Pediatric Sertoli-Leydig Cell Tumors of the Ovary: An Integrated Study of Clinicopathological Features, Pan-cancer-Targeted Next-generation Sequencing and Chromosomal Microarray Analysis From a Single Institution.

Sertoli-Leydig cell tumors (SLCTs) are currently classified into 3 molecular subtypes: DICER1 -mutant (younger patient age), FOXL2 -mutant, and DICER1/FOXL2 -wildtype. However, it is not clear whether all pediatric SLCTs are DICER1 -mutant molecular subtypes and whether other molecular genetic aberrations besides DICER1 are involved in the pathogenesis and prognosis of these tumors. We studied comprehensive data for 8 cases of pediatric SLCTs, including clinicopathological features, pan-cancer-targeted next-generation sequencing/OncoKids panel, and chromosomal microarray analysis, to further analyze the correlation among clinicopathological features, molecular genetic aberrations, and prognosis. The ages of the patients ranged from 4 to 16 years (median, 14 y). Seven cases were moderately differentiated, and one was poorly differentiated with heterologous mesenchymal elements. Two cases had heterologous epithelium or retiform elements. Follow-up was available for all 8 patients (median, 49.5 mo). Seven patients were alive without evidence of recurrence or metastasis, and only case 5 developed metastases (synchronous bilateral pulmonary tumors with rhabdomyosarcomatous differentiation). All 8 tumors were found to harbor somatic hotspot DICER1 mutations, and 5 patients carried germline DICER1 mutations (2 of them had the phenotype of DICER1 syndrome). Together with recent studies, the DICER1 mutation frequency is 100% in pediatric SLCTs (n=27, age≤16 y). Copy number alterations were detected in 3 tumors; the only recurrent copy number alterations was the gain of whole chromosome 6 in case 5 and case 8. This is the first report describing clinicopathological features and molecular alterations in pediatric SLCTs. Our results demonstrate that all pediatric SLCTs belong to the DICER1 -mutant molecular subtype, highlighting that somatic hotspot DICER1 mutation detection has high sensitivity (100%) for the auxiliary diagnosis of pediatric SLCTs (age ≤16 y). Some pediatric SLCTs harbor molecular genetic aberrations other than DICER1 mutation, and their significance needs further study.

Association between frailty status and complications in patients undergoing surgical excision of malignant esophageal neoplasms.

Background: Research within the last decade highlights the patients' frailty status as an important predictor of esophageal cancer outcomes, but the literature evaluating frailty's role in these patients remains limited. We evaluated the role of frailty in patients undergoing resection of malignant esophageal neoplasms. Methods: We used the Nationwide Readmissions Database from 2016 and 2017 to identify patients who underwent excision of a malignant esophageal neoplasm. Patient frailty was queried using the Johns Hopkins Adjusted Clinical Groups frailty-defining diagnosis indicator. Propensity score matching identified 289 frail patients and 281 non-frail patients. Mann-Whitney U testing was performed and receiver operating characteristic (ROC) curves were created, following the creation of logistic regression models for predicting discharge disposition. The area under the curve (AUC) served as a proxy for model performance. Results: Frail patients had significantly more nonroutine discharges, longer inpatient lengths of stay, higher costs, more acute infections, posthemorrhagic anemia and deep vein thrombosis, and greater mortality (P<0.05). No significant differences were found between the 2 cohorts with respect to readmission rates, pulmonary embolism or dysphagia. Predictive models for patient discharge disposition demonstrated that frailty status in combination with age resulted in better ROC curves (AUC: 0.652) compared to models using age alone (AUC: 0.601). Conclusions: Frailty was found to be significantly correlated with higher rates of inpatient medical complications following esophagectomy. The inclusion of patient frailty status in predictive models for discharge disposition resulted in a better predictive capacity compared to those using age alone.

Effects of HLA single chain trimer design on peptide presentation and stability.

MHC class I "single-chain trimer" molecules, coupling MHC heavy chain, ß2-microglobulin, and a specific peptide into a single polypeptide chain, are widely used in research. To more fully understand caveats associated with this design that may affect its use for basic and translational studies, we evaluated a set of engineered single-chain trimers with combinations of stabilizing mutations across eight different classical and non-classical human class I alleles with 44 different peptides, including a novel human/murine chimeric design. While, overall, single-chain trimers accurately recapitulate native molecules, care was needed in selecting designs for studying peptides longer or shorter than 9-mers, as single-chain trimer design could affect peptide conformation. In the process, we observed that predictions of peptide binding were often discordant with experiment and that yields and stabilities varied widely with construct design. We also developed novel reagents to improve the crystallizability of these proteins and confirmed novel modes of peptide presentation.

Large libraries of single-chain trimer peptide-MHCs enable antigen-specific CD8+ T cell discovery and analysis.

The discovery and characterization of antigen-specific CD8+ T cell clonotypes typically involves the labor-intensive synthesis and construction of peptide-MHC tetramers. We adapt single-chain trimer (SCT) technologies into a high throughput platform for pMHC library generation, showing that hundreds can be rapidly prepared across multiple Class I HLA alleles. We use this platform to explore the impact of peptide and SCT template mutations on protein expression yield, thermal stability, and functionality. SCT libraries were an efficient tool for identifying T cells recognizing commonly reported viral epitopes. We then construct SCT libraries to capture SARS-CoV-2 specific CD8+ T cells from COVID-19 participants and healthy donors. The immunogenicity of these epitopes is validated by functional assays of T cells with cloned TCRs captured using SCT libraries. These technologies should enable the rapid analyses of peptide-based T cell responses across several contexts, including autoimmunity, cancer, or infectious disease.

Entropic analysis of antigen-specific CDR3 domains identifies essential binding motifs shared by CDR3s with different antigen specificities.

Antigen-specific T cell receptor (TCR) sequences can have prognostic, predictive, and therapeutic value, but decoding the specificity of TCR recognition remains challenging. Unlike DNA strands that base pair, TCRs bind to their targets with different orientations and different lengths, which complicates comparisons. We present scanning parametrized by normalized TCR length (SPAN-TCR) to analyze antigen-specific TCR CDR3 sequences and identify patterns driving TCR-pMHC specificity. Using entropic analysis, SPAN-TCR identifies 2-mer motifs that decrease the diversity (entropy) of CDR3s. These motifs are the most common patterns that can predict CDR3 composition, and we identify "essential" motifs that decrease entropy in the same CDR3 α or ß chain containing the 2-mer, and "super-essential" motifs that decrease entropy in both chains. Molecular dynamics analysis further suggests that these motifs may play important roles in binding. We then employ SPAN-TCR to resolve similarities in TCR repertoires against different antigens using public databases of TCR sequences.

Large libraries of single-chain trimer peptide-MHCs enable rapid antigen-specific CD8+ T cell discovery and analysis.

CD8 + cytotoxic T cell responses against viral infection represent a major element of the adaptive immune response. We describe the development of a peptide antigen - major histompatibility complex (pMHC) library representing the full SARS-CoV-2 viral proteome, and comprised of 634 pMHC multimers representing the A*02.01, A*24.02, and B*07.02 HLA alleles, as well as specific antigens associated with the cytomegalovirus (CMV). These libraries were used to capture non-expanded CD8 + T cells from blood samples collected from 64 infected individuals, and then analyzed using single cell RNA-seq. The discovery and characterization of antigen-specific CD8 + T cell clonotypes typically involves the labor-intensive synthesis and construction of peptide-MHC tetramers. We adapted single-chain trimer (SCT) technologies into a high throughput platform for pMHC library generation, showing that hundreds can be rapidly prepared across multiple Class I HLA alleles. We used this platform to explore the impact of peptide and SCT template mutations on protein expression yield, thermal stability, and functionality. SCT libraries were an efficient tool for identifying T cells recognizing commonly reported viral epitopes. We then constructed SCT libraries designed to capture SARS-CoV-2 specific CD8 + T cells from COVID-19 participants and healthy donors. The immunogenicity of these epitopes was validated by functional assays of T cells with cloned TCRs captured using SCT libraries. These technologies should enable the rapid analyses of peptide-based T cell responses across several contexts, including autoimmunity, cancer, or infectious disease.

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.

Multiple early factors anticipate post-acute COVID-19 sequelae.

Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific auto-antibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes, exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time, leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.

HLA-A∗02:01 restricted T cell receptors against the highly conserved SARS-CoV-2 polymerase cross-react with human coronaviruses.

Cross-reactivity and direct killing of target cells remain underexplored for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-specific CD8+ T cells. Isolation of T cell receptors (TCRs) and overexpression in allogeneic cells allows for extensive T cell reactivity profiling. We identify SARS-CoV-2 RNA-dependent RNA polymerase (RdRp/NSP12) as highly conserved, likely due to its critical role in the virus life cycle. We perform single-cell TCRαß sequencing in human leukocyte antigen (HLA)-A∗02:01-restricted, RdRp-specific T cells from SARS-CoV-2-unexposed individuals. Human T cells expressing these TCRαß constructs kill target cell lines engineered to express full-length RdRp. Three TCR constructs recognize homologous epitopes from common cold coronaviruses, indicating CD8+ T cells can recognize evolutionarily diverse coronaviruses. Analysis of individual TCR clones may help define vaccine epitopes that can induce long-term immunity against SARS-CoV-2 and other coronaviruses.

Angiotensin II receptor I auto-antibodies following SARS-CoV-2 infection.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is associated with endothelial activation and coagulopathy, which may be related to pre-existing or infection-induced pro-thrombotic autoantibodies such as those targeting angiotensin II type I receptor (AT1R-Ab). METHODS: We compared prevalence and levels of AT1R-Ab in COVID-19 cases with mild or severe disease to age and sex matched negative controls utilizing multivariate logistic and quantile regression adjusted for comorbidities including hypertension, diabetes, and heart disease. RESULTS: There were trends toward increased prevalence (50% vs. 33%, p = 0.1) and level of AT1R-Ab (median 9.8 vs. 6.1 U/mL, p = 0.06) in all cases versus controls. When considered by COVID-19 disease severity, there was a trend toward increased prevalence of AT1R-Ab (55% vs. 31%, p = 0.07), as well as significantly higher AT1R-Ab levels (median 10.7 vs. 5.9 U/mL, p = 0.03) amongst individuals with mild COVID-19 versus matched controls. In contrast, the prevalence (42% vs. 37%, p = 0.9) and level (both medians 6.7 U/mL, p = 0.9) of AT1R-Ab amongst those with severe COVID-19 did not differ from matched controls. CONCLUSIONS: These findings support an association between COVID-19 and AT1R-Ab, emphasizing that vascular pathology may be present in individuals with mild COVID-19 as well as those with severe disease.

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.

Sensitive Detection and Analysis of Neoantigen-Specific T Cell Populations from Tumors and Blood.

Neoantigen-specific T cells are increasingly viewed as important immunotherapy effectors, but physically isolating these rare cell populations is challenging. Here, we describe a sensitive method for the enumeration and isolation of neoantigen-specific CD8+ T cells from small samples of patient tumor or blood. The method relies on magnetic nanoparticles that present neoantigen-loaded major histocompatibility complex (MHC) tetramers at high avidity by barcoded DNA linkers. The magnetic particles provide a convenient handle to isolate the desired cell populations, and the barcoded DNA enables multiplexed analysis. The method exhibits superior recovery of antigen-specific T cell populations relative to literature approaches. We applied the method to profile neoantigen-specific T cell populations in the tumor and blood of patients with metastatic melanoma over the course of anti-PD1 checkpoint inhibitor therapy. We show that the method has value for monitoring clinical responses to cancer immunotherapy and might help guide the development of personalized mutational neoantigen-specific T cell therapies and cancer vaccines.

MATE-Seq: microfluidic antigen-TCR engagement sequencing.

Adaptive immunity is based on peptide antigen recognition. Our ability to harness the immune system for therapeutic gain relies on the discovery of the T cell receptor (TCR) genes that selectively target antigens from infections, mutated proteins, and foreign agents. Here we present a method that selectively labels peptide antigen-specific CD8+ T cells using magnetic nanoparticles functionalized with peptide-MHC tetramers, isolates these specific cells within an integrated microfluidic device, and directly amplifies the TCR genes for sequencing. Critically, the identity of the peptide recognized by the TCR is preserved, providing the link between peptide and gene. The platform requires inputs on the order of just 100 000 CD8+ T cells, can be multiplexed for simultaneous analysis of multiple peptides, and performs sorting and isolation on chip. We demonstrate 1000-fold sensitivity enhancement of detecting antigen-specific TCRs relative to bulk analysis and simultaneous capture of two virus antigen-specific TCRs from a population of T cells.