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Cancer immunoediting 1 is a hallmark of cancer 2 that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice 1 , 3 , whether immunoediting occurs naturally in human cancers remains unclear. Here, to address this, we investigate how 70 human pancreatic cancers evolved over 10 years. We find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic cancer who have stronger T cell activity in primary tumours develop genetically less heterogeneous recurrent tumours with fewer immunogenic mutations (neoantigens). To quantify whether immunoediting underlies these observations, we infer that a neoantigen is immunogenic (high-quality) by two features—‘non-selfness’  based on neoantigen similarity to known antigens 4 , 5 , and ‘selfness’  based on the antigenic distance required for a neoantigen to differentially bind to the MHC or activate a T cell compared with its wild-type peptide. Using these features, we estimate cancer clone fitness as the aggregate cost of T cells recognizing high-quality neoantigens offset by gains from oncogenic mutations. With this model, we predict the clonal evolution of tumours to reveal that long-term survivors of pancreatic cancer develop recurrent tumours with fewer high-quality neoantigens. Thus, we submit evidence that that the human immune system naturally edits neoantigens. Furthermore, we present a model to predict how immune pressure induces cancer cell populations to evolve over time. More broadly, our results argue that the immune system fundamentally surveils host genetic changes to suppress cancer. The human immune system naturally edits cancers of high-quality neoantigens.

Tertiary lymphoid structures (TLSs) are de novo ectopic lymphoid aggregates that regulate immunity in chronically inflamed tissues, including tumours. Although TLSs form due to inflammation-triggered activation of the lymphotoxin (LT)–LTβ receptor (LTβR) pathway 1 , the inflammatory signals and cells that induce TLSs remain incompletely identified. Here we show that interleukin-33 (IL-33), the alarmin released by inflamed tissues 2 , induces TLSs. In mice, Il33 deficiency severely attenuates inflammation- and LTβR-activation-induced TLSs in models of colitis and pancreatic ductal adenocarcinoma (PDAC). In PDAC, the alarmin domain of IL-33 activates group 2 innate lymphoid cells (ILC2s) expressing LT that engage putative LTβR + myeloid organizer cells to initiate tertiary lymphoneogenesis. Notably, lymphoneogenic ILC2s migrate to PDACs from the gut, can be mobilized to PDACs in different tissues and are modulated by gut microbiota. Furthermore, we detect putative lymphoneogenic ILC2s and IL-33-expressing cells within TLSs in human PDAC that correlate with improved prognosis. To harness this lymphoneogenic pathway for immunotherapy, we engineer a recombinant human IL-33 protein that expands intratumoural lymphoneogenic ILC2s and TLSs and demonstrates enhanced anti-tumour activity in PDAC mice. In summary, we identify the molecules and cells of a druggable pathway that induces inflammation-triggered TLSs. More broadly, we reveal a lymphoneogenic function for alarmins and ILC2s. IL-33 induces tertiary lymphoid structures.

Single-cell T cell repertoire sequencing can pair both T cell receptor (TCR) and gene expression sequence data, providing an enriched view of T cell behavior. This powerful tool can identify and characterize specific clonotypes and phenotypes as well as track their changes in response to therapy, such as immune checkpoint blockade (ICB). We present a novel information theoretic framework called TCRi for characterizing single cell T cell repertoires by formalizing the relationship between clonotype and phenotype in a joint probability distribution. Our strategy allows for the identification of subpopulations of T cells and jointly quantifies their TCR and expression profiles in response to stimuli, in addition the framework tracks the phenotypic changes in individual T cell clones over time. We applied this framework to four datasets of T cells sequenced from cancer patients treated with anti-PD-(L)1 ICB immunotherapies and examined evolution of T cell responses pre- and post-treatment. Quantitative of phenotypic and clonotypic entropy analysis with TCRi demonstrated improvements in characterization of the transcriptional signature of clonotypes. Furthermore, TCRi highlighted the importance of phenotypic flux and specific T-cell phenotypes as determinants of therapeutic response. Competing Interest Statement B.D.G. has received honoraria for speaking engagements from Merck, Bristol-Meyers Squibb and Chugai Pharmaceuticals; has received research funding from Bristol-Meyers Squibb; and has been a compensated consultant for PMV Pharma and Rome Therapeutics of which he is a co-founder. S.P.S. reports personal fees from Imagia Canexia Inc. O.A.-W. has served as a consultant for H3B Biomedicine, Foundation Medicine Inc, Merck, Prelude Therapeutics, and Janssen, and is on the Scientific Advisory Board of Envisagenics Inc., AIChemy, Harmonic Discovery Inc., and Pfizer Boulder. V.P.B. has received research support from Bristol-Myers Squibb and Genentech. J.W. is a consultant for Adaptive Biotech, Amgen, Apricity, Ascentage Pharma, Arsenal IO, Astellas, AstraZeneca, Bayer, Beigene, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Chugai, Eli Lilly, Elucida, F Star, Georgiamune, Imvaq, Kyowa Hakko Kirin, Linneaus, Merck, Neon Therapeutics, Polynoma, Psioxus, Recepta, Takara Bio, Trieza, Truvax, Sellas, Serametrix, Surface Oncology, Syndax, Syntalogic and Werewolf Therapeutics. Footnotes * https://github.com/nceglia/TCRi

We quantify the VDJ recombination and somatic hypermutation processes in human B cells using probabilistic inference methods on high-throughput DNA sequence repertoires of human B-cell receptor heavy chains. Our analysis captures the statistical properties of the naive repertoire, first after its initial generation via VDJ recombination and then after selection for functionality. We also infer statistical properties of the somatic hypermutation machinery (exclusive of subsequent effects of selection). Our main results are the following: the B-cell repertoire is substantially more diverse than T-cell repertoires, owing to longer junctional insertions; sequences that pass initial selection are distinguished by having a higher probability of being generated in a VDJ recombination event; somatic hypermutations have a non-uniform distribution along the V gene that is well explained by an independent site model for the sequence context around the hypermutation site.

The diversity of T-cell receptor (TCR) repertoires is achieved by a combination of two intrinsically stochastic steps: random receptor generation by VDJ recombination, and selection based on the recognition of random self-peptides presented on the major histocompatibility complex. These processes lead to a large receptor variability within and between individuals. However, the characterization of the variability is hampered by the limited size of the sampled repertoires. We introduce a new software tool SONIA to facilitate inference of individual-specific computational models for the generation and selection of the TCR beta chain (TRB) from sequenced repertoires of 651 individuals, separating and quantifying the variability of the two processes of generation and selection in the population. We find not only that most of the variability is driven by the VDJ generation process, but there is a large degree of consistency between individuals with the inter-individual variance of repertoires being about ∼2% of the intra-individual variance. Known viral-specific TCRs follow the same generation and selection statistics as all TCRs.

Pancreatic ductal adenocarcinoma (PDAC) is lethal in 88% of patients 1 , yet harbours mutation-derived T cell neoantigens that are suitable for vaccines 2 , 3 . Here in a phase I trial of adjuvant autogene cevumeran, an individualized neoantigen vaccine based on uridine mRNA–lipoplex nanoparticles, we synthesized mRNA neoantigen vaccines in real time from surgically resected PDAC tumours. After surgery, we sequentially administered atezolizumab (an anti-PD-L1 immunotherapy), autogene cevumeran (a maximum of 20 neoantigens per patient) and a modified version of a four-drug chemotherapy regimen (mFOLFIRINOX, comprising folinic acid, fluorouracil, irinotecan and oxaliplatin). The end points included vaccine-induced neoantigen-specific T cells by high-threshold assays, 18-month recurrence-free survival and oncologic feasibility. We treated 16 patients with atezolizumab and autogene cevumeran, then 15 patients with mFOLFIRINOX. Autogene cevumeran was administered within 3 days of benchmarked times, was tolerable and induced de novo high-magnitude neoantigen-specific T cells in 8 out of 16 patients, with half targeting more than one vaccine neoantigen. Using a new mathematical strategy to track T cell clones (CloneTrack) and functional assays, we found that vaccine-expanded T cells comprised up to 10% of all blood T cells, re-expanded with a vaccine booster and included long-lived polyfunctional neoantigen-specific effector CD8 + T cells. At 18-month median follow-up, patients with vaccine-expanded T cells (responders) had a longer median recurrence-free survival (not reached) compared with patients without vaccine-expanded T cells (non-responders; 13.4 months, P  = 0.003). Differences in the immune fitness of the patients did not confound this correlation, as responders and non-responders mounted equivalent immunity to a concurrent unrelated mRNA vaccine against SARS-CoV-2. Thus, adjuvant atezolizumab, autogene cevumeran and mFOLFIRINOX induces substantial T cell activity that may correlate with delayed PDAC recurrence. A phase I clinical trial of an adjuvant personalized mRNA neoantigen vaccine, autogene cevumeran, in patients with pancreatic ductal carcinoma demonstrates that the vaccine can induce T cell activity that may correlate with delayed recurrence of disease.

A fundamental challenge for cancer vaccines is to generate long-lived functional T cells that are specific for tumour antigens. Here we find that mRNA–lipoplex vaccines against somatic mutation-derived neoantigens may solve this challenge in pancreatic ductal adenocarcinoma (PDAC), a lethal cancer with few mutations. At an extended 3.2-year median follow-up from a phase 1 trial of surgery, atezolizumab (PD-L1 inhibitory antibody), autogene cevumeran 1 (individualized neoantigen vaccine with backbone-optimized uridine mRNA–lipoplex nanoparticles) and modified (m) FOLFIRINOX (chemotherapy) in patients with PDAC, we find that responders with vaccine-induced T cells ( n  = 8) have prolonged recurrence-free survival (RFS; median not reached) compared with non-responders without vaccine-induced T cells ( n  = 8; median RFS 13.4 months; P   =  0.007). In responders, autogene cevumeran induces CD8 + T cell clones with an average estimated lifespan of 7.7 years (range 1.5 to roughly 100 years), with approximately 20% of clones having latent multi-decade lifespans that may outlive hosts. Eighty-six percent of clones per patient persist at substantial frequencies approximately 3 years post-vaccination, including clones with high avidity to PDAC neoepitopes. Using PhenoTrack, a novel computational strategy to trace single T cell phenotypes, we uncover that vaccine-induced clones are undetectable in pre-vaccination tissues, and assume a cytotoxic, tissue-resident memory-like T cell state up to three years post-vaccination with preserved neoantigen-specific effector function. Two responders recurred and evidenced fewer vaccine-induced T cells. Furthermore, recurrent PDACs were pruned of vaccine-targeted cancer clones. Thus, in PDAC, autogene cevumeran induces de novo CD8 + T cells with multiyear longevity, substantial magnitude and durable effector functions that may delay PDAC recurrence. Adjuvant mRNA–lipoplex neoantigen vaccines may thus solve a pivotal obstacle for cancer vaccination. In a phase 1 trial, patients with pancreatic ductal adenocarcinoma who were treated with surgery and bespoke neoantigen mRNA vaccines combined with anti-PD-L1 and chemotherapy exhibited marked long-lived persistence of neoantigen-specific CD8 + T cell clones, which correlated with prolonged recurrence-free survival at a 3.2-year follow-up.

The ability of the adaptive immune system to respond to arbitrary pathogens stems from the broad diversity of immune cell surface receptors. This diversity originates in a stochastic DNA editing process (VDJ recombination) that acts on the surface receptor gene each time a new immune cell is created from a stem cell. By analyzing T-cell receptor (TCR) sequence repertoires taken from the blood and thymus of mice of different ages, we quantify the changes in the VDJ recombination process that occur from embryo to young adult. We find a rapid increase with age in the number of random insertions and a dramatic increase in diversity. Because the blood accumulates thymic output over time, blood repertoires are mixtures of different statistical recombination processes, and we unravel the mixture statistics to obtain a picture of the time evolution of the early immune system. Sequence repertoire analysis also allows us to detect the statistical impact of selection on the output of the VDJ recombination process. The effects we find are nearly identical between thymus and blood, suggesting that our analysis mainly detects selection for proper folding of the TCR receptor protein. We further find that selection is weaker in laboratory mice than in humans and it does not affect the diversity of the repertoire.

We quantify the VDJ recombination and somatic hypermutation processes in human B cells using probabilistic inference methods on high-throughput DNA sequence repertoires of human B-cell receptor heavy chains. Our analysis captures the statistical properties of the naive repertoire, first after its initial generation via VDJ recombination and then after selection for functionality. We also infer statistical properties of the somatic hypermutation machinery (exclusive of subsequent effects of selection). Our main results are the following: the B-cell repertoire is substantially more diverse than T-cell repertoires, owing to longer junctional insertions; sequences that pass initial selection are distinguished by having a higher probability of being generated in a VDJ recombination event; somatic hypermutations have a non-uniform distribution along the V gene that is well explained by an independent site model for the sequence context around the hypermutation site.

T-cell receptors (TCR) are key proteins of the adaptive immune system, generated randomly in each individual, whose diversity underlies our ability to recognize infections and malignancies. Modeling the distribution of TCR sequences is of key importance for immunology and medical applications. Here, we compare two inference methods trained on high-throughput sequencing data: a knowledge-guided approach, which accounts for the details of sequence generation, supplemented by a physics-inspired model of selection; and a knowledge-free Variational Auto-Encoder based on deep artificial neural networks. We show that the knowledge-guided model outperforms the deep network approach at predicting TCR probabilities, while being more interpretable, at a lower computational cost.