Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction.

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.

Isolation of a Structural Mechanism for Uncoupling T Cell Receptor Signaling from Peptide-MHC Binding.

TCR-signaling strength generally correlates with peptide-MHC binding affinity; however, exceptions exist. We find high-affinity, yet non-stimulatory, interactions occur with high frequency in the human T cell repertoire. Here, we studied human TCRs that are refractory to activation by pMHC ligands despite robust binding. Analysis of 3D affinity, 2D dwell time, and crystal structures of stimulatory versus non-stimulatory TCR-pMHC interactions failed to account for their different signaling outcomes. Using yeast pMHC display, we identified peptide agonists of a formerly non-responsive TCR. Single-molecule force measurements demonstrated the emergence of catch bonds in the activating TCR-pMHC interactions, correlating with exclusion of CD45 from the TCR-APC contact site. Molecular dynamics simulations of TCR-pMHC disengagement distinguished agonist from non-agonist ligands based on the acquisition of catch bonds within the TCR-pMHC interface. The isolation of catch bonds as a parameter mediating the coupling of TCR binding and signaling has important implications for TCR and antigen engineering for immunotherapy.

Multi-cohort analysis of host immune response identifies conserved protective and detrimental modules associated with severity across viruses.

Viral infections induce a conserved host response distinct from bacterial infections. We hypothesized that the conserved response is associated with disease severity and is distinct between patients with different outcomes. To test this, we integrated 4,780 blood transcriptome profiles from patients aged 0 to 90 years infected with one of 16 viruses, including SARS-CoV-2, Ebola, chikungunya, and influenza, across 34 cohorts from 18 countries, and single-cell RNA sequencing profiles of 702,970 immune cells from 289 samples across three cohorts. Severe viral infection was associated with increased hematopoiesis, myelopoiesis, and myeloid-derived suppressor cells. We identified protective and detrimental gene modules that defined distinct trajectories associated with mild versus severe outcomes. The interferon response was decoupled from the protective host response in patients with severe outcomes. These findings were consistent, irrespective of age and virus, and provide insights to accelerate the development of diagnostics and host-directed therapies to improve global pandemic preparedness.

Early IFN-α signatures and persistent dysfunction are distinguishing features of NK cells in severe COVID-19.

Longitudinal analyses of the innate immune system, including the earliest time points, are essential to understand the immunopathogenesis and clinical course of coronavirus disease (COVID-19). Here, we performed a detailed characterization of natural killer (NK) cells in 205 patients (403 samples; days 2 to 41 after symptom onset) from four independent cohorts using single-cell transcriptomics and proteomics together with functional studies. We found elevated interferon (IFN)-α plasma levels in early severe COVD-19 alongside increased NK cell expression of IFN-stimulated genes (ISGs) and genes involved in IFN-α signaling, while upregulation of tumor necrosis factor (TNF)-induced genes was observed in moderate diseases. NK cells exert anti-SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) activity but are functionally impaired in severe COVID-19. Further, NK cell dysfunction may be relevant for the development of fibrotic lung disease in severe COVID-19, as NK cells exhibited impaired anti-fibrotic activity. Our study indicates preferential IFN-α and TNF responses in severe and moderate COVID-19, respectively, and associates a prolonged IFN-α-induced NK cell response with poorer disease outcome.

Non-viral precision T cell receptor replacement for personalized cell therapy.

T cell receptors (TCRs) enable T cells to specifically recognize mutations in cancer cells1-3. Here we developed a clinical-grade approach based on CRISPR-Cas9 non-viral precision genome-editing to simultaneously knockout the two endogenous TCR genes TRAC (which encodes TCRα) and TRBC (which encodes TCRß). We also inserted into the TRAC locus two chains of a neoantigen-specific TCR (neoTCR) isolated from circulating T cells of patients. The neoTCRs were isolated using a personalized library of soluble predicted neoantigen-HLA capture reagents. Sixteen patients with different refractory solid cancers received up to three distinct neoTCR transgenic cell products. Each product expressed a patient-specific neoTCR and was administered in a cell-dose-escalation, first-in-human phase I clinical trial ( NCT03970382 ). One patient had grade 1 cytokine release syndrome and one patient had grade 3 encephalitis. All participants had the expected side effects from the lymphodepleting chemotherapy. Five patients had stable disease and the other eleven had disease progression as the best response on the therapy. neoTCR transgenic T cells were detected in tumour biopsy samples after infusion at frequencies higher than the native TCRs before infusion. This study demonstrates the feasibility of isolating and cloning multiple TCRs that recognize mutational neoantigens. Moreover, simultaneous knockout of the endogenous TCR and knock-in of neoTCRs using single-step, non-viral precision genome-editing are achieved. The manufacture of neoTCR engineered T cells at clinical grade, the safety of infusing up to three gene-edited neoTCR T cell products and the ability of the transgenic T cells to traffic to the tumours of patients are also demonstrated.

Physical and in silico immunopeptidomic profiling of a cancer antigen prostatic acid phosphatase reveals targets enabling TCR isolation.

Tissue-specific antigens can serve as targets for adoptive T cell transfer-based cancer immunotherapy. Recognition of tumor by T cells is mediated by interaction between peptide-major histocompatibility complexes (pMHCs) and T cell receptors (TCRs). Revealing the identity of peptides bound to MHC is critical in discovering cognate TCRs and predicting potential toxicity. We performed multimodal immunopeptidomic analyses for human prostatic acid phosphatase (PAP), a well-recognized tissue antigen. Three physical methods, including mild acid elution, coimmunoprecipitation, and secreted MHC precipitation, were used to capture a thorough signature of PAP on HLA-A*02:01. Eleven PAP peptides that are potentially A*02:01-restricted were identified, including five predicted strong binders by NetMHCpan 4.0. Peripheral blood mononuclear cells (PBMCs) from more than 20 healthy donors were screened with the PAP peptides. Seven cognate TCRs were isolated which can recognize three distinct epitopes when expressed in PBMCs. One TCR shows reactivity toward cell lines expressing both full-length PAP and HLA-A*02:01. Our results show that a combined multimodal immunopeptidomic approach is productive in revealing target peptides and defining the cloned TCR sequences reactive with prostatic acid phosphatase epitopes.

The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection fatality rate (IFR) doubles with every 5 y of age from childhood onward. Circulating autoantibodies neutralizing IFN-α, IFN-ω, and/or IFN-ß are found in ∼20% of deceased patients across age groups, and in ∼1% of individuals aged <70 y and in >4% of those >70 y old in the general population. With a sample of 1,261 unvaccinated deceased patients and 34,159 individuals of the general population sampled before the pandemic, we estimated both IFR and relative risk of death (RRD) across age groups for individuals carrying autoantibodies neutralizing type I IFNs, relative to noncarriers. The RRD associated with any combination of autoantibodies was higher in subjects under 70 y old. For autoantibodies neutralizing IFN-α2 or IFN-ω, the RRDs were 17.0 (95% CI: 11.7 to 24.7) and 5.8 (4.5 to 7.4) for individuals <70 y and ≥70 y old, respectively, whereas, for autoantibodies neutralizing both molecules, the RRDs were 188.3 (44.8 to 774.4) and 7.2 (5.0 to 10.3), respectively. In contrast, IFRs increased with age, ranging from 0.17% (0.12 to 0.31) for individuals <40 y old to 26.7% (20.3 to 35.2) for those ≥80 y old for autoantibodies neutralizing IFN-α2 or IFN-ω, and from 0.84% (0.31 to 8.28) to 40.5% (27.82 to 61.20) for autoantibodies neutralizing both. Autoantibodies against type I IFNs increase IFRs, and are associated with high RRDs, especially when neutralizing both IFN-α2 and IFN-ω. Remarkably, IFRs increase with age, whereas RRDs decrease with age. Autoimmunity to type I IFNs is a strong and common predictor of COVID-19 death.

Non-Mass Spectrometric Targeted Single-Cell Metabolomics.

Metabolic assays serve as pivotal tools in biomedical research, offering keen insights into cellular physiological and pathological states. While mass spectrometry (MS)-based metabolomics remains the gold standard for comprehensive, multiplexed analyses of cellular metabolites, innovative technologies are now emerging for the targeted, quantitative scrutiny of metabolites and metabolic pathways at the single-cell level. In this review, we elucidate an array of these advanced methodologies, spanning synthetic and surface chemistry techniques, imaging-based methods, and electrochemical approaches. We summarize the rationale, design principles, and practical applications for each method, and underscore the synergistic benefits of integrating single-cell metabolomics (scMet) with other single-cell omics technologies. Concluding, we identify prevailing challenges in the targeted scMet arena and offer a forward-looking commentary on future avenues and opportunities in this rapidly evolving field.

T cell antigen discovery via signaling and antigen-presenting bifunctional receptors.

CD8+ T cells recognize and eliminate tumors in an antigen-specific manner. Despite progress in characterizing the antitumor T cell repertoire and function, the identification of target antigens remains a challenge. Here we describe the use of chimeric receptors called signaling and antigen-presenting bifunctional receptors (SABRs) in a cell-based platform for T cell receptor (TCR) antigen discovery. SABRs present an extracellular complex comprising a peptide and major histocompatibility complex (MHC), and induce intracellular signaling via a TCR-like signal after binding with a cognate TCR. We devised a strategy for antigen discovery using SABR libraries to screen thousands of antigenic epitopes. We validated this platform by identifying the targets recognized by public TCRs of known specificities. Moreover, we extended this approach for personalized neoantigen discovery.

T cell antigen discovery via trogocytosis.

T cell receptor (TCR) ligand discovery is essential for understanding and manipulating immune responses to tumors. We developed a cell-based selection platform for TCR ligand discovery that exploits a membrane transfer phenomenon called trogocytosis. We discovered that T cell membrane proteins are transferred specifically to target cells that present cognate peptide-major histocompatibility complex (MHC) molecules. Co-incubation of T cells expressing an orphan TCR with target cells collectively presenting a library of peptide-MHCs led to specific labeling of cognate target cells, enabling isolation of these target cells and sequencing of the cognate TCR ligand. We validated this method for two clinically employed TCRs and further used the platform to identify the cognate neoepitope for a subject-derived neoantigen-specific TCR. Thus, target cell trogocytosis is a robust tool for TCR ligand discovery that will be useful for studying basic tumor immunology and identifying new targets for immunotherapy.

4D electron microscopy of T cell activation.

T cells can be controllably stimulated through antigen-specific or nonspecific protocols. Accompanying functional hallmarks of T cell activation can include cytoskeletal reorganization, cell size increase, and cytokine secretion. Photon-induced near-field electron microscopy (PINEM) is used to image and quantify evanescent electric fields at the surface of T cells as a function of various stimulation conditions. While PINEM signal strength scales with multiple of the biophysical changes associated with T cell functional activation, it mostly strongly correlates with antigen-engagement of the T cell receptors, even under conditions that do not lead to functional T cell activation. PINEM image analysis suggests that a stimulation-induced reorganization of T cell surface structure, especially over length scales of a few hundred nanometers, is the dominant contributor to these PINEM signal changes. These experiments reveal that PINEM can provide a sensitive label-free probe of nanoscale cellular surface structures.

Characteristics and Factors Associated With Coronavirus Disease 2019 Infection, Hospitalization, and Mortality Across Race and Ethnicity.

BACKGROUND: Data on the characteristics of coronavirus disease 2019 (COVID-19) patients disaggregated by race/ethnicity remains limited. We evaluated the sociodemographic and clinical characteristics of patients across racial/ethnic groups and assessed their associations with COVID-19 outcomes. METHODS: This retrospective cohort study examined 629 953 patients tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a large health system spanning California, Oregon, and Washington between March 1 and December 31, 2020. Sociodemographic and clinical characteristics were obtained from electronic health records. Odds of SARS-CoV-2 infection, COVID-19 hospitalization, and in-hospital death were assessed with multivariate logistic regression. RESULTS: A total of 570 298 patients with known race/ethnicity were tested for SARS-CoV-2, of whom 27.8% were non-White minorities: 54 645 individuals tested positive, with minorities representing 50.1%. Hispanics represented 34.3% of infections but only 13.4% of tests. Although generally younger than White patients, Hispanics had higher rates of diabetes but fewer other comorbidities. A total of 8536 patients were hospitalized and 1246 died, of whom 56.1% and 54.4% were non-White, respectively. Racial/ethnic distributions of outcomes across the health system tracked with state-level statistics. Increased odds of testing positive and hospitalization were associated with all minority races/ethnicities. Hispanic patients also exhibited increased morbidity, and Hispanic race/ethnicity was associated with in-hospital mortality (odds ratio [OR], 1.39; 95% confidence interval [CI], 1.14-1.70). CONCLUSION: Major healthcare disparities were evident, especially among Hispanics who tested positive at a higher rate, required excess hospitalization and mechanical ventilation, and had higher odds of in-hospital mortality despite younger age. Targeted, culturally responsive interventions and equitable vaccine development and distribution are needed to address the increased risk of poorer COVID-19 outcomes among minority populations.

Protein-Catalyzed Capture Agents.

Protein-catalyzed capture agents (PCCs) are synthetic and modular peptide-based affinity agents that are developed through the use of single-generation in situ click chemistry screens against large peptide libraries. In such screens, the target protein, or a synthetic epitope fragment of that protein, provides a template for selectively promoting the noncopper catalyzed azide-alkyne dipolar cycloaddition click reaction between either a library peptide and a known ligand or a library peptide and the synthetic epitope. The development of epitope-targeted PCCs was motivated by the desire to fully generalize pioneering work from the Sharpless and Finn groups in which in situ click screens were used to develop potent, divalent enzymatic inhibitors. In fact, a large degree of generality has now been achieved. Various PCCs have demonstrated utility for selective protein detection, as allosteric or direct inhibitors, as modulators of protein folding, and as tools for in vivo tumor imaging. We provide a historical context for PCCs and place them within the broader scope of biological and synthetic aptamers. The development of PCCs is presented as (i) Generation I PCCs, which are branched ligands engineered through an iterative, nonepitope-targeted process, and (ii) Generation II PCCs, which are typically developed from macrocyclic peptide libraries and are precisely epitope-targeted. We provide statistical comparisons of Generation II PCCs relative to monoclonal antibodies in which the protein target is the same. Finally, we discuss current challenges and future opportunities of PCCs.

Visualizing Subcellular Enrichment of Glycogen in Live Cancer Cells by Stimulated Raman Scattering.

Glycogen, a branched glucose polymer, helps regulate glucose homeostasis through immediate storage and release of glucose. Reprogramming of glycogen metabolism has recently been suggested to play an emerging role in cancer progression and tumorigenesis. However, regulation of metabolic rewiring for glycogen synthesis and breakdown in cancer cells remains less understood. Despite the availability of various glycogen detection methods, selective visualization of glycogen in living cells with high spatial resolution has proven to be highly challenging. Here, we present an optical imaging strategy to visualize glycogen in live cancer cells with minimal perturbation by combining stimulated Raman scattering microscopy with metabolic incorporation of deuterium-labeled glucose. We revealed the subcellular enrichment of glycogen in live cancer cells and achieved specific glycogen mapping through distinct spectral identification. Using this method, different glycogen metabolic phenotypes were characterized in a series of patient-derived BRAF mutant melanoma cell lines. Our results indicate that cell lines manifesting high glycogen storage level showed increased tolerance to glucose deficiency among the studied melanoma phenotypes. This method opens up the possibility for noninvasive study of complex glycogen metabolism at subcellular resolution and may help reveal new features of glycogen regulation in cancer systems.

Preinfusion polyfunctional anti-CD19 chimeric antigen receptor T cells are associated with clinical outcomes in NHL.

After treatment with chimeric antigen receptor (CAR) T cells, interleukin-15 (IL-15) elevation and CAR T-cell expansion are associated with non-Hodgkin lymphoma (NHL) outcomes. However, the association of preinfusion CAR product T-cell functionality with clinical outcomes has not been reported. A single-cell analysis of the preinfusion CD19 CAR product from patients with NHL demonstrated that CAR products contain polyfunctional T-cell subsets capable of deploying multiple immune programs represented by cytokines and chemokines, including interferon-γ, IL-17A, IL-8, and macrophage inflammatory protein 1α. A prespecified T-cell polyfunctionality strength index (PSI) applied to preinfusion CAR product was significantly associated with clinical response, and PSI combined with CAR T-cell expansion or pretreatment serum IL-15 levels conferred additional significance. Within the total product cell population, associations with clinical outcomes were greater with polyfunctional CD4+ T cells compared with CD8+ cells. Grade ≥3 cytokine release syndrome was associated with polyfunctional T cells, and both grade ≥3 neurologic toxicity and antitumor efficacy were associated with polyfunctional IL-17A-producing T cells. The findings in this exploratory study show that a preinfusion CAR product T-cell subset with a definable polyfunctional profile has a major association with clinical outcomes of CAR T-cell therapy. This trial was registered at www.clinicaltrials.gov as #NCT00924326.

Phenotypic heterogeneity and evolution of melanoma cells associated with targeted therapy resistance.

Phenotypic plasticity is associated with non-genetic drug tolerance in several cancers. Such plasticity can arise from chromatin remodeling, transcriptomic reprogramming, and/or protein signaling rewiring, and is characterized as a cell state transition in response to molecular or physical perturbations. This, in turn, can confound interpretations of drug responses and resistance development. Using BRAF-mutant melanoma cell lines as the prototype, we report on a joint theoretical and experimental investigation of the cell-state transition dynamics associated with BRAF inhibitor drug tolerance. Thermodynamically motivated surprisal analysis of transcriptome data was used to treat the cell population as an entropy maximizing system under the influence of time-dependent constraints. This permits the extraction of an epigenetic potential landscape for drug-induced phenotypic evolution. Single-cell flow cytometry data of the same system were modeled with a modified Fokker-Planck-type kinetic model. The two approaches yield a consistent picture that accounts for the phenotypic heterogeneity observed over the course of drug tolerance development. The results reveal that, in certain plastic cancers, the population heterogeneity and evolution of cell phenotypes may be understood by accounting for the competing interactions of the epigenetic potential landscape and state-dependent cell proliferation. Accounting for such competition permits accurate, experimentally verifiable predictions that can potentially guide the design of effective treatment strategies.

High-throughput screening of rare metabolically active tumor cells in pleural effusion and peripheral blood of lung cancer patients.

Malignant pleural effusion (MPE), the presence of malignant cells in pleural fluid, is often the first sign of many cancers and occurs in patients with metastatic malignancies. Accurate detection of tumor cells in pleural fluid is crucial because the presence of MPE denotes an advanced stage of disease and directs a switch in clinical managements. Cytology, as a traditional diagnostic tool, has limited sensitivity especially when tumor cells are not abundant, and may be confounded by reactive mesothelial cells in the pleural fluid. We describe a highly sensitive approach for rapid detection of metabolically active tumor cells in MPE via exploiting the altered glucose metabolism of tumor cells relative to benign cells. Metabolically active tumor cells with high glucose uptake, as evaluated by a fluorescent glucose analog (2-NBDG), are identified by high-throughput fluorescence screening within a chip containing 200,000 addressable microwells and collected for malignancy confirmation via single-cell sequencing. We demonstrate the utility of this approach through analyzing MPE from a cohort of lung cancer patients. Most candidate tumor cells identified are confirmed to harbor the same driver oncogenes as their primary lesions. In some patients, emergence of secondary mutations that mediate acquired resistance to ongoing targeted therapies is also detected before resistance is manifested in the clinical imaging. The detection scheme can be extended to analyze peripheral blood samples. Our approach may serve as a valuable complement to cytology in MPE diagnosis, helping identify the driver oncogenes and resistance-leading mutations for targeted therapies.

Single-cell analysis resolves the cell state transition and signaling dynamics associated with melanoma drug-induced resistance.

Continuous BRAF inhibition of BRAF mutant melanomas triggers a series of cell state changes that lead to therapy resistance and escape from immune control before establishing acquired resistance genetically. We used genome-wide transcriptomics and single-cell phenotyping to explore the response kinetics to BRAF inhibition for a panel of patient-derived BRAFV600 -mutant melanoma cell lines. A subset of plastic cell lines, which followed a trajectory covering multiple known cell state transitions, provided models for more detailed biophysical investigations. Markov modeling revealed that the cell state transitions were reversible and mediated by both Lamarckian induction and nongenetic Darwinian selection of drug-tolerant states. Single-cell functional proteomics revealed activation of certain signaling networks shortly after BRAF inhibition, and before the appearance of drug-resistant phenotypes. Drug targeting those networks, in combination with BRAF inhibition, halted the adaptive transition and led to prolonged growth inhibition in multiple patient-derived cell lines.

Inhibition of heme sequestration of histidine-rich protein 2 using multiple epitope-targeted peptides.

Plasmodium falciparum is the most lethal species of malaria. In infected human red blood cells, P. falciparum digests hemoglobin as a nutrient source, liberating cytotoxic free heme in the process. Sequestration and subsequent conversion of this byproduct into hemozoin, an inert biocrystalline heme aggregate, plays a key role in parasite survival. Hemozoin has been a longstanding target of antimalarials such as chloroquine (CQ), which inhibit the biocrystallization of free heme. In this study, we explore heme-binding interactions with histidine-rich-protein 2 (HRP2), a known malarial biomarker and purported player in free heme sequestration. HRP2 is notoriously challenging to target due to its highly repetitious sequence and irregular secondary structure. We started with three protein-catalyzed capture agents (PCCs) developed against epitopes of HRP2, inclusive of heme-binding motifs, and explored their ability to inhibit heme:HRP2 complex formation. Cocktails of the individual PCCs exhibit an inhibitory potency similar to CQ, while a covalently linked structure built from two separate PCCs provided considerably increased inhibition relative to CQ. Epitope-targeted disruption of heme:HRP2 binding is a novel approach towards disrupting P. falciparum-related hemozoin formation.

Intercellular signaling through secreted proteins induces free-energy gradient-directed cell movement.

Controlling cell migration is important in tissue engineering and medicine. Cell motility depends on factors such as nutrient concentration gradients and soluble factor signaling. In particular, cell-cell signaling can depend on cell-cell separation distance and can influence cellular arrangements in bulk cultures. Here, we seek a physical-based approach, which identifies a potential governed by cell-cell signaling that induces a directed cell-cell motion. A single-cell barcode chip (SCBC) was used to experimentally interrogate secreted proteins in hundreds of isolated glioblastoma brain cancer cell pairs and to monitor their relative motions over time. We used these trajectories to identify a range of cell-cell separation distances where the signaling was most stable. We then used a thermodynamics-motivated analysis of secreted protein levels to characterize free-energy changes for different cell-cell distances. We show that glioblastoma cell-cell movement can be described as Brownian motion biased by cell-cell potential. To demonstrate that the free-energy potential as determined by the signaling is the driver of motion, we inhibited two proteins most involved in maintaining the free-energy gradient. Following inhibition, cell pairs showed an essentially random Brownian motion, similar to the case for untreated, isolated single cells.