Dissecting the Distinct Tumor Microenvironments of HRD and HRP Ovarian Cancer: Implications for Targeted Therapies to Overcome PARPi Resistance in HRD Tumors and Refractoriness in HRP Tumors.

High-grade serous tubo-ovarian cancer (HGSTOC) is an aggressive gynecological malignancy including homologous recombination deficient (HRD) and homologous recombination proficient (HRP) groups. Despite the therapeutic potential of poly (ADP-ribose) polymerase inhibitors (PARPis) and anti-PDCD1 antibodies, acquired resistance in HRD and suboptimal response in HRP patients necessitate more precise treatment. Herein, single-cell RNA and single-cell T-cell receptor sequencing on 5 HRD and 3 HRP tumors are performed to decipher the heterogeneous tumor immune microenvironment (TIME), along with multiplex immunohistochemistry staining and animal experiments for validation. HRD tumors are enriched with immunogenic epithelial cells, FGFR1+PDGFRß+ myCAFs, M1 macrophages, tumor reactive CD8+/CD4+ Tregs, whereas HRP tumors are enriched with HDAC1-expressing epithelial cells, indolent CAFs, M2 macrophages, and bystander CD4+/CD8+ T cells. Significantly, customized therapies are proposed. For HRD patients, targeting FGFR1+PDGFRß+ myCAFs via tyrosine kinase inhibitors, targeting Tregs via anti-CCR8 antibodies/TNFRSF4 stimulation, and targeting CXCL13+ exhausted T cells by blocking PDCD1/CTLA-4/LAG-3/TIGIT are proposed. For HRP patients, targeting indolent CAFs, targeting M2 macrophages via CSF-1/CSF-1R inhibitors, targeting bystander T cells via tumor vaccines, and targeting epithelial cells via HDAC inhibitors. The study provides comprehensive insights into HRD and HRP TIME and tailored therapeutic approaches, addressing the challenges of PARPi-resistant HRD and refractory HRP tumors.

Single-cell Atlas of Penile Cancer Reveals TP53 Mutations as a Driver of an Aggressive Phenotype, Irrespective of Human Papillomavirus Status, and Provides Clues for Treatment Personalization.

BACKGROUND AND OBJECTIVE: TP53 loss-of-function (TP53LOF) mutations might be a driver of poor prognosis and chemoresistance in both human papillomavirus (HPV)-independent (HPV-) and HPV-associated (HPV+) penile squamous cell carcinoma (PSCC). Here, we aim to describe transcriptomic differences in the PSCC microenvironment stratified by TP53LOF and HPV status. METHODS: We used single-cell RNA sequencing (scRNA-seq) and T-cell receptor sequencing to obtain a comprehensive atlas of the cellular architecture of PSCC. TP53LOF and HPV status were determined by targeted next-generation sequencing and sequencing HPV-DNA reads. Six HPV+ TP53 wild type (WT), six HPV- TP53WT, and four TP53LOF PSCC samples and six controls were included. Immunohistochemistry and hematoxylin-eosin confirmed the morphological context of the observed signatures. Prognostic differences between patient groups were validated in 541 PSCC patients using Kaplan-Meier survival estimates. KEY FINDINGS AND LIMITATIONS: Patients with aberrant p53 staining fare much worse than patients with either HPV- or HPV+ tumors and WT p53 expression. Using scRNA-seq, we revealed 65 cell subtypes within 83 682 cells. TP53LOF tumors exhibit a partial epithelial-to-mesenchymal transition, immune-excluded, angiogenic, and morphologically invasive environment, underlying their aggressive phenotype. HPV- TP53WT tumors show stemness and immune exhaustion. HPV+ TP53WT tumors mirror normal epithelial maturation with upregulation of antibody-drug-conjugate targets and activation of innate immunity. Inherent to the scRNA-seq analysis, low sample size is a limitation and validation of signatures in large PSCC cohorts is needed. CONCLUSIONS AND CLINICAL IMPLICATIONS: This first scRNA-seq atlas offers unprecedented in-depth insights into PSCC biology underlying prognostic differences based on TP53 and HPV status. Our findings provide clues for testing novel biomarker-driven therapies in PSCC. PATIENT SUMMARY: Here, we analyzed tissues of penile cancer at the level of individual cells, which helps us understand why patients who harbor a deactivating mutation in the TP53 gene do much worse than patients lacking such a mutation. Such an analysis may help us tailor future therapies based on TP53 gene mutations and human papillomavirus status of these tumors.

Thymosin α1 modulated the immune landscape of COVID-19 patients revealed by single-cell RNA and TCR sequencing.

BACKGROUND: The Coronavirus disease-19 (COVID-19) pandemic has posed a serious threat to global health. Thymosin α1 (Tα1) was considered to be applied in COVID-19 therapy. However, the data remains limited. METHODS: Participants with or without Tα1 treatment were recruited. Single cell RNA-sequencing (scRNA-seq) and T cell receptor-sequencing (TCR-seq) of the peripheral blood mononuclear cell (PBMC) samples were done to analyze immune features. The differential expression analysis and functional enrichment analysis were performed to explore the mechanism of Tα1 therapy. RESULTS: 33 symptomatic SARS-CoV-2-infected individuals (COV) and 11 healthy controls (HC) were enrolled in this study. The proportion of CD3+ KLRD1+ NKT, TBX21+ CD8+ NKT was observed to increase in COVID-19 patients with Tα1 treatment (COVT) than those without Tα1 (COV) (p = 0.024; p = 0.010). These two clusters were also significantly higher in Health controls with Tα1 treatment (HCT) than those without Tα1 (HC) (p = 0.016; p = 0.031). Besides, a series of genes and pathways related to immune responses were significantly higher enriched in Tα1 groups TBX21+ CD8+ NKT, such as KLRB1, PRF1, natural killer cell-mediated cytotoxicity pathway, chemokine signaling pathway, JAK-STAT signaling pathway. The increased TRBV9-TRBJ1-1 pair existed in both HCs and COVID-19 patients after Tα1 treatment. 1389 common complementarity determining region 3 nucleotides (CDR 3 nt) were found in COV and HC, while 0 CDR 3 nt was common in COVT and HCT. CONCLUSIONS: Tα1 increased CD3+ KLRD1+ NKT, TBX21+ CD8+ NKT cell proportion and stimulated the diversity of TCR clones in COVT and HCT. And Tα1 could regulate the expression of genes associated with NKT activation or cytotoxicity to promote NKT cells. These data support the use of Tα1 in COVID-19 patients.

Host-specific differences in top-expanded TCR clonotypes correlate with divergent outcomes of anti-PD-L1 treatment in responders versus non-responders.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment; however, the responses to ICI treatment are highly variable in different individuals and the underlying mechanisms remain poorly understood. Here, we employed a mouse squamous cell carcinoma (SCC) model where tumor-bearing recipients diverged into responders (R) versus non-responders (NR) upon anti-PD-L1 treatment. We performed in-depth TCRß sequencing with immunoSEQ platform to delineate the differences in CD8 tumor-infiltrating lymphocytes (TILs). We found that R and NR CD8 TILs both exhibited evidence of clonal expansion, suggesting activation regardless of response status. We detected no differences in clonal expansion or clonal diversity indexes between R vs. NR. However, the top expanded (>1%) TCRß clonotypes appeared to be mutually exclusive between R and NR CD8 TILs, showing a preferential expansion of distinct TCRß clonotypes in response to the same SCC tumor in R vs. NR. Notably, the mutual exclusivity of TCR clonotypes in R vs. NR was only observed when top TCRß clonotypes were counted, because such top-expanded clonotypes are present in the opposite outcome group at a much lower frequency. Many TCRß sequences were detected in only one recipient at a high frequency, implicating highly individualized anti-tumor immune responses. We conclude that differences in the clonal frequency of top TCR clonotypes between R and NR CD8 TILs may be one of the factors underlying differential anti-PD-L1 responses. This notion may offer a novel explanation for variable ICI responses in different individuals, which may substantially impact the development of new strategies for personalized cancer immunotherapy.

Immune phenotypes and checkpoint molecule expression of clonally expanded lymph node-infiltrating T cells in classical Hodgkin lymphoma.

Lymph node-infiltrating T cells have been of particular interest in classical Hodgkin lymphoma (cHL). High rates of complete therapeutic responses to antibody-mediated immune checkpoint blockade, even in relapsed/refractory patients, suggest the existence of a T cell-dominated, antigen-experienced, functionally inhibited and lymphoma-directed immune microenvironment. We asked whether clonally expanded T cells (1) were detectable in cHL lymph nodes, (2) showed characteristic immune phenotypes, and (3) were inhibited by immune checkpoint molecule expression. We applied high-dimensional FACS index sorting and single cell T cell receptor αß sequencing to lymph node-infiltrating T cells from 10 treatment-naïve patients. T cells were predominantly CD4+ and showed memory differentiation. Expression of classical immune checkpoint molecules (CTLA-4, PD-1, TIM-3) was generally low (< 12.0% of T cells) and not different between CD4+ and CD8+ T cells. Degrees of clonal T cell expansion varied between patients (range: 1-18 expanded clones per patient) and was almost exclusively restricted to CD8+ T cells. Clonally expanded T cells showed non-naïve phenotypes and low checkpoint molecule expression similar to non-expanded T cells. Our data suggest that the therapeutic effects of immune checkpoint blockade require mechanisms in addition to dis-inhibition of pre-existing lymphoma-directed T cell responses. Future studies on immune checkpoint blockade-associated effects will identify molecular T cell targets, address dynamic aspects of cell compositions over time, and extend their focus beyond lymph node-infiltrating T cells.

Divergent outcomes of anti-PD-L1 treatment coupled with host-intrinsic differences in TCR repertoire and distinct T cell activation states in responding versus non-responding tumors.

Differential responses to immune checkpoint inhibitors (ICI) may be attributed to tumor-intrinsic factors or environmental cues; however, these mechanisms cannot fully explain the variable ICI responses in different individuals. Here, we investigate the potential contribution of immunological heterogeneity with a focus on differences in T-cell receptor (TCR) repertoire to ICI responses, which has not been defined previously. To reveal additional factors underlying heterogeneous responses to ICI, we employed a squamous cell carcinoma (SCC) mouse model in which tumor-bearing recipients unambiguously diverged into responders (R) or non-responders (NR) upon anti-PD-L1 treatment. Treatment efficacy absolutely required CD8 T-cells and correlated positively with effector functions of CD8 tumor-infiltrating lymphocytes (TILs). We showed that TCR repertoires exhibited a similar magnitude of clonal expansion in R vs. NR CD8 TILs. However, the top expanded TCR clonotypes appeared to be mutually exclusive between R and NR CD8 TILs, which also occurred in a recipient-specific manner, demonstrating preferential expansion of distinct TCR clonotypes against the same SCC tumor. Unexpectedly, R vs. NR CD8 TILs reached all activation clusters and did not exhibit substantial global differences in transcriptomes. By linking single-cell transcriptomic data with unique TCR clonotypes, CD8 TILs harboring top TCR clonotypes were found to occupy distinct activation clusters and upregulate genes favoring anti-tumor immunity to different extents in R vs. NR. We conclude that stochastic differences in CD8 TIL TCR repertoire and distinct activation states of top TCR clonotypes may contribute to differential anti-PD-L1 responses. Our study suggests that host-intrinsic immunological heterogeneity may offer a new explanation for differential ICI responses in different individuals, which could impact on strategies for personalized cancer immunotherapy.

Revealing the heterogeneity of CD4+ T cells through single-cell transcriptomics.

Single-cell RNA sequencing (scRNA-seq) offers the ability to resolve whole transcriptomes of single cells with substantial throughput, and it has revolutionized studies of gene expression. The transcriptional resolution available can uncover fine structures of biologic heterogeneity that are manifest among cell populations. Here, we review the applications of scRNA-seq to profile the phenotypes and clonotypes of CD4+ T cells. First, we describe challenges inherent to scRNA-seq that are important for analysis of CD4+ T cells, as well as the technical solutions that are emerging to address these challenges. We then consider major themes of the application of scRNA-seq to CD4+ T cells, including investigation of CD4+ T-cell heterogeneity in model systems, analysis of populations from the peripheral blood, and the profiling of tissue-resident populations. We place emphasis on capabilities unique to scRNA-seq, such as the ability to obtain paired T-cell receptor and transcriptome information from single T cells and the potential to elucidate interactions between CD4+ T cells and other cells in their environment. Finally, we conclude by considering future areas of technologic advancement and innovation through which scRNA-seq may further shape our understanding of the roles of CD4+ T cells in health and disease.

AMPLIFY-NEOVAC: a randomized, 3-arm multicenter phase I trial to assess safety, tolerability and immunogenicity of IDH1-vac combined with an immune checkpoint inhibitor targeting programmed death-ligand 1 in isocitrate dehydrogenase 1 mutant gliomas.

INTRODUCTION: Isocitrate dehydrogenase (IDH) mutations are disease-defining mutations in IDH-mutant astrocytomas and IDH-mutant and 1p/19q-codeleted oligodendrogliomas. In more than 80% of these tumors, point mutations in IDH type 1 (IDH1) lead to expression of the tumor-specific protein IDH1R132H. IDH1R132H harbors a major histocompatibility complex class II (MHCII)-restricted neoantigen that was safely and successfully targeted in a first-in human clinical phase 1 trial evaluating an IDH1R132H 20-mer peptide vaccine (IDH1-vac) in newly diagnosed astrocytomas concomitant to standard of care (SOC). METHODS: AMPLIFY-NEOVAC is a randomized, 3-arm, window-of-opportunity, multicenter national phase 1 trial to assess safety, tolerability and immunogenicity of IDH1-vac combined with avelumab (AVE), an immune checkpoint inhibitor (ICI) targeting programmed death-ligand 1 (PD-L1). The target population includes patients with resectable IDH1R132H-mutant recurrent astrocytoma or oligodendroglioma after SOC. Neoadjuvant and adjuvant immunotherapy will be administered to 48 evaluable patients. In arm 1, 12 patients will receive IDH1-vac; in arm 2, 12 patients will receive the combination of IDH1-vac and AVE, and in arm 3, 24 patients will receive AVE only. Until disease progression according to immunotherapy response assessment for neuro-oncology (iRANO) criteria, treatment will be administered over a period of maximum 43 weeks (primary treatment phase) followed by facultative maintenance treatment. PERSPECTIVE: IDH1R132H 20-mer peptide is a shared clonal driver mutation-derived neoepitope in diffuse gliomas. IDH1-vac safely targets IDH1R132H in newly diagnosed astrocytomas. AMPLIFY-NEOVAC aims at (1) demonstrating safety of enhanced peripheral IDH1-vac-induced T cell responses by combined therapy with AVE compared to IDH1-vac only and (2) investigating intra-glioma abundance and phenotypes of IDH1-vac induced T cells in exploratory post-treatment tissue analyses. In an exploratory analysis, both will be correlated with clinical outcome. TRIAL REGISTRATION: NCT03893903.

TCRpower: quantifying the detection power of T-cell receptor sequencing with a novel computational pipeline calibrated by spike-in sequences.

T-cell receptor (TCR) sequencing has enabled the development of innovative diagnostic tests for cancers, autoimmune diseases and other applications. However, the rarity of many T-cell clonotypes presents a detection challenge, which may lead to misdiagnosis if diagnostically relevant TCRs remain undetected. To address this issue, we developed TCRpower, a novel computational pipeline for quantifying the statistical detection power of TCR sequencing methods. TCRpower calculates the probability of detecting a TCR sequence as a function of several key parameters: in-vivo TCR frequency, T-cell sample count, read sequencing depth and read cutoff. To calibrate TCRpower, we selected unique TCRs of 45 T-cell clones (TCCs) as spike-in TCRs. We sequenced the spike-in TCRs from TCCs, together with TCRs from peripheral blood, using a 5' RACE protocol. The 45 spike-in TCRs covered a wide range of sample frequencies, ranging from 5 per 100 to 1 per 1 million. The resulting spike-in TCR read counts and ground truth frequencies allowed us to calibrate TCRpower. In our TCR sequencing data, we observed a consistent linear relationship between sample and sequencing read frequencies. We were also able to reliably detect spike-in TCRs with frequencies as low as one per million. By implementing an optimized read cutoff, we eliminated most of the falsely detected sequences in our data (TCR α-chain 99.0% and TCR ß-chain 92.4%), thereby improving diagnostic specificity. TCRpower is publicly available and can be used to optimize future TCR sequencing experiments, and thereby enable reliable detection of disease-relevant TCRs for diagnostic applications.

T cell receptor repertoire sequencing reveals chemotherapy-driven clonal expansion in colorectal liver metastases.

BACKGROUND: Colorectal liver metastasis (CLM) is a leading cause of colorectal cancer mortality, and the response to immune checkpoint inhibition (ICI) in microsatellite-stable CRC has been disappointing. Administration of cytotoxic chemotherapy may cause increased density of tumor-infiltrating T cells, which has been associated with improved response to ICI. This study aimed to quantify and characterize T-cell infiltration in CLM using T-cell receptor (TCR) repertoire sequencing. Eighty-five resected CLMs from patients included in the Oslo CoMet study were subjected to TCR repertoire sequencing. Thirty-five and 15 patients had received neoadjuvant chemotherapy (NACT) within a short or long interval, respectively, prior to resection, while 35 patients had not been exposed to NACT. T-cell fractions were calculated, repertoire clonality was analyzed based on Hill evenness curves, and TCR sequence convergence was assessed using network analysis. RESULTS: Increased T-cell fractions (10.6% vs. 6.3%) were detected in CLMs exposed to NACT within a short interval prior to resection, while modestly increased clonality was observed in NACT-exposed tumors independently of the timing of NACT administration and surgery. While private clones made up >90% of detected clones, network connectivity analysis revealed that public clones contributed the majority of TCR sequence convergence. CONCLUSIONS: TCR repertoire sequencing can be used to quantify T-cell infiltration and clonality in clinical samples. This study provides evidence to support chemotherapy-driven T-cell clonal expansion in CLM in a clinical context.

T-Cell Receptor Profiling and Prognosis After Stereotactic Body Radiation Therapy For Stage I Non-Small-Cell Lung Cancer.

Radiotherapy is known to influence immune function, including T cell receptor (TCR) repertoire. We evaluated the TCR repertoire before and after stereotactic body radiotherapy (SBRT) for stage I non-small-cell lung cancer (NSCLC) and explored correlations between TCR indexes and distant failure after SBRT. TCR repertoires were analyzed in peripheral blood mononuclear cells (PBMCs) collected before and after SBRT from 19 patients. TCR combinational diversity in V and J genes was assessed with multiplex PCR of genomic DNA from PBMCs and tested for associations with clinical response. All patients received definitive SBRT to a biologically effective dose of >=100 Gy. The number of unique TCR clones was decreased after SBRT versus before, but clonality and the Shannon Entropy did not change. Four patients (21%) developed distant metastases after SBRT (median 7 months); those patients had lower Shannon Entropy in post-SBRT samples than patients without metastasis. Patients with a low change in Shannon Entropy from before to after SBRT [(post-SBRT Shannon Entropy minus baseline Shannon)/(baseline Shannon) * 100] had poorer metastasis-free survival than those with high change in Shannon Entropy (P<0.001). Frequencies in V/J gene fragment expression in the TCR ß chain were also different for patients with or without metastases (two V fragments in baseline samples and 2 J and 9 V fragments in post-treatment samples). This comprehensive analysis of immune status before and after SBRT showed that quantitative assessments of TCRs can help evaluate prognosis in early-stage NSCLC.

Dynamic changes in the T cell receptor repertoire during treatment with radiotherapy combined with an immune checkpoint inhibitor.

Previous studies have indicated a synergistic effect between radiotherapy and immunotherapy. A better understanding of how this combination affects the immune system can help to clarify its role in the treatment of metastatic cancer. We performed T cell receptor (TCR) sequencing on 46 sequentially collected samples from 15 patients with stage IV non-small cell lung cancer, receiving stereotactic body radiotherapy combined with a programmed cell death ligand-1 (PD-L1) inhibitor. TCR repertoire diversity was assessed using Rényi diversity curves and the Shannon diversity index. TCR clones were tracked over time. We found decreasing or stable diversity in the best responders, and an increase in diversity at progression in patients with an initial response. Expansion of TCR clones was more often seen in responders. Several patients also developed new clones of high abundance. This seemed to be more related to radiotherapy than to immune checkpoint blockade. In summary, we observed similar dynamics in the TCR repertoire as have been described with immunotherapy alone. In addition, the occurrence of new unique clones of high abundance after radiotherapy may indicate that radiotherapy functions as a personalized cancer vaccine.

iCAT: diagnostic assessment tool of immunological history using high-throughput T-cell receptor sequencing.

The pathogen exposure history of an individual is recorded in their T-cell repertoire and can be accessed through the study of T-cell receptors (TCRs) if the tools to identify them were available. For each T-cell, the TCR loci undergoes genetic rearrangement that creates a unique DNA sequence. In theory these unique sequences can be used as biomarkers for tracking T-cell responses and cataloging immunological history. We developed the immune Cell Analysis Tool (iCAT), an R software package that analyzes TCR sequencing data from exposed (positive) and unexposed (negative) samples to identify TCR sequences statistically associated with positive samples. The presence and absence of associated sequences in samples trains a classifier to diagnose pathogen-specific exposure. We demonstrate the high accuracy of iCAT by testing on three TCR sequencing datasets. First, iCAT successfully diagnosed smallpox vaccinated versus naïve samples in an independent cohort of mice with 95% accuracy. Second, iCAT displayed 100% accuracy classifying naïve and monkeypox vaccinated mice.  Finally, we demonstrate the use of iCAT on human samples before and after exposure to SARS-CoV-2, the virus behind the COVID-19 global pandemic. We were able to correctly classify the exposed samples with perfect accuracy. These experimental results show that iCAT capitalizes on the power of TCR sequencing to simplify infection diagnostics. iCAT provides the option of a graphical, user-friendly interface on top of usual R interface allowing it to reach a wider audience.

Decreased Treg Cell and TCR Expansion Are Involved in Long-Lasting Graves' Disease.

Graves' disease (GD) is a T cell-mediated organ-specific autoimmune disorder. GD patients who have taken anti-thyroid drugs (ATDs) for more than 5 years with positive anti-thyroid stimulating hormone receptor autoantibodies value were defined as persistent GD (pGD). To develop novel immunotherapies for pGD, we investigated the role of T cells in the long-lasting phase of GD. Clinical characteristics were compared between the pGD and newly diagnosed GD (nGD) (N = 20 respectively). Flow cytometric analysis was utilized to determine the proportions of Treg and Th17 cells (pGD, N = 12; nGD, N = 14). T cell receptor sequencing (TCR-seq) and RNA sequencing (RNA-seq) were also performed (pGD, N = 13; nGD, N = 20). Flow cytometric analysis identified lower proportions of Th17 and Treg cells in pGD than in nGD (P = 0.0306 and P = 0.0223). TCR-seq analysis revealed a lower diversity (P = 0.0025) in pGD. Specifically, marked clonal expansion, represented by an increased percentage of top V-J recombination, was observed in pGD patients. Interestingly, pGD patients showed more public T cell clonotypes than nGD patients (2,741 versus 966). Meanwhile, RNA-seq analysis revealed upregulation of the inflammation and chemotaxis pathways in pGD. Specifically, the expression of pro-inflammatory and chemotactic genes (IL1B, IL13, IL8, and CCL4) was increased in pGD, whereas Th17 and Treg cells associated genes (RORC, CARD9, STAT5A, and SATB1) decreased in pGD. Additionally, TCR diversity was negatively correlated with the expression of pro-inflammatory or chemotactic genes (FASLG, IL18R1, CCL24, and CCL14). These results indicated that Treg dysregulation and the expansion of pathogenic T cell clones might be involved in the long-lasting phase of GD via upregulating chemotaxis or inflammation response. To improve the treatment of pGD patients, ATDs combined therapies, especially those aimed at improving Treg cell frequencies or targeting specific expanded pathogenic TCR clones, are worth exploring in the future.

COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas.

A dysfunctional immune response in coronavirus disease 2019 (COVID-19) patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells. The large dataset enabled us to identify that different peripheral immune subtype changes are associated with distinct clinical features, including age, sex, severity, and disease stages of COVID-19. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was found in diverse epithelial and immune cell types, accompanied by dramatic transcriptomic changes within virus-positive cells. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis of and developing effective therapeutic strategies for COVID-19.

Utility of flow cytometry and gene rearrangement analysis in tissue and blood of patients with suspected cutaneous T­cell lymphoma.

Cutaneous T­cell lymphoma (CTCL) is difficult to diagnose at an early stage. Current diagnostic tools include clinical examination, histomorphologic analysis, immunohistochemistry, flow cytometry of peripheral blood and/or lesional tissue, and evaluation of T­cell receptor (TCR) clonality by gene rearrangement analysis (TCRGR). Advances in genomic sequencing, including high­throughput sequencing (HTS), can be used to identify specific clones of rearranged TCR genes. Even with all of these tools, CTCL can take as long as a decade to definitively diagnose, potentially delaying treatment options and causing patient anxiety. This study aimed to evaluate the performance of the various ancillary testing modalities used to diagnose early­stage CTCL. In a subset of patients the performance of HTS was compared to flow cytometry and conventional TCRGR analysis via polymerase chain reaction (PCR). Fifty­five patients, with a total of 68 skin biopsies and peripheral blood draws, were evaluated using flow cytometry, PCR­TCRGR, and HTS­TCRGR to determine the sensitivity and specificity of each ancillary test. In tissue biopsies, flow cytometry (64%), PCR (71%) and HTS (69%) shared similar sensitivities; flow cytometry had the highest specificity (93%), followed by HTS (86%) and PCR (76.9%). However, flow cytometry and PCR had insufficient DNA quantities in 29 and 15% of the specimens, respectively. Peripheral blood testing was less sensitive than tissue testing (flow cytometry 14%, PCR 41%, HTS 33%); in peripheral blood, HTS was the most specific test (flow cytometry, 70%; PCR, 62.5%; and HTS, 100%). HTS is a highly specific molecular test for identifying CTCL in peripheral blood and skin biopsy specimens; however, our findings suggest a need for a continued search for more sensitive tests for early­stage CTCL.

The human T-cell receptor repertoire in health and disease and potential for omics integration.

The adaptive immune system arose 600 million years ago in a cold-blooded fish. Over countless generations, our antecedents tuned the function of the T-cell receptor (TCR). The TCR system is arguably the most complex known to science. The TCR evolved hypervariability to fight the hypervariability of pathogens and cancers that look to consume our resources. This review describes the genetics and architecture of the human TCR and highlights surprising new discoveries over the past years that have disproved very old dogmas. The standardization of TCR sequencing data is discussed in preparation for big data bioinformatics and predictive analysis. We next catalogue new signatures and phenomenon discovered by TCR next generation sequencing (NGS) in health and disease and work that remain to be done in this space. Finally, we discuss how TCR NGS can add to immunodiagnostics and integrate with other omics platforms for both a deeper understanding of TCR biology and its use in the clinical setting.

Impact of T Cell Repertoire Diversity on Mortality Following Cord Blood Transplantation.

INTRODUCTION: Cord blood transplantation (CBT) recipients are at increased risk of mortality due to delayed immune recovery (IR). Prior studies in CBT patients have shown that recovery of absolute lymphocyte count is predictive of survival after transplant. However, there are no data on the association of T-cell receptor (TCR) and clinical outcomes after CBT. Here we retrospectively performed TCR beta chain sequencing on peripheral blood (PB) samples of 34 CBT patients. METHODS: All patients received a total body irradiation based conditioning regimen and cyclosporine and MMF were used for graft versus host disease (GvHD) prophylaxis. PB was collected pretransplant on days 28, 56, 80, 180, and 1-year posttransplant for retrospective analysis of IR utilizing high-throughput sequencing of TCRß rearrangements from genomic DNA extracted from PB mononuclear cells. To test the association between TCR repertoire diversity and patient outcomes, we conducted a permutation test on median TCR repertoire diversity for patients who died within the first year posttransplant versus those who survived. RESULTS: Median age was 27 (range 1-58 years) and most of the patients (n = 27) had acute leukemias. There were 15 deaths occurring between 34 to 335 days after transplant. Seven deaths were due to relapse. Rapid turnover of T cell clones was observed at each time point, with TCR repertoires stabilizing by 1-year posttransplant. TCR diversity values at day 100 for patients who died between 100 and 365 days posttransplant were significantly lower than those of the surviving patients (p = 0.01). CONCLUSIONS: Using a fast high-throughput TCR sequencing assay we have demonstrated that high TCR diversity is associated with better patient outcomes following CBT. Importantly, this assay is easily performed on posttransplant PB samples, even as early as day 28 posttransplant, making it an excellent candidate for early identification of patients at high risk of death.