-L1 in peripheral blood will be helpful for the development of precision immunotherapy programs in treating various tumors.

Inside PD-1/PD-L1,2 with their inhibitors

This review summarizes current knowledge in the development of immune checkpoint inhibitors, including antibodies and small molecules.

Construction of stable membranal CMTM6-PD-L1 full-length complex to evaluate the PD-1/PD-L1-CMTM6 interaction and develop anti-tumor anti-CMTM6 nanobody

CKLF (chemokine-like factor)-MARVEL transmembrane domain containing protein 6 (CMTM6) is a novel regulator to maintain the stability of PD-L1. CMTM6 can colocalize and interact with PD-L1 on the recycling endosomes and cell membrane, preventing PD-L1 from lysosome-mediated degradation and proteasome-mediated degradation thus increasing the half-life of PD-L1 on the cell membrane. The difficulties in obtaining stable full-length PD-L1 and CMTM6 proteins hinder the research on their structures, function as well as related drug development. Using lauryl maltose neopentyl glycol (LMNG) as the optimized detergent and a cell membrane mimetic strategy, we assembled a stable membrane-bound full-length CMTM6-PD-L1 complex with amphipol A8-35. When the PD-1/PD-L1-CMTM6 interactions were analyzed, we found that CMTM6 greatly enhanced the binding and delayed the dissociation of PD-1/PD-L1, thus affecting immunosuppressive signaling and anti-apoptotic signaling. We then used the CMTM6-PD-L1 complex as immunogens to generate immune repertoires in camels, and identified a functional anti-CMTM6 nanobody, called 1A5. We demonstrated that the anti-CMTM6 nanobody greatly decreased T-cell immunosuppression and promoted apoptotic susceptibility of tumor cells in vitro, and mainly relied on the cytotoxic effect of CD8+ T-cells to exert tumor growth inhibitory effects in CT26 tumor-bearing mice. In conclusion, the stable membrane-bound full-length CMTM6-PD-L1 complex has been successfully used in studying PD-1/PD-L1-CMTM6 interactions and CMTM6-targeting drug development, suggesting CMTM6 as a novel tumor immunotherapy target.

Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition

Generating realistic virtual patients from a limited amount of patient data is one of the major challenges for quantitative systems pharmacology modeling in immuno-oncology. Quantitative systems pharmacology (QSP) is a mathematical modeling methodology that integrates mechanistic knowledge of biological systems to investigate dynamics in a whole system during disease progression and drug treatment. In the present analysis, we parameterized our previously published QSP model of the cancer-immunity cycle to non-small cell lung cancer (NSCLC) and generated a virtual patient cohort to predict clinical response to PD-L1 inhibition in NSCLC. The virtual patient generation was guided by immunogenomic data from iAtlas portal and population pharmacokinetic data of durvalumab, a PD-L1 inhibitor. With virtual patients generated following the immunogenomic data distribution, our model predicted a response rate of 18.6% (95% bootstrap confidence interval: 13.3-24.2%) and identified CD8/Treg ratio as a potential predictive biomarker in addition to PD-L1 expression and tumor mutational burden. We demonstrated that omics data served as a reliable resource for virtual patient generation techniques in immuno-oncology using QSP models.

The CTLA-4 immune checkpoint protein regulates PD-L1:PD-1 interaction via transendocytosis of its ligand CD80

CTLA-4 and PD-1 are key immune checkpoint receptors that are targeted in the treatment of cancer. A recently identified physical interaction between the respective ligands, CD80 and PD-L1, has been shown to block PD-L1/PD-1 binding and to prevent PD-L1 inhibitory functions. Since CTLA-4 is known to capture and degrade its ligands via transendocytosis, we investigated the interplay between CD80 transendocytosis and CD80/PD-L1 interaction. We find that transendocytosis of CD80 results in a time-dependent recovery of PD-L1 availability that correlates with CD80 removal. Moreover, CD80 transendocytosis is highly specific in that only CD80 is internalised, while its heterodimeric PD-L1 partner remains on the plasma membrane of the antigen-presenting cell (APC). CTLA-4 interactions with CD80 do not appear to be inhibited by PD-L1, but efficient removal of CD80 requires an intact CTLA-4 cytoplasmic domain, distinguishing this process from more general trogocytosis and simple CTLA-4 binding to CD80/PD-L1 complexes. These data are consistent with CTLA-4 acting as modulator of PD-L1:PD-1 interactions via control of CD80.

PD-1/PD-L1 and DNA Damage Response in Cancer

The application of immunotherapy for cancer treatment is rapidly becoming more widespread. Immunotherapeutic agents are frequently combined with various types of treatments to obtain a more durable antitumor clinical response in patients who have developed resistance to monotherapy. Chemotherapeutic drugs that induce DNA damage and trigger DNA damage response (DDR) frequently induce an increase in the expression of the programmed death ligand-1 (PD-L1) that can be employed by cancer cells to avoid immune surveillance. PD-L1 exposed on cancer cells can in turn be targeted to re-establish the immune-reactive tumor microenvironment, which ultimately increases the tumor's susceptibility to combined therapies. Here we review the recent advances in how the DDR regulates PD-L1 expression and point out the effect of etoposide, irinotecan, and platinum compounds on the anti-tumor immune response.

The RESP AI model accelerates the identification of tight-binding antibodies

High-affinity antibodies are often identified through directed evolution, which may require many iterations of mutagenesis and selection to find an optimal candidate. Deep learning techniques hold the potential to accelerate this process but the existing methods cannot provide the confidence interval or uncertainty needed to assess the reliability of the predictions. Here we present a pipeline called RESP for efficient identification of high affinity antibodies. We develop a learned representation trained on over 3 million human B-cell receptor sequences to encode antibody sequences. We then develop a variational Bayesian neural network to perform ordinal regression on a set of the directed evolution sequences binned by off-rate and quantify their likelihood to be tight binders against an antigen. Importantly, this model can assess sequences not present in the directed evolution library and thus greatly expand the search space to uncover the best sequences for experimental evaluation. We demonstrate the power of this pipeline by achieving a 17-fold improvement in the K_D of the PD-L1 antibody Atezolizumab and this success illustrates the potential of RESP in facilitating general antibody development.

Identification of specific carbonic anhydrase inhibitors via in situ click chemistry, phage-display and synthetic peptide libraries: comparison of the methods and structural study

The development of highly active and selective enzyme inhibitors is one of the priorities of medicinal chemistry. Typically, various high-throughput screening methods are used to find lead compounds from a large pool of synthetic compounds, and these are further elaborated and structurally refined to achieve the desired properties. In an effort to streamline this complex and laborious process, new selection strategies based on different principles have recently emerged as an alternative. Herein, we compare three such selection strategies with the aim of identifying potent and selective inhibitors of human carbonic anhydrase II. All three approaches, in situ click chemistry, phage-display libraries and synthetic peptide libraries, led to the identification of more potent inhibitors when compared to the parent compounds. In addition, one of the inhibitor-peptide conjugates identified from the phage libraries showed greater than 100-fold selectivity for the enzyme isoform used for the compound selection. In an effort to rationalize the binding properties of the conjugates, we performed detailed crystallographic and NMR structural analysis, which revealed the structural basis of the compound affinity towards the enzyme and led to the identification of a novel exosite that could be utilized in the development of isoform specific inhibitors.

Anti-PD-1 antibodies recognizing the membrane-proximal region are PD-1 agonists that can down-regulate inflammatory diseases

The PD-1 receptor triggers a negative immunoregulatory mechanism that prevents overactivation of immune cells and subsequent inflammatory diseases. Because of its biological significance, PD-1 has been a drug target for modulating immune responses. Immunoenhancing anti-PD-1 blocking antibodies have become a widely used cancer treatment; however, little is known about the required characteristics for anti-PD-1 antibodies to be capable of stimulating immunosuppressive activity. Here, we show that PD-1 agonists exist in the group of anti-PD-1 antibodies recognizing the membrane-proximal extracellular region in sharp contrast to the binding of the membrane-distal region by blocking antibodies. This trend was consistent in an analysis of 81 anti-human PD-1 monoclonal antibodies. Because PD-1 agonist antibodies trigger immunosuppressive signaling by cross-linking PD-1 molecules, Fc engineering to enhance FcγRIIB binding of PD-1 agonist antibodies notably improved human T cell inhibition. A PD-1 agonist antibody suppressed inflammation in murine disease models, indicating its clinical potential for treatment of various inflammatory disorders, including autoimmune diseases.

Dual CAR-T cells to treat cancers co-expressing NKG2D and PD1 ligands in xenograft models of peritoneal metastasis

While the expression of either NKG2D ligands or PD-1 ligands has been reported in various types of cancers, the co-expression of the two sets of ligands in the same tumour tissues is still un-investigated. After examining 68 primary ovarian cancer samples, we observed around 80% of the co-expression in low grade serous and endometrioid ovarian cancer samples. We then constructed a dual CAR system that splits the conventional single-input of a 2nd generation CAR into two independent chimeric receptors, one composed of the NKG2D extracellular domain linked with DAP12 for T cell activation and another using the PD-1 extracellular domain linked with 4-1BB for costimulatory signal 2 input. Given the limitation of the low-affinity PD-1 receptor in recognizing cancer cells with low levels of PD-1 ligands, we also used a high-affinity scFv specific to PD-L1 in our combinatorial approach to expand the range of target cancer cells with different expression levels of PD-L1. The two types of dual CAR-T cells were generated through electroporation of non-viral piggyBac transposon plasmids and were effective in eliminating the target cancer cells. Especially, the dual CAR-T cells with anti-PD-L1 scFv were capable of eradicating established tumors in mouse models of peritoneal metastasis of colorectal cancer and ovarian cancer. Since both NKG2D ligands and PD-1 ligands have been marked as favourable cancer therapeutic targets, the new dual CAR-T cells developed in this study hold attractive application potential in treating metastatic peritoneal carcinoma.

Combination CD200R/PD-1 blockade in a humanised mouse model

There is an increasing number of immune-checkpoint inhibitors being developed and approved for cancer immunotherapy. Most of the new therapies aim to reactivate tumour-infiltrating T cells, which are responsible for tumour killing. However, in many tumours, the most abundant infiltrating immune cells are macrophages and myeloid cells, which can be tumour-promoting as well as tumouricidal. CD200R was initially identified as a myeloid-restricted, inhibitory immune receptor, but was subsequently also found to be expressed within the lymphoid lineage. Using a mouse model humanised for CD200R and PD-1, we investigated the potential of a combination therapy comprising nivolumab, a clinically approved PD-1 blocking antibody, and OX108, a CD200R antagonist. We produced nivolumab as a murine IgG1 antibody and validated its binding activity in vitro as well as ex vivo. We then tested the combination therapy in the immunogenic colorectal cancer model MC38 as well as the PD-1 blockade-resistant lung cancer model LLC1, which is characterised by a large number of infiltrating myeloid cells, making it an attractive target for CD200R blockade. No significant improvement of overall survival was found in either model, compared to nivolumab mIgG1 monotherapy. There was a trend for more complete responses in the MC38 model, but investigation of the infiltrating immune cells failed to account for this. Importantly, MC38 cells expressed low levels of CD200, whereas LLC1 cells were CD200-negative. Further investigation of CD200R-blocking antibodies in tumours expressing high levels of CD200 could be warranted.

Research progress of therapeutic effects and drug resistance of immunotherapy based on PD-1/PD-L1 blockade

The binding of programmed death-1 (PD-1) on the surface of T cells and PD-1 ligand 1 (PD-L1) on tumor cells can prevent the immune-killing effect of T cells on tumor cells and promote the immune escape of tumor cells. Therefore, immune checkpoint blockade targeting PD-1/PD-L1 is a reliable tumor therapy with remarkable efficacy. However, the main challenges of this therapy are low response rate and acquired resistance, so that the outcomes of this therapy are usually unsatisfactory. This review begins with the description of biological structure of the PD-1/PD-L1 immune checkpoint and its role in a variety of cells. Subsequently, the therapeutic effects of immune checkpoint blockers (PD-1 / PD-L1 inhibitors) in various tumors were introduced and analyzed, and the reasons affecting the function of PD-1/PD-L1 were systematically analyzed. Then, we focused on analyzing, sorting out and introducing the possible underlying mechanisms of primary and acquired resistance to PD-1/PD-L1 blockade including abnormal expression of PD-1/PD-L1 and some factors, immune-related pathways, tumor immune microenvironment, and T cell dysfunction and others. Finally, promising therapeutic strategies to sensitize the resistant patients with PD-1/PD-L1 blockade treatment were described. This review is aimed at providing guidance for the treatment of various tumors, and highlighting the drug resistance mechanisms to offer directions for future tumor treatment and improvement of patient prognosis.

Advances in the structural characterization of complexes of therapeutic antibodies with PD-1 or PD-L1

Antibody-based immune checkpoint blockade (ICB)-based therapeutics have become effective clinical applications for cancers. Applications of monoclonal antibodies (mAbs) to de-activate the PD-1-PD-L1 pathway could effectively reverse the phenotype of depleted activated thymocytes (T cells) to recover their anti-tumoral activities. High-resolution structures of the complexes of the therapeutic monoclonal antibodies with PD-1 or PD-L1 have revealed the key inter-molecular interactions and provided valuable insights into the fundamental mechanisms by which these antibodies inhibit PD-L1-PD-1 binding. Each anti-PD-1 mAb exhibits a unique blockade mechanism, such as interference with large PD-1-PD-L1 contacting interfaces, steric hindrance by overlapping a small area of this site, or binding to an N-glycosylated site. In contrast, all therapeutic anti-PD-L1 mAbs bind to a similar area of PD-L1. Here, we summarized advances in the structural characterization of the complexes of commercial mAbs that target PD-1 or PD-L1. In particular, we focus on the unique characteristics of those mAb structures, epitopes, and blockade mechanisms. It is well known that the use of antibodies as anti-tumor drugs has increased recently and both PD-1 and PD-L1 have attracted substantial attention as target for antibodies derived from new technologies. By focusing on structural characterization, this review aims to aid the development of novel antibodies targeting PD-1 or PD-L1 in the future.

Identification, binding, and structural characterization of single domain anti-PD-L1 antibodies inhibitory of immune regulatory proteins PD-1 and CD80

Programmed death-ligand 1 (PD-L1) is a key immune regulatory protein that interacts with programmed cell death protein 1 (PD-1), leading to T-cell suppression. Whilst this interaction is key in self-tolerance, cancer cells evade the immune system by overexpressing PD-L1. Inhibition of the PD-1/PD-L1 pathway with standard monoclonal antibodies has proven a highly effective cancer treatment; however, single domain antibodies (VHH) may offer numerous potential benefits. Here, we report the identification and characterization of a diverse panel of 16 novel VHHs specific to PD-L1. The panel of VHHs demonstrate affinities of 0.7 nM to 5.1 μM and were able to completely inhibit PD-1 binding to PD-L1. The binding site for each VHH on PD-L1 was determined using NMR chemical shift perturbation mapping and revealed a common binding surface encompassing the PD-1-binding site. Additionally, we solved crystal structures of two representative VHHs in complex with PD-L1, which revealed unique binding modes. Similar NMR experiments were used to identify the binding site of CD80 on PD-L1, which is another immune response regulatory element and interacts with PD-L1 localized on the same cell surface. CD80 and PD-1 were revealed to share a highly overlapping binding site on PD-L1, with the panel of VHHs identified expected to inhibit CD80 binding. Comparison of the CD80 and PD-1 binding sites on PD-L1 enabled the identification of a potential antibody binding region able to confer specificity for the inhibition of PD-1 binding only, which may offer therapeutic benefits to counteract cancer cell evasion of the immune system.

Selection of a PD-1 blocking antibody from a novel fully human phage display library

Programmed cell death protein 1 (PD-1) is an immunoregulatory target which is recognized by different monoclonal antibodies, approved for the therapy of multiple types of cancer. Different anti-PD-1 antibodies display different therapeutic properties and there is a pharmaceutical interest to generate and characterize novel anti-PD-1 antibodies. We screened multiple human antibody phage display libraries to target novel epitopes on the PD-1 surface and we discovered a unique and previously undescribed binding specificity (termed D12) from a new antibody library (termed AMG). The library featured antibody fragments in single-chain fragment variable (scFv) format, based on the IGHV3-23*03 (VH ) and IGKV1-39*01 (Vκ) genes. The D12 antibody was characterized by surface plasmon resonance (SPR), cross-reacted with the Cynomolgus monkey antigen and bound to primary human T cells, as shown by flow cytometry. The antibody blocked the PD-1/PD-L1 interaction in vitro with an EC50 value which was comparable to the one of nivolumab, a clinically approved antibody. The fine details of the interaction between D12 and PD-1 were elucidated by x-ray crystallography of the complex at a 3.5 Å resolution, revealing an unprecedented conformational change at the N-terminus of PD-1 following D12 binding, as well as partial overlap with the binding site for the cognate PD-L1 and PD-L2 ligands which prevents their binding. The results of the study suggest that the expansion of antibody library repertoires may facilitate the discovery of novel binding specificities with unique properties that hold promises for the modulation of PD-1 activity in vitro and in vivo.

Optimal timing of steroid initiation in response to CTLA-4 antibody in metastatic cancer: A mathematical model

Immune checkpoint inhibitors, introduced in recent years, have revolutionized the treatment of many cancers. However, the toxicity associated with this therapy may cause severe adverse events. In the case of advanced lung cancer or metastatic melanoma, a significant number (10%) of patients treated with CTLA-4 inhibitor incur damage to the pituitary gland. In order to reduce the risk of hypophysitis and other severe adverse events, steroids may be combined with CTLA-4 inhibitor; they reduce toxicity, but they also diminish the anti-cancer effect of the immunotherapy. This trade-off between tumor reduction and the risk of severe adverse events poses the following question: What is the optimal time to initiate treatment with steroid. We address this question with a mathematical model from which we can also evaluate the comparative benefits of each schedule of steroid administration. In particular, we conclude that treatment with steroid should not begin too early, but also not very late, after immunotherapy began; more precisely, it should start as soon as tumor volume, under the effect of CTLA-4 inhibitor alone, begins to decrease. We can also compare the benefits of short term treatment of steroid at high doses to a longer term treatment with lower doses.

Exploiting the Innate Plasticity of the Programmed Cell Death-1 (PD1) Receptor to Design Pembrolizumab H3 Loop Mimics

Checkpoint blockade of the immunoreceptor programmed cell death-1 (PD1) with its ligand-1 (PDL1) by monoclonal antibodies such as pembrolizumab provided compelling clinical results in various cancer types, yet the molecular mechanism by which this drug blocks the PD1/PDL1 interface remains unclear. To address this question, we examined the conformational motion of PD1 associated with the binding of pembrolizumab. Our results revealed that the innate plasticity of both C'D and FG loops is crucial to form a deep binding groove (371 Å3 ) across several distant epitopes of PD1. This analysis ultimately provided a rational-design to create pembrolizumab H3 loop mimics [RDYRFDMGFD] into β-hairpin scaffolds. As a result, a 20-residue long β-hairpin peptide 1 e was identified as a first-in-class potent PD1-inhibitor (EC50 of 0.29 μM; Ki of 41 nM).

Mathematical modeling for the combination treatment of IFN- γ and anti-PD-1 in cancer immunotherapy

When the immune-checkpoint programmed death-1 (PD-1) binds to its ligand programmed death ligand 1 (PD-L1) to form the complex PD-1-PD-L1, this complex inactivates immune cells resulting in cell apoptosis, downregulation of immune reaction, and tumor evasion. The antibody, anti-PD-1 or anti-PD-L1, blocks the PD-1-PD-L1 complex formation to restore the functions of T cells. Combination of anti-PD-1 with other treatment shows promising in different types of cancer treatments. Interferon-gamma (IFN-γ) plays an important role in immune responses. It is mainly regarded as a pro-inflammatory cytokine that promotes the proliferation of CD8⁺ T cell and cytotoxic T cell, enhances the activation of Th1 cells and CD8⁺ T cells, and enhances tumor elimination. However, recent studies have been discovering many anti-inflammatory functions of IFN-γ, such as promotion of the PD-L1 expression, T cell apoptosis, and tumor metastasis, as well as inhibition of the immune recognition and the killing rates by T cells. In this work, we construct a mathematical model incorporating pro-inflammatory and anti-inflammatory functions of IFN-γ to capture tumor growth under anti-PD-1 treatment in the wild type and IFN-γ null mutant melanoma. Our simulation results qualitatively fit experimental data that IFN-γ null mutant with anti-PD-1 obtains the highest tumor reduction comparing to IFN-γ null mutant without anti-PD-1 and wild type tumor with anti-PD-1 therapy. Moreover, our synergy analysis indicates that, in the combination treatment, the tumor volume decreases as either the dosage of anti-PD-1 increases or the IFN-γ production efficiency decreases. Thus, the combination of anti-PD-1 and IFN-γ blockade improves the tumor reduction comparing to the monotherapy of anti-PD-1 or the monotherapy of IFN-γ blockade. We also find a threshold curve of the minimal dosage of anti-PD-1 corresponding to the IFN-γ production efficiency to ensure the tumor reduction under the presence of IFN-γ.

Dynamics of tumor-associated macrophages in a quantitative systems pharmacology model of immunotherapy in triple-negative breast cancer

Quantitative systems pharmacology (QSP) modeling is an emerging mechanistic computational approach that couples drug pharmacokinetics/pharmacodynamics and the course of disease progression. It has begun to play important roles in drug development for complex diseases such as cancer, including triple-negative breast cancer (TNBC). The combination of the anti-PD-L1 antibody atezolizumab and nab-paclitaxel has shown clinical activity in advanced TNBC with PD-L1-positive tumor-infiltrating immune cells. As tumor-associated macrophages (TAMs) serve as major contributors to the immuno-suppressive tumor microenvironment, we incorporated the dynamics of TAMs into our previously published QSP model to investigate their impact on cancer treatment. We show that through proper calibration, the model captures the macrophage heterogeneity in the tumor microenvironment while maintaining its predictive power of the trial results at the population level. Despite its high mechanistic complexity, the modularized QSP platform can be readily reproduced, expanded for new species of interest, and applied in clinical trial simulation.

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A mechanistic model of quantitative systems pharmacology in immuno-oncology

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Dynamics of tumor-associated macrophages are integrated into our previous work

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Conducting in silico clinical trials to predict clinical response to cancer therapy

Cell-based receptor discovery identifies host factors specifically targeted by the SARS CoV-2 spike

Receptor-ligand interactions on the plasma membrane regulate cellular communication and play a key role in viral infection. Despite representing main targets for drug development, the characterization of these interactions remains challenging in part due to the dearth of optimal technologies. Here, we build a comprehensive library of human proteins engineered for controlled cell surface expression. Coupled to tetramer-based screening for increased binding avidity, we develop a high throughput cell-based platform that enables systematic interrogation of receptor-ligand interactomes. Using this technology, we characterize the cell surface proteins targeted by the receptor binding domain (RBD) of the SARS-CoV spike protein. Host factors that specifically bind to SARS CoV-2 but not SARS CoV RBD are identified, including proteins that are expressed in the nervous system or olfactory epithelium. Remarkably, our results show that Contactin-1, a previously unknown SARS CoV-2 spike-specific receptor that is upregulated in COVID-19 patients, significantly enhances ACE2-dependent pseudotyped virus infection. Starting from a versatile platform to characterize cell surface interactomes, this study uncovers host factors specifically targeted by SARS CoV-2, information that may help design improved therapeutic strategies against COVID-19.

A high-throughput cell-based platform is developed for systematic investigation of receptor-ligand interactions and applied to identify cell-surface proteins that bind to SARS CoV-2.

PTX3 mediates the infiltration, migration, and inflammation-resolving-polarization of macrophages in glioblastoma

Introduction

Pentraxin 3 (PTX3) is an essential regulator of the immune system. However, the immune‐modulatory role of PTX3 in the tumor microenvironment of glioma has not been elucidated.

Methods

The RNA seq samples were obtained from The Cancer Genome Atlas (TCGA) and the China Glioma Genome Atlas (CGGA) datasets. The single‐cell sequencing data of glioblastoma (GBM) samples were obtained from the Single Cell Portal platform (http://singlecell.broadinstitute.org). Immunohistochemistry was used to assess PTX3 expression, HAVCR2, PD‐1, PD‐L1, and CD276 in glioma sections from the Xiangya cohort (n = 60). Multiplex immunofluorescence staining of PTX3, CD68, and CD163 was performed in several solid cancer types, including GBM. HMC3 was cocultured with U251 and U87, and transwell assay and flow cytometry assay were performed to explore the migration and polarization activity of HMC3.

Results

PTX3 expression is significantly increased in GBM. PTX3 expression predicts worse survival in the Xiangya cohort. PTX3 is closely related to the expression of PD‐1, PD‐L1, CD276, and HAVCR2 in the tumor microenvironment. Additionally, PTX3 is involved in tumorigenic and immunogenic processes, especially the activity of macrophages based on various signaling pathways in cellular communications and critical transcription factors. Specifically, PTX3 actively mediates macrophages' infiltration, migration, and inflammation‐resolving‐polarization. PTX3 could also predict immunotherapy response.

Conclusion

PTX3 is critically involved in macrophage infiltration, migration, and inflammation‐resolving‐polarization and modulates an immunosuppressive microenvironment.

Mapping CAR T-Cell Design Space Using Agent-Based Models

Chimeric antigen receptor (CAR) T-cell therapy shows promise for treating liquid cancers and increasingly for solid tumors as well. While potential design strategies exist to address translational challenges, including the lack of unique tumor antigens and the presence of an immunosuppressive tumor microenvironment, testing all possible design choices in vitro and in vivo is prohibitively expensive, time consuming, and laborious. To address this gap, we extended the modeling framework ARCADE (Agent-based Representation of Cells And Dynamic Environments) to include CAR T-cell agents (CAR T-cell ARCADE, or CARCADE). We conducted in silico experiments to investigate how clinically relevant design choices and inherent tumor features—CAR T-cell dose, CD4⁺:CD8⁺ CAR T-cell ratio, CAR-antigen affinity, cancer and healthy cell antigen expression—individually and collectively impact treatment outcomes. Our analysis revealed that tuning CAR affinity modulates IL-2 production by balancing CAR T-cell proliferation and effector function. It also identified a novel multi-feature tuned treatment strategy for balancing selectivity and efficacy and provided insights into how spatial effects can impact relative treatment performance in different contexts. CARCADE facilitates deeper biological understanding of treatment design and could ultimately enable identification of promising treatment strategies to accelerate solid tumor CAR T-cell design-build-test cycles.

Modeling the effect of gut microbiome on therapeutic efficacy of immune checkpoint inhibitors against cancer

Immune checkpoint inhibitors have been shown to be highly successful against some solid metastatic malignancies, but only for a subset of patients who show durable clinical responses. The overall patient response rate is limited due to the interpatient heterogeneity. Preclinical and clinical studies have recently shown that the therapeutic responses can be improved through the modulation of gut microbiome. However, the underlying mechanisms are not fully understood. In this paper, we explored the effect of favorable and unfavorable gut bacteria on the therapeutic efficacy of anti-PD-1 against cancer by modeling the tumor-immune-gut microbiome interactions, and further examined the predictive markers of responders and non-responders to anti-PD-1. The dynamics of the gut bacteria was fitted to the clinical data of melanoma patients, and virtual patients data were generated based on the clinical patient survival data. Our simulation results show that low initial growth rate and low level of favorable bacteria at the initiation of anti-PD-1 therapy are predictive of non-responders, while high level of favorable bacteria at the initiation of anti-PD-1 therapy is predictive of responders. Simulation results also confirmed that it is possible to promote patients' response rate to anti-PD-1 by manipulating the gut bacteria composition of non-responders, whereby achieving long-term progression-free survival.