FUME-TCRseq Enables Sensitive and Accurate Sequencing of the T-cell Receptor from Limited Input of Degraded RNA.

Genomic analysis of the T-cell receptor (TCR) reveals the strength, breadth, and clonal dynamics of the adaptive immune response to pathogens or cancer. The diversity of the TCR repertoire, however, means that sequencing is technically challenging, particularly for samples with low-quality, degraded nucleic acids. Here, we developed and validated FUME-TCRseq, a robust and sensitive RNA-based TCR sequencing methodology that is suitable for formalin-fixed paraffin-embedded samples and low amounts of input material. FUME-TCRseq incorporates unique molecular identifiers into each molecule of cDNA, allowing correction for sequencing errors and PCR bias. Using RNA extracted from colorectal and head and neck cancers to benchmark the accuracy and sensitivity of FUME-TCRseq against existing methods demonstrated excellent concordance between the datasets. Furthermore, FUME-TCRseq detected more clonotypes than a commercial RNA-based alternative, with shorter library preparation time and significantly lower cost. The high sensitivity and the ability to sequence RNA of poor quality and limited amount enabled quantitative analysis of small numbers of cells from archival tissue sections, which is not possible with other methods. Spatially resolved FUME-TCRseq analysis of colorectal cancers using macrodissected archival samples revealed the shifting T-cell landscapes at the transition to an invasive phenotype and between tumor subclones containing distinct driver alterations. In summary, FUME-TCRseq represents an accurate, sensitive, and low-cost tool for the characterization of T-cell repertoires, particularly in samples with low-quality RNA that have not been accessible using existing methodology. SIGNIFICANCE: FUME-TCRseq is a TCR sequencing methodology that supports sensitive and spatially resolved detection of TCR clones in archival clinical specimens, which can facilitate longitudinal tracking of immune responses through disease course and treatment.

Generation of a C57BL/6J mouse strain expressing the CD45.1 epitope to improve hematopoietic stem cell engraftment and adoptive cell transfer experiments.

Adoptive cell transfer between genetically identical hosts relies on the use of a congenic marker to distinguish the donor cells from the host cells. CD45, a glycoprotein expressed by all hematopoietic cells, is one of the main congenic markers used because its two isoforms, CD45.1 and CD45.2, can be discriminated by flow cytometry. As a consequence, C57BL/6J (B6; CD45.2) and B6.SJL-Ptprca Pepcb/BoyJ (B6.SJL; CD45.1) mice are widely used in adoptive cell transfer experiments, under the presumption that they differ only at the CD45 (Ptprc) locus. However, recent studies have identified genetic variations between these congenic strains and have notably highlighted a differential expression of cathepsin E (CTSE). The B6.SJL mouse presents a number of functional differences in hematopoietic stem cell engraftment potential and immune cell numbers compared with the B6 mouse. In this study, we showed that B6 and B6.SJL mice also differ in their CD8+ T cell compartment and CD8+ T cell responses to viral infection. We identified Ctse as the most differentially expressed gene between CD8+ T cells of B6 and B6.SJL and demonstrated that the differences reported between these two mouse strains are not due to CTSE. Finally, using CRISPR-Cas9 genome editing, we generated a CD45.1-expressing B6 mouse by inserting one nucleotide mutation (A904G) leading to an amino acid change (K302E) in the Ptprc gene of the B6 mouse. We showed that this new B6-Ptprcem(K302E)Jmar/J mouse resolves the experimental biases reported between the B6 and B6.SJL mouse lines and should thus represent the new gold standard for adoptive cell transfer experiments in B6.

Evolutionary and immune microenvironment dynamics during neoadjuvant treatment of oesophagael adenocarcinoma.

Locally advanced oesophageal adenocarcinoma (EAC) remains difficult to treat because of common resistance to neoadjuvant therapy and high recurrence rates. The ecological and evolutionary dynamics responsible for treatment failure are incompletely understood. Here, we performed a comprehensive multi-omic analysis of samples collected from EAC patients in the MEMORI clinical trial, revealing major changes in gene expression profiles and immune microenvironment composition that did not appear to be driven by changes in clonal composition. Multi-region multi-timepoint whole exome (300x depth) and paired transcriptome sequencing was performed on 27 patients pre-, during and after neoadjuvant treatment. EAC showed major transcriptomic changes during treatment with upregulation of immune and stromal pathways and oncogenic pathways such as KRAS, Hedgehog and WNT. However, genetic data revealed that clonal sweeps were rare, suggesting that gene expression changes were not clonally driven. Additional longitudinal image mass cytometry was performed in a subset of 15 patients and T-cell receptor sequencing in 10 patients, revealing remodelling of the T-cell compartment during treatment and other shifts in microenvironment composition. The presence of immune escape mechanisms and a lack of clonal T-cell expansions were linked to poor clinical treatment response. This study identifies profound transcriptional changes during treatment with limited evidence that clonal replacement is the cause, suggesting phenotypic plasticity and immune dynamics as mechanisms for therapy resistance with pharmacological relevance.

Signatures of T cell immunity revealed using sequence similarity with TCRDivER algorithm.

Changes in the T cell receptor (TCR) repertoires have become important markers for monitoring disease or therapy progression. With the rise of immunotherapy usage in cancer, infectious and autoimmune disease, accurate assessment and comparison of the "state" of the TCR repertoire has become paramount. One important driver of change within the repertoire is T cell proliferation following immunisation. A way of monitoring this is by investigating large clones of individual T cells believed to bind epitopes connected to the disease. However, as a single target can be bound by many different TCRs, monitoring individual clones cannot fully account for T cell cross-reactivity. Moreover, T cells responding to the same target often exhibit higher sequence similarity, which highlights the importance of accounting for TCR similarity within the repertoire. This complexity of binding relationships between a TCR and its target convolutes comparison of immune responses between individuals or comparisons of TCR repertoires at different timepoints. Here we propose TCRDivER algorithm (T cell Receptor Diversity Estimates for Repertoires), a global method of T cell repertoire comparison using diversity profiles sensitive to both clone size and sequence similarity. This approach allowed for distinction between spleen TCR repertoires of immunised and non-immunised mice, showing the need for including both facets of repertoire changes simultaneously. The analysis revealed biologically interpretable relationships between sequence similarity and clonality. These aid in understanding differences and separation of repertoires stemming from different biological context. With the rise of availability of sequencing data we expect our tool to find broad usage in clinical and research applications.

T-cell receptor determinants of response to chemoradiation in locally-advanced HPV16-driven malignancies.

Background: The effect of chemoradiation on the anti-cancer immune response is being increasingly acknowledged; however, its clinical implications in treatment responses are yet to be fully understood. Human papillomavirus (HPV)-driven malignancies express viral oncogenic proteins which may serve as tumor-specific antigens and represent ideal candidates for monitoring the peripheral T-cell receptor (TCR) changes secondary to chemoradiotherapy (CRT). Methods: We performed intra-tumoral and pre- and post-treatment peripheral TCR sequencing in a cohort of patients with locally-advanced HPV16-positive cancers treated with CRT. An in silico computational pipeline was used to cluster TCR repertoire based on epitope-specificity and to predict affinity between these clusters and HPV16-derived epitopes. Results: Intra-tumoral repertoire diversity, intra-tumoral and post-treatment peripheral CDR3ß similarity clustering were predictive of response. In responders, CRT triggered an increase peripheral TCR clonality and clonal relatedness. Post-treatment expansion of baseline peripheral dominant TCRs was associated with response. Responders showed more baseline clustered structures of TCRs maintained post-treatment and displayed significantly more maintained clustered structures. When applying clustering by TCR-specificity methods, responders displayed a higher proportion of intra-tumoral TCRs predicted to recognise HPV16 peptides. Conclusions: Baseline TCR characteristics and changes in the peripheral T-cell clones triggered by CRT are associated with treatment outcome. Maintenance and boosting of pre-existing clonotypes are key elements of an effective anti-cancer immune response driven by CRT, supporting a paradigm in which the immune system plays a central role in the success of CRT in current standard-of-care protocols.

The Intra-Tumoral T Cell Receptor Repertoire: Steps Towards a Useful Clinical Biomarker.

Adaptive immunity recognizes and responds to tumors, although they are part of the immunological "self." T cells, both CD4+ and CD8+, play a key role in the process, and the specific set of receptors which recognize tumor antigens therefore has the potential to provide prognostic biomarkers for tracking tumor growth after cancer therapy, including immunotherapy. Most published data on the T cell repertoire continue to rely on commercial proprietary methods, which often do not allow access to the raw data, and are difficult to validate. We describe an open-source protocol for amplifying, sequencing, and analyzing T cell receptors which is economical, robust, sensitive, and versatile. The key experimental step is the ligation of a single-stranded oligonucleotide to the 3' end of the T cell receptor cDNA, which allows easy amplification of all possible rearrangements using only a single set of primers per locus, while simultaneously introducing a unique molecular identifier to label each starting cDNA molecule. After sequencing, this molecular identifier can be used to correct both sequence errors and the effects of differential PCR amplification efficiency, thus producing a more accurate measure of the true T cell receptor frequency within the sample. Samples are then tagged with unique pairs of indices, facilitating robotic scale-up and significantly reducing cross-sample contamination from index hopping. This method has been applied to the analysis of tumor-infiltrating lymphocytes and matched peripheral blood samples from patients with a variety of solid tumors.

Tracking down tumor-specific T cells.

Two papers published in this edition of Cancer Cell (Zheng et al., 2022 and Veatch et al., 2022) provide an elegant illustration of how single-cell sequencing can be used to define a molecular phenotype which identifies tumor-specific T cells.

Information-Driven Docking for TCR-pMHC Complex Prediction.

T cell receptor (TCR) recognition of peptides presented by major histocompatibility complex (MHC) molecules is a fundamental process in the adaptive immune system. An understanding of this recognition process at the molecular level is crucial for TCR based therapeutics and vaccine design. The broad nature of TCR diversity and cross-reactivity presents a challenge for traditional structural resolution. Computational modelling of TCR-pMHC complexes offers an efficient alternative. This study compares the ability of four general-purpose docking platforms (ClusPro, LightDock, ZDOCK and HADDOCK) to make use of varying levels of binding interface information for accurate TCR-pMHC modelling. Each platform was tested on an expanded benchmark set of 44 TCR-pMHC docking cases. In general, HADDOCK is shown to be the best performer. Docking strategy guidance is provided to obtain the best models for each platform for future research. The TCR-pMHC docking cases used in this study can be downloaded from https://github.com/innate2adaptive/ExpandedBenchmark.

Increased Immune-Regulatory Receptor Expression on Effector T Cells as Early Indicators of Relapse Following Autologous Stem Cell Transplantation for Multiple Myeloma.

The benefit of autologous stem cell transplantation (ASCT) in newly diagnosed myeloma patients, apart from supporting high dose chemotherapy, may include effects on T cell function in the bone marrow (BM). We report our exploratory findings on marrow infiltrating T cells early post-ASCT (day+100), examining phenotype and T cell receptor (TCR) repertoire, seeking correlations with timing of relapse. Compared to healthy donors (HD), we observed an increase in regulatory T cells (CD4+FoxP3+, Tregs) with reduction in CD4 T cells, leading to lower CD4:8 ratios. Compared to paired pre-treatment marrow, both CD4 and CD8 compartments showed a reduction in naïve, and increase in effector memory subsets, suggestive of a more differentiated phenotype. This was supported by increased levels of several immune-regulatory and activation proteins (ICOS, PD-1, LAG-3, CTLA-4 and GzmB) when compared with HD. Unsupervised analysis identified a patient subgroup with shorter PFS (p=0.031) whose BM contained increased Tregs, and higher immune-regulatory markers (ICOS, PD-1, LAG-3) on effector T cells. Using single feature analysis, higher frequencies of marrow PD-1+ on CD4+FoxP3- cells and Ki67+ on CD8 cells were independently associated with early relapse. Finally, studying paired pre-treatment and post-ASCT BM (n=5), we note reduced abundance of TCR sequences at day+100, with a greater proportion of expanded sequences indicating a more focused persistent TCR repertoire. Our findings indicate that, following induction chemotherapy and ASCT, marrow T cells demonstrate increased activation and differentiation, with TCR repertoire focusing. Pending confirmation in larger series, higher levels of immune-regulatory proteins on T cell effectors at day+100 may indicate early relapse.

The clonal structure and dynamics of the human T cell response to an organic chemical hapten.

Diphenylcyclopropenone (DPC) is an organic chemical hapten which induces allergic contact dermatitis and is used in the treatment of warts, melanoma, and alopecia areata. This therapeutic setting therefore provided an opportunity to study T cell receptor (TCR) repertoire changes in response to hapten sensitization in humans. Repeated exposure to DPC induced highly dynamic transient expansions of a polyclonal diverse T cell population. The number of TCRs expanded early after sensitization varies between individuals and predicts the magnitude of the allergic reaction. The expanded TCRs show preferential TCR V and J gene usage and consist of clusters of TCRs with similar sequences, two characteristic features of antigen-driven responses. The expanded TCRs share subtle sequence motifs that can be captured using a dynamic Bayesian network. These observations suggest the response to DPC is mediated by a polyclonal population of T cells recognizing a small number of dominant antigens.

T cell receptor sequence clustering and antigen specificity.

There has been increasing interest in the role of T cells and their involvement in cancer, autoimmune and infectious diseases. However, the nature of T cell receptor (TCR) epitope recognition at a repertoire level is not yet fully understood. Due to technological advances a plethora of TCR sequences from a variety of disease and treatment settings has become readily available. Current efforts in TCR specificity analysis focus on identifying characteristics in immune repertoires which can explain or predict disease outcome or progression, or can be used to monitor the efficacy of disease therapy. In this context, clustering of TCRs by sequence to reflect biological similarity, and especially to reflect antigen specificity have become of paramount importance. We review the main TCR sequence clustering methods and the different similarity measures they use, and discuss their performance and possible improvement. We aim to provide guidance for non-specialists who wish to use TCR repertoire sequencing for disease tracking, patient stratification or therapy prediction, and to provide a starting point for those aiming to develop novel techniques for TCR annotation through clustering.

The T cell differentiation landscape is shaped by tumour mutations in lung cancer.

Tumour mutational burden (TMB) predicts immunotherapy outcome in non-small cell lung cancer (NSCLC), consistent with immune recognition of tumour neoantigens. However, persistent antigen exposure is detrimental for T cell function. How TMB affects CD4 and CD8 T cell differentiation in untreated tumours, and whether this affects patient outcomes is unknown. Here we paired high-dimensional flow cytometry, exome, single-cell and bulk RNA sequencing from patients with resected, untreated NSCLC to examine these relationships. TMB was associated with compartment-wide T cell differentiation skewing, characterized by loss of TCF7-expressing progenitor-like CD4 T cells, and an increased abundance of dysfunctional CD8 and CD4 T cell subsets, with significant phenotypic and transcriptional similarity to neoantigen-reactive CD8 T cells. A gene signature of redistribution from progenitor-like to dysfunctional states associated with poor survival in lung and other cancer cohorts. Single-cell characterization of these populations informs potential strategies for therapeutic manipulation in NSCLC.

Publisher Correction: Spatial heterogeneity of the T cell receptor repertoire reflects the mutational landscape in lung cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Quantitative analysis of the T cell receptor repertoire.

The T cell receptor repertoire provides a window into the cellular adaptive immune response. In the context of cancer, determining the repertoire within a tumor can give important insights into the evolution of the T cell anti-cancer response, and has the potential to identify specific personalized biomarkers for tracking host responses during cancer therapy, including immunotherapy. We describe a protocol for amplifying, sequencing and analyzing T cell receptors which is economical, robust, sensitive and versatile. The key experimental step is the ligation of a single stranded oligonucleotide to the 3' end of the T cell receptor cDNA, which allows easy amplification of all possible rearrangements using only a single set of primers per locus, while simultaneously introducing a unique molecular identifier to label each starting cDNA molecule. After sequencing, this molecular identifier can be used to correct both sequence errors and the effects of differential PCR amplification efficiency, thus producing a more accurate measure of the true T cell receptor frequency within the sample. We describe a detailed protocol describing this method to create libraries of T cell receptors from in vitro T cell cultures, blood or tissue samples. We combine this with a computational pipeline, which incorporates sample multiplexing, T cell receptor annotation and error correction to provide accurate counts of individual T cell receptor sequences within samples. The integrated experimental and computational pipeline should be of value to researchers interested in documenting and understanding the T cell immune response to cancer, and in manipulating it for therapeutic purposes.

Spatial heterogeneity of the T cell receptor repertoire reflects the mutational landscape in lung cancer.

Somatic mutations together with immunoediting drive extensive heterogeneity within non-small-cell lung cancer (NSCLC). Herein we examine heterogeneity of the T cell antigen receptor (TCR) repertoire. The number of TCR sequences selectively expanded in tumors varies within and between tumors and correlates with the number of nonsynonymous mutations. Expanded TCRs can be subdivided into TCRs found in all tumor regions (ubiquitous) and those present in a subset of regions (regional). The number of ubiquitous and regional TCRs correlates with the number of ubiquitous and regional nonsynonymous mutations, respectively. Expanded TCRs form part of clusters of TCRs of similar sequence, suggestive of a spatially constrained antigen-driven process. CD8+ tumor-infiltrating lymphocytes harboring ubiquitous TCRs display a dysfunctional tissue-resident phenotype. Ubiquitous TCRs are preferentially detected in the blood at the time of tumor resection as compared to routine follow-up. These findings highlight a noninvasive method to identify and track relevant tumor-reactive TCRs for use in adoptive T cell immunotherapy.

Neoantigen-directed immune escape in lung cancer evolution.

The interplay between an evolving cancer and a dynamic immune microenvironment remains unclear. Here we analyse 258 regions from 88 early-stage, untreated non-small-cell lung cancers using RNA sequencing and histopathology-assessed tumour-infiltrating lymphocyte estimates. Immune infiltration varied both between and within tumours, with different mechanisms of neoantigen presentation dysfunction enriched in distinct immune microenvironments. Sparsely infiltrated tumours exhibited a waning of neoantigen editing during tumour evolution, indicative of historical immune editing, or copy-number loss of previously clonal neoantigens. Immune-infiltrated tumour regions exhibited ongoing immunoediting, with either loss of heterozygosity in human leukocyte antigens or depletion of expressed neoantigens. We identified promoter hypermethylation of genes that contain neoantigenic mutations as an epigenetic mechanism of immunoediting. Our results suggest that the immune microenvironment exerts a strong selection pressure in early-stage, untreated non-small-cell lung cancers that produces multiple routes to immune evasion, which are clinically relevant and forecast poor disease-free survival.

An Economical, Quantitative, and Robust Protocol for High-Throughput T Cell Receptor Sequencing from Tumor or Blood.

The T cell receptor repertoire provides a window to the cellular adaptive immune response within a tumor, and has the potential to identify specific and personalized biomarkers for tracking host responses during cancer therapy, including immunotherapy. We describe a protocol for amplifying, sequencing, and analyzing T cell receptors which is economical, robust, sensitive, and versatile. The key experimental step is the ligation of a single-stranded oligonucleotide to the 3' end of the T cell receptor cDNA, which allows easy amplification of all possible rearrangements using only a single set of primers per locus, while simultaneously introducing a unique molecular identifier to label each starting cDNA molecule. After sequencing, this molecular identifier can be used to correct both sequence errors and the effects of differential PCR amplification efficiency, thus producing a more accurate measure of the true T cell receptor frequency within the sample. This method has been applied to the analysis of unfractionated human tumor lysates, subpopulations of tumor-infiltrating lymphocytes, and peripheral blood samples from patients with a variety of solid tumors.

Clinical T Cell Receptor Repertoire Deep Sequencing and Analysis: An Application to Monitor Immune Reconstitution Following Cord Blood Transplantation.

Spectratyping assays are well recognized as the clinical gold standard for assessing the T cell receptor (TCR) repertoire in haematopoietic stem cell transplant (HSCT) recipients. These assays use length distributions of the hyper variable complementarity-determining region 3 (CDR3) to characterize a patient's T cell immune reconstitution post-transplant. However, whilst useful, TCR spectratyping is notably limited by its resolution, with the technique unable to provide data on the individual clonotypes present in a sample. High-resolution clonotype data are necessary to provide quantitative clinical TCR assessments and to better understand clonotype dynamics during clinically relevant events such as viral infections or GvHD. In this study we developed and applied a CDR3 Next Generation Sequencing (NGS) methodology to assess the TCR repertoire in cord blood transplant (CBT) recipients. Using this, we obtained comprehensive TCR data from 16 CBT patients and 5 control cord samples at Great Ormond Street Hospital (GOSH). These were analyzed to provide a quantitative measurement of the TCR repertoire and its constituents in patients post-CBT. We were able to both recreate and quantify inferences typically drawn from spectratyping data. Additionally, we demonstrate that an NGS approach to TCR assessment can provide novel insights into the recovery of the immune system in these patients. We show that NGS can be used to accurately quantify TCR repertoire diversity and to provide valuable inference on clonotypes detected in a sample. We serially assessed the progress of T cell immune reconstitution demonstrating that there is dramatic variation in TCR diversity immediately following transplantation and that the dynamics of T cell immune reconstitution is perturbed by the presence of GvHD. These findings provide a proof of concept for the adoption of NGS TCR sequencing in clinical practice.

Exploring Carbon Nanomaterial Diversity for Nucleation of Protein Crystals.

Controlling crystal nucleation is a crucial step in obtaining high quality protein crystals for structure determination by X-ray crystallography. Carbon nanomaterials (CNMs) including carbon nanotubes, graphene oxide, and carbon black provide a range of surface topographies, porosities and length scales; functionalisation with two different approaches, gas phase radical grafting and liquid phase reductive grafting, provide routes to a range of oligomer functionalised products. These grafted materials, combined with a range of controls, were used in a large-scale assessment of the effectiveness for protein crystal nucleation of 20 different carbon nanomaterials on five proteins. This study has allowed a direct comparison of the key characteristics of carbon-based nucleants: appropriate surface chemistry, porosity and/or roughness are required. The most effective solid system tested in this study, carbon black nanoparticles functionalised with poly(ethylene glycol) methyl ether of mean molecular weight 5000, provides a novel highly effective nucleant, that was able to induce crystal nucleation of four out of the five proteins tested at metastable conditions.

Pre-clinical assessment of autologous DC-based therapy in ovarian cancer patients with progressive disease.

Dendritic cell-based vaccines offer promise for therapy of ovarian cancer. Previous studies have demonstrated that oxidation of several antigens, including ovarian cancer cells, using hypochlorous acid strongly enhances their immunogenicity and their uptake and presentation by dendritic cells. The response of T cells and dendritic cells to autologous tumour from patients with active disease has not previously been investigated. Monocyte-derived dendritic cells were generated from patients with active disease and activated by co-culture with oxidised tumour cells and the TLR agonist poly I:C. The dendritic cells showed an activated phenotype, but secreted high levels of TGFß. Co-culture of the antigen-loaded dendritic cells with autologous T cells generated a population of effector T cells that showed a low level of specific lytic activity against autologous tumour, as compared to autologous mesothelium. The addition of neutralising antibody to TGFß in DC/T cell co-cultures increased the levels of subsequent tumour killing in three samples tested. Co-culture of monocytes from healthy volunteers with the ovarian cell line SKOV-3 prior to differentiation into dendritic cells reduced the ability of dendritic cells to stimulate cytotoxic effector cells. The study suggests that co-culture of dendritic cells with oxidised tumour cells can generate effector cells able to kill autologous tumour, but that the high tumour burden in patients with active disease may compromise dendritic cell and/or T cell function.