Distinct genomic and immunologic tumor evolution in germline TP53-driven breast cancers.

Pathogenic germline TP53 alterations cause Li-Fraumeni Syndrome (LFS), and breast cancer is the most common cancer in LFS females. We performed first of its kind multimodal analysis of LFS breast cancer (LFS-BC) compared to sporadic premenopausal BC. Nearly all LFS-BC underwent biallelic loss of TP53 with no recurrent oncogenic variants except ERBB2 (HER2) amplification. Compared to sporadic BC, in situ and invasive LFS-BC exhibited a high burden of short amplified aneuploid segments (SAAS). Pro-apoptotic p53 target genes BAX and TP53I3 failed to be up-regulated in LFS-BC as was seen in sporadic BC compared to normal breast tissue. LFS-BC had lower CD8+ T-cell infiltration compared to sporadic BC yet higher levels of proliferating cytotoxic T-cells. Within LFS-BC, progression from in situ to invasive BC was marked by an increase in chromosomal instability with a decrease in proliferating cytotoxic T-cells. Our study uncovers critical events in mutant p53-driven tumorigenesis in breast tissue.

Clinical and molecular features of acquired resistance to immunotherapy in non-small cell lung cancer.

Although immunotherapy with PD-(L)1 blockade is routine for lung cancer, little is known about acquired resistance. Among 1,201 patients with non-small cell lung cancer (NSCLC) treated with PD-(L)1 blockade, acquired resistance is common, occurring in >60% of initial responders. Acquired resistance shows differential expression of inflammation and interferon (IFN) signaling. Relapsed tumors can be separated by upregulated or stable expression of IFNγ response genes. Upregulation of IFNγ response genes is associated with putative routes of resistance characterized by signatures of persistent IFN signaling, immune dysfunction, and mutations in antigen presentation genes which can be recapitulated in multiple murine models of acquired resistance to PD-(L)1 blockade after in vitro IFNγ treatment. Acquired resistance to PD-(L)1 blockade in NSCLC is associated with an ongoing, but altered IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance may inform therapeutic strategies to effectively reprogram and reverse acquired resistance.

Structures, functions and adaptations of the human LINE-1 ORF2 protein.

The LINE-1 (L1) retrotransposon is an ancient genetic parasite that has written around one-third of the human genome through a 'copy and paste' mechanism catalysed by its multifunctional enzyme, open reading frame 2 protein (ORF2p)1. ORF2p reverse transcriptase (RT) and endonuclease activities have been implicated in the pathophysiology of cancer2,3, autoimmunity4,5 and ageing6,7, making ORF2p a potential therapeutic target. However, a lack of structural and mechanistic knowledge has hampered efforts to rationally exploit it. We report structures of the human ORF2p 'core' (residues 238-1061, including the RT domain) by X-ray crystallography and cryo-electron microscopy in several conformational states. Our analyses identified two previously undescribed folded domains, extensive contacts to RNA templates and associated adaptations that contribute to unique aspects of the L1 replication cycle. Computed integrative structural models of full-length ORF2p show a dynamic closed-ring conformation that appears to open during retrotransposition. We characterize ORF2p RT inhibition and reveal its underlying structural basis. Imaging and biochemistry show that non-canonical cytosolic ORF2p RT activity can produce RNA:DNA hybrids, activating innate immune signalling through cGAS/STING and resulting in interferon production6-8. In contrast to retroviral RTs, L1 RT is efficiently primed by short RNAs and hairpins, which probably explains cytosolic priming. Other biochemical activities including processivity, DNA-directed polymerization, non-templated base addition and template switching together allow us to propose a revised L1 insertion model. Finally, our evolutionary analysis demonstrates structural conservation between ORF2p and other RNA- and DNA-dependent polymerases. We therefore provide key mechanistic insights into L1 polymerization and insertion, shed light on the evolutionary history of L1 and enable rational drug development targeting L1.

Trade-offs inside the black box of neoantigen prediction.

Success of precision neoantigen-based immunotherapies hinges on the selection of immunogenic neoantigens, yet currently neither large-scale datasets nor streamlined methods are available to achieve this goal. Müller et al. present a large experimental dataset resource along with machine learning-based models to classify immunogenic neoantigens.

Tissue-specific features of the T cell repertoire after allogeneic hematopoietic cell transplantation in human and mouse.

T cells are the central drivers of many inflammatory diseases, but the repertoire of tissue-resident T cells at sites of pathology in human organs remains poorly understood. We examined the site-specificity of T cell receptor (TCR) repertoires across tissues (5 to 18 tissues per patient) in prospectively collected autopsies of patients with and without graft-versus-host disease (GVHD), a potentially lethal tissue-targeting complication of allogeneic hematopoietic cell transplantation, and in mouse models of GVHD. Anatomic similarity between tissues was a key determinant of TCR repertoire composition within patients, independent of disease or transplant status. The T cells recovered from peripheral blood and spleens in patients and mice captured a limited portion of the TCR repertoire detected in tissues. Whereas few T cell clones were shared across patients, motif-based clustering revealed shared repertoire signatures across patients in a tissue-specific fashion. T cells at disease sites had a tissue-resident phenotype and were of donor origin based on single-cell chimerism analysis. These data demonstrate the complex composition of T cell populations that persist in human tissues at the end stage of an inflammatory disorder after lymphocyte-directed therapy. These findings also underscore the importance of studying T cell in tissues rather than blood for tissue-based pathologies and suggest the tissue-specific nature of both the endogenous and posttransplant T cell landscape.

Identification of transcriptional programs using dense vector representations defined by mutual information with GeneVector.

Deciphering individual cell phenotypes from cell-specific transcriptional processes requires high dimensional single cell RNA sequencing. However, current dimensionality reduction methods aggregate sparse gene information across cells, without directly measuring the relationships that exist between genes. By performing dimensionality reduction with respect to gene co-expression, low-dimensional features can model these gene-specific relationships and leverage shared signal to overcome sparsity. We describe GeneVector, a scalable framework for dimensionality reduction implemented as a vector space model using mutual information between gene expression. Unlike other methods, including principal component analysis and variational autoencoders, GeneVector uses latent space arithmetic in a lower dimensional gene embedding to identify transcriptional programs and classify cell types. In this work, we show in four single cell RNA-seq datasets that GeneVector was able to capture phenotype-specific pathways, perform batch effect correction, interactively annotate cell types, and identify pathway variation with treatment over time.

Cancer cells co-evolve with retrotransposons to mitigate viral mimicry.

Overexpression of repetitive elements is an emerging hallmark of human cancers 1 . Diverse repeats can mimic viruses by replicating within the cancer genome through retrotransposition, or presenting pathogen-associated molecular patterns (PAMPs) to the pattern recognition receptors (PRRs) of the innate immune system 2-5 . Yet, how specific repeats affect tumor evolution and shape the tumor immune microenvironment (TME) in a pro- or anti-tumorigenic manner remains poorly defined. Here, we integrate whole genome and total transcriptome data from a unique autopsy cohort of multiregional samples collected in pancreatic ductal adenocarcinoma (PDAC) patients, into a comprehensive evolutionary analysis. We find that more recently evolved S hort I nterspersed N uclear E lements (SINE), a family of retrotransposable repeats, are more likely to form immunostimulatory double-strand RNAs (dsRNAs). Consequently, younger SINEs are strongly co-regulated with RIG-I like receptor associated type-I interferon genes but anti-correlated with pro-tumorigenic macrophage infiltration. We discover that immunostimulatory SINE expression in tumors is regulated by either L ong I nterspersed N uclear E lements 1 (LINE1/L1) mobility or ADAR1 activity in a TP53 mutation dependent manner. Moreover, L1 retrotransposition activity tracks with tumor evolution and is associated with TP53 mutation status. Altogether, our results suggest pancreatic tumors actively evolve to modulate immunogenic SINE stress and induce pro-tumorigenic inflammation. Our integrative, evolutionary analysis therefore illustrates, for the first time, how dark matter genomic repeats enable tumors to co-evolve with the TME by actively regulating viral mimicry to their selective advantage.

Personalized RNA neoantigen vaccines stimulate T cells in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is lethal in 88% of patients1, 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.

Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer.

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up To Cancer-Mark Foundation cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including (1) favorable (for example, ATM altered) and unfavorable (for example, TERT amplified) genomic subgroups, (2) a prominent association between expression of inducible components of the immunoproteasome and response and (3) a dedifferentiated tumor-intrinsic subtype with enhanced response to checkpoint blockade. Taken together, results from this cohort demonstrate the complexity of biological determinants underlying immunotherapy outcomes and reinforce the discovery potential of integrative analysis within large, well-curated, cancer-specific cohorts.

Perfecting antigen prediction.

Advances in genomics and precision measurement have continued to demonstrate the importance of the immune system across many disease types. At the heart of many emerging approaches to leverage these insights for precision immunotherapies is the computational antigen prediction problem. We propose a threefold approach to improving antigen predictions: further defining the geometry of the antigen landscape, incorporating the coupling of antigen recognition to other cellular processes, and diversifying the training sets used for models that predict immunogenicity.

Y RNAs are conserved endogenous RIG-I ligands across RNA virus infection and are targeted by HIV-1.

Pattern recognition receptors (PRRs) protect against microbial invasion by detecting specific molecular patterns found in pathogens and initiating an immune response. Although microbial-derived PRR ligands have been extensively characterized, the contribution and relevance of endogenous ligands to PRR activation remains overlooked. Here, we characterize the landscape of endogenous ligands that engage RIG-I-like receptors (RLRs) upon infection by different RNA viruses. In each infection, several RNAs transcribed by RNA polymerase III (Pol3) specifically engaged RLRs, particularly the family of Y RNAs. Sensing of Y RNAs was dependent on their mimicking of viral secondary structure and their 5'-triphosphate extremity. Further, we found that HIV-1 triggered a VPR-dependent downregulation of RNA triphosphatase DUSP11 in vitro and in vivo, inducing a transcriptome-wide change of cellular RNA 5'-triphosphorylation that licenses Y RNA immunogenicity. Overall, our work uncovers the contribution of endogenous RNAs to antiviral immunity and demonstrates the importance of this pathway in HIV-1 infection.

Satellite repeat RNA expression in epithelial ovarian cancer associates with a tumor-immunosuppressive phenotype.

Aberrant expression of viral-like repeat elements is a common feature of epithelial cancers, and the substantial diversity of repeat species provides a distinct view of the cancer transcriptome. Repeatome profiling across ovarian, pancreatic, and colorectal cell lines identifies distinct clustering independent of tissue origin that is seen with coding gene analysis. Deeper analysis of ovarian cancer cell lines demonstrated that human satellite II (HSATII) satellite repeat expression was highly associated with epithelial-mesenchymal transition (EMT) and anticorrelated with IFN-response genes indicative of a more aggressive phenotype. SATII expression - and its correlation with EMT and anticorrelation with IFN-response genes - was also found in ovarian cancer RNA-Seq data and was associated with significantly shorter survival in a second independent cohort of patients with ovarian cancer. Repeat RNAs were enriched in tumor-derived extracellular vesicles capable of stimulating monocyte-derived macrophages, demonstrating a mechanism that alters the tumor microenvironment with these viral-like sequences. Targeting of HSATII with antisense locked nucleic acids stimulated IFN response and induced MHC I expression in ovarian cancer cell lines, highlighting a potential strategy of modulating the repeatome to reestablish antitumor cell immune surveillance.

Systemic and Oligo-Acquired Resistance to PD-(L)1 Blockade in Lung Cancer.

PURPOSE: Clinical patterns and the associated optimal management of acquired resistance to PD-(L)1 blockade are poorly understood. EXPERIMENTAL DESIGN: All cases of metastatic lung cancer treated with PD-(L)1 blockade at Memorial Sloan Kettering were reviewed. In acquired resistance (complete/partial response per RECIST, followed by progression), clinical patterns were distinguished as oligo (OligoAR ≤ 3 lesions of disease progression) or systemic (sAR). We analyzed the relationships between patient characteristics, burden/location of disease, outcomes, and efficacy of therapeutic interventions. RESULTS: Of 1,536 patients, 312 (20%) had an initial response and 143 developed AR (9% overall, 46% of responders). OligoAR was the most common pattern (80/143, 56%). Baseline tumor mutational burden, depth of response, and duration of response were significantly increased in oligoAR compared with sAR (P < 0.001, P = 0.03, P = 0.04, respectively), whereas baseline PD-L1 and tumor burden were similar. Post-progression, oligoAR was associated with improved overall survival (median 28 months vs. 10 months, P < 0.001) compared with sAR. Within oligoAR, post-progression survival was greater among patients treated with locally-directed therapy (e.g., radiation, surgery; HR, 0.41; P = 0.039). Fifty-eight percent of patients with oligoAR treated with locally-directed therapy alone are progression-free at last follow-up (median 16 months), including 13 patients who are progression-free more than 2 years after local therapy. CONCLUSIONS: OligoAR is a common and distinct pattern of acquired resistance to PD-(L)1 blockade compared with sAR. OligoAR is associated with improved post-progression survival and some cases can be effectively managed with local therapies with durable benefit.

Fundamental immune-oncogenicity trade-offs define driver mutation fitness.

Missense driver mutations in cancer are concentrated in a few hotspots1. Various mechanisms have been proposed to explain this skew, including biased mutational processes2, phenotypic differences3-6 and immunoediting of neoantigens7,8; however, to our knowledge, no existing model weighs the relative contribution of these features to tumour evolution. We propose a unified theoretical 'free fitness' framework that parsimoniously integrates multimodal genomic, epigenetic, transcriptomic and proteomic data into a biophysical model of the rate-limiting processes underlying the fitness advantage conferred on cancer cells by driver gene mutations. Focusing on TP53, the most mutated gene in cancer1, we present an inference of mutant p53 concentration and demonstrate that TP53 hotspot mutations optimally solve an evolutionary trade-off between oncogenic potential and neoantigen immunogenicity. Our model anticipates patient survival in The Cancer Genome Atlas and patients with lung cancer treated with immunotherapy as well as the age of tumour onset in germline carriers of TP53 variants. The predicted differential immunogenicity between hotspot mutations was validated experimentally in patients with cancer and in a unique large dataset of healthy individuals. Our data indicate that immune selective pressure on TP53 mutations has a smaller role in non-cancerous lesions than in tumours, suggesting that targeted immunotherapy may offer an early prophylactic opportunity for the former. Determining the relative contribution of immunogenicity and oncogenic function to the selective advantage of hotspot mutations thus has important implications for both precision immunotherapies and our understanding of tumour evolution.

Neoantigen quality predicts immunoediting in survivors of pancreatic cancer.

Cancer immunoediting1 is a hallmark of cancer2 that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice1,3, 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 antigens4,5, 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.

Reverse Transcriptase Inhibition Disrupts Repeat Element Life Cycle in Colorectal Cancer.

Altered RNA expression of repetitive sequences and retrotransposition are frequently seen in colorectal cancer, implicating a functional importance of repeat activity in cancer progression. We show the nucleoside reverse transcriptase inhibitor 3TC targets activities of these repeat elements in colorectal cancer preclinical models with a preferential effect in p53-mutant cell lines linked with direct binding of p53 to repeat elements. We translate these findings to a human phase II trial of single-agent 3TC treatment in metastatic colorectal cancer with demonstration of clinical benefit in 9 of 32 patients. Analysis of 3TC effects on colorectal cancer tumorspheres demonstrates accumulation of immunogenic RNA:DNA hybrids linked with induction of interferon response genes and DNA damage response. Epigenetic and DNA-damaging agents induce repeat RNAs and have enhanced cytotoxicity with 3TC. These findings identify a vulnerability in colorectal cancer by targeting the viral mimicry of repeat elements. SIGNIFICANCE: Colorectal cancers express abundant repeat elements that have a viral-like life cycle that can be therapeutically targeted with nucleoside reverse transcriptase inhibitors (NRTI) commonly used for viral diseases. NRTIs induce DNA damage and interferon response that provide a new anticancer therapeutic strategy. This article is highlighted in the In This Issue feature, p. 1397.

sgDI-tector: defective interfering viral genome bioinformatics for detection of coronavirus subgenomic RNAs.

Coronavirus RNA-dependent RNA polymerases produce subgenomic RNAs (sgRNAs) that encode viral structural and accessory proteins. User-friendly bioinformatic tools to detect and quantify sgRNA production are urgently needed to study the growing number of next-generation sequencing (NGS) data of SARS-CoV-2. We introduced sgDI-tector to identify and quantify sgRNA in SARS-CoV-2 NGS data. sgDI-tector allowed detection of sgRNA without initial knowledge of the transcription-regulatory sequences. We produced NGS data and successfully detected the nested set of sgRNAs with the ranking M > ORF3a > N>ORF6 > ORF7a > ORF8 > S > E>ORF7b. We also compared the level of sgRNA production with other types of viral RNA products such as defective interfering viral genomes.

Probing T-cell response by sequence-based probabilistic modeling.

With the increasing ability to use high-throughput next-generation sequencing to quantify the diversity of the human T cell receptor (TCR) repertoire, the ability to use TCR sequences to infer antigen-specificity could greatly aid potential diagnostics and therapeutics. Here, we use a machine-learning approach known as Restricted Boltzmann Machine to develop a sequence-based inference approach to identify antigen-specific TCRs. Our approach combines probabilistic models of TCR sequences with clone abundance information to extract TCR sequence motifs central to an antigen-specific response. We use this model to identify patient personalized TCR motifs that respond to individual tumor and infectious disease antigens, and to accurately discriminate specific from non-specific responses. Furthermore, the hidden structure of the model results in an interpretable representation space where TCRs responding to the same antigen cluster, correctly discriminating the response of TCR to different viral epitopes. The model can be used to identify condition specific responding TCRs. We focus on the examples of TCRs reactive to candidate neoantigens and selected epitopes in experiments of stimulated TCR clone expansion.

HNRNPM controls circRNA biogenesis and splicing fidelity to sustain cancer cell fitness.

High spliceosome activity is a dependency for cancer cells, making them more vulnerable to perturbation of the splicing machinery compared to normal cells. To identify splicing factors important for prostate cancer (PCa) fitness, we performed pooled shRNA screens in vitro and in vivo. Our screens identified heterogeneous nuclear ribonucleoprotein M (HNRNPM) as a regulator of PCa cell growth. RNA- and eCLIP-sequencing identified HNRNPM binding to transcripts of key homeostatic genes. HNRNPM binding to its targets prevents aberrant exon inclusion and backsplicing events. In both linear and circular mis-spliced transcripts, HNRNPM preferentially binds to GU-rich elements in long flanking proximal introns. Mimicry of HNRNPM-dependent linear-splicing events using splice-switching-antisense-oligonucleotides was sufficient to inhibit PCa cell growth. This suggests that PCa dependence on HNRNPM is likely a result of mis-splicing of key homeostatic coding and non-coding genes. Our results have further been confirmed in other solid tumors. Taken together, our data reveal a role for HNRNPM in supporting cancer cell fitness. Inhibition of HNRNPM activity is therefore a potential therapeutic strategy in suppressing growth of PCa and other solid tumors.