Recognition Receptors Research Articles

Evaluating TcAs for Use in Biotechnology Applications

ABC toxin complexes (Tcs) are tripartite complexes that come together to form nano-syringe-like translocation systems. ABC Tcs are often compared with Bacillus thuringiensis (Bt) toxins, and as such, they have been highly studied as a potential novel pesticide to combat growing insect resistance. Moreover, it is possible to substitute the cytotoxic hypervariable region with alternative peptides, which promise potential use as a novel peptide delivery system. These toxins possess the unique ability to form active chimeric holotoxins across species and display the capability to translocate a variety of payloads across membrane bilayers. Additionally, mutagenesis on the linker region and the receptor binding domains (RBDs) show that mutations do not inherently cause a loss of functionality for translocation. For these reasons, Tcs have emerged as an ideal candidate for targeted protein engineering. However, elucidation of the specific function of each RBD in relation to target receptor recognition currently limits the use of a rational design approach with any ABC Tc. Additionally, there is a distinct lack of targeting and biodistribution data for many Tcs among mammals and mammalian cell lines. Here, we outline two separate strategies for modifying the targeting capabilities of the A subunit (TcA) from Xenorhabdus nematophilus, Xn-XptA2. We identify novel structural differences that make Xn-XptA2 different than other characterized TcAs and display the modular capabilities of substituting RBDs from alternative TcAs into the Xn-XptA2 scaffold. Finally, we show the first, to our knowledge, biodistribution data of any TcA in mice.

Phages adapt to recognize an O-antigen polysaccharide site by mutating the ‘backup’ tail protein ORF59, enabling reinfection of phage-resistant Klebsiella pneumoniae

Phages demonstrate remarkable promise as antimicrobial agents against antibiotic-resistant bacteria. However, the emergence of phage-resistant strains poses challenges to their effective application. In this paper, we presented the isolation of a phage adaptive mutant that demonstrated enhanced and sustained antibacterial efficacy through the co-evolution of Klebsiella pneumoniae (K. pneumoniae) 111-2 and phage ZX1Δint in vitro. Our experiments revealed that phage ZX1Δint successfully completed the adsorption phase by binding to the host surface, specifically targeting the capsular polysaccharide (CPS) receptor via the primary receptor-binding protein (RBP) ORF60 and the auxiliary RBP ORF59. Upon exposure to phage predation, mutations in genes wbaP, wbaZ or wzc, which encode the synthesis of the CPS, conferred resistance by reducing phage adsorption. In response to these host defense mechanisms, the adaptive mutant phages have evolved to utilize an alternative binding site located on an O-antigen site of lipopolysaccharide (LPS) through a mutation in the backup RBP ORF59. This evolutionary change enabled the phages to reinfect previously phage-resistant strains. Notably, the adaptive mutant phage PR2 carrying the ORF59 mutation Q777R, demonstrated the capacity to infect both wild-type and resistant strains, exhibiting prolonged antimicrobial activity against the wild strains. In conclusion, our findings elucidated a complex phage-host adsorption-antagonism mechanism characterized by mutation-driven alterations in phage receptor recognition. This work contributes to a deeper understanding of phage adaptability and highlights the potential for phages to combat phage-resistant bacteria through an in vitro evolutionary approach.

Botulinum Toxin: A Comprehensive Review of Its Molecular Architecture and Mechanistic Action.

Botulinum toxin (BoNT), the most potent substance known to humans, likely evolved not to kill but to serve other biological purposes. While its use in cosmetic applications is well known, its medical utility has become increasingly significant due to the intricacies of its structure and function. The toxin's structural complexity enables it to target specific cellular processes with remarkable precision, making it an invaluable tool in both basic and applied biomedical research. BoNT's potency stems from its unique structural features, which include domains responsible for receptor recognition, membrane binding, internalization, and enzymatic cleavage. This division of labor within the toxin's structure allows it to specifically recognize and interact with synaptic proteins, leading to precise cleavage at targeted sites within neurons. The toxin's mechanism of action involves a multi-step process: recognition, binding, and catalysis, ultimately blocking neurotransmitter release by cleaving proteins like SNAP-25, VAMP, and syntaxin. This disruption in synaptic vesicle fusion causes paralysis, typically in peripheral neurons. However, emerging evidence suggests that BoNT also affects the central nervous system (CNS), influencing presynaptic functions and distant neuronal systems. The evolutionary history of BoNT reveals that its neurotoxic properties likely provided a selective advantage in certain ecological contexts. Interestingly, the very features that make BoNT a potent toxin also enable its therapeutic applications, offering precision in treating neurological disorders like dystonia, spasticity, and chronic pain. In this review, we highlight the toxin's structural, functional, and evolutionary aspects, explore its clinical uses, and identify key research gaps, such as BoNT's central effects and its long-term cellular impact. A clear understanding of these aspects could facilitate the representation of BoNT as a unique scientific paradigm for studying neuronal processes and developing targeted therapeutic strategies.

Establishment of a Yeast Two-Hybrid-Based High-Throughput Screening Model for Selection of SARS-CoV-2 Spike-ACE2 Interaction Inhibitors.

The recent coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has exerted considerable impact on global health. To prepare for rapidly mutating viruses and for the forthcoming pandemic, effective therapies targeting the critical stages of the viral life cycle need to be developed. Viruses are dependent on the interaction between the receptor-binding domain (RBD) of the viral Spike (S) protein (S-RBD) and the angiotensin-converting enzyme 2 (ACE2) receptor to efficiently establish infection and the following replicate. Targeting this interaction provides a promising strategy to inhibit the entry process of the virus, which in turn has both preventive and therapeutic effects. In this study, we developed a robust and straightforward assay based on the Yeast-Two Hybrid system (Y2H) for identifying inhibitors targeting the S-RBD-ACE2 interaction of SARS-CoV-2. Through high-throughput screening, two compounds were identified as potential entry inhibitors. Among them, IMB-1C was superior in terms of pseudovirus entry inhibition and toxicity. It could bind to both ACE2 and S-RBD and induce conformational change in the S-RBD+ACE2 complex. This is the first study to verify the feasibility of utilizing the Y2H system to discover potent SARS-CoV-2 inhibitors targeting the receptor recognition stage. This approach may also be applied in the discovery of other virus receptor recognition inhibitors.

UNC119 regulates T-cell receptor signalling in primary T cells and T acute lymphocytic leukaemia.

T-cell receptor recognition of cognate peptide-MHC leads to the formation of signalling domains and the immunological synapse. Because of the close membrane apposition, there is rapid exclusion of CD45, and therefore LCK activation. Much less is known about whether spatial regulation of the intracellular face dictates LCK activity and TCR signal transduction. Moreover, as LCK is a driver in T acute lymphocytic leukaemia, it is important to understand its regulation. Here, we demonstrate a direct role of the ciliary protein UNC119 in trafficking LCK to the immunological synapse. Inhibiting UNC119 reduces localisation of LCK without impairing LCK phosphorylation and reduces T-cell receptor signal transduction. Although important for initial LCK reorganisation, activated CD8+ T cells retained their ability to kill target tumour cells when UNC119 was inhibited. UNC119 was also needed to sustain proliferation in patient-derived T-ALL cells. UNC119 may therefore represent a novel therapeutic target in T acute lymphocytic leukaemia, which alters the subcellular localisation of LCK in T acute lymphocytic leukaemia cells but preserves the function of existing cytotoxic lymphocytes.

Structural basis of Epstein-Barr virus gp350 receptor recognition and neutralization.

Epstein-Barr virus (EBV) is an oncogenic virus associated with multiple lymphoid malignancies and autoimmune diseases. During infection in B cells, EBV uses its major glycoprotein gp350 to recognize the host receptor CR2, initiating viral attachment, a process that has lacked direct structural evidence for decades. In this study, we resolved the structure of the gp350-CR2 complex, elucidated their key interactions, and determined the site-specific N-glycosylation map of gp350. Our findings reveal that CR2 primarily binds to gp350 through an electrostatically complementary and glycan-free interface and that the diversity of key residues in CR2 across different species influences EBV host selectivity mediated by gp350. With the confirmed binding, we constructed a CR2-Fc antibody analog that targets the vulnerable site of gp350, demonstrating a potent neutralization effect against EBV infection in B cells. Our work provides essential structural insights into the mechanism of EBV infection and host tropism, suggesting a potential antiviral agent.

Whole-Body Physiologically Based Pharmacokinetic Modeling of GalNAc-Conjugated siRNAs.

Background/Objectives: N-acetyl-galactosamine small interfering RNAs (GalNAc-siRNA) are an emerging class of drugs due to their durable knockdown of disease-related proteins. Direct conjugation of GalNAc onto the siRNA enables targeted uptake into hepatocytes via GalNAc recognition of the Asialoglycoprotein Receptor (ASGPR). With a transient plasma exposure combined with a prolonged liver half-life, GalNAc-siRNA exhibits distinct disposition characteristics. We aimed to develop a generic GalNAc-siRNAs whole-body physiologically based pharmacokinetic-pharmacodynamic (WB-PBPK-PD) model for describing the pharmacokinetic-pharmacodynamic (PK-PD) relationship and overall tissue distribution in the open-source platform Open Systems Pharmacology Suite. Methods: Model development was performed using published studies in mice leveraging the PK-Sim® standard implementation for large molecules with added implementations of ASGPR-mediated liver disposition and downstream target effects. Adequate model performance was achieved across study measurements and included studies adopting a combination of global and compound-specific parameters. Results: The analysis identified significant compound dependencies, e.g., endosomal stability, with direct consequences for the pharmacological effect. Additionally, knowledge gaps in mechanistic understanding related to extravasation and overall tissue distribution were identified during model development. The presented study provides a generic WB-PBPK-PD model for the investigation of GalNAc-siRNAs implemented in a standardized open-source platform.

Molecular basis for shifted receptor recognition by an encephalitic arbovirus.

After decades of inactivity throughout the Americas, western equine encephalitis virus (WEEV) recently re-emerged in South America, causing a large-scale outbreak in humans and horses. WEEV binds protocadherin 10 (PCDH10) as a receptor; however, nonpathogenic strains no longer bind human or equine PCDH10 but retain the ability to bind avian receptors. Highly virulent WEEV strains can also bind the very low-density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2) as alternative receptors. Here, by determining cryo-electron microscopy structures of WEEV strains isolated from 1941-2005 bound to mammalian receptors, we identify polymorphisms in the WEEV spike protein that explain shifts in receptor dependencies and that can allow nonpathogenic strains to infect primary cortical neurons. We predict the receptor dependencies of additional strains and of a related North American alphavirus. Our findings have implications for outbreak preparedness and enhance understanding of arbovirus neurovirulence through virus receptor binding patterns.

The Evolving T Cell Receptor Recognition Code: The Rules Are More Like Guidelines.

αβ T cell receptor (TCR) recognition of peptide-MHC complexes lies at the core of adaptive immunity, balancing specificity and cross-reactivity to facilitate effective antigen discrimination. Early structural studies established basic frameworks helpful for understanding and contextualizing TCR recognition and features such as peptide specificity and MHC restriction. However, the growing TCR structural database and studies launched from structural work continue to reveal exceptions to common assumptions and simplifications derived from earlier work. Here we explore our evolving understanding of TCR recognition, illustrating how structural and biophysical investigations regularly uncover complex phenomena that push against paradigms and expand our understanding of how TCRs bind to and discriminate between peptide/MHC complexes. We discuss the implications of these findings for basic, translational, and predictive immunology, including the challenges in accounting for the inherent adaptability, flexibility, and occasional biophysical sloppiness that characterize TCR recognition.

Mesenchymal Stem Cells Carrying Viral Fusogenic Protein p14 to Treat Solid Tumors by Inducing Cell-Cell Fusion and Immune Activation.

Background: Chimeric antigen receptor (CAR)-based immune cell therapies attack neighboring cancer cells after receptor recognition but are unable to directly affect distant tumor cells. This limitation may contribute to their inefficiency in treating solid tumors, given the restricted intratumoral infiltration and immunosuppressive tumor microenvironment. Therefore, cell-cell fusion as a cell-killing mechanism might develop a novel cytotherapy aimed at improving the efficacy against solid tumors. Methods: We constructed a fusogenic protein, fusion-associated small transmembrane (FAST) p14 of reptilian reovirus, into cancer cells and mesenchymal stem cells (MSCs), which cocultured with various colon cancer cells and melenoma cells to validate its ability to induce cell fusion and syncytia formation. RNA sequencing, quantitative reverse transcription polymerase chain reaction, and Western blot were performed to elucidate the mechanism of syncytia death. Cell viability assay was employed to assess the killing effects of MSCs carrying the p14 protein (MSCs-p14), which was also identified in the subcutaneous tumor models. Subsequently, the Tet-On system was introduced to enhance the controllability and safety of therapy. Results: Cancer cells incorporated with fusogenic protein p14 FAST from reovirus fused together to form syncytia and subsequently died through apoptosis and pyroptosis. MSCs-p14 cocultured with different cancer cells and effienctly induced cancer cell fusion and caused widespread cancer cell death invitro. In mouse tumor models, mMSCs-p14 treatment markedly suppressed tumor growth and also enhanced the activity of natural killer cells and macrophages. Controllability and safety of MSCs-p14 therapy were further improved by introducing the tetracycline-controlled transcriptional system. Conclusion: MSC-based cytotherapy carrying viral fusogenic protein in this study kills cancer cells by inducing cell-cell fusion. It has demonstrated definite efficacy in treating solid tumors and is worth considering for clinical development.

Development of metastasis and survival prediction model of luminal and non-luminal breast cancer with weakly supervised learning based on pathomics.

Breast cancer stands as the most prevalent form of cancer among women globally. This heterogeneous disease exhibits varying clinical behaviors. The stratification of breast cancer patients into risk groups, determined by their metastasis and survival outcomes, is pivotal for tailoring personalized treatments and therapeutic interventions. The pathological sections of radical specimens encompass a diverse range of histological information pertinent to the metastasis and survival of patients. In this study, our objective is to develop a deep learning model utilizing pathological images to predict the metastasis and survival outcomes for breast cancer patients. This study utilized pathological sections from 204 radical mastectomy specimens obtained between January 2013 and December 2014 at the Second Affiliated Hospital of the Medical College of Zhejiang University. The 204 pathological slices were scanned and transformed into whole slide imaging (WSI), with manual labeling of all tumor areas. The WSI was then partitioned into smaller tiles measuring 512 × 512 pixels. Three networks, namely Densely Connected Convolutional Network 121 (DenseNet121), Residual Network (ResNet50), and Inception_v3, were assessed. Subsequently, we combined patch-level predictions, probability histograms, and Term Frequency-Inverse Document Frequency (TF-IDF) features to create comprehensive participants representations. These features served as the foundational input for developing a machine learning algorithm for metastasis analysis and a Cox regression model for survival analysis. Our results show that the Inception_v3 model shows a particularly robust patch recognition ability for estrogen receptor (ER) recognition. Our pathological model shows high accuracy in predicting tumor regions. The train area under the curve (AUC) of the Inception_v3 model based on supervised learning is 0.975, which is higher than the model established by weakly supervised learning. But the AUC of the metastasis prediction in training and testing sets is higher than value based on supervised learning. Furthermore, the C-index of the survival prediction model is 0.710 in the testing sets, which is also better than the value by supervised learning. Our study demonstrates the significant potential of deep learning models in predicting breast cancer metastasis and prognosis, with the pathomic model showing high accuracy in identifying tumor areas and ER status. The integration of clinical features and pathomics signature into a nomogram further provides a valuable tool for clinicians to make individualized treatment decisions.

Folate receptor-targeted thiol-maleimide clicked chitosan/carboxymethyl cellulose nanoparticles for cisplatin delivery in oral carcinoma.

This study aimed to develop cisplatin (CDDP)-loaded folic acid (FA)-decorated nanoparticles (NPs) as targeted drug carrier towards overexpressed folate receptors on the oral carcinoma cell line (KB cells). The FA-conjugated thiolated succinyl chitosan (FA-SH-SCS) and maleimide-grafted-carboxymethyl cellulose (CMC-MAL) were synthesized and acquired in the preparation of NPs via thiol-maleimide click reaction. The physicochemical characteristics, drug loading, and drug release of the FA-decorated NPs (FA-NPs) were examined. Also, the in vitro biocompatibility, cellular uptake, and cell death mechanism were investigated. Relatively spherical NPs with negative charge were obtained with a size of approximately 200 nm. The formation of FA-NPs through click reaction was confirmed by the pH change and Ellman's assay. The release of CDDP from the FA-NPs was influenced by the acidic tumor environment condition. The FA-NPs were non-toxic to the normal cells. Furthermore, FA-NPs improved the cellular uptake of CDDP in oral carcinoma cells through specific recognition of folate receptors by FA-NPs. The delivery of CDDP by FA-NPs to the KB cell induced the apoptotic cell death pathway. Therefore, FA-NPs presented the potential to be effective nanocarriers for CDDP delivery in the treatment of oral cancer via active targeting approach.

A single mutation in bovine influenza H5N1 hemagglutinin switches specificity to human receptors.

In 2024, several human infections with highly pathogenic clade 2.3.4.4b bovine influenza H5N1 viruses in the United States raised concerns about their capability for bovine-to-human or even human-to-human transmission. In this study, analysis of the hemagglutinin (HA) from the first-reported human-infecting bovine H5N1 virus (A/Texas/37/2024, Texas) revealed avian-type receptor binding preference. Notably, a Gln226Leu substitution switched Texas HA binding specificity to human-type receptors, which was enhanced when combined with an Asn224Lys mutation. Crystal structures of the Texas HA with avian receptor analog LSTa and its Gln226Leu mutant with human receptor analog LSTc elucidated the structural basis for this preferential receptor recognition. These findings highlight the need for continuous surveillance of emerging mutations in avian and bovine clade 2.3.4.4b H5N1 viruses.

Competitive binding of small antagonistic peptides to the OsER1 receptor optimizes rice panicle architecture.

Rice panicle architecture is a pivotal trait that strongly contributes to grain yield. Small peptide ligands from the OsEPF/EPFL family synergistically control panicle architecture by recognition of the OsER1 receptor and subsequent activation of the OsMKKK10-OsMKK4-OsMPK6 cascade, indicating that specific ligand-receptor pairs orchestrate rice panicle development. However, how small homologous peptides fine-tune organ morphogenesis by targeting a common receptor remains elusive. Here, we report that the small peptide OsEPFL5 acts as a ligand of the OsER1 receptor that inactivates the OsMKKK10-OsMKK4-OsMPK6 cascade, suggesting that OsEPFL5 plays the opposite role to that of the OsEPFL6/7/8/9 subfamily in regulating spikelet number per panicle and grain size. Notably, OsEPFL5 competitively replaces the OsEPFL6, OsEPFL7, OsEPFL8, or OsEPFL9 binding to the OsER1 receptor, exposing antagonistic competition between small homologous peptides. Specifically enhancing expression of OsEPFL5 significantly improves grain yield by suppressing functions of the ligand-receptor pairs of OsEPFL6-OsER1, OsEPFL7-OsER1, OsEPFL8-OsER1, and OsEPFL9-OsER1, suggesting that competitive binding to the OsER1 receptor by small antagonistic peptides can optimize rice panicle architecture. Our findings elucidate how a receptor agonist and antagonist define inductive and inhibitory cues to shape rice panicle architecture, thus providing a new method of rationally breaking yield trait coupling by manipulating small antagonistic peptides.

Plasma Protein Adsorption on Melphalan Prodrug Bearing Liposomes - Bare, Stealth, and Targeted

Background: Plasma protein binding is inevitable for nanomaterials injected into blood circulation. For liposomes, this process is affected by the lipid composition of the bilayer. Membrane constituents and their ratio define liposome characteristics, namely, surface charge and hydrophobicity, which drive protein adsorption. Roughly 30 years ago, the correlation between the amount of bound proteins and the resulting circulation time of liposomes was established by S. Semple, A. Chonn, and P. Cullis. Here, we have estimated ex vivo plasma protein binding, primarily to determine the impact of melphalan prodrug inclusion into bilayer on bare, PEGylated (stealth), and Sialyl Lewis X (SiaLeX)-decorated liposomes. Experimental: Liposomes were allowed to bind plasma proteins for 15 minutes, then liposome-protein complexes were isolated, and protein and lipid quantities were assessed in the complexes. In addition, the uptake by activated HUVEC cells was evaluated for SiaLeX-decorated liposomes. Results:: Melphalan moieties on the bilayer surface enrich protein adsorption compared to pure phosphatidylcholine sample. Although PEG-lipid had facilitated a significant decrease in protein adsorption in the control sample, when prodrug was added to the composition, the degree of pro-tein binding was restored to the level of melphalan liposomes without a stealth barrier. A similar effect was observed for SiaLeX-decorated liposomes. Conclusion: None of the compositions reported here should suffer from quick elimination from circulation, according to the cut-off values introduced by Cullis and colleagues. Nevertheless, the amount of bound proteins is sufficient to affect biodistribution, namely, to impair receptor recog-nition of SiaLeX and reduce liposome uptake by endothelial cells.

Regulating IL-2 Immune Signaling Function Via A Core Allosteric Structural Network.

Human interleukin-2 (IL-2) is a crucial cytokine for T cell regulation, with therapeutic potential in cancer and autoimmune diseases. However, IL-2's pleiotropic effects across different immune cell types often lead to toxicity and limited efficacy. Previous efforts to enhance IL-2's therapeutic profile have focused on modifying its receptor binding sites. Yet, the underlying dynamics and intramolecular networks contributing to IL-2 receptor recognition remain unexplored. This study presents a detailed characterization of IL-2 dynamics compared to two engineered IL-2 mutants, "superkines" S15 and S1, which exhibit biased signaling towards effector T cells. Using NMR spectroscopy and molecular dynamics simulations, we demonstrate significant variations in core dynamic pathways and conformational exchange rates across these three IL-2 variants. We identify distinct allosteric networks and minor state conformations in the superkines, despite their structural similarity to wild-type IL-2. Furthermore, we rationally design a mutation (L56A) in the S1 superkine's core network, which partially reverts its dynamics, receptor binding affinity, and T cell signaling behavior towards that of wild-type IL-2. Our results reveal that IL-2 superkine core dynamics play a critical role in their enhanced receptor binding and function, suggesting that modulating IL-2 dynamics and core allostery represents an untapped approach for designing immunotherapies with improved immune cell selectivity profiles.

Rational Design of Hydrogel Polymer Nanoparticles Based on a Receptor Recognition Mechanism of Endotoxin and Its Application in Endotoxin Removal

Rational Design of Hydrogel Polymer Nanoparticles Based on a Receptor Recognition Mechanism of Endotoxin and Its Application in Endotoxin Removal

An immune suppressive tumor microenvironment in primary prostate cancer promotes tumor immune escape.

Immunotherapy has demonstrated limited activity in prostate cancer to date. This likely reflects an immune suppressive tumor microenvironment (TME), with previous studies suggesting low PD-L1 expression and a sparse immune cell infiltrate. We aimed to further characterise the immune TME in primary prostate cancer and correlate immune subset densities with clinical outcomes. Two distinct cohorts of patients treated with radical prostatectomy were identified, based on the development of biochemical recurrence (BCR), one subgroup with high International Society of Urological Pathologists (ISUP) grade group, recurrent disease and a second with low grade, non-recurrent disease. A prostate immunohistochemical (IHC) antibody cocktail was used to differentiate tumor and peritumoral benign tissue. Specific CD8+, CD4+, FoxP3+, CD20+ and CD68+ cell subsets were identified using IHC staining of consecutive slides. PD-L1 and CD8/PD-L1 dual staining were also performed. Cell subset densities were quantified within tumor and peritumoral regions. We used descriptive statistics to report cell subset densities and T-tests to compare groups by age, grade and the development of BCR. Univariable and multivariable logistic regression were used to analyse risk factors for BCR and the development of metastatic disease. A total of 175 patients were included, with a median age of 63 years and median pre-operative PSA of 8.2ng/ml. BCR occurred in 115 patients (66%) and 56 (32%) developed metastatic disease. CD68+ cells were the most abundant (median 648.8/mm2 intratumoral, 247.6/mm2 peritumoral), while PD-L1+ and PD-L1/CD8+ cell density was low overall (PD-L1+ median 162.4/mm2 intratumoral, 141.7/mm2 peritumoral; PD-L1/CD8+ (median 5.52/mm2 intratumoral, 3.41/mm2 peritumoral). Overall, grade group and T-stage were independently associated with BCR and metastatic disease. Higher density of peritumoral PD-L1+ cells was an independent risk factor for BCR (OR 5.33, 95%CI 1.31-21.61, p = 0.019).Although higher densities of CD8+ and CD4+ cells were observed in higher grade group 3-5 tumors, these were not associated with the development of BCR or metastasis. In our cohort of prostate cancer patients who underwent radical prostatectomy, higher grade group and T-stage were independent predictors of BCR and metastasis. Despite higher grade group being associated with higher CD8+ cell density, PD-L1+ and PD-L1/CD8+ cell densities were low overall, suggesting lower T cell receptor recognition of tumor antigens. Further understanding of this phenomenon would influence development of future immunotherapeutic strategies in prostate cancer.

Structural characterization and AlphaFold modeling of human T cell receptor recognition of NRAS cancer neoantigens.

T cell receptors (TCRs) that recognize cancer neoantigens are important for anticancer immune responses and immunotherapy. Understanding the structural basis of TCR recognition of neoantigens provides insights into their exquisite specificity and can enable design of optimized TCRs. We determined crystal structures of a human TCR in complex with NRAS Q61K and Q61R neoantigen peptides and HLA-A1 major histocompatibility complex (MHC), revealing the molecular underpinnings for dual recognition and specificity versus wild-type NRAS peptide. We then used multiple versions of AlphaFold to model the corresponding complex structures, given the challenge of immune recognition for such methods. One implementation of AlphaFold2 (TCRmodel2) with additional sampling was able to generate accurate models of the complexes, while AlphaFold3 also showed strong performance, although success was lower for other complexes. This study provides insights into TCR recognition of a shared cancer neoantigen as well as the utility and practical considerations for using AlphaFold to model TCR-peptide-MHC complexes.

Attention-aware differential learning for predicting peptide-MHC class I binding and T cell receptor recognition.

The identification of neoantigens is crucial for advancing vaccines, diagnostics, and immunotherapies. Despite this importance, a fundamental question remains: how to model the presentation of neoantigens by major histocompatibility complex class I molecules and the recognition of the peptide-MHC-I (pMHC-I) complex by T cell receptors (TCRs). Accurate prediction of pMHC-I binding and TCR recognition remains a significant computational challenge in immunology due to intricate binding motifs and the long-tail distribution of known binding pairs in public databases. Here, we propose an attention-aware framework comprising TranspMHC for pMHC-I binding prediction and TransTCR for TCR-pMHC-I recognition prediction. Leveraging the attention mechanism, TranspMHC surpasses existing algorithms on independent datasets at both pan-specific and allele-specific levels. For TCR-pMHC-I recognition, TransTCR incorporates transfer learning and a differential learning strategy, demonstrating superior performance and enhanced generalization on independent datasets compared to existing methods. Furthermore, we identify key amino acids associated with binding motifs of peptides and TCRs that facilitate pMHC-I and TCR-pMHC-I binding, indicating the potential interpretability of our proposed framework.