Peptide/MHC tetramer-based sorting of CD8⁺ T cells to a leukemia antigen yields clonotypes drawn nonspecifically from an underlying restricted repertoire

Retina-arrestin specific CD8+ T cells are not implicated in HLA-A29-positive birdshot chorioretinitis

BACKGROUND

HLA-A29-positive birdshot chorioretinitis (BCR) is an inflammatory eye disorder that is generally assumed to be caused by an autoimmune response to HLA-A29-presented peptides from retinal arrestin (SAG), yet the epitopes recognized by CD8+ T cells from patients remain to be identified.

OBJECTIVES

The identification of natural ligands of SAG presented by HLA-A29. To quantify CD8+ T cells reactive to antigenic SAG peptides presented by HLA-A29 in patients and controls.

METHODS

We performed mass-spectrometry based immunopeptidomics of HLA-A29 of antigen-presenting cell lines from patients engineered to express SAG. MHC-I Dextramer technology was utilised to determine expansion of antigen-specific CD8+ T cells reactive to SAG peptides in complex with HLA-A29 in a cohort of BCR patients, HLA-A29-positive controls, and HLA-A29-negative controls.

RESULTS

We report on the naturally presented antigenic SAG peptides identified by sequencing the HLA-A29 immunopeptidome of antigen-presenting cells of patients. We show that the N-terminally extended SAG peptide precursors can be trimmed in vitro by the antigen-processing aminopeptidases ERAP1 and ERAP2. Unexpectedly, no enhanced antigen engagement by CD8+ T cells upon stimulation with SAG peptides was observed in patients or HLA-A29-positive controls. Multiplexed HLA-A29-peptide dextramer profiling of a case-control cohort revealed that CD8+ T cells specific for these SAG peptides were neither detectable in peripheral blood nor in eye biopsies of patients.

CONCLUSIONS

Collectively, these findings demonstrate that SAG is not a CD8+ T cell autoantigen and sharply contrast the paradigm in the pathogenesis of BCR. Therefore, the mechanism by which HLA-A29 is associated with BCR does not involve SAG.

Comprehensive Analysis of the Immunogenomics of Triple-Negative Breast Cancer Brain Metastases From LCCC1419

Background

Triple negative breast cancer (TNBC) is an aggressive variant of breast cancer that lacks the expression of estrogen and progesterone receptors (ER and PR) and HER2. Nearly 50% of patients with advanced TNBC will develop brain metastases (BrM), commonly with progressive extracranial disease. Immunotherapy has shown promise in the treatment of advanced TNBC; however, the immune contexture of BrM remains largely unknown. We conducted a comprehensive analysis of TNBC BrM and matched primary tumors to characterize the genomic and immune landscape of TNBC BrM to inform the development of immunotherapy strategies in this aggressive disease.

Methods

Whole-exome sequencing (WES) and RNA sequencing were conducted on formalin-fixed, paraffin-embedded samples of BrM and primary tumors of patients with clinical TNBC (n = 25, n = 9 matched pairs) from the LCCC1419 biobank at UNC—Chapel Hill. Matched blood was analyzed by DNA sequencing as a comparison for tumor WES for the identification of somatic variants. A comprehensive genomics assessment, including mutational and copy number alteration analyses, neoantigen prediction, and transcriptomic analysis of the tumor immune microenvironment were performed.

Results

Primary and BrM tissues were confirmed as TNBC (23/25 primaries, 16/17 BrM) by immunohistochemistry and of the basal intrinsic subtype (13/15 primaries and 16/19 BrM) by PAM50. Compared to primary tumors, BrM demonstrated a higher tumor mutational burden. TP53 was the most frequently mutated gene and was altered in 50% of the samples. Neoantigen prediction showed elevated cancer testis antigen- and endogenous retrovirus-derived MHC class I-binding peptides in both primary tumors and BrM and predicted that single-nucleotide variant (SNV)-derived peptides were significantly higher in BrM. BrM demonstrated a reduced immune gene signature expression, although a signature associated with fibroblast-associated wound healing was elevated in BrM. Metrics of T and B cell receptor diversity were also reduced in BrM.

Conclusions

BrM harbored higher mutational burden and SNV-derived neoantigen expression along with reduced immune gene signature expression relative to primary TNBC. Immune signatures correlated with improved survival, including T cell signatures. Further research will expand these findings to other breast cancer subtypes in the same biobank. Exploration of immunomodulatory approaches including vaccine applications and immune checkpoint inhibition to enhance anti-tumor immunity in TNBC BrM is warranted.

Tetramer-Associated T Cell Receptor Sequencing

Linking antigen specificity to T cell receptor (TCR) sequences is critical, albeit challenging, to both understanding T cell biology and developing T cell-based therapeutics. Here, we describe in detail tetramer-associated TCR sequencing (TetTCR-Seq), a novel approach to tackling this challenge. TetTCR-Seq is accomplished by multiplexing DNA-barcoded peptide-MHC (pMHC) tetramers, allowing for simultaneous recall of antigen specificity and TCR sequences after single cell sequencing. Additionally, TetTCR-Seq simplifies labor and cuts cost by taking advantage of in vitro transcription and translation (IVTT) to generate peptide libraries and DNA barcodes, in parallel, from the same template. Thus, TetTCR-Seq is a powerful technology capable of quickly and affordably surveying the T cell repertoire for hundreds of antigen specificities in a single experiment.

FACS isolation of low percentage human antigen-specific CD8+ T cells based on activation-induced CD3 and CD8 downregulation

As T cell activation leads to downregulation of T cell receptor (TCR) and coreceptor CD8, we developed a novel FACS-based sorting method to enrich activated antigen-specific CD8⁺ T cells. Using multiple established or low percentage T cell cultures, with either single antigen specificity or multiple influenza A virus antigen specificities, we have optimized the sorting method for T cell activation time and stimulating antigen dose. We have also sorted various numbers of antigen-specific CD8⁺ T cells into 96-well plates to demonstrate these T cells are capable of expanding into nearly pure CD8⁺ T cell lines. Our approach has the advantage of sorting antigen-specific T cells without knowing their specific antigenic epitopes or restricting HLA. We believe this method can be very helpful for successfully establishing CD8⁺ T cell lines for various purpose, including immunotherapy.

Computational modeling and confirmation of leukemia-associated minor histocompatibility antigens

T-cell responses to minor histocompatibility antigens (mHAs) mediate both antitumor immunity (graft-versus-leukemia [GVL]) and graft-versus-host disease (GVHD) in allogeneic stem cell transplant. Identifying mHAs with high allele frequency, tight binding affinity to common HLA molecules, and narrow tissue restriction could enhance immunotherapy against leukemia. Genotyping and HLA allele data from 101 HLA-matched donor-recipient pairs (DRPs) were computationally analyzed to predict both class I and class II mHAs likely to induce either GVL or GVHD. Roughly twice as many mHAs were predicted in HLA-matched unrelated donor (MUD) stem cell transplantation (SCT) compared with HLA-matched related transplants, an expected result given greater genetic disparity in MUD SCT. Computational analysis predicted 14 of 18 previously identified mHAs, with 2 minor antigen mismatches not being contained in the patient cohort, 1 missed mHA resulting from a noncanonical translation of the peptide antigen, and 1 case of poor binding prediction. A predicted peptide epitope derived from GRK4, a protein expressed in acute myeloid leukemia and testis, was confirmed by targeted differential ion mobility spectrometry-tandem mass spectrometry. T cells specific to UNC-GRK4-V were identified by tetramer analysis both in DRPs where a minor antigen mismatch was predicted and in DRPs where the donor contained the allele encoding UNC-GRK4-V, suggesting that this antigen could be both an mHA and a cancer-testis antigen. Computational analysis of genomic and transcriptomic data can reliably predict leukemia-associated mHA and can be used to guide targeted mHA discovery.

T Cell Receptor Profiling in Type 1 Diabetes

PURPOSE OF REVIEW

The genetic susceptibility and dominant protection for type 1 diabetes (T1D) associated with human leukocyte antigen (HLA) haplotypes, along with minor risk variants, have long been thought to shape the T cell receptor (TCR) repertoire and eventual phenotype of autoreactive T cells that mediate β-cell destruction. While autoantibodies provide robust markers of disease progression, early studies tracking autoreactive T cells largely failed to achieve clinical utility.

RECENT FINDINGS

Advances in acquisition of pancreata and islets from T1D organ donors have facilitated studies of T cells isolated from the target tissues. Immunosequencing of TCR α/β-chain complementarity determining regions, along with transcriptional profiling, offers the potential to transform biomarker discovery. Herein, we review recent studies characterizing the autoreactive TCR signature in T1D, emerging technologies, and the challenges and opportunities associated with tracking TCR molecular profiles during the natural history of T1D.

Identification and isolation of antigen-specific cytotoxic T lymphocytes with an automated microraft sorting system

The simultaneous measurement of T cell function with recovery of individual T cells would greatly facilitate characterizing antigen-specific responses both in vivo and in model systems. We have developed a microraft array methodology that automatically measures the ability of individual T cells to kill a population of target cells and viably sorts specific cells into a 96-well plate for expansion. A human T cell culture was generated against the influenza M1p antigen. Individual microrafts on a 70 × 70 array were loaded with on average 1 CD8+ cell from the culture and a population of M1p presenting target cells. Target cell killing, measured by fluorescence microscopy, was quantified in each microraft. The rates of target cell death among the individual CD8+ T cells varied greatly; however, individual T cells maintained their rates of cytotoxicity throughout the time course of the experiment enabling rapid identification of highly cytotoxic CD8+ T cells. Microrafts with highly active CD8+ T cells were individually transferred to wells of a 96-well plate, using a needle-release device coupled to the microscope. Three sorted T cells clonally expanded. All of these expressed high-avidity T cell receptors for M1p/HLA*02:01 tetramers, and 2 of the 3 receptors were sequenced. While this study investigated single T cell cytotoxicity rates against simple targets with subsequent cell sorting, future studies will involve measuring T cell mediated cytotoxicity in more complex cellular environments, enlarging the arrays to identify very rare antigen specific T cells, and measuring single cell CD4+ and CD8+ T cell proliferation.

Assembly-based inference of B-cell receptor repertoires from short read RNA sequencing data with V'DJer

Motivation: B-cell receptor (BCR) repertoire profiling is an important tool for understanding the biology of diverse immunologic processes. Current methods for analyzing adaptive immune receptor repertoires depend upon PCR amplification of VDJ rearrangements followed by long read amplicon sequencing spanning the VDJ junctions. While this approach has proven to be effective, it is frequently not feasible due to cost or limited sample material. Additionally, there are many existing datasets where short-read RNA sequencing data are available but PCR amplified BCR data are not.

Results: We present here V’DJer, an assembly-based method that reconstructs adaptive immune receptor repertoires from short-read RNA sequencing data. This method captures expressed BCR loci from a standard RNA-seq assay. We applied this method to 473 Melanoma samples from The Cancer Genome Atlas and demonstrate V’DJer’s ability to accurately reconstruct BCR repertoires from short read mRNA-seq data.

Availability and Implementation: V’DJer is implemented in C/C ++, freely available for academic use and can be downloaded from Github: https://github.com/mozack/vdjer

Contact:benjamin_vincent@med.unc.edu or parkerjs@email.unc.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

Dynamical System Modeling to Simulate Donor T Cell Response to Whole Exome Sequencing-Derived Recipient Peptides Demonstrates Different Alloreactivity Potential in HLA-Matched and -Mismatched Donor-Recipient Pairs

Immune reconstitution kinetics and subsequent clinical outcomes in HLA-matched recipients of allogeneic stem cell transplantation (SCT) are variable and difficult to predict. Considering SCT as a dynamical system may allow sequence differences across the exomes of the transplant donors and recipients to be used to simulate an alloreactive T cell response, which may allow better clinical outcome prediction. To accomplish this, whole exome sequencing was performed on 34 HLA-matched SCT donor-recipient pairs (DRPs) and the nucleotide sequence differences translated to peptides. The binding affinity of the peptides to the relevant HLA in each DRP was determined. The resulting array of peptide-HLA binding affinity values in each patient was considered as an operator modifying a hypothetical T cell repertoire vector, in which each T cell clone proliferates in accordance with the logistic equation of growth. Using an iterating system of matrices, each simulated T cell clone's growth was calculated with the steady-state population being proportional to the magnitude of the binding affinity of the driving HLA-peptide complex. Incorporating competition between T cell clones responding to different HLA-peptide complexes reproduces a number of features of clinically observed T cell clonal repertoire in the simulated repertoire, including sigmoidal growth kinetics of individual T cell clones and overall repertoire, Power Law clonal frequency distribution, increase in repertoire complexity over time with increasing clonal diversity, and alteration of clonal dominance when a different antigen array is encountered, such as in SCT. The simulated, alloreactive T cell repertoire was markedly different in HLA-matched DRPs. The patterns were differentiated by rate of growth and steady-state magnitude of the simulated T cell repertoire and demonstrate a possible correlation with survival. In conclusion, exome wide sequence differences in DRPs may allow simulation of donor alloreactive T cell response to recipient antigens and may provide a quantitative basis for refining donor selection and titration of immunosuppression after SCT.

Immunotherapies and immune biomarkers in Type 1 diabetes: A partnership for success

The standard of care (SoC) for Type 1 diabetes (T1D) today is much the same as it was in the early 1920s, simply with more insulin options-fast-acting, slow-acting, injectable, and inhalable insulins. However, these well-tolerated treatments only manage the symptoms and complications, but do nothing to halt the underlying immune response. There is an unmet need for better treatment options for T1D that address all aspects of the disease. For decades, we have successfully treated T1D in preclinical animal models with immune-modifying therapies that have not demonstrated comparable efficacy in humans. The path to bringing such options to the clinic will depend on the implementation and standard inclusion of biomarkers of immune and therapeutic efficacy in T1D clinical trials, and dictate if we can create a new SoC that treats the underlying autoimmunity as well as the symptoms it causes.