A Novel Preclinical In Vitro 3D Model of Oral Carcinogenesis for Biomarker Discovery and Drug Testing.

This study aimed to develop an in vitro three-dimensional (3D) cell culture model of oral carcinogenesis for the rapid, scalable testing of chemotherapeutic agents. Spheroids of normal (HOK) and dysplastic (DOK) human oral keratinocytes were cultured and treated with 4-nitroquinoline-1-oxide (4NQO). A 3D invasion assay using Matrigel was performed to validate the model. RNA was extracted and subjected to transcriptomic analysis to validate the model and assess carcinogen-induced changes. The VEGF inhibitors pazopanib and lenvatinib were tested in the model and were validated by a 3D invasion assay, which demonstrated that changes induced by the carcinogen in spheroids were consistent with a malignant phenotype. Further validation was obtained by bioinformatic analyses, which showed the enrichment of pathways associated with hallmarks of cancer and VEGF signalling. Overexpression of common genes associated with tobacco-induced oral squamous cell carcinoma (OSCC), such as MMP1, MMP3, MMP9, YAP1, CYP1A1, and CYP1B1, was also observed. Pazopanib and lenvatinib inhibited the invasion of transformed spheroids. In summary, we successfully established a 3D spheroid model of oral carcinogenesis for biomarker discovery and drug testing. This model is a validated preclinical model for OSCC development and would be suitable for testing a range of chemotherapeutic agents.

Single-cell transcriptomic and spatial landscapes of the developing human pancreas.

Current differentiation protocols have not been successful in reproducibly generating fully functional human beta cells in vitro, partly due to incomplete understanding of human pancreas development. Here, we present detailed transcriptomic analysis of the various cell types of the developing human pancreas, including their spatial gene patterns. We integrated single-cell RNA sequencing with spatial transcriptomics at multiple developmental time points and revealed distinct temporal-spatial gene cascades. Cell trajectory inference identified endocrine progenitor populations and branch-specific genes as the progenitors differentiate toward alpha or beta cells. Spatial differentiation trajectories indicated that Schwann cells are spatially co-located with endocrine progenitors, and cell-cell connectivity analysis predicted that they may interact via L1CAM-EPHB2 signaling. Our integrated approach enabled us to identify heterogeneity and multiple lineage dynamics within the mesenchyme, showing that it contributed to the exocrine acinar cell state. Finally, we have generated an interactive web resource for investigating human pancreas development for the research community.

Two subsets of human marginal zone B cells resolved by global analysis of lymphoid tissues and blood.

B cells generate antibodies that are essential for immune protection, but their subgroups are poorly defined. Here, we perform undirected deep profiling of B cells in matched human lymphoid tissues from deceased transplant organ donors and blood. In addition to identifying unanticipated features of tissue-based B cell differentiation, we resolve two subsets of marginal zone B (MZB) cells differing in cell surface and transcriptomic profiles, clonal relationships to other subsets, enrichment of genes in the NOTCH pathway, distribution bias within splenic marginal zone microenvironment, and immunoglobulin repertoire diversity and hypermutation frequency. Each subset is present in spleen, gut-associated lymphoid tissue, mesenteric lymph nodes, and blood. MZB cells and the lineage from which they are derived are depleted in lupus nephritis. Here, we show that this depletion is of only one MZB subset. The other remains unchanged as a proportion of total B cells compared with health. Thus, it is important to factor MZB cell heterogeneity into studies of human B cell responses and pathology.

Human marginal zone B cell development from early T2 progenitors.

B cells emerge from the bone marrow as transitional (TS) B cells that differentiate through T1, T2, and T3 stages to become naive B cells. We have identified a bifurcation of human B cell maturation from the T1 stage forming IgMhi and IgMlo developmental trajectories. IgMhi T2 cells have higher expression of α4ß7 integrin and lower expression of IL-4 receptor (IL4R) compared with the IgMlo branch and are selectively recruited into gut-associated lymphoid tissue. IgMhi T2 cells also share transcriptomic features with marginal zone B cells (MZBs). Lineage progression from T1 cells to MZBs via an IgMhi trajectory is identified by pseudotime analysis of scRNA-sequencing data. Reduced frequency of IgMhi gut-homing T2 cells is observed in severe SLE and is associated with reduction of MZBs and their putative IgMhi precursors. The collapse of the gut-associated MZB maturational axis in severe SLE affirms its existence in health.

Suppression of Th1 Priming by TLR2 Agonists during Cutaneous Immunization Is Mediated by Recruited CCR2+ Monocytes.

Effective subunit vaccines require the incorporation of adjuvants that stimulate cells of the innate immune system to generate protective adaptive immune responses. Pattern recognition receptor agonists are a growing class of potential adjuvants that can shape the character of the immune response to subunit vaccines by directing the polarization of CD4 T cell differentiation to various functional subsets. In the current study, we applied a high-throughput in vitro screen to assess murine CD4 T cell polarization by a panel of pattern recognition receptor agonists. This identified lipopeptides with TLR2 agonist activity as exceptional Th1-polarizing adjuvants. In vivo, we demonstrated that i.v. administration of TLR2 agonists with Ag in mice replicated the findings from in vitro screening by promoting strong Th1 polarization. In contrast, TLR2 agonists inhibited priming of Th1 responses when administered cutaneously in mice. This route-specific suppression was associated with infiltrating CCR2+ cells in the skin-draining lymph nodes and was not uniquely dependent on any of the well characterized subsets of dendritic cells known to reside in the skin. We further demonstrated that priming of CD4 T cells to generate Th1 effectors following immunization with the Mycobacterium bovis bacillus Calmette-Guérin (BCG) strain, a lipoprotein-rich bacterium recognized by TLR2, was dependent on the immunization route, with significantly greater Th1 responses with i.v. compared with intradermal administration of BCG. A more complete understanding of route-dependent TLR2 responses may be critical for informed design of novel subunit vaccines and for improvement of BCG and other vaccines based on live-attenuated organisms.

How is the effectiveness of immune surveillance impacted by the spatial distribution of spreading infections?

What effect does the spatial distribution of infected cells have on the efficiency of their removal by immune cells, such as cytotoxic T lymphocytes (CTL)? If infected cells spread in clusters, CTL may initially be slow to locate them but subsequently kill more rapidly than in diffuse infections. We address this question using stochastic, spatially explicit models of CTL interacting with different patterns of infection. Rather than the effector : target ratio, we show that the relevant quantity is the ratio of a CTL's expected time to locate its next target (search time) to the average time it spends conjugated with a target that it is killing (handling time). For inefficient (slow) CTL, when the search time is always limiting, the critical density of CTL (that required to control 50% of infections, C(*)) is independent of the spatial distribution and derives from simple mass-action kinetics. For more efficient CTL such that handling time becomes limiting, mass-action underestimates C(*), and the more clustered an infection the greater is C(*). If CTL migrate chemotactically towards targets the converse holds-C(*) falls, and clustered infections are controlled most efficiently. Real infections are likely to spread patchily; this combined with even weak chemotaxis means that sterilizing immunity may be achieved with substantially lower numbers of CTL than standard models predict.

Spatial heterogeneity and peptide availability determine CTL killing efficiency in vivo.

The rate at which a cytotoxic T lymphocyte (CTL) can survey for infected cells is a key ingredient of models of vertebrate immune responses to intracellular pathogens. Estimates have been obtained using in vivo cytotoxicity assays in which peptide-pulsed splenocytes are killed by CTL in the spleens of immunised mice. However the spleen is a heterogeneous environment and splenocytes comprise multiple cell types. Are some cell types intrinsically more susceptible to lysis than others? Quantitatively, what impacts are made by the spatial distribution of targets and effectors, and the level of peptide-MHC on the target cell surface? To address these questions we revisited the splenocyte killing assay, using CTL specific for an epitope of influenza virus. We found that at the cell population level T cell targets were killed more rapidly than B cells. Using modeling, quantitative imaging and in vitro killing assays we conclude that this difference in vivo likely reflects different migratory patterns of targets within the spleen and a heterogeneous distribution of CTL, with no detectable difference in the intrinsic susceptibilities of the two populations to lysis. Modeling of the stages involved in the detection and killing of peptide-pulsed targets in vitro revealed that peptide dose influenced the ability of CTL to form conjugates with targets but had no detectable effect on the probability that conjugation resulted in lysis, and that T cell targets took longer to lyse than B cells. We also infer that incomplete killing in vivo of cells pulsed with low doses of peptide may be due to a combination of heterogeneity in peptide uptake and the dissociation, but not internalisation, of peptide-MHC complexes. Our analyses demonstrate how population-averaged parameters in models of immune responses can be dissected to account for both spatial and cellular heterogeneity.

Quantifying the impact of human immunodeficiency virus-1 escape from cytotoxic T-lymphocytes.

HIV-1 escape from the cytotoxic T-lymphocyte (CTL) response leads to a weakening of viral control and is likely to be detrimental to the patient. To date, the impact of escape on viral load and CD4(+) T cell count has not been quantified, primarily because of sparse longitudinal data and the difficulty of separating cause and effect in cross-sectional studies. We use two independent methods to quantify the impact of HIV-1 escape from CTLs in chronic infection: mathematical modelling of escape and statistical analysis of a cross-sectional cohort. Mathematical modelling revealed a modest increase in log viral load of 0.051 copies ml(-1) per escape event. Analysis of the cross-sectional cohort revealed a significant positive association between viral load and the number of "escape events", after correcting for length of infection and rate of replication. We estimate that a single CTL escape event leads to a viral load increase of 0.11 log copies ml(-1) (95% confidence interval: 0.040-0.18), consistent with the predictions from the mathematical modelling. Overall, the number of escape events could only account for approximately 6% of the viral load variation in the cohort. Our findings indicate that although the loss of the CTL response for a single epitope results in a highly statistically significant increase in viral load, the biological impact is modest. We suggest that this small increase in viral load is explained by the small growth advantage of the variant relative to the wildtype virus. Escape from CTLs had a measurable, but unexpectedly low, impact on viral load in chronic infection.

HLA class I binding of HBZ determines outcome in HTLV-1 infection.

CD8(+) T cells can exert both protective and harmful effects on the virus-infected host. However, there is no systematic method to identify the attributes of a protective CD8(+) T cell response. Here, we combine theory and experiment to identify and quantify the contribution of all HLA class I alleles to host protection against infection with a given pathogen. In 432 HTLV-1-infected individuals we show that individuals with HLA class I alleles that strongly bind the HTLV-1 protein HBZ had a lower proviral load and were more likely to be asymptomatic. We also show that in general, across all HTLV-1 proteins, CD8(+) T cell effectiveness is strongly determined by protein specificity and produce a ranked list of the proteins targeted by the most effective CD8(+) T cell response through to the least effective CD8(+) T cell response. We conclude that CD8(+) T cells play an important role in the control of HTLV-1 and that CD8(+) cells specific to HBZ, not the immunodominant protein Tax, are the most effective. We suggest that HBZ plays a central role in HTLV-1 persistence. This approach is applicable to all pathogens, even where data are sparse, to identify simultaneously the HLA Class I alleles and the epitopes responsible for a protective CD8(+) T cell response.

T-cell epitope prediction: rescaling can mask biological variation between MHC molecules.

Theoretical methods for predicting CD8+ T-cell epitopes are an important tool in vaccine design and for enhancing our understanding of the cellular immune system. The most popular methods currently available produce binding affinity predictions across a range of MHC molecules. In comparing results between these MHC molecules, it is common practice to apply a normalization procedure known as rescaling, to correct for possible discrepancies between the allelic predictors. Using two of the most popular prediction software packages, NetCTL and NetMHC, we tested the hypothesis that rescaling removes genuine biological variation from the predicted affinities when comparing predictions across a number of MHC molecules. We found that removing the condition of rescaling improved the prediction software's performance both qualitatively, in terms of ranking epitopes, and quantitatively, in the accuracy of their binding affinity predictions. We suggest that there is biologically significant variation among class 1 MHC molecules and find that retention of this variation leads to significantly more accurate epitope prediction.