Antigen presentation profiling reveals recognition of lymphoma immunoglobulin neoantigens.

Cancer somatic mutations can generate neoantigens that distinguish malignant from normal cells. However, the personalized identification and validation of neoantigens remains a major challenge. Here we discover neoantigens in human mantle-cell lymphomas by using an integrated genomic and proteomic strategy that interrogates tumour antigen peptides presented by major histocompatibility complex (MHC) class I and class II molecules. We applied this approach to systematically characterize MHC ligands from 17 patients. Remarkably, all discovered neoantigenic peptides were exclusively derived from the lymphoma immunoglobulin heavy- or light-chain variable regions. Although we identified MHC presentation of private polymorphic germline alleles, no mutated peptides were recovered from non-immunoglobulin somatically mutated genes. Somatic mutations within the immunoglobulin variable region were almost exclusively presented by MHC class II. We isolated circulating CD4+ T cells specific for immunoglobulin-derived neoantigens and found these cells could mediate killing of autologous lymphoma cells. These results demonstrate that an integrative approach combining MHC isolation, peptide identification, and exome sequencing is an effective platform to uncover tumour neoantigens. Application of this strategy to human lymphoma implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.

Minimal residual disease negativity using deep sequencing is a major prognostic factor in multiple myeloma.

The introduction of novel agents has led to major improvements in clinical outcomes for patients with multiple myeloma. To shorten evaluation times for new treatments, health agencies are currently examining minimal residual disease (MRD) as a surrogate end point in clinical trials. We assessed the prognostic value of MRD, measured during maintenance therapy by next-generation sequencing (NGS). MRD negativity was defined as the absence of tumor plasma cell within 1 000 000 bone marrow cells (<10-6). Data were analyzed from a recent clinical trial that evaluated the role of transplantation in newly diagnosed myeloma patients treated with lenalidomide, bortezomib, and dexamethasone (RVD). MRD negativity was achieved at least once during maintenance in 127 patients (25%). At the start of maintenance therapy, MRD was a strong prognostic factor for both progression-free survival (adjusted hazard ratio, 0.22; 95% confidence interval, 0.15-0.34; P < .001) and overall survival (adjusted hazard ratio, 0.24; 95% confidence interval, 0.11-0.54; P = .001). Patients who were MRD negative had a higher probability of prolonged progression-free survival than patients with detectable residual disease, regardless of treatment group (RVD vs transplant), cytogenetic risk profile, or International Staging System disease stage at diagnosis. These results were similar after completion of maintenance therapy. Our findings confirm the value of MRD status, as determined by NGS, as a prognostic biomarker in multiple myeloma, and suggest that this approach could be used to adapt treatment strategies in future clinical trials.

Analytical evaluation of the clonoSEQ Assay for establishing measurable (minimal) residual disease in acute lymphoblastic leukemia, chronic lymphocytic leukemia, and multiple myeloma.

BACKGROUND: The clonoSEQ® Assay (Adaptive Biotechnologies Corporation, Seattle, USA) identifies and tracks unique disease-associated immunoglobulin (Ig) sequences by next-generation sequencing of IgH, IgK, and IgL rearrangements and IgH-BCL1/2 translocations in malignant B cells. Here, we describe studies to validate the analytical performance of the assay using patient samples and cell lines. METHODS: Sensitivity and specificity were established by defining the limit of detection (LoD), limit of quantitation (LoQ) and limit of blank (LoB) in genomic DNA (gDNA) from 66 patients with multiple myeloma (MM), acute lymphoblastic leukemia (ALL), or chronic lymphocytic leukemia (CLL), and three cell lines. Healthy donor gDNA was used as a diluent to contrive samples with specific DNA masses and malignant-cell frequencies. Precision was validated using a range of samples contrived from patient gDNA, healthy donor gDNA, and 9 cell lines to generate measurable residual disease (MRD) frequencies spanning clinically relevant thresholds. Linearity was determined using samples contrived from cell line gDNA spiked into healthy gDNA to generate 11 MRD frequencies for each DNA input, then confirmed using clinical samples. Quantitation accuracy was assessed by (1) comparing clonoSEQ and multiparametric flow cytometry (mpFC) measurements of ALL and MM cell lines diluted in healthy mononuclear cells, and (2) analyzing precision study data for bias between clonoSEQ MRD results in diluted gDNA and those expected from mpFC based on original, undiluted samples. Repeatability of nucleotide base calls was assessed via the assay's ability to recover malignant clonotype sequences across several replicates, process features, and MRD levels. RESULTS: LoD and LoQ were estimated at 1.903 cells and 2.390 malignant cells, respectively. LoB was zero in healthy donor gDNA. Precision ranged from 18% CV (coefficient of variation) at higher DNA inputs to 68% CV near the LoD. Variance component analysis showed MRD results were robust, with expected laboratory process variations contributing ≤3% CV. Linearity and accuracy were demonstrated for each disease across orders of magnitude of clonal frequencies. Nucleotide sequence error rates were extremely low. CONCLUSIONS: These studies validate the analytical performance of the clonoSEQ Assay and demonstrate its potential as a highly sensitive diagnostic tool for selected lymphoid malignancies.

Prognostic value of deep sequencing method for minimal residual disease detection in multiple myeloma.

We assessed the prognostic value of minimal residual disease (MRD) detection in multiple myeloma (MM) patients using a sequencing-based platform in bone marrow samples from 133 MM patients in at least very good partial response (VGPR) after front-line therapy. Deep sequencing was carried out in patients in whom a high-frequency myeloma clone was identified and MRD was assessed using the IGH-VDJH, IGH-DJH, and IGK assays. The results were contrasted with those of multiparametric flow cytometry (MFC) and allele-specific oligonucleotide polymerase chain reaction (ASO-PCR). The applicability of deep sequencing was 91%. Concordance between sequencing and MFC and ASO-PCR was 83% and 85%, respectively. Patients who were MRD(-) by sequencing had a significantly longer time to tumor progression (TTP) (median 80 vs 31 months; P < .0001) and overall survival (median not reached vs 81 months; P = .02), compared with patients who were MRD(+). When stratifying patients by different levels of MRD, the respective TTP medians were: MRD ≥10(-3) 27 months, MRD 10(-3) to 10(-5) 48 months, and MRD <10(-5) 80 months (P = .003 to .0001). Ninety-two percent of VGPR patients were MRD(+). In complete response patients, the TTP remained significantly longer for MRD(-) compared with MRD(+) patients (131 vs 35 months; P = .0009).

Diverse somatic mutation patterns and pathway alterations in human cancers.

The systematic characterization of somatic mutations in cancer genomes is essential for understanding the disease and for developing targeted therapeutics. Here we report the identification of 2,576 somatic mutations across approximately 1,800 megabases of DNA representing 1,507 coding genes from 441 tumours comprising breast, lung, ovarian and prostate cancer types and subtypes. We found that mutation rates and the sets of mutated genes varied substantially across tumour types and subtypes. Statistical analysis identified 77 significantly mutated genes including protein kinases, G-protein-coupled receptors such as GRM8, BAI3, AGTRL1 (also called APLNR) and LPHN3, and other druggable targets. Integrated analysis of somatic mutations and copy number alterations identified another 35 significantly altered genes including GNAS, indicating an expanded role for galpha subunits in multiple cancer types. Furthermore, our experimental analyses demonstrate the functional roles of mutant GNAO1 (a Galpha subunit) and mutant MAP2K4 (a member of the JNK signalling pathway) in oncogenesis. Our study provides an overview of the mutational spectra across major human cancers and identifies several potential therapeutic targets.

Circulating tumour DNA and CT monitoring in patients with untreated diffuse large B-cell lymphoma: a correlative biomarker study.

BACKGROUND: Diffuse large-B-cell lymphoma is curable, but when treatment fails, outcome is poor. Although imaging can help to identify patients at risk of treatment failure, they are often imprecise, and radiation exposure is a potential health risk. We aimed to assess whether circulating tumour DNA encoding the clonal immunoglobulin gene sequence could be detected in the serum of patients with diffuse large-B-cell lymphoma and used to predict clinical disease recurrence after frontline treatment. METHODS: We used next-generation DNA sequencing to retrospectively analyse cell-free circulating tumour DNA in patients assigned to one of three treatment protocols between May 8, 1993, and June 6, 2013. Eligible patients had diffuse large-B-cell lymphoma, no evidence of indolent lymphoma, and were previously untreated. We obtained serial serum samples and concurrent CT scans at specified times during most treatment cycles and up to 5 years of follow-up. VDJ gene segments of the rearranged immunoglobulin receptor genes were amplified and sequenced from pretreatment specimens and serum circulating tumour DNA encoding the VDJ rearrangements was quantitated. FINDINGS: Tumour clonotypes were identified in pretreatment specimens from 126 patients who were followed up for a median of 11 years (IQR 6·8-14·2). Interim monitoring of circulating tumour DNA at the end of two treatment cycles in 108 patients showed a 5-year time to progression of 41·7% (95% CI 22·2-60·1) in patients with detectable circulating tumour DNA and 80·2% (69·6-87·3) in those without detectable circulating tumour DNA (p<0·0001). Detectable interim circulating tumour DNA had a positive predictive value of 62·5% (95% CI 40·6-81·2) and a negative predictive value of 79·8% (69·6-87·8). Surveillance monitoring of circulating tumour DNA was done in 107 patients who achieved complete remission. A Cox proportional hazards model showed that the hazard ratio for clinical disease progression was 228 (95% CI 51-1022) for patients who developed detectable circulating tumour DNA during surveillance compared with patients with undetectable circulating tumour DNA (p<0·0001). Surveillance circulating tumour DNA had a positive predictive value of 88·2% (95% CI 63·6-98·5) and a negative predictive value of 97·8% (92·2-99·7) and identified risk of recurrence at a median of 3·5 months (range 0-200) before evidence of clinical disease. INTERPRETATION: Surveillance circulating tumour DNA identifies patients at risk of recurrence before clinical evidence of disease in most patients and results in a reduced disease burden at relapse. Interim circulating tumour DNA is a promising biomarker to identify patients at high risk of treatment failure. FUNDING: National Cancer Institute and Adaptive Biotechnologies.

Immunoglobulin and T cell receptor gene high-throughput sequencing quantifies minimal residual disease in acute lymphoblastic leukemia and predicts post-transplantation relapse and survival.

Minimal residual disease (MRD) quantification is an important predictor of outcome after treatment for acute lymphoblastic leukemia (ALL). Bone marrow ALL burden ≥ 10(-4) after induction predicts subsequent relapse. Likewise, MRD ≥ 10(-4) in bone marrow before initiation of conditioning for allogeneic (allo) hematopoietic cell transplantation (HCT) predicts transplantation failure. Current methods for MRD quantification in ALL are not sufficiently sensitive for use with peripheral blood specimens and have not been broadly implemented in the management of adults with ALL. Consensus-primed immunoglobulin (Ig), T cell receptor (TCR) amplification and high-throughput sequencing (HTS) permit use of a standardized algorithm for all patients and can detect leukemia at 10(-6) or lower. We applied the LymphoSIGHT HTS platform (Sequenta Inc., South San Francisco, CA) to quantification of MRD in 237 samples from 29 adult B cell ALL patients before and after allo-HCT. Using primers for the IGH-VDJ, IGH-DJ, IGK, TCRB, TCRD, and TCRG loci, MRD could be quantified in 93% of patients. Leukemia-associated clonotypes at these loci were identified in 52%, 28%, 10%, 35%, 28%, and 41% of patients, respectively. MRD ≥ 10(-4) before HCT conditioning predicted post-HCT relapse (hazard ratio [HR], 7.7; 95% confidence interval [CI], 2.0 to 30; P = .003). In post-HCT blood samples, MRD ≥10(-6) had 100% positive predictive value for relapse with median lead time of 89 days (HR, 14; 95% CI, 4.7 to 44, P < .0001). The use of HTS-based MRD quantification in adults with ALL offers a standardized approach with sufficient sensitivity to quantify leukemia MRD in peripheral blood. Use of this approach may identify a window for clinical intervention before overt relapse.

Deep-sequencing approach for minimal residual disease detection in acute lymphoblastic leukemia.

The persistence of minimal residual disease (MRD) during therapy is the strongest adverse prognostic factor in acute lymphoblastic leukemia (ALL). We developed a high-throughput sequencing method that universally amplifies antigen-receptor gene segments and identifies all clonal gene rearrangements (ie, leukemia-specific sequences) at diagnosis, allowing monitoring of disease progression and clonal evolution during therapy. In the present study, the assay specifically detected 1 leukemic cell among greater than 1 million leukocytes in spike-in experiments. We compared this method with the gold-standard MRD assays multiparameter flow cytometry and allele-specific oligonucleotide polymerase chain reaction (ASO-PCR) using diagnostic and follow-up samples from 106 patients with ALL. Sequencing detected MRD in all 28 samples shown to be positive by flow cytometry and in 35 of the 36 shown to be positive by ASO-PCR and revealed MRD in 10 and 3 additional samples that were negative by flow cytometry and ASO-PCR, respectively. We conclude that this new method allows monitoring of treatment response in ALL and other lymphoid malignancies with great sensitivity and precision. The www.clinicaltrials.gov identifier number for the Total XV study is NCT00137111.

Population structure, differential bias and genomic control in a large-scale, case-control association study.

The main problems in drawing causal inferences from epidemiological case-control studies are confounding by unmeasured extraneous factors, selection bias and differential misclassification of exposure. In genetics the first of these, in the form of population structure, has dominated recent debate. Population structure explained part of the significant +11.2% inflation of test statistics we observed in an analysis of 6,322 nonsynonymous SNPs in 816 cases of type 1 diabetes and 877 population-based controls from Great Britain. The remainder of the inflation resulted from differential bias in genotype scoring between case and control DNA samples, which originated from two laboratories, causing false-positive associations. To avoid excluding SNPs and losing valuable information, we extended the genomic control method by applying a variable downweighting to each SNP.

High-throughput method for analyzing methylation of CpGs in targeted genomic regions.

A unique microarray-based method for determining the extent of DNA methylation has been developed. It relies on a selective enrichment of the regions to be assayed by target amplification by capture and ligation (mTACL). The assay is quantitatively accurate, relatively precise, and lends itself to high-throughput determination using nanogram amounts of DNA. The measurements using mTACLs are highly reproducible and in excellent agreement with those obtained by sequencing (r = 0.94). In the present work, the methylation status of >145,000 CpGs from 5,472 promoters in 221 samples was measured. The methylation levels of nearby CpGs are correlated, but the correlation falls off dramatically over several hundred base pairs. In some instances, nearby CpGs have very different levels of methylation. Comparison of normal and tumor samples indicates that in tumors, the promoter regions of genes involved in differentiation and signaling are preferentially hypermethylated, whereas those of housekeeping genes remain hypomethylated. mTACL is a platform for profiling the state of methylation of a large number of CpG in many samples in a cost-effective fashion, and is capable of scaling to much larger numbers of CpGs than those collected here.

High-throughput, high-accuracy array-based resequencing.

Although genomewide association studies have successfully identified associations of many common single-nucleotide polymorphisms (SNPs) with common diseases, the SNPs implicated so far account for only a small proportion of the genetic variability of tested diseases. It has been suggested that common diseases may often be caused by rare alleles missed by genomewide association studies. To identify these rare alleles we need high-throughput, high-accuracy resequencing technologies. Although array-based genotyping has allowed genomewide association studies of common SNPs in tens of thousands of samples, array-based resequencing has been limited for 2 main reasons: the lack of a fully multiplexed pipeline for high-throughput sample processing, and failure to achieve sufficient performance. We have recently solved both of these problems and created a fully multiplexed high-throughput pipeline that results in high-quality data. The pipeline consists of target amplification from genomic DNA, followed by allele enrichment to generate pools of purified variant (or nonvariant) DNA and ends with interrogation of purified DNA on resequencing arrays. We have used this pipeline to resequence approximately 5 Mb of DNA (on 3 arrays) corresponding to the exons of 1,500 genes in >473 samples; in total >2,350 Mb were sequenced. In the context of this large-scale study we obtained a false positive rate of approximately 1 in 500,000 bp and a false negative rate of approximately 10%.

Cell-Selective Adeno-Associated Virus-Mediated SCN1A Gene Regulation Therapy Rescues Mortality and Seizure Phenotypes in a Dravet Syndrome Mouse Model and Is Well Tolerated in Nonhuman Primates.

Dravet syndrome (DS) is a developmental and epileptic encephalopathy caused by monoallelic loss-of-function variants in the SCN1A gene. SCN1A encodes for the alpha subunit of the voltage-gated type I sodium channel (NaV1.1), the primary voltage-gated sodium channel responsible for generation of action potentials in GABAergic inhibitory interneurons. In these studies, we tested the efficacy of an adeno-associated virus serotype 9 (AAV9) SCN1A gene regulation therapy, AAV9-REGABA-eTFSCN1A, designed to target transgene expression to GABAergic inhibitory neurons and reduce off-target expression within excitatory cells, in the Scn1a+/- mouse model of DS. Biodistribution and preliminary safety were evaluated in nonhuman primates (NHPs). AAV9-REGABA-eTFSCN1A was engineered to upregulate SCN1A expression levels within GABAergic inhibitory interneurons to correct the underlying haploinsufficiency and circuit dysfunction. A single bilateral intracerebroventricular (ICV) injection of AAV9-REGABA-eTFSCN1A in Scn1a+/- postnatal day 1 mice led to increased SCN1A mRNA transcripts, specifically within GABAergic inhibitory interneurons, and NaV1.1 protein levels in the brain. This was associated with a significant decrease in the occurrence of spontaneous and hyperthermia-induced seizures, and prolonged survival for over a year. In NHPs, delivery of AAV9-REGABA-eTFSCN1A by unilateral ICV injection led to widespread vector biodistribution and transgene expression throughout the brain, including key structures involved in epilepsy and cognitive behaviors, such as hippocampus and cortex. AAV9-REGABA-eTFSCN1A was well tolerated, with no adverse events during administration, no detectable changes in clinical observations, no adverse findings in histopathology, and no dorsal root ganglion-related toxicity. Our results support the clinical development of AAV9-REGABA-eTFSCN1A (ETX101) as an effective and targeted disease-modifying approach to SCN1A+ DS.

Prediction of epigenetically regulated genes in breast cancer cell lines.

BACKGROUND: Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profiles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profiles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fixed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. RESULTS: Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically significant negative correlation between methylation profiles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identified 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. CONCLUSIONS: Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.

Rapid identification of somatic mutations in colorectal and breast cancer tissues using mismatch repair detection (MRD).

Mismatch repair detection (MRD) was used to screen 93 matched tumor-normal sample pairs and 22 cell lines for somatic mutations in 30 cancer relevant genes. Using a starting amount of only 150 ng of genomic DNA, we screened 102 kb of sequence for somatic mutations in colon and breast cancer. A total of 152 somatic mutations were discovered, encompassing previously reported mutations, such as BRAF V600E and KRAS G12S, G12V, and G13D, as well as novel mutations, including some in genes in which somatic mutations have not previously been reported, such as MAP2K1 and MAP2K2. The distribution of mutations ranged widely within and across tumor types. The functional significance of many of these mutations is not understood, with patterns of selection only evident in KRAS and BRAF in colon cancer. These results present a novel approach to high-throughput mutation screening using small amounts of starting material and reveal a mutation spectrum across 30 genes in a large cohort of breast and colorectal cancers.

Allele quantification using molecular inversion probes (MIP).

Detection of genomic copy number changes has been an important research area, especially in cancer. Several high-throughput technologies have been developed to detect these changes. Features that are important for the utility of technologies assessing copy number changes include the ability to interrogate regions of interest at the desired density as well as the ability to differentiate the two homologs. In addition, assessing formaldehyde fixed and paraffin embedded (FFPE) samples allows the utilization of the vast majority of cancer samples. To address these points we demonstrate the use of molecular inversion probe (MIP) technology to the study of copy number. MIP is a high-throughput genotyping technology capable of interrogating >20 000 single nucleotide polymorphisms in the same tube. We have shown the ability of MIP at this multiplex level to provide copy number measurements while obtaining the allele information. In addition we have demonstrated a proof of principle for copy number analysis in FFPE samples.

Discovery of T Cell Receptor ß Motifs Specific to HLA-B27-Positive Ankylosing Spondylitis by Deep Repertoire Sequence Analysis.

OBJECTIVE: Ankylosing spondylitis (AS), a chronic inflammatory disorder, has a notable association with HLA-B27. One hypothesis suggests that a common antigen that binds to HLA-B27 is important for AS disease pathogenesis. This study was undertaken to determine sequences and motifs that are shared among HLA-B27-positive AS patients, using T cell repertoire next-generation sequencing. METHODS: To identify motifs enriched among B27-positive AS patients, we performed T cell receptor ß (TCRß) repertoire sequencing on samples from 191 B27-positive AS patients, 43 B27-negative AS patients, and 227 controls, and we obtained >77 million TCRß clonotype sequences. First, we assessed whether any of 50 previously published sequences were enriched in B27-positive AS patients. We then used training and test cohorts to identify discovered motifs that were enriched in B27-positive AS patients versus controls. RESULTS: Six previously published and 11 discovered motifs were enriched in the B27-positive AS samples as compared to controls. After combining motifs related by sequence, we identified a total of 15 independent motifs. Both the full set of 15 motifs and a set of 6 published motifs were enriched in the B27-positive AS patients as compared to B27-positive healthy individuals (P = 0.049 and P = 0.001, respectively). Using an independent cohort, we validated that at least some of these motifs were associated with AS, and not simply with B27-positive status. CONCLUSION: We identified TCRß motifs that are enriched in B27-positive AS patients as compared to B27-positive healthy controls. This suggests that a common antigen, presented by HLA-B27 and detected by CD8+ T cells, may be associated with AS disease pathogenesis.

Optimal genotype determination in highly multiplexed SNP data.

High-throughput genotyping technologies that enable large association studies are already available. Tools for genotype determination starting from raw signal intensities need to be automated, robust, and flexible to provide optimal genotype determination given the specific requirements of a study. The key metrics describing the performance of a custom genotyping study are assay conversion, call rate, and genotype accuracy. These three metrics can be traded off against each other. Using the highly multiplexed Molecular Inversion Probe technology as an example, we describe a methodology for identifying the optimal trade-off. The methodology comprises: a robust clustering algorithm and assessment of a large number of data filter sets. The clustering algorithm allows for automatic genotype determination. Many different sets of filters are then applied to the clustered data, and performance metrics resulting from each filter set are calculated. These performance metrics relate to the power of a study and provide a framework to choose the most suitable filter set to the particular study.

Multiplex Identification of Antigen-Specific T Cell Receptors Using a Combination of Immune Assays and Immune Receptor Sequencing.

Monitoring antigen-specific T cells is critical for the study of immune responses and development of biomarkers and immunotherapeutics. We developed a novel multiplex assay that combines conventional immune monitoring techniques and immune receptor repertoire sequencing to enable identification of T cells specific to large numbers of antigens simultaneously. We multiplexed 30 different antigens and identified 427 antigen-specific clonotypes from 5 individuals with frequencies as low as 1 per million T cells. The clonotypes identified were validated several ways including repeatability, concordance with published clonotypes, and high correlation with ELISPOT. Applying this technology we have shown that the vast majority of shared antigen-specific clonotypes identified in different individuals display the same specificity. We also showed that shared antigen-specific clonotypes are simpler sequences and are present at higher frequencies compared to non-shared clonotypes specific to the same antigen. In conclusion this technology enables sensitive and quantitative monitoring of T cells specific for hundreds or thousands of antigens simultaneously allowing the study of T cell responses with an unprecedented resolution and scale.