Single-cell RNA Research Articles

Expansion of a CD8+ Temra Population and Activating T-Cell Interactions Characterize the Graft Versus Leukemia Response in Relapsed AML

Graft-versus-leukemia (GvL) activity underlies the curative potential of allogeneic hematopoietic stem cell transplantation. Its effectiveness is well-exemplified by donor lymphocyte infusion (DLI), an established adoptive cellular therapy for treatment of relapsed disease. Whereas ~80% of chronic myelogenous leukemia (CML) patients achieve durable remissions to DLI, responses for acute myelogenous leukemia (AML) are only 15-20%. We hypothesized that systematic characterization of immune cell composition and cellular interactions within the marrow tumor microenvironment in relation to DLI would illuminate the molecular basis of the disease-specific susceptibility to GvL. Given the heterogeneous nature of AML, we suspected AML response to comprise more complex leukemic-immune cell interactions than in CML. To these ends, we generated 5’ single-cell RNA- and TCR-sequencing (scTCRseq) and cell surface marker profiling (scCITE-seq) on 24 bone marrow biopsy samples collected before and after DLI from 9 patients with relapsed AML (5 responders [R], 4 nonresponders [NR]). We merged this dataset with our previously reported CML dataset (14 patients, 8 R, 6 NR [PMID: 34758319]) and batch corrected these data with scVI to obtain a total of 414,000 high-quality single-cell transcriptomes for analysis. Evaluation of the immune cell subset proportions over time revealed 10 populations with distinct dynamics in AML responders to DLI but not CML, while 3 other populations showed similar dynamics across diseases. Both CML and AML DLI response were associated with pre-treatment enrichment of an NK cell population highly expressing XCL1, XCL2, CCL3, CCL4, CCL4L2, and CCL5, consistent with a tumor-infiltrating expression profile. Unique to CML (i.e. not observed in AML), in addition to post-DLI enrichment of the TPEX population previously identified, we found a γδ-like T cell population and a classical dendritic cell population exhibiting post-DLI enrichment associated with response to DLI. In AML, response to DLI was most consistently associated with expansion of a CD8+ T cell population (6.03% of total pre-DLI cells vs 18.31% post-DLI for R [p=0.016] compared to 8.68% pre-DLI vs 9.55% post-DLI for NR [p=0.454]) and a naïve B cell population (4.02% pre-DLI vs 11.68% post-DLI for R [p=0.002] compared to 5.42% pre-DLI vs 5.17% post-DLI for NR [p=0.471]). The CD8+ T cell population was characterized by high expression of cytotoxicity genes (e.g. GZMA, GZMB, GZMH, GZMM, PRF1, KLRG1, TOX, EOMES, TBX21) and was most consistent with a T effector memory re-expressing RA (TEMRA) profile, supported by high CD45RA expression by scCITE-seq. This population also highly expressed ZNF683, which encodes the transcription factor Hobit, known to regulate cytotoxicity in CD8+ T cells. Differential gene expression between AML R and NR TEMRA cells revealed enriched expression of ZNF683, GZMH, NKG7, CCL5, and CXCR4 in R and the exhaustion marker TIGIT and the senescence marker KLRG1 in NR. scTCR-seq of the TEMRA subset demonstrated clonal expansion and differentiation into a more proliferative expression profile post-DLI. Among AML cases, 2-20% of the post-DLI repertoire of responders originated from the DLI product while no TCR from the DLI product was detected in the single NR patient available for analysis. We applied predictive interaction modeling among all 50 cell type pairs using CellPhoneDB (PMID: 32103204), which utilizes a publicly available curated database of receptor-ligand interactions. Predicted interactions unique to R between CD8+ TEMRA and AML leukemia cells included CD226-PVR, CD6-ALCAM, and CD46-JAG1, which have been associated with T cell activation. Interactions unique to NR between CD8+ TEMRA and AML leukemia included the inhibitory interactions TIGIT-NECTIN and PTPRC-MRC1. These interactions were not observed in CML patients in either R or NR between CD8+ TEMRA and CML cells, suggesting disease-specific response and resistance mechanisms. Here we show that response to DLI in AML is associated with largely distinct expansion of immune cell populations compared to CML, including not only T cells but an orchestration of B, NK, and myeloid cell subsets. AML responders were uniquely characterized by expansion of a TEMRA subset marked by high expression of the pro-cytotoxic gene ZNF683. Further investigation is needed to evaluate the role of this population in mediating GvL response.

Longitudinal Single Cell Multiomic Analysis of a Patient with GATA2 Haploinsufficiency with ASXL1 Mutant Clonal Hematopoiesis

Introduction: GATA2 haploinsufficiency syndrome (G2HS) is an autosomal dominant germline predisposition state with broad phenotypic variability and high risk of developing myeloid neoplasms (74.3%, median age of onset 17 years; Homan CC, et al. 2021). Mechanisms resulting in myeloid transformation remain to be elucidated. To identify molecular changes and relevant drivers of gene expression prior to progression, we performed serial, single cell multiomics on a proband with G2HS and ASXL1 mutant clonal hematopoiesis (CH) over 7 years. Case report: The proband was diagnosed with G2HS at age 19 years when he presented with recurrent infections, scrotal and penile lymphedema and cytopenias. Bone marrow (BM) biopsy at diagnosis was hypocellular with minimal atypia. Next generation sequencing (NGS) identified a novel pathogenic variant in GATA2 (NM_001145661.2: c.1143+200_1198delinsC; Dorn J et al, 2017) confirmed to be germline, and a somatic pathogenic variant in ASXL1 (NM_015338.6: c.2638dupA; p.Thr880Asnfs*2) with a variant allele frequency (VAF) of 11%, indicative of CH. Methods: After IRB approval, clinical data was abstracted from the medical records. Four aliquots of BM mononuclear cells from BM biopsies obtained 6 months apart were subjected to targeted NGS, single cell RNA (scRNA-seq) and scATAC-seq. Preprocessing and poor-quality cell filtering were performed using the Cell Ranger pipeline. For scRNA-seq, filtered counts were clustered and annotated using Seurat v4.1.0 onto a CITEseq PBMC reference (Hao Y, et al. 2021). Genes were ranked within each cluster between samples based on their average log-fold change, and gene set enrichment analysis (GSEA) was performed using the fgsea package v1.16.0. In parallel, filtered scATAC-seq data was integrated with scRNA using the cluster-label transfer from Signa v1.5.0 and Seurat v4.1.0. Using MAESTRO (Wang C, et al. 2020), we predicted the transcriptional factors (TF) regulating the expression from differentially expressed genes and differential peaks between samples based on the enrichment scores from algorithms LISA (Qin Q, et al. 2020) and GIGGLE (Layer RM, et al. 2018) for RNAseq and ATACseq respectively. Results: Serial blood cell counts, blood indices and BM biopsies over 7 years remained stable (macrocytosis, monocytopenia and neutropenia), with the BM demonstrating stable hypocellularity (10-20%) with minimal atypia and with no evidence for progression to myelodysplastic syndrome (MDS). ASXL1 mutant VAF also remained stable (11 to 16% at last measurement). Quantitative flow cytometric assessments in blood revealed decreases in B and NK cells. Analysis of scRNA/scATAC-seq successfully identified monocytes, B-cells, CD4, CD8 and NK Cells yielding comparable counts to those obtained by flow cytometry. The G2HS-associated cytopenias resulted in very small numbers of monocytes and B cells being identified, and hence differential gene expression analysis was limited to CD4+, CD8+ T cells and NK cells, between time points 1 and 3 (Figure 1A). Differentially expressed genes showed aberrant enrichment of downregulated genes in pathways related to hematopoietic stem cell (HSC) maturation in all three populations, while upregulated genes were enriched in cell cycle and innate immune responses. Analysis of regulatory drivers identified BRD4 as the main TF controlling the differentially expressed genes in CD4+ T cells and NK cells, and ERG in CD8+ T cells. The expression of these TF did not change between timepoints. (Figure 1B) Discussion: We present a GATA2 haploinsufficient proband who has remained stable and MDS-free over 7 years, even with ASXL1 mutant CH. Despite the stability in his blood counts and BM, single cell analysis has identified progressive qualitative changes impacting relevant pathways including HSC maturation, cell cycle regulation and innate immune responses in T and NK cells. In addition, our scATAC-seq data predicts BRD4 and ERG to be important epigenetic readers/TF that regulate these changes. We plan to study larger cohorts of patients and additional time points to understand transcriptional and epigenetic changes induced by GATA2 haploinsufficiency and elucidate the role of ASXL1 mutant CH in disease progression. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Fc-Mediated Antibody Effector Function, Inflammation Resolution and Oligoclonality on TCR Rearrangements Predict Sustained MRD Negativity in Newly Diagnosed Multiple Myeloma Treated with Immunotherapy Regimens

Background: Targeted immunotherapy combinations including anti-CD38 monoclonal antibody daratumumab have significantly increased the depth of response and clinical outcome in newly diagnosed multiple myeloma (NDMM). Despite this improvement, 30-40% of patients still progress early and fail to achieve sustained minimal residual disease (MRD) negativity through largely unknown resistance mechanisms. Here we integrate whole genome sequencing (WGS) and single cell RNA (scRNA), surface protein (CITE), and TCR sequencing from patients with NDMM to characterize genomic and immune microenvironment features related to the failure to achieve sustained remission. Methods: 5'single-cell RNA-sequencing with an additional capture of the TCR and surface protein markers (CITEseq) was performed at both induction (T1) and at the end of induction (T2) with DKRd (Daratumumab-Carfilzomib, Lenalidomide and dexamethasone). A total of 148,280 cells were analyzed for RNA and CITE from 17 patients at T1 and 18 at T2. Twenty-seven cell types were identified and changes in their gene expression were examined. Data were integrated with 40,000 healthy bone marrow cells from the Human Cell Atlas. For TCR-seq, a total of 22,882 ⍺β clonotypes were analyzed. Fc-mediated antibody effector function is associated with sustained MRD negativity The microenvironment changed drastically between diagnosis and end of induction. The achievement of sustained MRD negativity were associated with an expansion of activated CD56-bright NK cells at T1 (chi-squared=4, p=0.044). Furthermore, significant changes in the monocyte profile were seen between timepoints and response groups. We identified a subset of resident-like macrophages expressing markers such as IL1B and CXCL2 suggesting that there are some immune hot tumors that are associated with suboptimal responses. Although there weren't absolute differences in T-cell subsets, PCA analysis showed that the combination of CD8 effector 1, CD16+monocytes and CD56+NK profiles could be used to identify a subset of good responders achieving sustained MRD negativity. Inflammation resolution is associated with sustained MRD negativity when complete response is achieved, significant changes in the microenvironment were observed and expansion of CD16+ monocytes associated with sustained MRD negativity. These data were validated prospectively using flow cytometry (n=31). These data suggest that the presence of cells mediating Fc-dependent immune effector mechanisms at diagnosis could predict good response and the resolution of tumor induced inflammation after treatment is associated with anti-inflammatory CD16+ monocytes. Oligoclonality in T-cell is associated with treatment and response TCR analysis was available for 22,882 cells and showed that there were significantly fewer clonotypes between T1 and T2 (Kruskal-Wallis chi-squared = 4.0, df = 1, p-value = 0.044) reflecting both the impact of treatment, possible antigen selection, and/or the disappearance of the chronic antigen in the form of the malignant plasma cells. Patients that failed to achieve MRD negativity at T2 had significantly more clonotypes suggesting an ineffective T-cell response to residual tumor. Diversity analysis is currently ongoing. Conclusion: In this multilayered analysis we show changes that the composition of the microenvironment is related to the level of response in the context of DKRd treatment. Fc-mediated antibody effector function and inflammation resolution are associated with sustained MRD negativity phenotypes response suggesting a significant contribution of the microenvironment to response, opening the way for therapeutic manipulation to enhance response. TCR analysis reveals for the first time that oligoclonal profiles seen on treatment may influence the fitness of the immune response.

Multiomic Single-Cell Sequencing of Mixed Phenotypic Acute Leukemia (MPAL) Reveals Complex Immunophenotypic, Transcriptional, and Genetic Heterogeneity

Introduction Mixed phenotypic acute leukemia (MPAL) is characterized by leukemic blasts with both lymphoid and myeloid cell-surface markers. Due to the relative rarity and heterogenous nature of MPAL, the optimal therapeutic strategy remains uncertain, although emerging data suggest further sub-classification of MPAL may facilitate therapeutic decision making. Using single cell (SC) multiomic profiling, we sought to further characterize the heterogenous transcriptional, genetic, and immunophenotypic landscape of MPAL. Methods We analyzed samples from 14 patients with newly diagnosed MPAL (11 B/myeloid; 3 T/myeloid). We performed high-throughput SC DNA sequencing (Mission Bio Tapestri) and SC RNA sequencing (Fluent BioSciences PIPseq) with simultaneous cell surface immunophenotyping. Results Using SC DNA sequencing, we analyzed a total of 51,847 cells (4,196 cells/patient); using RNA sequencing, we analyzed a total of 71,579 cells (6,143 cells/patient). Multiomic SC sequencing revealed striking intra-patient heterogeneity, with multiple immunophenotypically, genetically, and/or transcriptionally distinct populations within individual patients. Furthermore, for individual patients, "mixed” phenotype was not always correlated with genetics or gene expression. In 5/14 patients, immunophenotype correlated with both genotype and transcriptional signature in at least one subpopulation. For example, in one patient, 32% of biphenotypic blasts demonstrated monocytic features (CD11b, CD14, and CD64 expression). Unlike blasts without monocytic features in the same specimen, this population was IDH2mut and had increased differential expression of LYZ and S100A8/9. For 7/14 patients, however, phenotypic populations did not correlate with a clear genetic driver. In one patient, for example, we observed two blast populations, one with an immature immunophenotype characterized by elevated CD117 and CD34 expression, and one with a monocytic immunophenotype characterized by elevated CD14 and CD64 expression. Although these two populations were both TP53mut, they had different transcriptional signatures, with the immature population showing increased SOX4, FLT3, and VPREB expression and the monocytic population with increased LYZ, S100A8/9, and MNDA expression. Finally, 2 patients had immunophenotypic heterogeneity but we observed identical genetic and transcriptional signatures within the immunophenotypically distinct subpopulations. Across this cohort, we identified a recurrent transcriptional signature associated with immature blasts, characterized by increased CD34 and CD117 expression. Found in 7 patients with either B or T/myeloid MPAL, these immature subpopulations were enriched for expression of genes associated with lymphocyte development (DNTT, VPREB, PAX5), malignant myelopoiesis (SOX4, FLT3, SPINK2), and cell-cycle regulation (TUBB, UHRF1) compared to more differentiated blasts from the same patients. Phylogenic analysis revealed the effect of mutation acquisition on development of a malignant immunophenotype. In 3 patients, we observed both heterozygous and homozygous TP53mut populations. In all 3 patients, immunophenotypically normal T cells were identified within the heterozygous TP53mut population, consistent with initial acquisition of this mutation within a stem/progenitor population. In contrast, homozygous TP53mut cells all expressed aberrant immunophenotypes, consistent with leukemic blasts. Within each individual patient, relative to the heterozygous TP53mut cells, homozygous TP53mut cells demonstrated significantly increased CD33, CD34, and CD117 expression. Conclusions Multiomic SC sequencing allows for direct measurement of immunophenotypic, genetic, and transcriptional clonal architecture. We demonstrated considerable intra- and inter-patient heterogeneity, in which both genotype and transcriptional signature, transcriptional signature alone, or neither were found to correlate with immunophenotype. Despite this heterogeneity, in half our cohort, we identified a recurrent gene expression signature associated with immature immunophenotype, which correlated with genetic drivers of immunophenotype in some cases. Future multiomic studies are needed to completely subtype MPAL and elucidate the impact of these subtypes on treatment outcomes. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Identification of diagnostic genes for both Alzheimer's disease and Metabolic syndrome by the machine learning algorithm.

Alzheimer's disease is the most common neurodegenerative disease worldwide. Metabolic syndrome is the most common metabolic and endocrine disease in the elderly. Some studies have suggested a possible association between MetS and AD, but few studied genes that have a co-diagnostic role in both diseases. The microarray data of AD (GSE63060 and GSE63061 were merged after the batch effect was removed) and MetS (GSE98895) in the GEO database were downloaded. The WGCNA was used to identify the co-expression modules related to AD and MetS. RF and LASSO were used to identify the candidate genes. Machine learning XGBoost improves the diagnostic effect of hub gene in AD and MetS. The CIBERSORT algorithm was performed to assess immune cell infiltration MetS and AD samples and to investigate the relationship between biomarkers and infiltrating immune cells. The peripheral blood mononuclear cells (PBMCs) single-cell RNA (scRNA) sequencing data from patients with AD and normal individuals were visualized with the Seurat standard flow dimension reduction clustering the metabolic pathway activity changes each cell with ssGSEA. The brown module was identified as the significant module with AD and MetS. GO analysis of shared genes showed that intracellular transport and establishment of localization in cell and organelle organization were enriched in the pathophysiology of AD and MetS. By using RF and Lasso learning methods, we finally obtained eight diagnostic genes, namely ARHGAP4, SNRPG, UQCRB, PSMA3, DPM1, MED6, RPL36AL and RPS27A. Their AUC were all greater than 0.7. Higher immune cell infiltrations expressions were found in the two diseases and were positively linked to the characteristic genes. The scRNA-seq datasets finally obtained seven cell clusters. Seven major cell types including CD8 T cell, monocytes, T cells, NK cell, B cells, dendritic cells and macrophages were clustered according to immune cell markers. The ssGSEA revealed that immune-related gene (SNRPG) was significantly regulated in the glycolysis-metabolic pathway. We identified genes with common diagnostic effects on both MetS and AD, and found genes involved in multiple metabolic pathways associated with various immune cells.

Single-Cell Heterogeneity of the Liver-Infiltrating Lymphocytes in Individuals with Chronic Echinococcus multilocularis Infection.

Human alveolar echinococcosis (AE) is a tumor-like disease predominantly located in the liver. The cellular composition and heterogeneity of the lesion-infiltrating lymphocytes which produce an "immunosuppressive" microenvironment are poorly understood. Here, we profiled 83,921 CD45+ lymphocytes isolated from the peripheral blood (PB), perilesion (PL), and adjacent normal (AN) liver tissue of four advanced-stage AE patients using single-cell RNA and T-cell receptor (TCR) sequencing technology. We identified 23 large clusters, and the distributions and transcriptomes of these cell clusters in the liver and periphery were different. The cellular proportions of exhausted CD8+ T cells and group 2 innate lymphoid cells (ILC2s) were notably higher in PL tissue, and the expression features of these cell subsets were related to neoplasm metastasis and immune response suppression. In the 5 CD8+ T-cell populations, only CD8+ mucosa-associated invariant T (MAIT) cells were enriched in PL samples and the TRAV1-2_TRAJ33_TRAC TCR was clonally expanded. In the 11 subsets of CD4+ T cells, Th17 cells and induced regulatory T cells (iTregs) were preferentially enriched in PL samples, and their highly expressed genes were related to cell invasion, tumor metastasis, and inhibition of the inflammatory immune response. Exhaustion-specific genes (TIGIT, PD-1, and CTLA4) were upregulated in Tregs. Interestingly, there was a close contact between CD8+ T cells and iTregs or Th17 cells, especially for genes related to immunosuppression, such as PDCD1-FAM3C, which were highly expressed in PL tissue. This transcriptional data set provides valuable insights and a rich resource for deeply understanding the immune microenvironment in AE, which could provide potential target signatures for AE diagnosis and immunotherapies.

Multi-omics profiling identifies C1QA/B+ macrophages with multiple immune checkpoints associated with esophageal squamous cell carcinoma (ESCC) liver metastasis

Esophageal squamous cell carcinoma (ESCC) is a highly lethal malignant tumor lacking effective treatments; 20% of ESCC patients develop liver metastasis with an extremely short survival time of ≈5 months. The tumor microenvironment (TME) plays a crucial role in tumor homeostasis, but the relationship between the ESCC TME and liver metastasis is still unknown. To identify potential cell populations contributing to ESCC liver metastasis, single-cell RNA (scRNA) sequencing data were analyzed to identify the major cell populations within the TME. Each of the major cell populations was re-clustered to define detailed cell subsets. Thereafter, the gene set variation analysis (GSVA) score was calculated for the bulk RNA-seq data based on the gene signatures of each cell subset. The relationship between the GSVA score of each cellular subset and clinical outcome was further analyzed to identify the cellular subset associated with ESCC liver metastasis, which was validated by multiplex immunohistochemistry. C1QA/B+ tumor-associated macrophages (TAMs) acted as the central regulator of the ESCC TME, closely associated with several key cell subsets. Several immune checkpoints, including CD40, CD47 and LGALS9, were all positively expressed in C1QA/B+ macrophages, which may exert central regulatory control of immune evasion by ESCC via these immune checkpoints expressions. Our results comprehensively revealed the landscape of tumor-infiltrating immune cells associated with ESCC prognosis and metastasis, and suggest a novel strategy for developing immunotherapies for ESCC liver metastasis by targeting C1QA/B+ TAMs.

Clonal lineage tracing reveals mechanisms skewing CD8+ T cell fate decisions in chronic infection.

Although recent evidence demonstrates heterogeneity among CD8+ T cells during chronic infection, developmental relationships and mechanisms underlying their fate decisions remain incompletely understood. Using single-cell RNA and TCR sequencing, we traced the clonal expansion and differentiation of CD8+ T cells during chronic LCMV infection. We identified immense clonal and phenotypic diversity, including a subset termed intermediate cells. Trajectory analyses and infection models showed intermediate cells arise from progenitor cells before bifurcating into terminal effector and exhausted subsets. Genetic ablation experiments identified that type I IFN drives exhaustion through an IRF7-dependent mechanism, possibly through an IFN-stimulated subset bridging progenitor and exhausted cells. Conversely, Zeb2 was critical for generating effector cells. Intriguingly, some T cell clones exhibited lineage bias. Mechanistically, we identified that TCR avidity correlates with an exhausted fate, whereas SHP-1 selectively restricts low-avidity effector cell accumulation. Thus, our work elucidates novel mechanisms underlying CD8+ T cell fate determination during persistent infection and suggests two potential pathways leading to exhaustion.

BATF epigenetically and transcriptionally controls the activation program of regulatory T cells in human tumors.

Regulatory T (Treg) cells suppress effective antitumor immunity in tumor-bearing hosts, thereby becoming promising targets in cancer immunotherapy. Despite the importance of Treg cells in tumor immunity, little is known about their differentiation process and epigenetic profiles in the tumor microenvironment (TME). Here, we showed that Treg cells in the TME of human lung cancers harbored a completely different open chromatin profile compared with CD8+ T cells, conventional CD4+ T cells in the TME, and peripheral Treg cells. The integrative sequencing analyses including ATAC, single-cell RNA, and single-cell ATAC sequencing revealed that BATF, IRF4, NF-κB, and NR4A were important transcription factors for Treg cell differentiation in the TME. In particular, BATF was identified as a key regulator, which leveraged Treg cell differentiation through epigenetically controlling activation-associated gene expression, resulting in the robustness of Treg cells in the TME. The single-cell sequencing approaches also revealed that tissue-resident and tumor-infiltrating Treg cells followed a common pathway for differentiation and activation in a BATF-dependent manner heading toward Treg cells with the most differentiated and activated phenotypes in tissues and tumors. BATF deficiency in Treg cells remarkably inhibited tumor growth, and high BATF expression was associated with poor prognosis in lung cancer, kidney cancer, and melanoma. These findings indicate one of the specific chromatin remodeling and differentiation programs of Treg cells in the TME, which can be applied in the development of Treg cell-targeted therapies.

Molecular landscape of immune pressure and escape in aplastic anemia.

Idiopathic aplastic anemia (IAA) pathophysiology is dominated by autoreactivity of human leukocyte antigen (HLA)-restricted T-cells against antigens presented by hematopoietic stem and progenitor cells (HSPCs). Expansion of PIGA and HLA class I mutant HSPCs have been linked to immune evasion from T-cell mediated pressures. We hypothesized that in analogy with antitumor immunity, the pathophysiological cascade of immune escape in IAA is initiated by immunoediting pressures and culminates with mechanisms of clonal evolution characterized by hits in immune recognition and response genes. To that end, we studied the genetic and transcriptomic make-up of the antigen presentation complexes in a large cohort of patients with IAA and paroxysmal nocturnal hemoglobinuria (PNH) by using single-cell RNA, high throughput DNA sequencing and single nucleotide polymorphism (SNP)-array platforms. At disease onset, HSPCs displayed activation of selected HLA class I and II-restricted mechanisms, without extensive inhibition of immune checkpoint apparatus. Using a newly implemented bioinformatic framework we found that not only class I but also class II genes were often impaired by acquisition of genetic aberrations. We also demonstrated the presence of novel somatic alterations in immune genes possibly contributing to the evasion from the autoimmune T-cells. In contrast, these hits were absent in myeloid neoplasia. These aberrations were not mutually exclusive with PNH and did not correlate with the accumulation of myeloid-driver hits. Our findings shed light on the mechanisms of immune activation and escape in IAA and define alternative modes of clonal hematopoiesis.

Identification and exploration of pharmacological pyroptosis-related biomarkers of ulcerative colitis

Ulcerative colitis (UC) is a chronic inflammatory bowel disease (IBD). Its etiology is unclear. Much evidence suggests that the death of abnormal intestinal epithelial cells (IECs) leads to intestinal barrier disruption, and the subsequent inflammatory response plays a vital role in UC. Pyroptosis is a form of programmed inflammatory cell death, and the role of pyroptosis in UC etiology remains to be explored. This study identified 10 hub genes in pyroptosis by gene expression profiles obtained from the GSE87466 dataset. Meanwhile, the biomarkers were screened based on gene significance (GS) and module membership (MM) through the Weighted Gene Co-Expression Network Analysis (WGCNA). The following analysis indicated that hub genes were closely associated with the UC progression and therapeutic drug response. The single-cell RNA (scRNA) sequencing data from UC patients within the GSE162335 dataset indicated that macrophages were most related to pyroptosis. Finally, the expression of hub genes and response to the therapeutic drug [5-aminosalicylic acid (5-ASA)] were verified in dextran sulfate sodium (DSS)-induced colitis mice. Our study identified IL1B as the critical pyroptosis-related biomarker in UC. The crosstalk between macrophage pyroptosis and IEC pyroptosis may play an essential role in UC, deserving further exploration.

Evolution and modulation of antigen-specific T cell responses in melanoma patients

Analyzing antigen-specific T cell responses at scale has been challenging. Here, we analyze three types of T cell receptor (TCR) repertoire data (antigen-specific TCRs, TCR-repertoire, and single-cell RNA + TCRαβ-sequencing data) from 515 patients with primary or metastatic melanoma and compare it to 783 healthy controls. Although melanoma-associated antigen (MAA) -specific TCRs are restricted to individuals, they share sequence similarities that allow us to build classifiers for predicting anti-MAA T cells. The frequency of anti-MAA T cells distinguishes melanoma patients from healthy and predicts metastatic recurrence from primary melanoma. Anti-MAA T cells have stem-like properties and frequent interactions with regulatory T cells and tumor cells via Galectin9-TIM3 and PVR-TIGIT -axes, respectively. In the responding patients, the number of expanded anti-MAA clones are higher after the anti-PD1(+anti-CTLA4) therapy and the exhaustion phenotype is rescued. Our systems immunology approach paves the way for understanding antigen-specific responses in human disorders.

AgeAnno: a knowledgebase of single-cell annotation of aging in human.

Aging is a complex process that accompanied by molecular and cellular alterations. The identification of tissue-/cell type-specific biomarkers of aging and elucidation of the detailed biological mechanisms of aging-related genes at the single-cell level can help to understand the heterogeneous aging process and design targeted anti-aging therapeutics. Here, we built AgeAnno (https://relab.xidian.edu.cn/AgeAnno/#/), a knowledgebase of single cell annotation of aging in human, aiming to provide comprehensive characterizations for aging-related genes across diverse tissue-cell types in human by using single-cell RNA and ATAC sequencing data (scRNA and scATAC). The current version of AgeAnno houses 1 678 610 cells from 28 healthy tissue samples with ages ranging from 0 to 110 years. We collected 5580 aging-related genes from previous resources and performed dynamic functional annotations of the cellular context. For the scRNA data, we performed analyses include differential gene expression, gene variation coefficient, cell communication network, transcription factor (TF) regulatory network, and immune cell proportionc. AgeAnno also provides differential chromatin accessibility analysis, motif/TF enrichment and footprint analysis, and co-accessibility peak analysis for scATAC data. AgeAnno will be a unique resource to systematically characterize aging-related genes across diverse tissue-cell types in human, and it could facilitate antiaging and aging-related disease research.

TiO2 nanoparticles abrogate the protective effect of the Crohn’s disease-associated variation within the PTPN22 gene locus

ObjectiveInflammatory bowel disease (IBD) is a multifactorial condition driven by genetic and environmental risk factors. A genetic variation in the protein tyrosine phosphatase non-receptor type 22 (PTPN22) gene has been...

Identification and analysis of a CD8+ T cell-related prognostic signature for colorectal cancer based on bulk RNA sequencing and scRNA sequencing data: A STROBE-compliant retrospective study.

Colorectal cancer (CRC) is one of the most common malignancies worldwide, leading to a large number of cancer-related mortalities. Aberrant CD8+ T cell infiltration plays a critical role in tumor progression and patient prognosis. This study aimed to identify a prognostic model for CRC based on CD8+ T cell-related genes. The infiltration levels of immune cells in CRC tissues were accessed by the ESTIMATE algorithm. Weighted gene co-expression network analysis (WGCNA) analysis was used to select CD8+ T cell-related genes. Prognostic genes were identified using Cox regression analysis and Kaplan–Meier curves. The least absolute shrinkage and selection operator (LASSO) algorithm was used to construct prognostic models. Gene set enrichment analysis (GSEA) was performed to annotate enriched gene sets. Single-cell RNA (scRNA) sequencing analysis was used to examine gene expression in different cell types. We found that the downregulated infiltration level of CD8+ T cells was an independent prognostic factor for CRC and selected a cluster of differentially expressed genes correlated with CD8+ T cell infiltration (CD8TDEGs). Subsequently, we identified 18 prognostic CD8TDEGs, according to which patients were reclassified into two clusters with distinct overall survival. Seven prognostic CD8TDEGs were selected to calculate the constructed prognostic model’s risk scores. Interestingly, although CRC tissues with higher risk scores had higher infiltration levels of CD8+ T cells, the level of immune checkpoint genes was also high. Moreover, the scRNA-sequencing analysis showed that the expression levels of CD8TDEGs in the prognostic model varied among different types of cells. This study constructed a novel prognostic model for CRC and provided a foundation for targeting CD8+ T cell infiltration to improve the survival of CRC patients.

SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells.

Cell type-specific activities of cis-regulatory elements (CRE) are central to understanding gene regulation and disease predisposition. Single-cell RNA 5'end sequencing (sc-end5-seq) captures the transcription start sites (TSS) which can be used as a proxy to measure the activity of transcribed CREs (tCREs). However, a substantial fraction of TSS identified from sc-end5-seq data may not be genuine due to various artifacts, hindering the use of sc-end5-seq for de novo discovery of tCREs. We developed SCAFE-Single-Cell Analysis of Five-prime Ends-a software suite that processes sc-end5-seq data to de novo identify TSS clusters based on multiple logistic regression. It annotates tCREs based on the identified TSS clusters and generates a tCRE-by-cell count matrix for downstream analyses. The software suite consists of a set of flexible tools that could either be run independently or as pre-configured workflows. SCAFE is implemented in Perl and R. The source code and documentation are freely available for download under the MIT License from https://github.com/chung-lab/SCAFE. Docker images are available from https://hub.docker.com/r/cchon/scafe. The submitted software version and test data are archived at https://doi.org/10.5281/zenodo.7023163 and https://doi.org/10.5281/zenodo.7024060, respectively. Supplementary data are available at Bioinformatics online.

Reclassifying TNM stage I/II colorectal cancer into two subgroups with different overall survival, tumor microenvironment, and response to immune checkpoint blockade treatment

Background: The traditional TNM staging system is often insufficient to differentiate the survival discrepancies of colorectal cancer (CRC) patients at TNM stage I/II. Our study aimed to reclassify stage I/II CRC patients into several subgroups with different prognoses and explore their suitable therapeutic methods. Methods: Single-cell RNA (scRNA) sequencing data, bulk RNA sequencing data, and clinicopathological information of CRC patients were enrolled from the TCGA and GEO databases. The tumor microenvironment of CRC tissues was accessed by the ESTIMATE algorithm. The prognostic genes were identified by Cox regression analysis. GO and KEGG analyses were conducted in the DAVID database. GSEA analysis was performed for annotation of the correlated gene sets. Results: We successfully reclassified stage I/II CRC patients into two subgroups and discovered that patients in cluster-2 underwent worse overall survival than those in cluster-1. GSEA analysis showed that immune-associated gene sets were positively enriched in cluster-2. Besides, the differentially expressed genes (DEGs) between cluster-1 and cluster-2 patients also participated in immune-related biological processes and signaling pathways. Moreover, we found that more immune cells infiltrated the microenvironment of cluster-2 patients compared to that of cluster-1 patients, such as Tregs and tumor-associated macrophages. ScRNA sequencing analysis uncovered that most of the enriched immune-associated signaling in cluster-2 patients was mainly attributed to these upregulated immune cells whose infiltration levels were also high in CRC tissues rather than in normal tissues. In addition, we demonstrated that the expression of immune checkpoint genes was significantly higher in cluster-2 patients compared to cluster-1 patients. ScRNA sequencing analysis revealed that the infiltrated CD8+T cells in CRC were naïve T cells and can be activated into effector T cells after immune checkpoint blockade (ICB) treatment. Conclusion: TNM stage I/II CRC patients can be divided into two subgroups, which have different overall survival rates, tumor microenvironment, and response to ICB therapy.

Comprehensive multiomics analysis of cuproptosis-related gene characteristics in hepatocellular carcinoma.

Background: The mechanism of copper-induced cell death, which is called cuproptosis, has recently been clarified. However, the integrated role of cuproptosis-related genes in hepatocellular carcinoma (HCC) and its relationship with immune characteristics are still completely unknown. Methods: In this study, the expression, genetic, and transcriptional regulation states of 16 cuproptosis-related genes in HCC were systematically investigated. An unsupervised clustering method was used to identify distinct expression patterns in 370 HCC patients from the TCGA-HCC cohort. Differences in functional characteristics among different expression clusters were clarified by gene set variation analysis (GSVA). The abundances of immune cells in each HCC sample were calculated by the CIBERSORT algorithm. Next, a cuproptosis-related risk score was established based on the significant differentially expressed genes (DEGs) among different expression clusters. Results: A specific cluster of HCC patients with poor prognosis, an inhibitory immune microenvironment, and high expression levels of immune checkpoint molecules was identified based on the expression of the 16 cuproptosis-related genes. This cluster of patients could be well-identified by a cuproptosis-related risk score system. The prognostic value of this risk score was validated in the training and two validation cohorts (TCGA-HCC, China-HCC, and Japan-HCC cohorts). Moreover, the overall expression status of the cuproptosis-related genes and the genes used to establish the cuproptosis-related risk score in specific cell types of the tumor microenvironment were preliminarily clarified by single-cell RNA (scRNA) sequencing data. Conclusion: These results indicated that cuproptosis-related genes play an important role in HCC, and targeting these genes may ameliorate the inhibitory immune microenvironment to improve the efficacy of immunotherapy with immune checkpoint inhibitors (ICIs).

IFN-α with dasatinib broadens the immune repertoire in patients with chronic-phase chronic myeloid leukemia.

In chronic myeloid leukemia (CML), combination therapies with tyrosine kinase inhibitors (TKIs) aim to improve the achievement of deep molecular remission that would allow therapy discontinuation. IFN-α is one promising candidate, as it has long-lasting effects on both malignant and immune cells. In connection with a multicenter clinical trial combining dasatinib with IFN-α in 40 patients with chronic-phase CML (NordCML007, NCT01725204), we performed immune monitoring with single-cell RNA and T cell receptor (TCR) sequencing (n = 4, 12 samples), bulk TCRβ sequencing (n = 13, 26 samples), flow cytometry (n = 40, 106 samples), cytokine analyses (n = 17, 80 samples), and ex vivo functional studies (n = 39, 80 samples). Dasatinib drove the immune repertoire toward terminally differentiated NK and CD8+ T cells with dampened functional capabilities. Patients with dasatinib-associated pleural effusions had increased numbers of CD8+ recently activated effector memory T (Temra) cells. In vitro, dasatinib prevented CD3-induced cell death by blocking TCR signaling. The addition of IFN-α reversed the terminally differentiated phenotypes and increased the number of costimulatory intercellular interactions and the number of unique putative epitope-specific TCR clusters. In vitro IFN-α had costimulatory effects on TCR signaling. Our work supports the combination of IFN-α with TKI therapy, as IFN-α broadens the immune repertoire and restores immunological function.

Nonparametric single-cell multiomic characterization of trio relationships between transcription factors, target genes, and cis-regulatory regions.

The epigenetic control of gene expression is highly cell-type and context specific. Yet, despite its complexity, gene regulatory logic can be broken down into modular components consisting of a transcription factor (TF) activating or repressing the target gene expression through its binding to a cis-regulatory region. We propose a nonparametric approach, TRIPOD, to detect and characterize the three-way relationships between a TF, its target gene, and the accessibility of the TF's binding site using single-cell RNA and ATAC multiomic data. We apply TRIPOD to interrogate the cell-type-specific regulatory logic in peripheral blood mononuclear cells and contrast our results to detections from enhancer databases, cis-eQTL studies, ChIP-seq experiments, and TF knockdown/knockout studies. We then apply TRIPOD to mouse embryonic brain data and identify regulatory relationships, validated by ChIP-seq and PLAC-seq. Finally, we demonstrate TRIPOD on the SHARE-seq data of differentiating mouse hair follicle cells and identify lineage-specific regulation supported by histone marks and super-enhancer annotations. A record of this paper's transparent peer review process is included in the supplemental information.