Efficient and accurate mixed model association tool for single-cell eQTL analysis.

Understanding the genetic basis of gene expression can help us understand the molecular underpinnings of human traits and disease. Expression quantitative trait locus (eQTL) mapping can help in studying this relationship but have been shown to be very cell-type specific, motivating the use of single-cell RNA sequencing and single-cell eQTLs to obtain a more granular view of genetic regulation. Current methods for single-cell eQTL mapping either rely on the "pseudobulk" approach and traditional pipelines for bulk transcriptomics or do not scale well to large datasets. Here, we propose SAIGE-QTL, a robust and scalable tool that can directly map eQTLs using single-cell profiles without needing aggregation at the pseudobulk level. Additionally, SAIGE-QTL allows for testing the effects of less frequent/rare genetic variation through set-based tests, which is traditionally excluded from eQTL mapping studies. We evaluate the performance of SAIGE-QTL on both real and simulated data and demonstrate the improved power for eQTL mapping over existing pipelines.

Translational genetics identifies a phosphorylation switch in CARD9 required for innate inflammatory responses.

Population genetics continues to identify genetic variants associated with diseases of the immune system and offers a unique opportunity to discover mechanisms of immune regulation. Multiple genetic variants linked to severe fungal infections and autoimmunity are associated with caspase recruitment domain-containing protein 9 (CARD9). We leverage the CARD9 R101C missense variant to uncover a biochemical mechanism of CARD9 activation essential for antifungal responses. We demonstrate that R101C disrupts a critical signaling switch whereby phosphorylation of S104 releases CARD9 from an autoinhibited state to promote inflammatory responses in myeloid cells. Furthermore, we show that CARD9 R101C exerts dynamic effects on the skin cellular contexture during fungal infection, corrupting inflammatory signaling and cell-cell communication circuits. Card9 R101C mice fail to control dermatophyte infection in the skin, resulting in high fungal burden, yet show minimal signs of inflammation. Together, we demonstrate how translational genetics reveals molecular and cellular mechanisms of innate immune regulation.

An immunogenetic basis for lung cancer risk.

Cancer risk is influenced by inherited mutations, DNA replication errors, and environmental factors. However, the influence of genetic variation in immunosurveillance on cancer risk is not well understood. Leveraging population-level data from the UK Biobank and FinnGen, we show that heterozygosity at the human leukocyte antigen (HLA)-II loci is associated with reduced lung cancer risk in smokers. Fine-mapping implicated amino acid heterozygosity in the HLA-II peptide binding groove in reduced lung cancer risk, and single-cell analyses showed that smoking drives enrichment of proinflammatory lung macrophages and HLA-II+ epithelial cells. In lung cancer, widespread loss of HLA-II heterozygosity (LOH) favored loss of alleles with larger neopeptide repertoires. Thus, our findings nominate genetic variation in immunosurveillance as a critical risk factor for lung cancer.

The landscape of immune dysregulation in Crohn's disease revealed through single-cell transcriptomic profiling in the ileum and colon.

Crohn's disease (CD) is a chronic gastrointestinal disease that is increasing in prevalence worldwide. CD is multifactorial, involving the complex interplay of genetic, immune, and environmental factors, necessitating a system-level understanding of its etiology. To characterize cell-type-specific transcriptional heterogeneity in active CD, we profiled 720,633 cells from the terminal ileum and colon of 71 donors with varying inflammation status. Our integrated datasets revealed organ- and compartment-specific responses to acute and chronic inflammation; most immune changes were in cell composition, whereas transcriptional changes dominated among epithelial and stromal cells. These changes correlated with endoscopic inflammation, but small and large intestines exhibited distinct responses, which were particularly apparent when focusing on IBD risk genes. Finally, we mapped markers of disease-associated myofibroblast activation and identified CHMP1A, TBX3, and RNF168 as regulators of fibrotic complications. Altogether, our results provide a roadmap for understanding cell-type- and organ-specific differences in CD and potential directions for therapeutic development.

Unsupervised and supervised AI on molecular dynamics simulations reveals complex characteristics of HLA-A2-peptide immunogenicity.

Immunologic recognition of peptide antigens bound to class I major histocompatibility complex (MHC) molecules is essential to both novel immunotherapeutic development and human health at large. Current methods for predicting antigen peptide immunogenicity rely primarily on simple sequence representations, which allow for some understanding of immunogenic features but provide inadequate consideration of the full scale of molecular mechanisms tied to peptide recognition. We here characterize contributions that unsupervised and supervised artificial intelligence (AI) methods can make toward understanding and predicting MHC(HLA-A2)-peptide complex immunogenicity when applied to large ensembles of molecular dynamics simulations. We first show that an unsupervised AI method allows us to identify subtle features that drive immunogenicity differences between a cancer neoantigen and its wild-type peptide counterpart. Next, we demonstrate that a supervised AI method for class I MHC(HLA-A2)-peptide complex classification significantly outperforms a sequence model on small datasets corrected for trivial sequence correlations. Furthermore, we show that both unsupervised and supervised approaches reveal determinants of immunogenicity based on time-dependent molecular fluctuations and anchor position dynamics outside the MHC binding groove. We discuss implications of these structural and dynamic immunogenicity correlates for the induction of T cell responses and therapeutic T cell receptor design.

Tumor-associated macrophages expressing the transcription factor IRF8 promote T cell exhaustion in cancer.

Tumors are populated by antigen-presenting cells (APCs) including macrophage subsets with distinct origins and functions. Here, we examined how cancer impacts mononuclear phagocytic APCs in a murine model of breast cancer. Tumors induced the expansion of monocyte-derived tumor-associated macrophages (TAMs) and the activation of type 1 dendritic cells (DC1s), both of which expressed and required the transcription factor interferon regulatory factor-8 (IRF8). Although DC1s mediated cytotoxic T lymphocyte (CTL) priming in tumor-draining lymph nodes, TAMs promoted CTL exhaustion in the tumor, and IRF8 was required for TAMs' ability to present cancer cell antigens. TAM-specific IRF8 deletion prevented exhaustion of cancer-cell-reactive CTLs and suppressed tumor growth. Tumors from patients with immune-infiltrated renal cell carcinoma had abundant TAMs that expressed IRF8 and were enriched for an IRF8 gene expression signature. Furthermore, the TAM-IRF8 signature co-segregated with CTL exhaustion signatures across multiple cancer types. Thus, CTL exhaustion is promoted by TAMs via IRF8.

Cytotoxic innate lymphoid cells sense cancer cell-expressed interleukin-15 to suppress human and murine malignancies.

Malignancy can be suppressed by the immune system. However, the classes of immunosurveillance responses and their mode of tumor sensing remain incompletely understood. Here, we show that although clear cell renal cell carcinoma (ccRCC) was infiltrated by exhaustion-phenotype CD8+ T cells that negatively correlated with patient prognosis, chromophobe RCC (chRCC) had abundant infiltration of granzyme A-expressing intraepithelial type 1 innate lymphoid cells (ILC1s) that positively associated with patient survival. Interleukin-15 (IL-15) promoted ILC1 granzyme A expression and cytotoxicity, and IL-15 expression in chRCC tumor tissue positively tracked with the ILC1 response. An ILC1 gene signature also predicted survival of a subset of breast cancer patients in association with IL-15 expression. Notably, ILC1s directly interacted with cancer cells, and IL-15 produced by cancer cells supported the expansion and anti-tumor function of ILC1s in a murine breast cancer model. Thus, ILC1 sensing of cancer cell IL-15 defines an immunosurveillance mechanism of epithelial malignancies.

Programme of self-reactive innate-like T cell-mediated cancer immunity.

Cellular transformation induces phenotypically diverse populations of tumour-infiltrating T cells1-5, and immune checkpoint blockade therapies preferentially target T cells that recognize cancer cell neoantigens6,7. Yet, how other classes of tumour-infiltrating T cells contribute to cancer immunosurveillance remains elusive. Here, in a survey of T cells in mouse and human malignancies, we identified a population of αß T cell receptor (TCR)-positive FCER1G-expressing innate-like T cells with high cytotoxic potential8 (ILTCKs). These cells were broadly reactive to unmutated self-antigens, arose from distinct thymic progenitors following early encounter with cognate antigens, and were continuously replenished by thymic progenitors during tumour progression. Notably, expansion and effector differentiation of intratumoural ILTCKs depended on interleukin-15 (IL-15) expression in cancer cells, and inducible activation of IL-15 signalling in adoptively transferred ILTCK progenitors suppressed tumour growth. Thus, the antigen receptor self-reactivity, unique ontogeny, and distinct cancer cell-sensing mechanism distinguish ILTCKs from conventional cytotoxic T cells, and define a new class of tumour-elicited immune response.

Cytotoxic granzyme C-expressing ILC1s contribute to antitumor immunity and neonatal autoimmunity.

Innate lymphocytes are integral components of the cellular immune system that can coordinate host defense against a multitude of challenges and trigger immunopathology when dysregulated. Natural killer (NK) cells and innate lymphoid cells (ILCs) are innate immune effectors postulated to functionally mirror conventional cytotoxic T lymphocytes and helper T cells, respectively. Here, we showed that the cytolytic molecule granzyme C was expressed in cells with the phenotype of type 1 ILCs (ILC1s) in mouse liver and salivary gland. Cell fate-mapping and transfer studies revealed that granzyme C-expressing innate lymphocytes could be derived from ILC progenitors and did not interconvert with NK cells, ILC2s, or ILC3s. Granzyme C defined a maturation state of ILC1s. These granzyme C-expressing ILC1s required the transcription factors T-bet and, to a lesser extent, Eomes and support from transforming growth factor-ß (TGF-ß) signaling for their maintenance in the salivary gland. In a transgenic mouse breast cancer model, depleting ILC1s caused accelerated tumor growth. ILC1s gained granzyme C expression following interleukin-15 (IL-15) stimulation, which enabled perforin-mediated cytotoxicity. Constitutive activation of STAT5, a transcription factor regulated by IL-15, in granzyme C-expressing ILC1s triggered lethal perforin-dependent autoimmunity in neonatal mice. Thus, granzyme C marks a cytotoxic effector state of ILC1s, broadening their function beyond "helper-like" lymphocytes.

Rules of Engagement: The Lymphocyte Receptor Ecosystem in Renal Cell Carcinoma.

Immune receptor repertoires provide insight into the clonal distribution of tumor-infiltrating lymphocytes, yet the clinical implications of T-cell receptor (TCR) and B-cell receptor (BCR) repertoire diversity in cancer are unclear. In this issue of Cancer Research, Ferral-Fairbanks and colleagues reveal the interplay between repertoire diversity, tumor molecular features, and clinical outcome in renal cell carcinoma (RCC). The authors show that aggressive tumors harbor increasingly diverse TCR and BCR repertoires and that both repertoires are altered by common RCC driver mutations. Moreover, the authors demonstrate that high TCR diversity is associated with improved overall survival. This study highlights the contribution of lymphocyte receptor dynamics to the emerging complexity of RCC antitumor immune responses. See related article by Ferral-Fairbanks et al., p. 929.

Single-Cell Transcriptional Profiling Reveals Signatures of Helper, Effector, and Regulatory MAIT Cells during Homeostasis and Activation.

Mucosal-associated invariant T (MAIT) cells are innate-like lymphocytes that recognize microbial vitamin B metabolites and have emerging roles in infectious disease, autoimmunity, and cancer. Although MAIT cells are identified by a semi-invariant TCR, their phenotypic and functional heterogeneity is not well understood. Here we present an integrated single cell transcriptomic analysis of over 76,000 human MAIT cells during early and prolonged Ag-specific activation with the MR1 ligand 5-OP-RU and nonspecific TCR stimulation. We show that MAIT cells span a broad range of homeostatic, effector, helper, tissue-infiltrating, regulatory, and exhausted phenotypes, with distinct gene expression programs associated with CD4+ or CD8+ coexpression. During early activation, MAIT cells rapidly adopt a cytotoxic phenotype characterized by high expression of GZMB, IFNG and TNF In contrast, prolonged stimulation induces heterogeneous states defined by proliferation, cytotoxicity, immune modulation, and exhaustion. We further demonstrate a FOXP3 expressing MAIT cell subset that phenotypically resembles conventional regulatory T cells. Moreover, scRNAseq-defined MAIT cell subpopulations were also detected in individuals recently exposed to Mycobacterium tuberculosis, confirming their presence during human infection. To our knowledge, our study provides the first comprehensive atlas of human MAIT cells in activation conditions and defines substantial functional heterogeneity, suggesting complex roles in health and disease.

Improved prediction of immune checkpoint blockade efficacy across multiple cancer types.

Only a fraction of patients with cancer respond to immune checkpoint blockade (ICB) treatment, but current decision-making procedures have limited accuracy. In this study, we developed a machine learning model to predict ICB response by integrating genomic, molecular, demographic and clinical data from a comprehensively curated cohort (MSK-IMPACT) with 1,479 patients treated with ICB across 16 different cancer types. In a retrospective analysis, the model achieved high sensitivity and specificity in predicting clinical response to immunotherapy and predicted both overall survival and progression-free survival in the test data across different cancer types. Our model significantly outperformed predictions based on tumor mutational burden, which was recently approved by the U.S. Food and Drug Administration for this purpose1. Additionally, the model provides quantitative assessments of the model features that are most salient for the predictions. We anticipate that this approach will substantially improve clinical decision-making in immunotherapy and inform future interventions.

High Response Rate and Durability Driven by HLA Genetic Diversity in Patients with Kidney Cancer Treated with Lenvatinib and Pembrolizumab.

Immune checkpoint blockade (ICB) therapy has substantially improved the outcomes of patients with many types of cancers, including renal cell carcinoma (RCC). Initially studied as monotherapy, immunotherapy-based combination regimens have improved the clinical benefit achieved by ICB monotherapy and have revolutionized RCC treatment. While biomarkers like PD-L1 and tumor mutational burden (TMB) are FDA approved as biomarkers for ICB monotherapy, there are no known biomarkers for combination immunotherapies. Here, we describe the clinical outcomes and genomic determinants of response from a phase Ib/II clinical trial on patients with advanced RCC evaluating the efficacy of lenvatinib, a multi-kinase inhibitor mainly targeting VEGFR and FGFR plus pembrolizumab, an anti-PD1 immunotherapy. Concurrent treatment with lenvatinib and pembrolizumab resulted in an objective response rate of 79% (19/24) and tumor shrinkage in 96% (23/24) of patients. While tumor mutational burden (TMB) did not predict for clinical benefit, germline HLA-I diversity strongly impacted treatment efficacy. Specifically, HLA-I evolutionary divergence (HED), which measures the breadth of a patient's immunopeptidome, was associated with both improved clinical benefit and durability of response. Our results identify lenvatinib plus pembrolizumab as a highly active treatment strategy in RCC and reveal HLA-I diversity as a critical determinant of efficacy for this combination. HED also predicted better survival in a separate cohort of patients with RCC following therapy with anti-PD-1-based combination therapy. IMPLICATIONS: These findings have substantial implications for RCC therapy and for understanding immunogenetic mechanisms of efficacy and warrants further investigation.

Single-cell sequencing links multiregional immune landscapes and tissue-resident T cells in ccRCC to tumor topology and therapy efficacy.

Clear cell renal cell carcinomas (ccRCCs) are highly immune infiltrated, but the effect of immune heterogeneity on clinical outcome in ccRCC has not been fully characterized. Here we perform paired single-cell RNA (scRNA) and T cell receptor (TCR) sequencing of 167,283 cells from multiple tumor regions, lymph node, normal kidney, and peripheral blood of two immune checkpoint blockade (ICB)-naïve and four ICB-treated patients to map the ccRCC immune landscape. We detect extensive heterogeneity within and between patients, with enrichment of CD8A+ tissue-resident T cells in a patient responsive to ICB and tumor-associated macrophages (TAMs) in a resistant patient. A TCR trajectory framework suggests distinct T cell differentiation pathways between patients responding and resistant to ICB. Finally, scRNA-derived signatures of tissue-resident T cells and TAMs are associated with response to ICB and targeted therapies across multiple independent cohorts. Our study establishes a multimodal interrogation of the cellular programs underlying therapeutic efficacy in ccRCC.

Mutations in BRCA1 and BRCA2 differentially affect the tumor microenvironment and response to checkpoint blockade immunotherapy.

Immune checkpoint blockade (ICB) has improved outcomes for patients with advanced cancer, but the determinants of response remain poorly understood. Here we report differential effects of mutations in the homologous recombination genes BRCA1 and BRCA2 on response to ICB in mouse and human tumors, and further show that truncating mutations in BRCA2 are associated with superior response compared to those in BRCA1. Mutations in BRCA1 and BRCA2 result in distinct mutational landscapes and differentially modulate the tumor-immune microenvironment, with gene expression programs related to both adaptive and innate immunity enriched in BRCA2-deficient tumors. Single-cell RNA sequencing further revealed distinct T cell, natural killer, macrophage, and dendritic cell populations enriched in BRCA2-deficient tumors. Taken together, our findings reveal the divergent effects of BRCA1 and BRCA2-deficiency on ICB outcome, and have significant implications for elucidating the genetic and microenvironmental determinants of response to immunotherapy.

Qa-1b Modulates Resistance to Anti-PD-1 Immune Checkpoint Blockade in Tumors with Defects in Antigen Processing.

Immune checkpoint blockade (ICB) has improved cancer care, but ICB is only effective in some patients. The molecular mechanisms that influence ICB therapy response are not completely understood. The non-classical MHC class I molecule HLA-E and its mouse ortholog, Qa-1b, present a limited set of peptides in a TAP1-dependent manner to the NKG2A/CD94 heterodimer to transduce an inhibitory signal to natural killer (NK) and CD8+ T cells. However, deficiency of TAP1 allows Qa-1b to present an alternative peptidome to Qa-1b-restricted T-cell receptors of cytotoxic T cells. In this study, we used CRISPR-Cas9 to study the relationship between TAP1, Qa-1b, and response to anti-PD1 therapy. We hypothesized that immunotherapy response in TAP1-deficient tumors would be influenced by Qa-1b. Strikingly, using a syngeneic orthotopic mouse model, we found that although TAP1-deficient tumors were resistant to anti-PD1 treatment, anti-PD1 response was significantly enhanced in tumors lacking both TAP1 and Qa-1b. This increased sensitivity is partially dependent on NK cells. TAP1-deficient tumors were associated with an increase of intratumoral regulatory T cells (Treg) and neutrophils, whereas tumors lacking both TAP1 and Qa-1b exhibited an increased CD8+ T-cell to Treg ratio. These data suggest that direct inhibition of Qa-1b may alter the immune microenvironment to reverse resistance to anti-PD1 therapy, particularly in the context of antigen-processing defects. IMPLICATIONS: This study reveals important functional crosstalk between classical TAP-dependent MHC complexes and Qa-1b/HLA-E, particularly in tumors with impaired antigen-processing machinery. This can dramatically influence immunotherapy efficacy.

Genetic and environmental determinants of human TCR repertoire diversity.

T cell discrimination of self and non-self is the foundation of the adaptive immune response, and is orchestrated by the interaction between T cell receptors (TCRs) and their cognate ligands presented by major histocompatibility (MHC) molecules. However, the impact of host immunogenetic variation on the diversity of the TCR repertoire remains unclear. Here, we analyzed a cohort of 666 individuals with TCR repertoire sequencing. We show that TCR repertoire diversity is positively associated with polymorphism at the human leukocyte antigen class I (HLA-I) loci, and diminishes with age and cytomegalovirus (CMV) infection. Moreover, our analysis revealed that HLA-I polymorphism and age independently shape the repertoire in healthy individuals. Our data elucidate key determinants of human TCR repertoire diversity, and suggest a mechanism underlying the evolutionary fitness advantage of HLA-I heterozygosity.

Evolutionary divergence of HLA class I genotype impacts efficacy of cancer immunotherapy.

Functional diversity of the highly polymorphic human leukocyte antigen class I (HLA-I) genes underlies successful immunologic control of both infectious disease and cancer. The divergent allele advantage hypothesis dictates that an HLA-I genotype with two alleles with sequences that are more divergent enables presentation of more diverse immunopeptidomes1-3. However, the effect of sequence divergence between HLA-I alleles-a quantifiable measure of HLA-I evolution-on the efficacy of immune checkpoint inhibitor (ICI) treatment for cancer remains unknown. In the present study the germline HLA-I evolutionary divergence (HED) of patients with cancer treated with ICIs was determined by quantifying the physiochemical sequence divergence between HLA-I alleles of each patient's genotype. HED was a strong determinant of survival after treatment with ICIs. Even among patients fully heterozygous at HLA-I, patients with an HED in the upper quartile respond better to ICIs than patients with a low HED. Furthermore, HED strongly impacts the diversity of tumor, viral and self-immunopeptidomes and intratumoral T cell receptor clonality. Similar to tumor mutation burden, HED is a fundamental metric of diversity at the major histocompatibility complex-peptide complex, which dictates ICI efficacy. The data link divergent HLA allele advantage to immunotherapy efficacy and unveil how ICI response relies on the evolved efficiency of HLA-mediated immunity.