T-cell receptor profiling in cancer

A20 haploinsufficiency disturbs immune homeostasis and drives the transformation of lymphocytes with permissive antigen receptors

Genetic TNFAIP3 (A20) inactivation is a classical somatic lymphoma lesion and the genomic trait in haploinsufficiency of A20 (HA20). In a cohort of 34 patients with HA20, we show that heterozygous TNFAIP3 loss skews immune repertoires toward lymphocytes with classical self-reactive antigen receptors typically found in B and T cell lymphomas. This skewing was mediated by a feed-forward tumor necrosis factor (TNF)/A20/nuclear factor κB (NF-κB) loop that shaped pre-lymphoma transcriptome signatures in clonally expanded B (CD81, BACH2, and NEAT1) or T (GATA3, TOX, and PDCD1) cells. The skewing was reversed by anti-TNF treatment but could also progress to overt lymphoma. Analysis of conditional TNFAIP3 knock-out mice reproduced the wiring of the TNF/A20/NF-κB signaling axis with permissive antigen receptors and suggested a distinct regulation in B and T cells. Together, patients with the genetic disorder HA20 provide an exceptional window into A20/TNF/NF-κB-mediated control of immune homeostasis and early steps of lymphomagenesis that remain clinically unrecognized.

Assessing T-cell receptor clonality by next-generation sequencing in atypical cutaneous lymphoid infiltrates and cutaneous T-cell lymphoma: A scoping review

The diagnosis of cutaneous T-cell lymphoma (CTCL) remains challenging. Demonstration of a clonal T-cell population using T-cell receptor (TCR) gene rearrangement studies by next-generation sequencing (NGS) has been explored in several studies. This review summarizes the current literature on NGS-based sequencing methods for the assessment of TCR clonality in the evaluation of atypical cutaneous lymphoid infiltrates and CTCL on behalf of the American Society of Dermatopathology Appropriate Use Criteria Committee (lymphoproliferative subgroup). PubMed was searched for relevant articles, including CTCL and NGS, for clonality from 1967 to 2022. Thirteen studies were included in the analysis. The skin was the most commonly assayed compartment with TCR NGS. Sensitivity for TCR NGS in the skin ranged between 69% and 100%, compared to 44%-72% for polymerase chain reaction (PCR)-capillary electrophoresis. Specificity for TCR NGS in the skin ranged from 86% to 100%, compared to 77%-88% for PCR capillary electrophoresis. TCR NGS was also reported to have potential prognostic value in CTCL and can also be used to detect relapse and/or minimal residual disease after treatment.

The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood

T cells recognize tumor antigens and initiate an anticancer immune response in the very early stages of tumor development, and the antigen specificity of T cells is determined by the T-cell receptor (TCR). Therefore, monitoring changes in the TCR repertoire in peripheral blood may offer a strategy to detect various cancers at a relatively early stage. Here, we developed the deep learning framework iCanTCR to identify patients with cancer based on the TCR repertoire. The iCanTCR framework uses TCRβ sequences from an individual as an input and outputs the predicted cancer probability. The model was trained on over 2,000 publicly available TCR repertoires from 11 types of cancer and healthy controls. Analysis of several additional publicly available datasets validated the ability of iCanTCR to distinguish patients with cancer from noncancer individuals and demonstrated the capability of iCanTCR for the accurate classification of multiple cancers. Importantly, iCanTCR precisely identified individuals with early-stage cancer with an AUC of 86%. Altogether, this work provides a liquid biopsy approach to capture immune signals from peripheral blood for noninvasive cancer diagnosis.

SIGNIFICANCE

Development of a deep learning-based method for multicancer detection using the TCR repertoire in the peripheral blood establishes the potential of evaluating circulating immune signals for noninvasive early cancer detection.

Dynamics of The Γδtcr Repertoires During The Dedifferentiation Process and Pilot Implications for Immunotherapy of Thyroid Cancer

γδ T cells are evolutionarily conserved T lymphocytes that manifest unique antitumor efficacy independent of tumor mutation burden (TMB) and conventional human leukocyte antigen (HLA) recognition. However, the dynamic changes in their T cell receptor (TCR) repertoire during cancer progression and treatment courses remain unclear. Here, a comprehensive characterization of γδTCR repertoires are performed in thyroid cancers with divergent differentiation states through cross-sectional studies. The findings revealed a significant correlation between the differentiation states and TCR repertoire diversity. Notably, highly expanded clones are prominently enriched in γδ T cell compartment of dedifferentiated patients. Moreover, by longitudinal investigations of the γδ T cell response to various antitumor therapies, it is found that the emergence and expansion of the Vδ2neg subset may be potentially associated with favorable clinical outcomes after post-radiotherapeutic immunotherapy. These findings are further validated at single-cell resolution in both advanced thyroid cancer patients and a murine model, underlining the importance of further investigations into the role of γδTCR in cancer immunity and therapeutic strategies.

DeepLION2: deep multi-instance contrastive learning framework enhancing the prediction of cancer-associated T cell receptors by attention strategy on motifs

Introduction

T cell receptor (TCR) repertoires provide valuable insights into complex human diseases, including cancers. Recent advancements in immune sequencing technology have significantly improved our understanding of TCR repertoire. Some computational methods have been devised to identify cancer-associated TCRs and enable cancer detection using TCR sequencing data. However, the existing methods are often limited by their inadequate consideration of the correlations among TCRs within a repertoire, hindering the identification of crucial TCRs. Additionally, the sparsity of cancer-associated TCR distribution presents a challenge in accurate prediction.

Methods

To address these issues, we presented DeepLION2, an innovative deep multi-instance contrastive learning framework specifically designed to enhance cancer-associated TCR prediction. DeepLION2 leveraged content-based sparse self-attention, focusing on the top k related TCRs for each TCR, to effectively model inter-TCR correlations. Furthermore, it adopted a contrastive learning strategy for bootstrapping parameter updates of the attention matrix, preventing the model from fixating on non-cancer-associated TCRs.

Results

Extensive experimentation on diverse patient cohorts, encompassing over ten cancer types, demonstrated that DeepLION2 significantly outperformed current state-of-the-art methods in terms of accuracy, sensitivity, specificity, Matthews correlation coefficient, and area under the curve (AUC). Notably, DeepLION2 achieved impressive AUC values of 0.933, 0.880, and 0.763 on thyroid, lung, and gastrointestinal cancer cohorts, respectively. Furthermore, it effectively identified cancer-associated TCRs along with their key motifs, highlighting the amino acids that play a crucial role in TCR-peptide binding.

Conclusion

These compelling results underscore DeepLION2's potential for enhancing cancer detection and facilitating personalized cancer immunotherapy. DeepLION2 is publicly available on GitHub, at https://github.com/Bioinformatics7181/DeepLION2, for academic use only.

Immunosequencing applications in cutaneous T-cell lymphoma

Immunosequencing has emerged as a newer clinical test for assessment of T-cell clonality in the blood and skin of cutaneous T-cell lymphoma (CTCL) patients. Utilization of immunosequencing, also known as high-throughput sequencing of the T-cell receptor (HTS-TCR), enables identification and quantification of the precise genetic signature of dominant T-cell clones. Although immunosequencing is more sensitive than commonly used methods such as polymerase chain reaction (PCR) paired with capillary electrophoresis or flow cytometry, it remains underutilized for CTCL management. Nonetheless, incorporation of HTS-TCR in clinical practice offers distinct advantages compared to other molecular analyses that may improve diagnostic evaluation, prognostication, and disease monitoring in CTCL. The objective of this comprehensive review is to provide a thorough explanation of the application of immunosequencing in the context of CTCL. We describe the significance of T-cell clonality and the methods used to detect it, including a detailed comparison between PCR paired with capillary electrophoresis and HTS-TCR. The utilization of immunosequencing in the blood and skin of CTCL patients is discussed in depth, specifically outlining how HTS-TCR can assist in diagnosing CTCL, predicting outcomes, and tracking disease progression. Finally, we address the potential applications of immunosequencing in clinical management and research as well as the novel challenges it presents.

Integrated phenotyping of the anti-cancer immune response in HIV-associated hepatocellular carcinoma

Background & Aims

HIV-seropositivity shortens survival in patients with hepatocellular carcinoma (HCC). Although risk factors for HCC including HCV infection can influence T cell phenotype, it is unknown whether HIV can influence functional characteristics of the T cell infiltrate.

Methods

From the Liver Cancer in HIV biorepository, we derived 129 samples of transplanted (76%) or resected (20%) HCC in eight European and North American centres. We profiled intra- and peritumoural tissue to evaluate regulatory CD4+/FOXP3+ and immune-exhausted CD8+/PD1+ T cells in HIV+ (n = 66) and HIV- (n = 63) samples. We performed targeted transcriptomics and T-cell receptor sequencing in a restricted subset of samples evaluated in relationship with HIV status. We correlated immunopathologic features with patients' characteristics including markers of HIV infection.

Results

Of the 66 HIV+ patients, 83% were HCV coinfected with an undetectable HIV viral load (51%) and a median blood CD4+ cell count of 430 cells/mm³ (range 15-908). Patients who were HIV+ were compared with HIV- controls with similar staging characteristics including Barcelona Clinic Liver Cancer (BCLC) stage A-B (86% vs. 83%, p = 0.16), <3 nodules (90% vs. 83%, p = 0.3) and median alpha-foetoprotein values (10.9 vs. 12.8 ng/ml, p = 0.72). HIV+ samples had higher PD-L1 expression rates in tumour tissue (51% vs. 8% p <0.0001) and displayed denser intratumoural CD4+/FOXP3+ (p <0.0001), CD8+/PD1+ (p <0.0001), with lower total peritumoural CD4+ (p <0.0001) and higher peritumoural CD8+/PD1+ (p <0.0001). Gene set analysis revealed HIV+ cases to have evidence of dysregulated adaptive and innate immunity. Tumour-infiltrating lymphocyte clonality was not influenced by HIV status.

Conclusions

HIV-associated HCC harbours a profoundly immune-exhausted tumour microenvironment, warranting prospective testing of immunotherapy in this treatment-deprived patient population.

Impact and Implications

Hepatocellular carcinoma is a non-AIDS defining malignancy characterised by poor survival. The programmed cell death (PD-1) pathway governs antiviral and anticancer immune exhaustion and is a therapeutic target in HCC. This study highlights how HIV infection is associated with significantly higher PD-L1 expression in HCC cells and in the surrounding microenvironment, leading to changes in cytotoxic and regulatory T cell function and dysregulation of proinflammatory pathways. Taken together, our results suggest dysfunctional T cell immunity as a mechanism of worse outcome in these patients and suggest clinical testing of checkpoint inhibitors in HIV-associated HCC.

A systematic and comprehensive analysis of T cell exhaustion related to therapy in lung adenocarcinoma tumor microenvironment

Background: T cell exhaustion (TEX) is an important immune escape mechanism, and an in-depth understanding of it can help improve cancer immunotherapy. However, the prognostic role of TEX in malignant lung adenocarcinoma (LUAD) remains unclear. Methods: Through TCGA and GEO datasets, we enrolled a total of 498 LUAD patients. The patients in TCGA-LUAD were unsupervised clustered into four clusters according to TEX signaling pathway. WGCNA analysis, survival random forest analysis and lasso regression analysis were used to select five differentially expressed genes among different clusters to construct a TEX risk model. The risk model was subsequently validated with GEO31210. By analyzing signaling pathways, immune cells and immune checkpoints using GSEA, GSVA and Cibersortx, the relationship between TEX risk score and these variables was evaluated. In addition, we further analyzed the expression of CCL20 at the level of single-cell RNA-seq and verified it in cell experiments. Results: According to TEX signaling pathway, people with better prognosis can be distinguished. The risk model constructed by CD109, CCL20, DKK1, TNS4, and TRIM29 genes could further accurately identify the population with poor prognosis. Subsequently, it was found that dendritic cells, CD44 and risk score were closely related. The final single-cell sequencing suggested that CCL2O is a potential therapeutic target of TEX, and the interaction between TEX and CD8 + T is closely related. Conclusion: The classification of T cell depletion plays a crucial role in the clinical decision-making of lung adenocarcinoma and needs to be further deepened.

Changes in the Immune Cell Repertoire for the Treatment of Malignant Melanoma

Immune checkpoint inhibitors (ICIs) have been used for the treatment of various types of cancers, including malignant melanoma. Mechanistic exploration of tumor immune responses is essential to improve the therapeutic efficacy of ICIs. Since tumor immune responses are based on antigen-specific immune responses, investigators have focused on T cell receptors (TCRs) and have analyzed changes in the TCR repertoire. The proliferation of T cell clones against tumor antigens is detected in patients who respond to treatment with ICIs. The proliferation of these T cell clones is observed within tumors as well as in the peripheral blood. Clonal proliferation has been detected not only in CD8-positive T cells but also in CD4-positive T cells, resident memory T cells, and B cells. Moreover, changes in the repertoire at an early stage of treatment seem to be useful for predicting the therapeutic efficacy of ICIs. Further analyses of the repertoire of immune cells are desirable to improve and predict the therapeutic efficacy of ICIs.

Personalized neoantigen vaccine NEO-PV-01 with chemotherapy and anti-PD-1 as first-line treatment for non-squamous non-small cell lung cancer

Neoantigens arising from mutations in tumor DNA provide targets for immune-based therapy. Here, we report the clinical and immune data from a Phase Ib clinical trial of a personalized neoantigen-vaccine NEO-PV-01 in combination with pemetrexed, carboplatin, and pembrolizumab as first-line therapy for advanced non-squamous non-small cell lung cancer (NSCLC). This analysis of 38 patients treated with the regimen demonstrated no treatment-related serious adverse events. Multiple parameters including baseline tumor immune infiltration and on-treatment circulating tumor DNA levels were highly correlated with clinical response. De novo neoantigen-specific CD4⁺ and CD8⁺ T cell responses were observed post-vaccination. Epitope spread to non-vaccinating neoantigens, including responses to KRAS G12C and G12V mutations, were detected post-vaccination. Neoantigen-specific CD4⁺ T cells generated post-vaccination revealed effector and cytotoxic phenotypes with increased CD4⁺ T cell infiltration in the post-vaccine tumor biopsy. Collectively, these data support the safety and immunogenicity of this regimen in advanced non-squamous NSCLC.

Temporal development of T cell receptor repertoires during childhood in health and disease

T cell receptor (TCR) sequences are exceptionally diverse and can now be comprehensively measured with next-generation sequencing technologies. However, a thorough investigation of longitudinal TCR repertoires throughout childhood in health and during development of a common childhood disease, type 1 diabetes (T1D), has not been undertaken. Here, we deep sequenced the TCR-β chain repertoires from longitudinal peripheral blood DNA samples at 4 time points beginning early in life (median age of 1.4 years) from children who progressed to T1D (n = 29) and age/sex-matched islet autoantibody-negative controls (n = 25). From 53 million TCR-β sequences, we show that the repertoire is extraordinarily diverse early in life and narrows with age independently of disease. We demonstrate the ability to identify specific TCR sequences, including those known to recognize influenza A and, separately, those specific for insulin and its precursor, preproinsulin. Insulin-reactive TCR-β sequences were more common and frequent in number as the disease progressed in those who developed T1D compared with genetically at risk nondiabetic children, and this was not the case for influenza-reactive sequences. As an independent validation, we sequenced and analyzed TCR-β repertoires from a cohort of new-onset T1D patients (n = 143), identifying the same preproinsulin-reactive TCRs. These results demonstrate an enrichment of preproinsulin-reactive TCR sequences during the progression to T1D, highlighting the importance of using disease-relevant TCR sequences as powerful biomarkers in autoimmune disorders.

Immunogenomic profiling of lung adenocarcinoma reveals poorly differentiated tumors are associated with an immunogenic tumor microenvironment

OBJECTIVES

Pathologists have routinely observed distinct histologic patterns of growth in early-stage lung adenocarcinoma (LUAD), which have been suggested to be associated with prognosis. Herein, we investigated the relationship between LUAD patterns of growth, as defined by the updated international association for the study of lung cancer (IASLC) grading criteria, and differences in the tumor immune microenvironment to identify predictors of response to immunotherapy.

METHODS

174 resected stage I-III LUAD tumors were classified by histologic pattern of growth (i.e. solid, micropapillary, acinar, papillary, and lepidic) and then grouped as well differentiated, moderately differentiated, and poorly differentiated. Comprehensive multiplatform analysis including whole exome sequencing, gene expression profiling, immunohistochemistry, CIBERSORT, and T-cell receptor sequencing was performed and groups were compared for differences in genomic drivers, immune cell infiltrate, clonality, and survival. Finally, multivariate analysis was performed adjusting for pathologic stage and smoking status.

RESULTS

Poorly differentiated tumors demonstrated a strong association with smoking relative to moderately differentiated or well differentiated tumors. However, unlike in prior reports, poorly differentiated tumors were not associated with a worse survival after curative-intent resection. Genomic analysis revealed that poorly differentiated tumors are associated with high tumor mutation burden but showed no association with oncogenic drivers. Immune analyses revealed that poorly differentiated tumors are associated with increased T-cell clonality, expression of PD-L1, and infiltration by cytotoxic CD8 T-cells, activated CD4 T-cells, and pro-inflammatory (M1) macrophages. Finally, multivariate analysis controlling for stage and smoking status confirmed independence of immune differences between IASLC grade groups.

CONCLUSIONS

Poorly differentiated tumors, as defined by the updated IASLC grading criteria, are associated with a distinct immunogenic tumor microenvironment that predicts for therapeutic response to immune agents, including checkpoint inhibitors, and should be included in the clinical trial design of immunotherapy studies in early-stage lung adenocarcinoma.

Development and application of a next-generation sequencing protocol and bioinformatics pipeline for the comprehensive analysis of the canine immunoglobulin repertoire

Profiling the adaptive immune repertoire using next generation sequencing (NGS) has become common in human medicine, showing promise in characterizing clonal expansion of B cell clones through analysis of B cell receptors (BCRs) in patients with lymphoid malignancies. In contrast, most work evaluating BCR repertoires in dogs has employed traditional PCR-based approaches analyzing the IGH locus only. The objectives of this study were to: (1) describe a novel NGS protocol to evaluate canine BCRs; (2) develop a bioinformatics pipeline for processing canine BCR sequencing data; and (3) apply these methods to derive insights into BCR repertoires of healthy dogs and dogs undergoing treatment for B-cell lymphoma. RNA from peripheral blood mononuclear cells of healthy dogs (n = 25) and dogs newly diagnosed with intermediate-to-large B-cell lymphoma (n = 18) with intent to pursue chemotherapy was isolated, converted into cDNA and sequenced by NGS. The BCR repertoires were identified and quantified using a novel analysis pipeline. The IGK repertoires of the healthy dogs were far less diverse compared to IGL which, as with IGH, was highly diverse. Strong biases at key positions within the CDR3 sequence were identified within the healthy dog BCR repertoire. For a subset of the dogs with B-cell lymphoma, clonal expansion of specific IGH sequences pre-treatment and reduction post-treatment was observed. The degree of expansion and reduction correlated with the clinical outcome in this subset. Future studies employing these techniques may improve disease monitoring, provide earlier recognition of disease progression, and ultimately lead to more targeted therapeutics.

DeepLION: Deep Multi-Instance Learning Improves the Prediction of Cancer-Associated T Cell Receptors for Accurate Cancer Detection

Recent studies highlight the potential of T cell receptor (TCR) repertoires in accurately detecting cancers via noninvasive sampling. Unfortunately, due to the complicated associations among cancer antigens and the possible induced T cell responses, currently, the practical strategy for identifying cancer-associated TCRs is the computational prediction based on TCR repertoire data. Several state-of-the-art methods were proposed in recent year or two; however, the prediction algorithms were still weakened by two major issues. To facilitate the computational processes, the algorithms prefer to decompose the original TCR sequences into length-fixed amino acid fragments, while the first dilemma comes as the lengths of cancer-associated motifs are suggested to be various. Moreover, the correlations among TCRs in the same repertoire should be further considered, which are often ignored by the existing methods. We here developed a deep multi-instance learning method, named DeepLION, to improve the prediction of cancer-associated TCRs by considering these issues. First, DeepLION introduced a deep learning framework with alternative convolution filters and 1-max pooling operations to handle the amino acid fragments with different lengths. Then, the multi-instance learning framework modeled the TCR correlations and assigned adjusted weights for each TCR sequence during the predicting process. To validate the performance of DeepLION, we conducted a series of experiments on several cohorts of patients from nine cancer types. Compared to the existing methods, DeepLION achieved, on most of the cohorts, higher prediction accuracies, sensitivities, specificities, and areas under the curve (AUCs), where the AUC reached notably 0.97 and 0.90 for thyroid and lung cancer cohorts, respectively. Thus, DeepLION may further support the detection of cancers from TCR repertoire data. DeepLION is publicly available on GitHub, at https://github.com/Bioinformatics7181/DeepLION, for academic usage only.

Concurrent delivery of immune checkpoint blockade modulates T cell dynamics to enhance neoantigen vaccine-generated antitumor immunity

Neoantigen vaccines aiming to induce tumor-specific T cell responses have achieved promising antitumor effects in early clinical trials. However, the underlying mechanism regarding response or resistance to this treatment is unclear. Here we observe that neoantigen vaccine-generated T cells can synergize with the immune checkpoint blockade for effective tumor control. Specifically, we performed single-cell sequencing on over 100,000 T cells and uncovered that combined therapy induces an antigen-specific CD8 T cell population with active chemokine signaling (Cxcr3+/Ccl5+), lower co-inhibitory receptor expression (Lag3-/Havcr2-) and higher cytotoxicity (Fasl+/Gzma+). Furthermore, generation of neoantigen-specific T cells in the draining lymph node is required for combination treatment. Signature genes of this unique population are associated with T cell clonal frequency and better survival in humans. Our study profiles the dynamics of tumor-infiltrating T cells during neoantigen vaccine and immune checkpoint blockade treatments and high-dimensionally identifies neoantigen-reactive T cell signatures for future development of therapeutic strategies.

Safety and efficacy of mutant neoantigen-specific T-cell treatment combined anti-PD-1 therapy in stage IV solid tumors

Aims: This trial explored the safety and efficacy of neoantigen-specific T cells (Nas-Ts) combined with anti-PD-1 (Nas-T + anti-PD-1). Patients & methods: This non-randomized trial recruited participants with solid tumors treated with at least two prior systemic treatment lines. For comparison, 1:1-matched controls who received anti-PD-1 alone were recruited. The primary end point was safety. Results: 15 participants were enrolled in the Nas-T + anti-PD-1 group, the objective response rate was 33.3%, and the disease control rate was 93.3%. The median progression-free survival was significantly different between the Nas-T + anti-PD-1 and control groups (13.8 vs 4.2 months; p = 0.024), but no difference in overall survival was found (p = 0.126). The most common adverse events were maculopapular skin reaction (53.3%), rash (53.3%), hepatotoxicity (53.3%) and fever (53.3%) in the Nas-T + anti-PD-1 group. No serious safety issues were experienced. Conclusion: Nas-Ts combined with anti-PD-1 could be more effective than anti-PD-1 alone in prolonging progression-free survival, with good safety.

Early detection of cancer

Survival improves when cancer is detected early. However, ~50% of cancers are at an advanced stage when diagnosed. Early detection of cancer or precancerous change allows early intervention to try to slow or prevent cancer development and lethality. To achieve early detection of all cancers, numerous challenges must be overcome. It is vital to better understand who is at greatest risk of developing cancer. We also need to elucidate the biology and trajectory of precancer and early cancer to identify consequential disease that requires intervention. Insights must be translated into sensitive and specific early detection technologies and be appropriately evaluated to support practical clinical implementation. Interdisciplinary collaboration is key; advances in technology and biological understanding highlight that it is time to accelerate early detection research and transform cancer survival.

Combined IL-2, agonistic CD3 and 4-1BB stimulation preserve clonotype hierarchy in propagated non-small cell lung cancer tumor-infiltrating lymphocytes

Background

Adoptive cell transfer (ACT) of tumor-infiltrating lymphocytes (TIL) yielded clinical benefit in patients with checkpoint blockade immunotherapy-refractory non-small cell lung cancer (NSCLC) prompting a renewed interest in TIL-ACT. This preclinical study explores the feasibility of producing a NSCLC TIL product with sufficient numbers and enhanced attributes using an improved culture method.

Methods

TIL from resected NSCLC tumors were initially cultured using (1) the traditional method using interleukin (IL)-2 alone in 24-well plates (TIL 1.0) or (2) IL-2 in combination with agonistic antibodies against CD3 and 4-1BB (Urelumab) in a G-Rex flask (TIL 3.0). TIL subsequently underwent a rapid expansion protocol (REP) with anti-CD3. Before and after the REP, expanded TIL were phenotyped and the complementarity-determining region 3 β variable region of the T-cell receptor (TCR) was sequenced to assess the T-cell repertoire.

Results

TIL 3.0 robustly expanded NSCLC TIL while enriching for CD8⁺ TIL in a shorter manufacturing time when compared with the traditional TIL 1.0 method, achieving a higher success rate and producing 5.3-fold more TIL per successful expansion. The higher proliferative capacity and CD8 content of TIL 3.0 was also observed after the REP. Both steps of expansion did not terminally differentiate/exhaust the TIL but a lesser differentiated population was observed after the first step. TIL initially expanded with the 3.0 method exhibited higher breadth of clonotypes than TIL 1.0 corresponding to a higher repertoire homology with the original tumor, including a higher proportion of the top 10 most prevalent clones from the tumor. TIL 3.0 also retained a higher proportion of putative tumor-specific TCR when compared with TIL 1.0. Numerical expansion of TIL in a REP was found to perturb the clonal hierarchy and lessen the proportion of putative tumor-specific TIL from the TIL 3.0 process.

Conclusions

We report the feasibility of robustly expanding a T-cell repertoire recapitulating the clonal hierarchy of the T cells in the NSCLC tumor, including a large number of putative tumor-specific TIL clones, using the TIL 3.0 methodology. If scaled up and employed as a sole expansion platform, the robustness and speed of TIL 3.0 may facilitate the testing of TIL-ACT approaches in NSCLC.

A Bioinformatic Framework for Dissecting the Dynamics of T Cells from Single-Cell Transcriptome

The quantitative tracking of the dynamics of T cells is challenging in human immunology. Although bulk sequencing of T cell receptor (TCR) α- and β-chains has been widely used for determining the clonality of T cells, such methods are limited in unveiling the phenotypic differences of T cells with the same clonotypes. Here, we describe a bioinformatics framework, STARTRAC, that integrates the single-cell transcriptome and TCR sequences as lineage-specific markers to quantitatively assess the dynamics of T cells, including their clonal expansion, tissue migration, and developmental transition properties.

Pan-cancer single-cell landscape of tumor-infiltrating T cells

[Figure: see text].

Single-cell analysis of human non-small cell lung cancer lesions refines tumor classification and patient stratification

Immunotherapy is a mainstay of non-small cell lung cancer (NSCLC) management. While tumor mutational burden (TMB) correlates with response to immunotherapy, little is known about the relationship between the baseline immune response and tumor genotype. Using single-cell RNA sequencing, we profiled 361,929 cells from 35 early-stage NSCLC lesions. We identified a cellular module consisting of PDCD1⁺CXCL13⁺ activated T cells, IgG⁺ plasma cells, and SPP1⁺ macrophages, referred to as the lung cancer activation module (LCAM^hi). We confirmed LCAM^hi enrichment in multiple NSCLC cohorts, and paired CITE-seq established an antibody panel to identify LCAM^hi lesions. LCAM presence was found to be independent of overall immune cell content and correlated with TMB, cancer testis antigens, and TP53 mutations. High baseline LCAM scores correlated with enhanced NSCLC response to immunotherapy even in patients with above median TMB, suggesting that immune cell composition, while correlated with TMB, may be a nonredundant biomarker of response to immunotherapy.

An Allogeneic Multiple Myeloma GM-CSF-Secreting Vaccine with Lenalidomide Induces Long-term Immunity and Durable Clinical Responses in Patients in Near Complete Remission

PURPOSE

This proof-of-principle clinical trial evaluated whether an allogeneic multiple myeloma GM-CSF-secreting vaccine (MM-GVAX) in combination with lenalidomide could deepen the clinical response in patients with multiple myeloma in sustained near complete remission (nCR).

PATIENTS AND METHODS

Fifteen patients on lenalidomide were treated with MM-GVAX and pneumococcal conjugate vaccine (PCV; Prevnar) at 1, 2, 3, and 6 months.

RESULTS

Eight patients (53.3%) achieved a true CR. With a median follow-up of 5 years, the median progression-free survival had not been reached, and the median overall survival was 7.8 years from enrollment. MM-GVAX induced clonal T-cell expansion and measurable cytokine responses that persisted up to 7 years in all patients. At baseline, a higher minimal residual disease was predictive of early relapse. After vaccination, a lack of both CD27^-DNAM1^-CD8⁺ T cells and antigen-presenting cells was associated with disease progression.

CONCLUSIONS

MM-GVAX, along with lenalidomide, effectively primed durable immunity and resulted in long-term disease control, as suggested by the reappearance of a detectable, fluctuating M-spike without meeting the criteria for clinical relapse. For patients in a nCR, MM-GVAX administration was safe and resulted in prolonged clinical responses.

Minimal Residual Disease in Myeloma: Application for Clinical Care and New Drug Registration

The development of novel agents has transformed the treatment paradigm for multiple myeloma, with minimal residual disease (MRD) negativity now achievable across the entire disease spectrum. Bone marrow-based technologies to assess MRD, including approaches using next-generation flow and next-generation sequencing, have provided real-time clinical tools for the sensitive detection and monitoring of MRD in patients with multiple myeloma. Complementary liquid biopsy-based assays are now quickly progressing with some, such as mass spectrometry methods, being very close to clinical use, while others utilizing nucleic acid-based technologies are still developing and will prove important to further our understanding of the biology of MRD. On the regulatory front, multiple retrospective individual patient and clinical trial level meta-analyses have already shown and will continue to assess the potential of MRD as a surrogate for patient outcome. Given all this progress, it is not surprising that a number of clinicians are now considering using MRD to inform real-world clinical care of patients across the spectrum from smoldering myeloma to relapsed refractory multiple myeloma, with each disease setting presenting key challenges and questions that will need to be addressed through clinical trials. The pace of advances in targeted and immune therapies in multiple myeloma is unprecedented, and novel MRD-driven biomarker strategies are essential to accelerate innovative clinical trials leading to regulatory approval of novel treatments and continued improvement in patient outcomes.

Impact of HLA type, age and chronic viral infection on peripheral T-cell receptor sharing between unrelated individuals

The human adaptive immune system must generate extraordinary diversity to be able to respond to all possible pathogens. The T-cell repertoire derives this high diversity through somatic recombination of the T-cell receptor (TCR) locus, a random process that results in repertoires that are largely private to each individual. However, factors such as thymic selection and T-cell proliferation upon antigen exposure can affect TCR sharing among individuals. By immunosequencing the TCRβ variable region of 426 healthy individuals, we find that, on average, fewer than 1% of TCRβ clones are shared between individuals, consistent with largely private TCRβ repertoires. However, we detect a significant correlation between increased HLA allele sharing and increased number of shared TCRβ clones, with each additional shared HLA allele contributing to an increase in ~0.01% of the total shared TCRβ clones, supporting a key role for HLA type in shaping the immune repertoire. Surprisingly, we find that shared antigen exposure to CMV leads to fewer shared TCRβ clones, even after controlling for HLA, indicative of a largely private response to major viral antigenic exposure. Consistent with this hypothesis, we find that increased age is correlated with decreased overall TCRβ clone sharing, indicating that the pattern of private TCRβ clonal expansion is a general feature of the T-cell response to other infectious antigens as well. However, increased age also correlates with increased sharing among the lowest frequency clones, consistent with decreased repertoire diversity in older individuals. Together, all of these factors contribute to shaping the TCRβ repertoire, and understanding their interplay has important implications for the use of T cells for therapeutics and diagnostics.

Assessment of Clonotypic Rearrangements and Minimal Residual Disease in Lymphoid Malignancies: A Large Cancer Center Experience Using clonoSEQ

CONTEXT.—

Measurable (minimal) residual disease (MRD) is an independent prognostic factor for survival outcomes in patients with lymphoid and plasma cell malignancies and has been incorporated into consensus criteria regarding treatment response, strategy, and clinical trial endpoints. clonoSEQ (a next-generation sequencing [NGS]-MRD assay) uses multiplex polymerase chain reaction and NGS to identify clonotypic rearrangements at the immunoglobulin (Ig) H, IgK, IgL, T-cell receptor (TCR)-β, and TCR-γ loci, and translocated B-cell lymphoma 1/IgH and 2/IgH sequences for MRD assessment. Additionally, it can be used to confirm diagnoses of cutaneous T-cell lymphoma (CTCL).

OBJECTIVE.—

To review the technical aspects of our experience using the clonoSEQ Assay in routine clinical practice.

DESIGN.—

In this single-center experience, 390 patients with lymphoid and plasma cell malignancies were assessed with the NGS-MRD Assay at a central laboratory.

RESULTS.—

Median time from arrival of the shipment to initiation of the assay (defined as captured in Adaptive's secure tracking system) was 2.1 hours. Overall, 317 patients had 1 or more samples submitted for sequence identification. Of these, 290 (91.5%) had trackable sequences identified. The median calibration rate of samples by malignancy (where n ≥ 10 samples, excluding CTCL samples) was 88.1%, across a variety of fresh and archived sample sources (177 of 201 samples). TCR-β and/or TCR-γ clonotypes were identified in 40 of 95 samples (42.1%) from 66 patients with suspected CTCL.

CONCLUSIONS.—

This NGS-MRD Assay is a valuable and sensitive tool for monitoring MRD in patients with plasma cell and lymphoid malignancies and assisting in the diagnosis of CTCL.

Prediction of Immunotherapy Response in Melanoma through Combined Modeling of Neoantigen Burden and Immune-Related Resistance Mechanisms

PURPOSE

While immune checkpoint blockade (ICB) has become a pillar of cancer treatment, biomarkers that consistently predict patient response remain elusive due to the complex mechanisms driving immune response to tumors. We hypothesized that a multi-dimensional approach modeling both tumor and immune-related molecular mechanisms would better predict ICB response than simpler mutation-focused biomarkers, such as tumor mutational burden (TMB).

EXPERIMENTAL DESIGN

Tumors from a cohort of patients with late-stage melanoma (n = 51) were profiled using an immune-enhanced exome and transcriptome platform. We demonstrate increasing predictive power with deeper modeling of neoantigens and immune-related resistance mechanisms to ICB.

RESULTS

Our neoantigen burden score, which integrates both exome and transcriptome features, more significantly stratified responders and nonresponders (P = 0.016) than TMB alone (P = 0.049). Extension of this model to include immune-related resistance mechanisms affecting the antigen presentation machinery, such as HLA allele-specific LOH, resulted in a composite neoantigen presentation score (NEOPS) that demonstrated further increased association with therapy response (P = 0.002).

CONCLUSIONS

NEOPS proved the statistically strongest biomarker compared with all single-gene biomarkers, expression signatures, and TMB biomarkers evaluated in this cohort. Subsequent confirmation of these findings in an independent cohort of patients (n = 110) suggests that NEOPS is a robust, novel biomarker of ICB response in melanoma.

Deep Sequencing of T-Cell Receptors for Monitoring Peripheral CD8+ T Cells in Chinese Advanced Non-Small-Cell Lung Cancer Patients Treated With the Anti-PD-L1 Antibody

Background: Atezolizumab, a high-affinity engineered human anti-PD-L1 antibody, has produced a clinical benefit for patients with advanced non-small-cell lung cancer (NSCLC). However, associated with T-cell regulation, the immunomodulatory effect of PD-L1 blockade and its biomarker in peripheral immunity remains elusive. Methods: In a prospective cohort with 12 Chinese advanced NSCLC patients who received atezolizumab 1,200 mg every 3 weeks as a second-line treatment, blood samples were obtained before and 6 weeks after atezolizumab initiation, and when disease progression was confirmed. Patients were classified into a response or progression group according to response evaluation criteria in solid tumors (RECIST) 1.1. Fresh peripheral blood mononuclear cells (PBMCs) from patients were stained with antihuman CD3, CD8, and PD-1 antibodies for flow cytometry analysis. T-cell receptor (TCR)-β chains of CD8⁺ T cells were analyzed by next-generation sequencing (NGS) at the deep level. Diversity, clonality, and similarity of TCR have been calculated before and after treatment in both groups. Results: Clonal expansion with high PD-1 expression was detected in all patients' peripheral CD8⁺ T cells before the treatment of atezolizumab. Unlike the progression group, the diversity of TCR repertoire and singletons in the TCRβ pool increased over time with atezolizumab administration, and the TCR repertoire dynamically changes in the response group. The percentage of CD8⁺ PD-1^high terminal exhausted T cells declined in the response group after the PD-L1 blockade. Two patterns of TCR changes among patients who received PD-L1-targeted immunotherapy were observed. Conclusions: Deep sequencing of the T-cell receptors confirmed the existence of CD8⁺ PD-1high T cells with an exhaustion phenotype in Chinese NSCLC patients. Our study demonstrated that efficient anti-PD-L1 therapy could reshape the TCR repertoire for antitumor patients. Furthermore, singleton frequency may help us select patients who are sensitive to anti-PD-L1 immunotherapy.

Evaluating T-cell cross-reactivity between tumors and immune-related adverse events with TCR sequencing: pitfalls in interpretations of functional relevance

T-cell receptor sequencing (TCRseq) enables tracking of T-cell clonotypes recognizing the same antigen over time and across biological compartments. TCRseq has been used to test if cross-reactive antitumor T cells are responsible for development of immune-related adverse events (irAEs) following immune checkpoint blockade. Prior studies have interpreted T-cell clones shared among the tumor and irAE as evidence supporting this, but interpretations of these findings are challenging, given the constraints of TCRseq. Here we capitalize on a rare opportunity to understand the impact of potential confounders, such as sample size, tissue compartment, and collection batch/timepoint, on the relative proportion of shared T-cell clones between an irAE and tumor specimens. TCRseq was performed on tumor-involved and -uninvolved tissues, including an irAE, that were obtained throughout disease progression and at the time of rapid autopsy from a patient with renal cell carcinoma treated with programmed death-1 (PD-1) blockade. Our analyses show significant effects of these confounders on our ability to understand T-cell receptor overlap, and we present mitigation strategies and study design recommendations to reduce these errors. Implementation of these strategies will enable more rigorous TCRseq-based studies of immune responses in human tissues, particularly as they relate to antitumor T-cell cross-reactivity in irAEs following checkpoint blockade.

Characterization of Circulating T Cell Receptor Repertoire Provides Information about Clinical Outcome after PD-1 Blockade in Advanced Non-Small Cell Lung Cancer Patients

Simple Summary

Immune checkpoint blockers (ICBs) have demonstrated durable anti-tumor responses in advanced non-small cell lung cancer (NSCLC). Despite progress in development of new predictive biomarkers, such as PD-L1 expression, TMB, or MSI, there is still an urge for a better selection of patients that will benefit from the blockade of PD-1/PD-L1 axis. In this study, peripheral blood T cell receptor beta chain (TCR-β) repertoire, at baseline (PRE) and first response (FR) assessment, was analyzed with high-throughput sequencing in a cohort of advanced NSCLC patients receiving first-line pembrolizumab. Our results suggest that measuring TCR-β features in peripheral blood may be a potential tool to assess patients’ immune response. Furthermore, the usage of the TRBV20-1 segment highly predicts host response and survival in anti-PD-1 treated NSCLC patients.

Abstract

Despite the success of immunotherapies in lung cancer, development of new biomarkers for patient selection is urgently needed. This study aims to explore minimally invasive approaches to characterize circulating T cell receptor beta chain (TCR-β) repertoire in a cohort of advanced non-small cell lung cancer (NSCLC) patients treated with first-line pembrolizumab. Peripheral blood samples were obtained at two time points: i) pretreatment (PRE) and ii) first response assessment (FR). Next-generation sequencing (NGS) was used to analyze the hypervariable complementary determining region 3 (CDR3) of TCR-β chain. Richness, evenness, convergence, and Jaccard similarity indexes plus variable (V) and joining (J)-gene usage were studied. Our results revealed that increased richness during treatment was associated with durable clinical benefit (DCB; p = 0.046), longer progression-free survival (PFS; p = 0.007) and overall survival (OS; p = 0.05). Patients with Jaccard similarity index ≥0.0605 between PRE and FR samples showed improved PFS (p = 0.021). Higher TRBV20-1 PRE usage was associated with DCB (p = 0.027). TRBV20-1 levels ≥9.14% in PRE and ≥9.02% in FR significantly increased PFS (p = 0.025 and p = 0.016) and OS (p = 0.035 and p = 0.018). Overall, analysis of circulating TCR-β repertoire may provide information about the immune response in anti-PD-1 treated NSCLC patients; in this scenario, it can also offer important information about the clinical outcome.

Phenotypic Characteristics of the Tumour Microenvironment in Primary and Secondary Hepatocellular Carcinoma

(1) Background: The intra-tumoural heterogeneity (ITH) of hepatocellular carcinoma (HCC) and its microenvironment (TME) across primary and secondary disease is poorly characterised. (2) Methods: Intra-tumoural (IT) and peri-tumoural (PT) staining of matched primary and secondary samples was conducted to evaluate the distribution of CD4+/FOXP3+ and CD8+/PD1+ T-cells. Samples underwent PD-L1/2 immunostaining, tumour mutational burden (TMB) evaluation, and high-resolution T-cell receptor (TCR) sequencing to derive T-cell clonality and targeted transcriptomics. (3) Results: We analysed 24 samples from matched primary (n = 11) and secondary (n = 13; 5 synchronous, 6 metachronous) deposits, 11 being extrahepatic (84.6%). IT CD8+ density was lower than PT in both primary (p = 0.005) and secondary deposits (p = 0.01), consistent with immune exclusion. PD-L1+ tumours displayed higher IT and PT CD8+/PD1+ cell density compared to PD-L1- (p < 0.05), and primary IT infiltrate was enriched in CD4+/FOXP3+ cells, compared to PT regions (p = 0.004). TCR-sequencing demonstrated enrichment of the top T-cell clonotype in secondary versus primary HCC (p = 0.02), without differences in overall productive clonality (p = 0.35). TMB was similar across primary versus secondary HCC (p = 0.95). While directed gene set analysis demonstrated the uniformity of transcriptional signatures of individual immune cell types, secondary deposits demonstrated higher COLEC12 (p = 0.004), CCL26 (p = 0.02), CD1E (p = 0.02) and CD36 (p = 0.03) expression with downregulation of CXCL1 (p = 0.03), suggesting differential regulation of innate immunity. (4) Conclusion: Immune exclusion is a defining feature of the HCC TME. Despite evidence of homogeneity in somatic TMB, secondary HCC is characterised by the expansion of a distinct T-cell clonotype and differential regulation of innate immune pathways.

Next-Generation Immunosequencing Reveals Pathological T-Cell Architecture in Autoimmune Hepatitis

BACKGROUND AND AIMS

Autoimmune hepatitis (AIH) is a chronic liver disease that regularly relapses when immunosuppression is tapered. It is thought to be driven by T-cells, whereas the etiologic impact of an apparently deregulated B lineage system, as evidenced by hypergammaglobulinemia and autoantibodies, remains elusive. We set out to investigate T and B cell repertoires supporting chronic inflammation in AIH.

APPROACH AND RESULTS

T and B cell receptor (TCR/BCR) and human leukocyte antigen (HLA) next-generation immunosequencing were used to record immune signatures from a cohort of 60 patients with AIH and disease controls. Blood and liver B lineage immune metrics were not indicative of a dominant directional antigen selection apart from a slight skewing of IGHV-J genes. More importantly, we found strong AIH-specific TRBV-J skewing not attributable to the HLA-DRB1 specificities of the cohort. This TCR repertoire bias was generated as a result of peripheral T cell (de)selection and persisted in disease remission. Using a clustering algorithm according to antigenic specificity, we identified liver TCR clusters that were shared between patients with AIH but were absent or deselected in patients with other liver pathologies.

CONCLUSIONS

Patients with AIH show profound and persisting T-cell architectural changes that may explain high relapse rates after tapering immunosuppression. Liver T-cell clusters shared between patients may mediate liver damage and warrant further study.

Cancer Cell Intrinsic and Immunologic Phenotypes Determine Clinical Outcomes in Basal-like Breast Cancer

PURPOSE

Basal-like breast cancer (BLBC) is a particularly aggressive intrinsic molecular subtype of breast cancer that lacks targeted therapies. There is also no clinically useful test to risk stratify patients with BLBC. We hypothesized that a transcriptome-based phenotypic characterization of BLBC tumors and their microenvironments may overcome these challenges.

EXPERIMENTAL DESIGN

We conducted a retrospective correlative genomic sequencing study using a matched pairs design with validation in five independent cohorts. The study was conducted on a large population-based prospective cohort of the major molecular subtypes of breast cancer conducted in the greater Seattle-Puget Sound metropolitan area. Cases consisted of women 20-69 years of age first diagnosed with invasive breast cancer identified through the population-based Surveillance Epidemiology and End Results program. Patients for this analysis (n = 949) were identified from the 1,408 patients with stage I-III triple-negative breast cancer [estrogen receptor-negative (ER^-), progesterone receptor-negative (PR^-), HER2^-]. Of the 949 women, 248 developed a recurrence after their initial diagnosis. A matched set of 67 recurrent and nonrecurrent BLBC tumors was subjected to transcriptome sequencing. Through RNA sequencing of the matched sets of recurrent and nonrecurrent BLBC tumors, we aimed to identify prognostic phenotypes.To identify nonredundant and uncorrelated prognostic genes, we used an ensemble of variable selection algorithms, which resulted in a ranking of genes on the basis of their expected utility in classification. Using leave-one-out cross-validation, we trained a random forest classifier on the basis of the top 21 genes (BRAVO-DX). Validations were performed in five independent triple-negative or BLBC cohorts, and biomarker robustness and transferability were demonstrated by employing real-time PCR.

RESULTS

We found that cancer cell intrinsic and immunologic phenotypes are independent predictors of recurrence. By simultaneously interrogating the tumor and its microenvironment, we developed a compound risk model that stratified patients into low-, medium-, and high-risk groups, with a 14%/56%/74% chance of recurrence, respectively. Biologically, the primary tumors of patients who developed a recurrence had increased growth factor signaling and stem-like features, while nonrecurrent tumors showed high lymphocyte infiltration with clonal expansion of T and B cells, as well as antitumor polarization of macrophages. We validated our model in five independent cohorts, including three large cohorts, where BRAVO-DX was highly informative in identifying patients with disease recurrence [HR, 6.79 (95% confidence interval (CI), 1.89-24.37); HR, 3.45 (95% CI, 2.41-4.93); and HR, 1.69 (95% CI, 1.17-2.46)]. A smaller gene set focused on the tumor immunophenotype, BRAVO-IMMUNE, was highly prognostic in all five cohorts.

CONCLUSIONS

Together, these results indicate that phenotypic characteristics of BLBCs and their microenvironment are associated with recurrence-free survival and demonstrate the utility of intrinsic and extrinsic phenotypes as independent prognostic biomarkers in BLBC. Pending further evaluation and validation, our prognostic model has the potential to inform clinical decision-making for patients with BLBC as it identifies those at high risk of rapidly progressing on standard chemotherapy, as well as those who may benefit from alternative first-line therapies.

Characteristics of T-Cell Receptor Repertoire and Correlation With EGFR Mutations in All Stages of Lung Cancer

Lung cancer is the leading cause of cancer-related deaths worldwide, and its occurrence is related to the accumulation of gene mutations and immune escape of the tumor. Sequencing of the T-cell receptor (TCR) repertoire can reveal the immunosurveillance status of the tumor microenvironment, which is related to tumor escape and immunotherapy. This study aimed to determine the characteristics and clinical significance of the TCR repertoire in lung cancer. To comprehensively profile the TCR repertoire, results from high-throughput sequencing of samples from 93 Chinese patients with lung cancer were analyzed. We found that the TCR clonality of tissues was related to smoking, with higher clonality in patients who had quit smoking for less than 1 year. As expected, TCR clonality was correlated with stages: patients with stage IV disease showed higher clonality than others. The correlation between TCR repertoire and epidermal growth factor receptor (EGFR) status was also investigated. Patients with EGFR non-L858R mutations showed higher clonality and a lower Shannon index than other groups, including patients with EGFR L858R mutation and wild-type EGFR. Furthermore, we analyzed the TCR similarity metrics—that is, the TCR shared between postoperative peripheral blood and tissue of patients with non-distant metastasis of lung cancer. A similar trend was found, in which patients with EGFR L858R mutations had lower overlap index (OLI) and Morisita index (MOI) scores. Moreover, the OLI showed a positive correlation with several clinical characteristics, including the tumor mutational burden of tissues and the maximum somatic allele frequency of blood; OLI showed a negative correlation with the ratio of CD4+CD28+ in CD4+ cells and the ratio of CD8+CD28+ in CD8+ cells. In conclusion, TCR clonality and TCR similarity metrics correlated with clinical characteristics of patients with lung cancer. Differences in TCR clonality, Shannon index, and OLI across EGFR subtypes provide information to improve understanding about varied responses to immunotherapy in patients with different EGFR mutations.

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.

Evidence of B Cell Clonality and Investigation Into Properties of the IgM in Patients With Schnitzler Syndrome

The Schnitzler Syndrome (SchS) is an acquired, autoinflammatory condition successfully treated with IL-1 inhibition. The two main defining features of this late-onset condition are neutrophilic urticarial dermatoses (NUD) and the presence of an IgM monoclonal component. While the former aspect has been extensively studied in this disease setting, the enigmatic paraproteinaemia and its potential consequential effects within SchS, has not previously been thoroughly addressed. Previous studies analyzing clonal B cell repertoires have largely focused on autoimmune disorders such as Systemic Lupus Erythematous (SLE) and hematological malignancies such as Chronic Lymphocytic Leukaemia (CLL), where B-cell clonality is central to disease pathology. The present study uses next-generation sequencing to provide detailed insight into aspects of B cell VDJ recombination and properties of the resulting immunoglobulin chains. An overview of IgH regional dynamics in 10 SchS patients, with a particular focus on CDR3 sequences and VDJ gene usage is reported, highlighting the presence of specific B cell expansions. Protein microarray detected a substantial proportion of autoreactive IgM to nuclear target proteins, though a single universal target was not identified. Together, these genetic and functional findings impart new understanding into this rare disorder.

Combined TCR Repertoire Profiles and Blood Cell Phenotypes Predict Melanoma Patient Response to Personalized Neoantigen Therapy plus Anti-PD-1

T cells use highly diverse receptors (TCRs) to identify tumor cells presenting neoantigens arising from genetic mutations and establish anti-tumor activity. Immunotherapy harnessing neoantigen-specific T cells to target tumors has emerged as a promising clinical approach. To assess whether a comprehensive peripheral mononuclear blood cell analysis predicts responses to a personalized neoantigen cancer vaccine combined with anti-PD-1 therapy, we characterize the TCR repertoires and T and B cell frequencies in 21 patients with metastatic melanoma who received this regimen. TCR-α/β-chain sequencing reveals that prolonged progression-free survival (PFS) is strongly associated with increased clonal baseline TCR repertoires and longitudinal repertoire stability. Furthermore, the frequencies of antigen-experienced T and B cells in the peripheral blood correlate with repertoire characteristics. Analysis of these baseline immune features enables prediction of PFS following treatment. This method offers a pragmatic clinical approach to assess patients’ immune state and to direct therapeutic decision making.

Pre-treatment blood-based factors predict response to immunotherapy

TCR repertoire clonality and stability associate with improved clinical outcomes

Baseline T and B cell memory phenotypes associate with improved clinical outcomes

Combined baseline TCR repertoire and PBMC phenotypes predict immunotherapy response

Angiogenic and Immune-Related Biomarkers and Outcomes Following Axitinib/Pembrolizumab Treatment in Patients with Advanced Renal Cell Carcinoma

PURPOSE

Combined axitinib/pembrolizumab is approved for advanced renal cell carcinoma (aRCC). This exploratory analysis examined associations between angiogenic and immune-related biomarkers and outcomes following axitinib/pembrolizumab treatment.

PATIENTS AND METHODS

Prospectively defined retrospective correlative exploratory analyses tested biospecimens from 52 treatment-naïve patients receiving axitinib and pembrolizumab (starting doses 5 mg twice daily and 2 mg/kg respectively, every 3 weeks). Tumor tissue, serum, and whole blood samples were collected at baseline, at cycle 2 day 1 (C2D1), and end of treatment (EOT) for blood-based samples. Clinical outcomes were objective response rate (ORR) and progression-free survival (PFS).

RESULTS

Higher baseline tumor levels of CD8 showed a trend toward longer PFS (HR 0.4; P = 0.091). Higher baseline serum levels of CXCL10 (P = 0.0197) and CEACAM1 (P = 0.085) showed a trend toward better ORR and longer PFS, respectively. Patients for whom IL6 was not detected at baseline had longer PFS versus patients for whom it was detected (HR 0.4; P = 0.028). At C2D1 and/or EOT, mainly immune-related biomarkers showed any association with better outcomes. The genes CA9 (P = 0.084), HIF1A (P = 0.064), and IFNG (P = 0.073) showed trending associations with ORR, and AKT3 (P = 0.0145), DDX58 (P = 0.0726), GZMA (P = 0.0666), LCN2 (NGAL; P = 0.0267), and PTPN11 (P = 0.0287) with PFS.

CONCLUSIONS

With combined axitinib/pembrolizumab treatment in patients with aRCC, mostly immune-related biomarkers are associated with better treatment outcomes. This exploratory analysis has identified some candidate biomarkers to consider in future prospective testing.

A Phase Ib Trial of Personalized Neoantigen Therapy Plus Anti-PD-1 in Patients with Advanced Melanoma, Non-small Cell Lung Cancer, or Bladder Cancer

Neoantigens arise from mutations in cancer cells and are important targets of T cell-mediated anti-tumor immunity. Here, we report the first open-label, phase Ib clinical trial of a personalized neoantigen-based vaccine, NEO-PV-01, in combination with PD-1 blockade in patients with advanced melanoma, non-small cell lung cancer, or bladder cancer. This analysis of 82 patients demonstrated that the regimen was safe, with no treatment-related serious adverse events observed. De novo neoantigen-specific CD4⁺ and CD8⁺ T cell responses were observed post-vaccination in all of the patients. The vaccine-induced T cells had a cytotoxic phenotype and were capable of trafficking to the tumor and mediating cell killing. In addition, epitope spread to neoantigens not included in the vaccine was detected post-vaccination. These data support the safety and immunogenicity of this regimen in patients with advanced solid tumors (Clinicaltrials.gov: NCT02897765).

Systematic analysis of the transcriptome in small-cell carcinoma of the oesophagus reveals its immune microenvironment

Objectives

Although the genomic landscape of small-cell carcinoma of the oesophagus (SCCE) has been dissected, its transcriptome-level aberration and immune microenvironment status are unknown.

Methods

Using ultra-deep whole transcriptome sequencing, we analysed the expression profile of nine paired SCCE samples and compared the transcriptome with public transcriptomic data set of normal oesophageal mucosa and other cancer types. Based on the transcriptome data, the immune signatures were investigated. The genomic data of 55 SCCE samples were also applied for immune checkpoint blockade therapy (ICBT) biomarker evaluation including microsatellite instability (MSI) status, tumor mutation burden (TMB) and neoantigen burden (TNB). Also, we evaluated the CD8, CD68 and programmed death-ligand 1 (PD-L1) in 62 retrospective SCCE samples with IHC assay.

Results

Differential expression analysis revealed that the cell cycle, p53, and Wnt pathways are significantly deregulated in SCCE. Immune microenvironment analysis showed that high leucocyte infiltration and adaptive immune resistance did occur in certain individuals, while the majority showed a relatively suppressive immune status. Immune checkpoints such as CD276 and LAG-3 were upregulated, and higher M2 macrophage infiltration in tumor tissues. Furthermore, normal tissues adjacent to the tumors of SCCE presented a more activated inflammatory status than tumor-free healthy controls. These observations showed that ICBT might benefit SCCE patients. As the critical biomarker of ICBT, TMB of SCCE was 3.64 with the predictive objective response rate 13.2%, while the PD-L1-positive rate was 43%.

Conclusions

Our study systematically characterized the immune microenvironment in small-cell carcinoma of the esophagus and provided evidence that several patients with SCCE may benefit from immune checkpoint blockade therapy.

Exhaustion of tumour-infiltrating T-cell receptor repertoire diversity is an age-dependent indicator of immunological fitness independently predictive of clinical outcome in Burkitt lymphoma

Burkitt lymphoma (BL) is an aggressive B-cell-malignancy derived from germinal-centre B-cells. Curative therapy traditionally requires intensive immunochemotherapy. Recently, immuno-oncological approaches, modulating the T-cell tumour response, were approved for the treatment of a variety of malignancies. The architecture of the tumour-infiltrating T-cell receptor (TCR) repertoire in BL remains insufficiently characterized. We therefore performed a large-scale, next-generation sequencing study of the complimentary-determining region (CDR)-3 region of the TCRβ chain repertoire in a large cohort of all epidemiological subtypes of BL (n = 82) and diffuse large B-cell lymphoma (DLBCL; n = 34). Molecular data were subsequently assessed for correlation with clinical outcome. Our investigations revealed an age-dependent immunoprofile in BL as in DLBCL. Moreover, we found several public clonotypes in numerous patients suggestive of shared tumour neoantigen selection exclusive to BL and distinct from DLBCL regardless of Epstein-Barr virus and/or human immunodeficiency virus status. Compared with baseline, longitudinal analysis unveiled significant repertoire restrictions upon relapse (P = 0·0437) while productive TCR repertoire clonality proved to be a useful indicator of both overall and progression-free-survival [OS: P = 0·0001; hazard ratio (HR): 6·220; confidence interval (CI): 2·263-11·78; PFS: P = 0·0025; HR: 3·086; CI: 1·555-7·030]. Multivariate analysis confirmed its independence from established prognosticators, including age at diagnosis and comorbidities. Our findings establish the clinical relevance of the architecture and clonality of the TCR repertoire and its age-determined dynamics in BL.

T Cell Repertoire Dynamics during Pregnancy in Multiple Sclerosis

Identifying T cell clones associated with human autoimmunity has remained challenging. Intriguingly, many autoimmune diseases, including multiple sclerosis (MS), show strongly diminished activity during pregnancy, providing a unique research paradigm to explore dynamics of immune repertoire changes during active and inactive disease. Here, we characterize immunomodulation at the single-clone level by sequencing the T cell repertoire in healthy women and female MS patients over the course of pregnancy. Clonality is significantly reduced from the first to third trimester in MS patients, indicating that the T cell repertoire becomes less dominated by expanded clones. However, only a few T cell clones are substantially modulated during pregnancy in each patient. Moreover, relapse-associated T cell clones identified in an individual patient contract during pregnancy and expand during a postpartum relapse. Our data provide evidence that profiling the T cell repertoire during pregnancy could serve as a tool to discover and track "private" T cell clones associated with disease activity in autoimmunity.

Recharacterizing Tumor-Infiltrating Lymphocytes by Single-Cell RNA Sequencing

T cells are central players in cancer immunotherapy. Despite much concentrated effort on the study of tumor-infiltrating lymphocytes (TIL), such as T cells, a series of fundamental properties that include heterogeneity, clonal expansion, migration, and functional state transition remain elusive. Advances of single-cell sequencing have enabled the detailed characterization of immune cells in tumors and have vastly improved our understanding of less-defined cell subsets. Here, we discuss the current strategies for uncovering the heterogeneity of TILs, and how the deep transcriptome coupled with T-cell receptor analysis enhances the understanding of detailed properties of T-cell subsets. We further discuss the identification of novel T-cell markers with therapeutic or prognosis potentials, and highlight distinct T-cell properties among different cancer indications.

Lymphocytic infiltration in stage II microsatellite stable colorectal tumors: A retrospective prognosis biomarker analysis

BACKGROUND

Identifying stage II patients with colorectal cancer (CRC) at higher risk of progression is a clinical priority in order to optimize the advantages of adjuvant chemotherapy while avoiding unnecessary toxicity. Recently, the intensity and the quality of the host immune response in the tumor microenvironment have been reported to have an important role in tumorigenesis and an inverse association with tumor progression. This association is well established in microsatellite instable CRC. In this work, we aim to assess the usefulness of measures of T-cell infiltration as prognostic biomarkers in 640 stage II, CRC tumors, 582 of them confirmed microsatellite stable.

METHODS AND FINDINGS

We measured both the quantity and clonality index of T cells by means of T-cell receptor (TCR) immunosequencing in a discovery dataset (95 patients with colon cancer diagnosed at stage II and microsatellite stable, median age 67, 30% women) and replicated the results in 3 additional series of stage II patients from 2 countries. Series 1 and 2 were recruited in Barcelona, Spain and included 112 fresh frozen (FF, median age 69, 44% women) and 163 formalin-fixed paraffin-embedded (FFPE, median age 67, 39% women) samples, respectively. Series 3 included 270 FFPE samples from patients recruited in Haifa, Northern Israel, as part of a large case-control study of CRC (median age 73, 46% women). Median follow-up time was 81.1 months. Cox regression models were fitted to evaluate the prognostic value of T-cell abundance and Simpson clonality of TCR variants adjusting by sex, age, tumor location, and stage (IIA and IIB). In the discovery dataset, higher TCR abundance was associated with better prognosis (hazard ratio [HR] for ≥Q1 = 0.25, 95% CI 0.10-0.63, P = 0.003). A functional analysis of gene expression on these tumors revealed enrichment in pathways related to immune response. Higher values of clonality index (lower diversity) were not associated with worse disease-free survival, though the HR for ≥Q3 was 2.32 (95% CI 0.90-5.97, P = 0.08). These results were replicated in an independent FF dataset (TCR abundance: HR = 0.30, 95% CI 0.12-0.72, P = 0.007; clonality: HR = 3.32, 95% CI 1.38-7.94, P = 0.007). Also, the association with prognosis was tested in 2 independent FFPE datasets. The same association was observed with TCR abundance (HR = 0.41, 95% CI 0.18-0.93, P = 0.03 and HR = 0.56, 95% CI 0.31-1, P = 0.042, respectively, for each FFPE dataset). However, the clonality index was associated with prognosis only in the FFPE dataset from Israel (HR = 2.45, 95% CI 1.39-4.32, P = 0.002). Finally, a combined analysis combining all microsatellite stable (MSS) samples demonstrated a clear prognosis value both for TCR abundance (HR = 0.39, 95% CI 0.26-0.57, P = 1.3e-06) and the clonality index (HR = 2.13, 95% CI 1.44-3.15, P = 0.0002). These associations were also observed when variables were considered continuous in the models (HR per log2 of TCR abundance = 0.85, 95% CI 0.78-0.93, P = 0.0002; HR per log2 or clonality index = 1.16, 95% CI 1.03-1.31, P = 0.016).

LIMITATIONS

This is a retrospective study, and samples had been preserved with different methods. Validation series lack complete information about microsatellite instability (MSI) status and pathology assessment. The Molecular Epidemiology of Colorectal Cancer (MECC) study had information about overall survival instead of progression-free survival.

CONCLUSION

Results from this study demonstrate that tumor lymphocytes, assessed by TCR repertoire quantification based on a sequencing method, are an independent prognostic factor in microsatellite stable stage II CRC.

Unraveling tumor-immune heterogeneity in advanced ovarian cancer uncovers immunogenic effect of chemotherapy

In metastatic cancer, the degree of heterogeneity of the tumor microenvironment (TME) and its molecular underpinnings remain largely unstudied. To characterize the tumor-immune interface at baseline and during neoadjuvant chemotherapy (NACT) in high-grade serous ovarian cancer (HGSOC), we performed immunogenomic analysis of treatment-naive and paired samples from before and after treatment with chemotherapy. In treatment-naive HGSOC, we found that immune-cell-excluded and inflammatory microenvironments coexist within the same individuals and within the same tumor sites, indicating ubiquitous variability in immune cell infiltration. Analysis of TME cell composition, DNA copy number, mutations and gene expression showed that immune cell exclusion was associated with amplification of Myc target genes and increased expression of canonical Wnt signaling in treatment-naive HGSOC. Following NACT, increased natural killer (NK) cell infiltration and oligoclonal expansion of T cells were detected. We demonstrate that the tumor-immune microenvironment of advanced HGSOC is intrinsically heterogeneous and that chemotherapy induces local immune activation, suggesting that chemotherapy can potentiate the immunogenicity of immune-excluded HGSOC tumors.

Unravelling the heterogeneity and dynamic relationships of tumor-infiltrating T cells by single-cell RNA sequencing analysis

T cells are crucial for the success of immune-based cancer therapy. Reinvigorating antitumor T cell activity by blocking checkpoint inhibitory receptors has provided clinical benefits for many cancer patients. However, the efficacy of these treatments varies in cancer patients and the mechanisms underlying these diverse responses remain elusive. The density and status of tumor-infiltrating T cells have been shown to positively correlate with patient response to checkpoint blockades. Therefore, further understanding of the heterogeneity, clonal expansion, migration, and effector functions of tumor-infiltrating T cells will provide fundamental insights into antitumor immune responses. To this end, recent advances in single-cell RNA sequencing technology have enabled profound and extensive characterization of intratumoral immune cells and have improved our understanding of their dynamic relationships. Here, we summarize recent progress in single-cell RNA sequencing technology and current strategies to uncover heterogeneous tumor-infiltrating T cell subsets. In particular, we discuss how the coupling of deep transcriptome information with T cell receptor (TCR)-based lineage tracing has furthered our understanding of intratumoral T cell populations. We also discuss the functional implications of various T cell subsets in tumors and highlight the identification of novel T cell markers with therapeutic or prognostic potential.

Liquid biopsy and tumor heterogeneity in metastatic solid tumors: the potentiality of blood samples

In a large number of cancer types, treatment selection depends on the presence of specific tumor biomarkers. Due to the dynamic nature of cancer, very often these predictive biomarkers are not uniformly present in all cancer cells. Tumor heterogeneity represents indeed one of the main causes of therapeutic failure, and its decoding remains a major ongoing challenge in the field.

Liquid biopsy is the sampling and analysis of non-solid biological tissue often through rapid and non-invasive methods, which allows the assessment in real-time of the evolving landscape of cancer. Samples can be obtained from blood and most other bodily fluids. A blood-based liquid biopsy can capture circulating tumor cells and leukocytes, as well as circulating tumor-derived nucleic acids.

In this review, we discuss the current and possibly future applications of blood-based liquid biopsy in oncology, its advantages and its limitations in clinical practice. We specifically focused on its role as a tool to capture tumor heterogeneity in metastatic cancer patients.

Deep immune profiling of patients treated with lenalidomide and dexamethasone with or without daratumumab

CD38-targeted antibody, daratumumab, is approved for the treatment of multiple myeloma (MM). Phase 1/2 studies GEN501/SIRIUS revealed a novel immunomodulatory mechanism of action (MOA) of daratumumab that enhanced the immune response, reducing natural killer (NK) cells without affecting efficacy or safety. We further evaluated daratumumab's effects on immune cells in whole blood samples of relapsed/refractory MM patients from both treatment arms of the phase 3 POLLUX study (lenalidomide/dexamethasone [Rd] or daratumumab plus Rd [D-Rd]) at baseline (D-Rd, 40; Rd, 45) and after 2 months on treatment (D-Rd, 31; Rd, 33) using cytometry by time-of-flight. We confirmed previous reports of NK cell reduction with D-Rd. Persisting NK cells were phenotypically distinct, with increased expression of HLA-DR, CD69, CD127, and CD27. The proportion of T cells increased preferentially in deep responders to D-Rd, with a higher proportion of CD8⁺ versus CD4⁺ T cells. The expansion of CD8⁺ T cells correlated with clonality, indicating generation of adaptive immune response with D-Rd. D-Rd resulted in a higher proportion of effector memory T cells versus Rd. D-Rd reduced immunosuppressive CD38⁺ regulatory T cells. This study confirms daratumumab's immunomodulatory MOA in combination with immunomodulatory drugs and provides further insight into immune cell changes and activation status following daratumumab-based therapy.