Hallmarks of tumor-experienced T cells are absent in multiple myeloma patients from diagnosis through maintenance therapy.

Dysregulation of the bone marrow (BM) niche in multiple myeloma (MM) alters the composition and state of resident immune cells, potentially impeding anti-tumor immunity. One common mechanism of immune inhibition in solid tumors is the induction of exhaustion in tumor-specific T cells. However, the extent of T cell tumor recognition and exhaustion is not well-characterized in MM. As the specific mechanisms of immune evasion are critical for devising effective therapeutic strategies, we deeply profiled the CD8 + T cell compartment of newly-diagnosed MM (NDMM) patients for evidence of tumor reactivity and T cell exhaustion. We applied single-cell multi-omic sequencing and antigen-specific mass cytometry to longitudinal BM and peripheral blood (PB) samples taken from timepoints spanning from diagnosis through induction therapy, autologous stem cell transplant (ASCT), and maintenance therapy. We identified an exhausted-like population that lacked several canonical exhaustion markers, was not significantly enriched in NDMM patients, and consisted of small, nonpersistent clones. We also observed an activated population with increased frequency in the PB of NDMM patients exhibiting phenotypic and clonal features consistent with homeostatic, antigen-nonspecific activation. However, there was no evidence of "tumor-experienced" T cells displaying hallmarks of terminal exhaustion and/or tumor-specific activation/expansion in NDMM patients at any timepoint.

Cell Simulation as Cell Segmentation.

Single-cell spatial transcriptomics promises a highly detailed view of a cell's transcriptional state and microenvironment, yet inaccurate cell segmentation can render this data murky by misattributing large numbers of transcripts to nearby cells or conjuring nonexistent cells. We adopt methods from ab initio cell simulation to rapidly infer morphologically plausible cell boundaries that preserve cell type heterogeneity. Benchmarking applied to datasets generated by three commercial platforms show superior performance and computational efficiency of this approach compared with existing methods. We show that improved accuracy in cell segmentation aids greatly in detection of difficult to accurately segment tumor infiltrating immune cells such as neutrophils and T cells. Lastly, through improvements in our ability to delineate subsets of tumor infiltrating T cells, we show that CXCL13-expressing CD8+ T cells tend to be more closely associated with tumor cells than their CXCL13-negative counterparts in data generated from renal cell carcinoma patient samples. Proseg is available under at open source license at https://github.com/dcjones/proseg.

Multi-omic profiling reveals the endogenous and neoplastic responses to immunotherapies in cutaneous T cell lymphoma.

Cutaneous T cell lymphomas (CTCLs) are skin cancers with poor survival rates and limited treatments. While immunotherapies have shown some efficacy, the immunological consequences of administering immune-activating agents to CTCL patients have not been systematically characterized. We apply a suite of high-dimensional technologies to investigate the local, cellular, and systemic responses in CTCL patients receiving either mono- or combination anti-PD-1 plus interferon-gamma (IFN-γ) therapy. Neoplastic T cells display no evidence of activation after immunotherapy. IFN-γ induces muted endogenous immunological responses, while anti-PD-1 elicits broader changes, including increased abundance of CLA+CD39+ T cells. We develop an unbiased multi-omic profiling approach enabling discovery of immune modules stratifying patients. We identify an enrichment of activated regulatory CLA+CD39+ T cells in non-responders and activated cytotoxic CLA+CD39+ T cells in leukemic patients. Our results provide insights into the effects of immunotherapy in CTCL patients and a generalizable framework for multi-omic analysis of clinical trials.

Type 2-polarized memory B cells hold allergen-specific IgE memory.

Allergen-specific immunoglobulin E (IgE) antibodies mediate pathology in diseases such as allergic rhinitis and food allergy. Memory B cells (MBCs) contribute to circulating IgE by regenerating IgE-producing plasma cells upon allergen encounter. Here, we report a population of type 2-polarized MBCs defined as CD23hi, IL-4Rαhi, and CD32low at both the transcriptional and surface protein levels. These MBC2s are enriched in IgG1- and IgG4-expressing cells while constitutively expressing germline transcripts for IgE. Allergen-specific B cells from patients with allergic rhinitis and food allergy were enriched in MBC2s. Furthermore, MBC2s generated allergen-specific IgE during sublingual immunotherapy, thereby identifying these cells as a major reservoir for IgE. The identification of MBC2s provides insights into the maintenance of IgE memory, which is detrimental in allergic diseases but could be beneficial in protection against venoms and helminths.

Unravelling human hematopoietic progenitor cell diversity through association with intrinsic regulatory factors.

Hematopoietic stem and progenitor cell (HSPC) transplantation is an essential therapy for hematological conditions, but finer definitions of human HSPC subsets with associated function could enable better tuning of grafts and more routine, lower-risk application. To deeply phenotype HSPCs, following a screen of 328 antigens, we quantified 41 surface proteins and functional regulators on millions of CD34+ and CD34- cells, spanning four primary human hematopoietic tissues: bone marrow, mobilized peripheral blood, cord blood, and fetal liver. We propose more granular definitions of HSPC subsets and provide new, detailed differentiation trajectories of erythroid and myeloid lineages. These aspects of our revised human hematopoietic model were validated with corresponding epigenetic analysis and in vitro clonal differentiation assays. Overall, we demonstrate the utility of using molecular regulators as surrogates for cellular identity and functional potential, providing a framework for description, prospective isolation, and cross-tissue comparison of HSPCs in humans.

CD4+ T cells expressing CX3CR1, GPR56, with variable CD57 are associated with cardiometabolic diseases in persons with HIV.

Persons with HIV (PWH) on long-term antiretroviral therapy (ART) have a higher incidence and prevalence of cardiometabolic diseases attributed, in part, to persistent inflammation despite viral suppression. In addition to traditional risk factors, immune responses to co-infections such as cytomegalovirus (CMV) may play an unappreciated role in cardiometabolic comorbidities and offer new potential therapeutic targets in a subgroup of individuals. We assessed the relationship of CX3CR1+, GPR56+, and CD57+/- T cells (termed CGC+) with comorbid conditions in a cohort of 134 PWH co-infected with CMV on long-term ART. We found that PWH with cardiometabolic diseases (non-alcoholic fatty liver disease, calcified coronary arteries, or diabetes) had higher circulating CGC+CD4+ T cells compared to metabolically healthy PWH. The traditional risk factor most correlated with CGC+CD4+ T cell frequency was fasting blood glucose, as well as starch/sucrose metabolites. While unstimulated CGC+CD4+ T cells, like other memory T cells, depend on oxidative phosphorylation for energy, they exhibited higher expression of carnitine palmitoyl transferase 1A compared to other CD4+ T cell subsets, suggesting a potentially greater capacity for fatty acid ß-oxidation. Lastly, we show that CMV-specific T cells against multiple viral epitopes are predominantly CGC+. Together, this study suggests that among PWH, CGC+ CD4+ T cells are frequently CMV-specific and are associated with diabetes, coronary arterial calcium, and non-alcoholic fatty liver disease. Future studies should assess whether anti-CMV therapies could reduce cardiometabolic disease risk in some individuals.

Magnitude and kinetics of the human immune cell response associated with severe dengue progression by single-cell proteomics.

Approximately 5 million dengue virus-infected patients progress to a potentially life-threatening severe dengue (SD) infection annually. To identify the immune features and temporal dynamics underlying SD progression, we performed deep immune profiling by mass cytometry of PBMCs collected longitudinally from SD progressors (SDp) and uncomplicated dengue (D) patients. While D is characterized by early activation of innate immune responses, in SDp there is rapid expansion and activation of IgG-secreting plasma cells and memory and regulatory T cells. Concurrently, SDp, particularly children, demonstrate increased proinflammatory NK cells, inadequate expansion of CD16+ monocytes, and high expression of the FcγR CD64 on myeloid cells, yet a signature of diminished antigen presentation. Syndrome-specific determinants include suppressed dendritic cell abundance in shock/hemorrhage versus enriched plasma cell expansion in organ impairment. This study reveals uncoordinated immune responses in SDp and provides insights into SD pathogenesis in humans with potential implications for prediction and treatment.

Supervised dimensionality reduction for exploration of single-cell data by HSS-LDA.

Single-cell technologies generate large, high-dimensional datasets encompassing a diversity of omics. Dimensionality reduction captures the structure and heterogeneity of the original dataset, creating low-dimensional visualizations that contribute to the human understanding of data. Existing algorithms are typically unsupervised, using measured features to generate manifolds, disregarding known biological labels such as cell type or experimental time point. We repurpose the classification algorithm, linear discriminant analysis (LDA), for supervised dimensionality reduction of single-cell data. LDA identifies linear combinations of predictors that optimally separate a priori classes, enabling the study of specific aspects of cellular heterogeneity. We implement feature selection by hybrid subset selection (HSS) and demonstrate that this computationally efficient approach generates non-stochastic, interpretable axes amenable to diverse biological processes such as differentiation over time and cell cycle. We benchmark HSS-LDA against several popular dimensionality-reduction algorithms and illustrate its utility and versatility for the exploration of single-cell mass cytometry, transcriptomics, and chromatin accessibility data.

Data science through the lens of systems immunology.

Glass, a post-doctoral researcher, and Amouzgar, a PhD student, in Bendall lab proposed a supervised dimensionality reduction method to explore and analyze single-cell data. Their Patterns paper highlights the advantages of supervised learning in single-cell datasets with class labels. They talk about the essential role of data science in this project and in their lives.

Human IL-10-producing B cells have diverse states that are induced from multiple B cell subsets.

Regulatory B cells (Bregs) suppress immune responses through the secretion of interleukin-10 (IL-10). This immunomodulatory capacity holds therapeutic potential, yet a definitional immunophenotype for enumeration and prospective isolation of B cells capable of IL-10 production remains elusive. Here, we simultaneously quantify cytokine production and immunophenotype in human peripheral B cells across a range of stimulatory conditions and time points using mass cytometry. Our analysis shows that multiple functional B cell subsets produce IL-10 and that no phenotype uniquely identifies IL-10+ B cells. Further, a significant portion of IL-10+ B cells co-express the pro-inflammatory cytokines IL-6 and tumor necrosis factor alpha (TNFα). Despite this heterogeneity, operationally tolerant liver transplant recipients have a unique enrichment of IL-10+, but not TNFα+ or IL-6+, B cells compared with transplant recipients receiving immunosuppression. Thus, human IL-10-producing B cells constitute an induced, transient state arising from a diversity of B cell subsets that may contribute to maintenance of immune homeostasis.

Transition to invasive breast cancer is associated with progressive changes in the structure and composition of tumor stroma.

Ductal carcinoma in situ (DCIS) is a pre-invasive lesion that is thought to be a precursor to invasive breast cancer (IBC). To understand the changes in the tumor microenvironment (TME) accompanying transition to IBC, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) and a 37-plex antibody staining panel to interrogate 79 clinically annotated surgical resections using machine learning tools for cell segmentation, pixel-based clustering, and object morphometrics. Comparison of normal breast with patient-matched DCIS and IBC revealed coordinated transitions between four TME states that were delineated based on the location and function of myoepithelium, fibroblasts, and immune cells. Surprisingly, myoepithelial disruption was more advanced in DCIS patients that did not develop IBC, suggesting this process could be protective against recurrence. Taken together, this HTAN Breast PreCancer Atlas study offers insight into drivers of IBC relapse and emphasizes the importance of the TME in regulating these processes.

Single-cell metabolic profiling of human cytotoxic T cells.

Cellular metabolism regulates immune cell activation, differentiation and effector functions, but current metabolic approaches lack single-cell resolution and simultaneous characterization of cellular phenotype. In this study, we developed an approach to characterize the metabolic regulome of single cells together with their phenotypic identity. The method, termed single-cell metabolic regulome profiling (scMEP), quantifies proteins that regulate metabolic pathway activity using high-dimensional antibody-based technologies. We employed mass cytometry (cytometry by time of flight, CyTOF) to benchmark scMEP against bulk metabolic assays by reconstructing the metabolic remodeling of in vitro-activated naive and memory CD8+ T cells. We applied the approach to clinical samples and identified tissue-restricted, metabolically repressed cytotoxic T cells in human colorectal carcinoma. Combining our method with multiplexed ion beam imaging by time of flight (MIBI-TOF), we uncovered the spatial organization of metabolic programs in human tissues, which indicated exclusion of metabolically repressed immune cells from the tumor-immune boundary. Overall, our approach enables robust approximation of metabolic and functional states in individual cells.

An Integrated Multi-omic Single-Cell Atlas of Human B Cell Identity.

B cells are capable of a wide range of effector functions including antibody secretion, antigen presentation, cytokine production, and generation of immunological memory. A consistent strategy for classifying human B cells by using surface molecules is essential to harness this functional diversity for clinical translation. We developed a highly multiplexed screen to quantify the co-expression of 351 surface molecules on millions of human B cells. We identified differentially expressed molecules and aligned their variance with isotype usage, VDJ sequence, metabolic profile, biosynthesis activity, and signaling response. Based on these analyses, we propose a classification scheme to segregate B cells from four lymphoid tissues into twelve unique subsets, including a CD45RB+CD27- early memory population, a class-switched CD39+ tonsil-resident population, and a CD19hiCD11c+ memory population that potently responds to immune activation. This classification framework and underlying datasets provide a resource for further investigations of human B cell identity and function.

Multiplexed single-cell morphometry for hematopathology diagnostics.

The diagnosis of lymphomas and leukemias requires hematopathologists to integrate microscopically visible cellular morphology with antibody-identified cell surface molecule expression. To merge these into one high-throughput, highly multiplexed, single-cell assay, we quantify cell morphological features by their underlying, antibody-measurable molecular components, which empowers mass cytometers to 'see' like pathologists. When applied to 71 diverse clinical samples, single-cell morphometric profiling reveals robust and distinct patterns of 'morphometric' markers for each major cell type. Individually, lamin B1 highlights acute leukemias, lamin A/C helps distinguish normal from neoplastic mature T cells, and VAMP-7 recapitulates light-cytometric side scatter. Combined with machine learning, morphometric markers form intuitive visualizations of normal and neoplastic cellular distribution and differentiation. When recalibrated for myelomonocytic blast enumeration, this approach is superior to flow cytometry and comparable to expert microscopy, bypassing years of specialized training. The contextualization of traditional surface markers on independent morphometric frameworks permits more sensitive and automated diagnosis of complex hematopoietic diseases.

Synthesis of isotopically labeled 1,3-dithiane.

The 1,3-dithiane is a protected formaldehyde anion equivalent that could serve as a useful labeled synthon. We report a facile synthesis of 1,3-[2-(13)C]- and 1,3-[2-(13)C, 2-(2)H2]dithiane in two steps from [(13)C]- or [(13) C, (2)H3 ]methyl phenyl sulfoxide. We have previously reported the high yield synthesis of [(13)C]methyl phenyl sulfide from [(13)C]MEOH and the oxidation of [(13)C]methyl phenyl sulfide to [(13)C]methyl phenyl sulfoxide. Here, we describe the facile exchange of deuterium from (2) H2 O into [(13)C]methyl phenyl sulfoxide to yield [(13)C, (2)H3]methyl phenyl sulfoxide. Thus, from [(13)C]MEOH and (2)H2O, all possible C2 stable isotopomers of 1,3-dithiane are available. Our synthetic route is also amenable to preparation of radiolabeled 1,3-dithianes.

Large-scale preparation of (13) C-labeled 2-(phenylthio)acetic acid and the corresponding labeled sulfoxides and sulfones.

We have developed large-scale efficient procedures for the conversion of commercially available [(13) C]- or [(2) H3 ,(13) C]methanol and (13) CO2 or (13) C-labeled bromoacetic acid to 2-(phenylthio)[1,2-(13) C2 ]-, [1-(13) C]-, and [2-(13) C]acetic acid. The resulting derivatives are versatile, chemically stable, and nonvolatile two-carbon labeling precursors. We have used the (13) C-isotopomers of 2-(phenylthio)acetic acid in the synthesis of (13) C-labeled acrylic acid, methacrylic acid, and trans-crotonic acid.

Bis(2,5-dimethoxy-4-methylphenyl)methane and bis(2,5-dimethoxy-3,4,6-trimethylphenyl)methane.

Bis(2,5-dimethoxy-4-methylphenyl)methane, C(19)H(24)O(4), (IIa), was obtained and characterized as a minor product from the reaction of toluhydroquinone dimethyl ether (1,4-dimethoxy-2-methylbenzene) with N-(hydroxymethyl)trifluoroacetamide. Similarly, bis(2,5-dimethoxy-3,4,6-trimethylphenyl)methane, C(23)H(32)O(4), (IIb), was prepared from the corresponding reaction of trimethylhydroquinone dimethyl ether (2,5-dimethoxy-1,3,4-trimethylbenzene). The molecules of (IIa) and (IIb) each lie on a twofold axis passing through the methylene group. The dihedral angle between the planar phenyl rings is 73.4 (1) degrees in (IIa) and 77.9 (1) degrees in (IIb). The external bond angles around the bridging methylene group are 116.6 (2) and 117.3 (2) degrees for (IIa) and (IIb), respectively. In (IIa), the methoxy substituents lie in the plane of the ring and are conjugated with the aromatic system, whereas in (IIb), they are almost perpendicular to the phenyl ring and are positioned on opposite sides.