Comparing nonverbal synchrony in racially concordant and racially discordant oncology interactions

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Background: Communication in racially discordant (Black patient, non-Black physician) oncology interactions, which constitute about 80% of Black patients’ interactions, is generally poorer than in racially concordant interactions, and likely contributes to treatment disparities. However, the nonverbal behaviors that contribute to this problem are largely unknown. We examined nonverbal synchrony, or the nonconscious coordination of movement, which can reflect relationship quality. We hypothesized that racially discordant interactions will have lower levels of nonverbal synchrony. Methods: Data include video recordings of 68 Black patients and 163 White patients discussing treatment with their non-Black oncologists. Recordings were submitted to motion detection software to measure nonverbal synchrony. This software measures global synchrony (all correlated motion), peak synchrony (all positively correlated motion), who is leading the interaction (similar to who is leading in ballroom dancing), and how much synchrony occurs based on who is leading the interaction. Using multi-level models, we investigated whether nonverbal synchrony differed in racially concordant and racially discordant dyads. Results: Findings showed greater levels of global synchrony (p < .05) and greater peak synchrony (p < .05) in racially discordant interactions compared to racially concordant interactions. Global synchrony was the same in racially concordant interactions regardless of who was leading, but greater global synchrony occurred in racially discordant interactions when the patient was leading (p < .05). Conclusions: This is the first study to use a dynamic jointly determined measure of behavior to assess oncology interactions. Contrary to our hypothesis, nonverbal synchrony was greater in racially discordant interactions than in racially concordant interactions. It appears patients are driving more of the synchrony in racially discordant interactions. This may suggest that patients in racially discordant interactions adapt to their physicians to bridge racial differences. Findings could contribute to physician training to enhance coordination and outcomes in oncology interactions.

Quantitative Proteomics Reveals the Dynamic Protein Landscape during Initiation of Human Th17 Cell Polarization

Th17 cells contribute to the pathogenesis of inflammatory and autoimmune diseases and cancer. To reveal the Th17 cell-specific proteomic signature regulating Th17 cell differentiation and function in humans, we used a label-free mass spectrometry-based approach. Furthermore, a comprehensive analysis of the proteome and transcriptome of cells during human Th17 differentiation revealed a high degree of overlap between the datasets. However, when compared with corresponding published mouse data, we found very limited overlap between the proteins differentially regulated in response to Th17 differentiation. Validations were made for a panel of selected proteins with known and unknown functions. Finally, using RNA interference, we showed that SATB1 negatively regulates human Th17 cell differentiation. Overall, the current study illustrates a comprehensive picture of the global protein landscape during early human Th17 cell differentiation. Poor overlap with mouse data underlines the importance of human studies for translational research.

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Quantitative proteomics analysis of early human Th17 cell polarization

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The proteome and transcriptome highly correlate during early Th17 polarization

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Poor overlap of proteome profiles of human and mouse during early Th17 polarization

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The results underline the importance of human studies for translational research

Nonverbal synchrony as a behavioural marker of patient and physician race-related attitudes and a predictor of outcomes in oncology interactions: protocol for a secondary analysis of video-recorded cancer treatment discussions

INTRODUCTION

Racial disparities in cancer treatment contribute to racial disparities in mortality rates. The quality of patient-physician communication during clinical interactions with black patients and non-black physicians (racially discordant) is poorer than communication quality with white patients (racially concordant). Patient and physician race-related attitudes affect the quality of this communication. These attitudes are likely expressed through subtle non-verbal behaviours, but prior research has not examined these behaviours. Nonverbal synchrony, the coordination of physical movement, reflects the preinteraction attitudes of participants in interactions and predicts their postinteraction perceptions of and affect towards one another. In this study, peer reviewed and funded by the National Institute of Minority Health and Health Disparities (R21MD011766), we will investigate non-verbal synchrony in racially concordant and discordant interactions to better understand racial disparities in clinical communication.

METHODS AND ANALYSIS

This secondary analysis includes racially concordant (n=163) and racially discordant (n=68) video-recorded oncology interactions, patient and oncologist self-reported race-related attitudes, perceptions of the interaction and observer ratings of physician patient-centred communication and patient and physician affect and rapport. In aim 1, we will assess and compare non-verbal synchrony between physicians and patients in racially concordant and discordant interactions. In aim 2, we will determine the influence of non-verbal synchrony on patient and physician affect and communication. In aim 3, we will examine possible causes (ie, race-related attitudes) and consequences (ie, negative perceptions) of non-verbal synchrony in racially discordant interactions. In aim 4, we will develop and test a mediational model linking physician and patient race-related attitudes to non-verbal synchrony and, in turn, interaction outcomes.

ETHICS AND DISSEMINATION

The parent and current studies were approved by the Wayne State University Institutional Review Board. Since only archival data will be used, ethical or safety risks are low. We will disseminate our findings to relevant conferences and journals.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

Quantitative proteomic characterization and comparison of T helper 17 and induced regulatory T cells

The transcriptional network and protein regulators that govern T helper 17 (Th17) cell differentiation have been studied extensively using advanced genomic approaches. For a better understanding of these biological processes, we have moved a step forward, from gene- to protein-level characterization of Th17 cells. Mass spectrometry–based label-free quantitative (LFQ) proteomics analysis were made of in vitro differentiated murine Th17 and induced regulatory T (iTreg) cells. More than 4,000 proteins, covering almost all subcellular compartments, were detected. Quantitative comparison of the protein expression profiles resulted in the identification of proteins specifically expressed in the Th17 and iTreg cells. Importantly, our combined analysis of proteome and gene expression data revealed protein expression changes that were not associated with changes at the transcriptional level. Our dataset provides a valuable resource, with new insights into the proteomic characteristics of Th17 and iTreg cells, which may prove useful in developing treatment of autoimmune diseases and developing tumor immunotherapy.

T helper 17 (Th17) cells and induced regulatory T (iTreg) cells are two subsets of T helper cells differentiated from naïve cells that play important roles in autoimmune diseases, immune homeostasis, and tumor immunity. The differentiation process is achieved by changes in numerous proteins, including transcription regulators, enzymes, membrane receptors, and cytokines, which are critical in lineage commitment. To profile protein expression changes in Th17 and iTreg cells, we polarized murine naïve CD4+ T (Thp) cells in vitro to Th17 and iTreg cells and performed quantitative proteomic analysis of these cells. More than 4,000 proteins, covering almost all subcellular compartments, were detected. Quantitative comparison of the protein expression profiles resulted in the identification of proteins specifically expressed in the Th17 and iTreg cells. Importantly, our combined analysis of proteome and gene expression data revealed protein expression changes that were not associated with changes at the transcriptional level. The present study serves as a valuable resource that may prove useful in developing treatment of autoimmune diseases and cancer.

Is it a Small World After All? Investigating the Theoretical Structure of Working Memory Cross-Nationally

To our knowledge, this is one of the first studies to test different theoretical models of working memory in childhood based on a computerized assessment. We tested this across several countries: Argentina, Brazil, Canada, Italy, and uk. The present study addressed the wider macro-cultural context and how this impacts working memory. We used two economic indices (gdp and ppp) to characterize the participating countries and ranked the countries based on the Global Index of Cognitive Skills and Educational Attainment. Children between 5 and 10 years completed the same set of short-term and working memory tests. There were two main findings. First, there was a similar pattern in verbal working memory across countries, which suggests that this skill may be relatively consistent across different cultural groups. In contrast, the pattern for visuo-spatial working memory was different across countries, which may explained by cultural differences and educational rankings of the countries. The second main finding was that both a domain-general model (3-factor) and a domain-specific model (4-factor) provided a reasonably good fit with the data, there was the high relationship between the verbal and visuo-spatial working memory constructs across the countries in the latter model. Thus, it may be a more parsimonious choice to rely on a three-factor model. The data also suggest culture-similar patterns in a computerized assessment of working memory.

DNA methylation and Transcriptome Changes Associated with Cisplatin Resistance in Ovarian Cancer

High-grade serous ovarian cancer is the most common ovarian cancer type. Although the combination of surgery and platinum-taxane chemotherapy provide an effective treatment, drug resistance frequently occurs leading to poor outcome. In order to clarify the molecular mechanisms of drug resistance, the DNA methylation and transcriptomic changes, associated with the development of drug resistance in high-grade serous ovarian cancer, were examined from patient derived malignant ascites cells. In parallel with large-scale transcriptome changes, cisplatin resistance was associated with loss of hypermethylation at several CpG sites primarily localized in the intergenic regions of the genome. The transcriptome and CpG methylome changes in response to cisplatin treatment of both sensitive and resistant cells were minimal, indicating the importance of post-translational mechanisms in regulating death or survival of the cells. The response of resistant cells to high concentrations of cisplatin revealed transcriptomic changes in potential key drivers of drug resistance, such as KLF4. Among the strongest changes was also induction of IL6 in resistant cells and the expression was further increased in response to cisplatin. Also, several other components of IL6 signaling were affected, further supporting previous observations on its importance in malignant transformation and development of drug resistance in ovarian cancer.

Mass Spectrometry-Based Serum Proteomics for Biomarker Discovery and Validation

Blood protein measurements are used frequently in the clinic in the assessment of patient health. Nevertheless, there remains the need for new biomarkers with better diagnostic specificities. With the advent of improved technology for bioanalysis and the growth of biobanks including collections from specific disease risk cohorts, the plasma proteome has remained a target of proteomics research toward the characterization of disease-related biomarkers. The following protocol presents a workflow for serum/plasma proteomics including details of sample preparation both with and without immunoaffinity depletion of the most abundant plasma proteins and methodology for selected reaction monitoring mass spectrometry validation.

The progress and potential of proteomic biomarkers for type 1 diabetes in children

INTRODUCTION

Although it is possible to identify the genetic risk for type 1 diabetes (T1D), it is not possible to predict who will develop the disease. New biomarkers are needed that would help understand the mechanisms of disease onset and when to administer targeted therapies and interventions. Areas covered: An overview is presented of international study efforts towards understanding the cause of T1D, including the collection of several extensive temporal sample series that follow the development of T1D in at risk children. The results of the proteomics analysis of these materials are presented, which have included bodily fluids, such as serum or plasma and urine, as well as tissue samples from the pancreas. Expert commentary: Promising recent reports have indicated detection of early proteomic changes in the serum of patients prior to diagnosis, potentially providing new measures for risk assessment. Similarly, there has been evidence that post-translational modification (PTM) may result in the recognition of islet cell proteins as autoantigens; modified proteins could thus be used as targets for immunomodulation to overcome the threat of the autoimmune response.

Pulmonary sarcoidosis is associated with exosomal vitamin D-binding protein and inflammatory molecules

BACKGROUND

Sarcoidosis is an inflammatory granulomatous disorder characterized by accumulation of T_H1-type CD4⁺ T cells and immune effector cells within affected organs, most frequently the lungs. Exosomes are extracellular vesicles conveying intercellular communication with possible diagnostic and therapeutic applications.

OBJECTIVES

We aimed to provide an understanding of the proinflammatory role of bronchoalveolar lavage fluid (BALF) exosomes in patients with sarcoidosis and to find candidates for disease biomarkers.

METHODS

We performed a mass spectrometric proteomics characterization of BALF exosomes from 15 patients with sarcoidosis and 5 healthy control subjects and verified the most interesting results with flow cytometry, ELISA, and Western blot analyses in an additional 39 patients and 22 control subjects.

RESULTS

More than 690 proteins were identified in the BALF exosomes, several of which displayed significant upregulation in patients, including inflammation-associated proteins, such as leukotriene A₄ hydrolase. Most of the complement-activating factors were upregulated, whereas the complement regulator CD55 was seen less in patients compared with healthy control subjects. In addition, for the first time, we detected vitamin D-binding protein in BALF exosomes, which was more abundant in patients. To evaluate exosome-associated vitamin D-binding protein as a biomarker for sarcoidosis, we investigated plasma exosomes from 23 patients and 11 healthy control subjects and found significantly higher expression in patients.

CONCLUSION

Together, these data contribute to understanding the role of exosomes in lung disease and provide suggestions for highly warranted sarcoidosis biomarkers. Furthermore, the validation of an exosome-associated biomarker in the blood of patients provides novel, and less invasive, opportunities for disease diagnosis.

Early signs of disease in type 1 diabetes

As a severe chronic disease with long-term complications, type 1 diabetes (T1D) is a burden to the patients and their families as well as a challenge to the health care system. T1D is a heterogeneous disease with a variety of etiologies and a wide range in the rate of progression to the disease. In order to prevent and treat T1D it would be important to identify measures that could be used to predict and monitor disease progression, as well as to further understand the molecular mechanisms involved. During the past 20 yr since its initiation, the Finnish Diabetes Prediction and Prevention Project (DIPP) has collected longitudinal biological samples from children with a human leukocyte antigen gene-conferred risk of T1D. This large sample collection has provided detailed sample series that enable studies to map the progression from health to disease, as well as the healthy maturation of risk-matched children. The DIPP samples have been used in a large body of research to elucidate the factors involved in the development of T1D. Interestingly, results from recent studies exploiting omics platforms have revealed that signs of the disease process can be detected very early on, even prior to appearance of the first T1D-associated antibodies, which are currently considered the earliest indications of the emerging disease. Identification and validation of multi-modal molecular markers will we hope provide a means to subgroup the heterogeneous group of T1D patients and enable prediction, diagnosis, and monitoring of T1D. Discovery of such markers is important in the design and testing of prevention and therapies for T1D.

Label-Free Quantitation for Clinical Proteomics

Label-free quantification (LFQ) has emerged as a viable option for quantitative LC-MS/MS-based proteomic analyses for use on the scale of hundreds of samples such as are encountered in clinical analysis. Notably, sample preparation, sample loading, HPLC separations, and mass spectrometric performance must be highly reproducible for this approach to be effective. The following protocols describe the key steps in the methods related to sample preparation and analysis for LC-MS/MS-based label-free quantitation using standard data-dependent acquisition.

Serum proteomes distinguish children developing type 1 diabetes in a cohort with HLA-conferred susceptibility

We determined longitudinal serum proteomics profiles from children with HLA-conferred diabetes susceptibility to identify changes that could be detected before seroconversion and positivity for disease-associated autoantibodies. Comparisons were made between children who seroconverted and progressed to type 1 diabetes (progressors) and those who remained autoantibody negative, matched by age, sex, sample periodicity, and risk group. The samples represented the prediabetic period and ranged from the age of 3 months to 12 years. After immunoaffinity depletion of the most abundant serum proteins, isobaric tags for relative and absolute quantification were used for sample labeling. Quantitative proteomic profiles were then measured for 13 case-control pairs by high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Additionally, a label-free LC-MS/MS approach was used to analyze depleted sera from six case-control pairs. Importantly, differences in abundance of a set of proteins were consistently detected before the appearance of autoantibodies in the progressors. Based on top-scoring pairs analysis, classification of such progressors was observed with a high success rate. Overall, the data provide a reference of temporal changes in the serum proteome in healthy children and children progressing to type 1 diabetes, including new protein candidates, the levels of which change before clinical diagnosis.

Quantitative proteomics analysis of the nuclear fraction of human CD4+ cells in the early phases of IL-4-induced Th2 differentiation

We used stable isotope labeling with 4-plex iTRAQ (isobaric tags for relative and absolute quantification) reagents and LC-MS/MS to investigate proteomic changes in the nucleus of activated human CD4⁺ cells during the early stages of Th2 cell differentiation. The effects of IL-4 stimulation upon activated naïve CD4⁺ cells were measured in the nuclear fractions from 6 and 24 h in three biological replicates, each using pooled cord blood samples derived from seven or more individuals. In these analyses, in the order of 800 proteins were detected with two or more peptides and quantified in three biological replicates. In addition to consistent differences observed with the nuclear localization/expression of established human Th2 and Th1 markers, there were changes that suggested the involvement of several proteins either only recently reported or otherwise not known in this context. These included SATB1 and among the novel changes detected and validated an IL-4-induced increase in the level of YB1. This unique data set from human cord blood CD4⁺ T cells details an extensive list of protein determinations that compares with and complements previous data determined from the Jurkat cell nucleus.

Identification of novel Stat6 regulated proteins in IL-4-treated mouse lymphocytes

Interleukin 4 (IL-4) has an indispensable role in the differentiation of naive T helper (Th) cells toward the Th2 phenotype and induction of B cells to produce the IgE class of Igs. By regulating these two cell types, IL-4 has a pre-eminent role in regulation of allergic inflammation. IL-4-mediated regulation of T and B cell functions is largely transmitted through signal transducer and activator of transcription 6 (Stat6). In this study, we have used metabolic labeling and 2-D electrophoresis to detect differences in the proteomes of IL-4 stimulated spleen mononuclear cells of Stat6-/- and wild type mice and MS/MS for protein identification. With this methodology, we identified 49 unique proteins from 21 protein spots to be differentially expressed. Interestingly, in Stat6-/- CD4(+) cells the expression of isoform 2 of core binding factor b (CBFb2) was enhanced. CBFb is a non-DNA binding cofactor for the Runx family of transcription factors, which have been implicated in regulation of Th cell differentiation. We also found cellular nucleic acid protein (CNBP) to be downregulated in Stat6-/- cells. None of the proteins identified in this study have previously been reported to be regulated via Stat6. The results highlight the importance of exploiting proteomics tools to complement the studies on Stat6 target genes identified through transcriptional profiling.

Quantitative proteomics reveals GIMAP family proteins 1 and 4 to be differentially regulated during human T helper cell differentiation

T helper (Th) cells differentiate into functionally distinct effector cell subsets of which Th1 and Th2 cells are best characterized. Besides T cell receptor signaling, IL-12-induced STAT4 and T-bet- and IL-4-induced STAT6 and GATA3 signaling pathways are the major players regulating the Th1 and Th2 differentiation process, respectively. However, there are likely to be other yet unknown factors or pathways involved. In this study we used quantitative proteomics exploiting cleavable ICAT labeling and LC-MS/MS to identify IL-4-regulated proteins from the microsomal fractions of CD4(+) cells extracted from umbilical cord blood. We were able to identify 557 proteins of which 304 were also quantified. This study resulted in the identification of the down-regulation of small GTPases GIMAP1 and GIMAP4 by IL-4 during Th2 differentiation. We also showed that both GIMAP1 and GIMAP4 genes are up-regulated by IL-12 and other Th1 differentiation-inducing cytokines in cells induced to differentiate toward Th1 lineage and down-regulated by IL-4 in cells induced to Th2. Our results indicate that the GIMAP (GTPase of the immunity-associated protein) family of proteins is differentially regulated during Th cell differentiation.

Quality classification of tandem mass spectrometry data

Peptide identification by tandem mass spectrometry is an important tool in proteomic research. Powerful identification programs exist, such as SEQUEST, ProICAT and Mascot, which can relate experimental spectra to the theoretical ones derived from protein databases, thus removing much of the manual input needed in the identification process. However, the time-consuming validation of the peptide identifications is still the bottleneck of many proteomic studies. One way to further streamline this process is to remove those spectra that are unlikely to provide a confident or valid peptide identification, and in this way to reduce the labour from the validation phase.

RESULTS

We propose a prefiltering scheme for evaluating the quality of spectra before the database search. The spectra are classified into two classes: spectra which contain valuable information for peptide identification and spectra that are not derived from peptides or contain insufficient information for interpretation. The different spectral features developed for the classification are tested on a real-life material originating from human lymphoblast samples and on a standard mixture of 9 proteins, both labelled with the ICAT-reagent. The results show that the prefiltering scheme efficiently separates the two spectra classes.

A comparative evaluation of software for the analysis of liquid chromatography-tandem mass spectrometry data from isotope coded affinity tag experiments

The options available for processing quantitative data from isotope coded affinity tag (ICAT) experiments have mostly been confined to software specific to the instrument of acquisition. However, recent developments with data format conversion have subsequently increased such processing opportunities. In the present study, data sets from ICAT experiments, analysed with liquid chromatography/tandem mass spectrometry (MS/MS), using an Applied Biosystems QSTAR Pulsar quadrupole-TOF mass spectrometer, were processed in triplicate using separate mass spectrometry software packages. The programs Pro ICAT, Spectrum Mill and SEQUEST with XPRESS were employed. Attention was paid towards the extent of common identification and agreement of quantitative results, with additional interest in the flexibility and productivity of these programs. The comparisons were made with data from the analysis of a specifically prepared test mixture, nine proteins at a range of relative concentration ratios from 0.1 to 10 (light to heavy labelled forms), as a known control, and data selected from an ICAT study involving the measurement of cytokine induced protein expression in human lymphoblasts, as an applied example. Dissimilarities were detected in peptide identification that reflected how the associated scoring parameters favoured information from the MS/MS data sets. Accordingly, there were differences in the numbers of peptides and protein identifications, although from these it was apparent that both confirmatory and complementary information was present. In the quantitative results from the three programs, no statistically significant differences were observed.