BackgroundTumor-infiltrating immune cells play an important role against cancer and are critical to controlling tumor growth and spread. Immunotherapy drugs such as immune checkpoint inhibitors, ...despite inducing long-term responses in many cancer types, remain ineffective for a majority of patients. A better understanding of the tumor microenvironment (TME), and the characterization of populations of immune cells, their activation status, spatial distribution, and relationship, along with cytokine signaling, may help to better stratify patients and explain mechanisms of resistance to immunotherapy.Veracyte’s Brightplex® is a chromogenic multiplex immunohistochemistry (IHC) technology that leverages digital pathology enhanced by artificial intelligence. It allows the detection of up to eight biomarkers on a single FFPE slide to identify cellular subpopulations. However, to characterize the exact role of an immune cell it is often necessary to determine if it expresses soluble proteins which cannot be detected by IHC, such as cytokines or activation factors. In that case, the detection of the corresponding RNA transcripts by in situ hybridization (ISH) can be used as a substitute for protein detection.MethodsHere, we propose a multiplex technology automated on the Leica Bond RX platform which combines ISH and IHC staining on a single FFPE tissue section. In brief, that tissue section is sequentially stained to detect biomarkers of interest either with antibodies for proteins or nucleic probes for transcripts. Each round of staining is followed by the digitization of the slide. Whole slide images are fused to create a virtual multi-channel image where biomarkers are detected by digital pathology and combined to identify immune cell populations. The spatial distribution and cell-to-cell interactions within a slide or between multiple adjacent slides are assessed by combining multiplex ISH/IHC panels.ResultsThis technology allowed us to quantify different sub-populations of tumor-infiltrating-lymphocytes (activated, cytotoxic and exhausted), interferon-γ producing cells, and tumor-associated-macrophages expressing the chemokine CXCL9. We investigated the spatial distribution of these immune cells within the TME. We also assessed the cell-to-cell proximity between these populations to assess their interactions.ConclusionsIntegrated into an Immunogram, an analytics platform that integrates multi-omics datasets from Veracyte Biopharma Atlas, this new tool could be a powerful solution to decipher the tumor landscape and predict response to immunotherapy and patient outcome.
BackgroundDensity and localization of T cells within the tumor microenvironment (TME) is critical to control tumor growth. Immunotherapy with antibodies against immune checkpoint inhibitors (ICI), ...which aim to reinvigorate exhausted T cells, despite inducing long-term response in many cancer types, remains ineffective for most patients. Other factors present in the TME may participate in the control of tumors, among several candidates, the role of B cells has been underestimated. Publications revealed that B-cells are associated with good prognosis in several indications. However, there are no general rules since neutral or even deleterious impact of the presence of B-cells in the tumor was reported. Among other hypotheses, we can suppose that the level of activation and isotype switch will be important to mediate activation of NK cells or ADCC within the tumor and will have a favorable impact on the prognosis. In addition, the spatial distribution of B-cells may be important since, in the TME, they are mostly located in Tertiary Lymphoid Structures (TLS) which are ectopic lymphoid organs. Mature TLSs contain zones where dendritic cells (DC) present antigen to T-cells and others where proliferating B-cells undergo class switch and maturation toward plasma cells. Antigen presentation by B cells to T cells is supported by DCs, therefore, the presence of these three types of cells within the TLS allows T cell activation in the TME. If B-cells are major players in the therapeutic efficacy of ICI antibodies, not all subtypes of tumor infiltrating B-cells are likely to participate in response to immunotherapy.MethodsTo decipher the roles of B cells, new tools are needed to identify the differentiation and activation status of individual B cells. We have developed a 7-plex panel of antibodies against biomarkers that allow the identification of main types of B cells.ResultsOn a single FFPE tissue section: naïve, unswitched memory, switched memory, activated, plasmablast and plasma B cells, as well as T cells and DC are identified. Following images registration, complex cells phenotypes can be detected and quantified. Furthermore, digital pathology tools allow the evaluation of the spatial distribution within the TME of subtypes of B cells especially in association with TLSs.ConclusionsThis new tool unravels the heterogeneity of B cells in TME and could help clinical researchers to understand their contribution to the response to immunotherapy. Integrated into an Immunogram, this new Brightplex® Panel will be critical to understand the immune contexture of the tumor.
BackgroundCancer immunotherapy reinvigorates tumor-specific T cell responses of CD8+ cytotoxic T lymphocytes that detect intracellular antigens that are presented by MHC class I molecules expressed ...by all tumor cell types. Because most tumors do not express MHC class II, the potential antitumor protective role of CD4 T cells, which bind MHC class II molecules on target cells, has been less studied. However, CD4+ T cells are also required for efficacious antitumor immunity; they are core components of adaptive immunity that differentiate into lineages responsible for effector activities. Both TH1 and TH2 cell types mediate antitumor immunity, although TH1 cells may be more potent due to the production of large amounts of IFN-γ, as well as chemokines that enhance the priming and expansion of CD8 cells. TH1 cells help in recruiting natural killer cells and type I macrophages to tumor sites, which can act in concert toward tumor eradication. The ability of TH2 cells to mobilize innate cells, may represent a general pathway for their impact on the host antitumor response. Tumor infiltrating TFH cells play a key role in immune cell recruitment to the tumor and in the formation of intratumoral follicular structures, which correlate with a positive prognosis. On the contrary, cells from the TH17 subset induces inflammatory responses resulting in a tumor-promoting environment. CD4+ Tregs which are critically important for the maintenance of self-tolerance, impede effective immunity against the tumor when they are present in the tumor microenvironment (TME).Therefore, beyond the detection of total CD4+ T cells within the TME, it is of critical importance to determine to which subpopulation each CD4+ T cell belongs to decipher their roles in tumor rejection.MethodsWe have developed a multiplex 7-plex panel of of antibodies against biomarkers to identify main types of CD4+ T cellsResultsOn a single FFPE tissue section, main types of CD4+ T cells: TH1, TH2, TFH, TH17 and Tregs are identified by a combination of antibodies against transcription factors and membrane proteins. Following images registration, complex cells phenotypes can be detected and quantified. Furthermore, digital pathology tools allow the evaluation of the spatial distribution of CD4+ T cells within the TME.ConclusionsThis new tool unravels the diversity of CD4+ T cells in TME and could help clinical researchers to design more effective immunotherapies in cancer treatment. Integrated into an Immunogram, this new Brightplex® Panel will also be critical to understand the immune contexture of tumors.
Myosin V motors mediate cargo transport; however, the identity of neuronal molecules transported by these proteins remains unknown. Here we show that myosin Vb is expressed in several neuronal ...populations and associates with the α-amino-3-hydroxy-5-methyl-4-isoxazole propionate-type glutamate receptor subunit GluR1. In developing hippocampal neurons, expression of the tail domain of myosin Vb, but not myosin Va, enhanced GluR1 accumulation in the soma and reduced its surface expression. These changes were accompanied by reduced GluR1 clustering and diminished frequency of excitatory but not inhibitory synaptic currents. Similar effects were observed upon expression of full-length myosin Vb lacking a C-terminal region required for binding to the small GTPase Rab11. In contrast, mutant myosin Vb did not change the localization of several other neurotransmitter receptors, including the glutamate receptor subunit NR1. These results reveal a novel mechanism for the transport of a specific glutamate receptor subunit in neurons mediated by a member of the myosin V family.
The goal of this study was to investigate the efficacy of diagnosing shoulder dislocation using a single-view, posterior approach point-of-care ultrasound (POCUS) performed by undergraduate research ...students, and to establish the range of measured distance that discriminates dislocated shoulder from normal.
We enrolled a prospective, convenience sample of adult patients presenting to the emergency department with acute shoulder pain following injury. Patients underwent ultrasonographic evaluation of possible shoulder dislocation comprising a single transverse view of the posterior shoulder and assessment of the relative positioning of the glenoid fossa and the humeral head. The sonographic measurement of the distance between these two anatomic structures was termed the Glenohumeral Separation Distance (GhSD). A positive GhSD represented a posterior position of the glenoid rim relative to the humeral head and a negative GhSD value represented an anterior position of the glenoid rim relative to the humeral head. We compared ultrasound (US) findings to conventional radiography to determine the optimum GhSD cutoff for the diagnosis of shoulder dislocation. Sensitivity, specificity, positive predictive value, and negative predictive value of the derived US method were calculated.
A total of 84 patients were enrolled and 19 (22.6%) demonstrated shoulder dislocation on conventional radiography, all of which were anterior. All confirmed dislocations had a negative measurement of the GhSD, while all patients with normal anatomic position had GhSD>0. This value represents an optimum GhSD cutoff of 0 for the diagnosis of (anterior) shoulder dislocation. This method demonstrated a sensitivity of 100% (95% CI 82.4-100), specificity of 100% (95% CI 94.5-100), positive predictive value of 100% (95% CI 82.4-100), and negative predictive value of 100% (95% CI 94.5-100).
Our study suggests that a single, posterior-approach POCUS can diagnose anterior shoulder dislocation, and that this method can be employed by novice ultrasonographers, such as non-medical trainees, after a brief educational session. Further validation studies are necessary to confirm these findings.
Adeno-associated virus (AAV)-mediated gene therapy may provide durable protection from bleeding events and reduce treatment burden for people with hemophilia A (HA). However, pre-existing immunity ...against AAV may limit transduction efficiency and hence treatment success. Global data on the prevalence of AAV serotypes are limited. In this global, prospective, noninterventional study, we determined the prevalence of pre-existing immunity against AAV2, AAV5, AAV6, AAV8, and AAVrh10 among people ≥12 years of age with HA and residual FVIII levels ≤2 IU/dL. Antibodies against each serotype were detected using validated, electrochemiluminescent-based enzyme-linked immunosorbent assays. To evaluate changes in antibody titers over time, 20% of participants were retested at 3 and 6 months. In total, 546 participants with HA were enrolled at 19 sites in 9 countries. Mean (standard deviation) age at enrollment was 36.0 (14.87) years, including 12.5% younger than 18 years, and 20.0% 50 years of age and older. On day 1, global seroprevalence was 58.5% for AAV2, 34.8% for AAV5, 48.7% for AAV6, 45.6% for AAV8, and 46.0% for AAVrh10. Considerable geographic variability was observed in the prevalence of pre-existing antibodies against each serotype, but AAV5 consistently had the lowest seroprevalence across the countries studied. AAV5 seropositivity rates were 51.8% in South Africa (
= 56), 46.2% in Russia (
= 91), 40% in Italy (
= 20), 37.2% in France (
= 86), 26.8% in the United States (
= 71), 26.9% in Brazil (
= 26), 28.1% in Germany (
= 89), 29.8% in Japan (
= 84), and 5.9% in the United Kingdom (
= 17). For all serotypes, seropositivity tended to increase with age. Serostatus and antibody titer were generally stable over the 6-month sampling period. As clinical trials of AAV-mediated gene therapies progress, data on the natural prevalence of antibodies against various AAV serotypes may become increasingly important.
Objectives
To evaluate the utility of routinely collected Hendrich II fall scores in predicting returns to the emergency department (ED) for falls within 6 months.
Design
Retrospective electronic ...record review.
Setting
Academic medical center ED.
Participants
Individuals aged 65 and older seen in the ED from January 1, 2013, through September 30, 2015.
Measurements
We evaluated the utility of routinely collected Hendrich II fall risk scores in predicting ED visits for a fall within 6 months of an all‐cause index ED visit.
Results
For in‐network patient visits resulting in discharge with a completed Hendrich II score (N = 4,366), the return rate for a fall within 6 months was 8.3%. When applying the score alone to predict revisit for falls among the study population the resultant receiver operating characteristic (ROC) plot had an area under the curve (AUC) of 0.64. In a univariate model, the odds of returning to the ED for a fall in 6 months were 1.23 times as high for every 1‐point increase in Hendrich II score (odds ratio (OR)=1.23 (95% confidence interval (CI)=1.19–1.28). When included in a model with other potential confounders or predictors of falls, the Hendrich II score is a significant predictor of a return ED visit for fall (adjusted OR=1.15, 95% CI=1.10–1.20, AUC=0.75).
Conclusion
Routinely collected Hendrich II scores were correlated with outpatient falls, but it is likely that they would have little utility as a stand‐alone fall risk screen. When combined with easily extractable covariates, the screen performs much better. These results highlight the potential for secondary use of electronic health record data for risk stratification of individuals in the ED. Using data already routinely collected, individuals at high risk of falls after discharge could be identified for referral without requiring additional screening resources.
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