Proton pump inhibitor effect on esophageal protein signature of eosinophilic esophagitis, prediction, and evaluation of treatment response.

Recently, we have identified a dysregulated protein signature in the esophageal epithelium of eosinophilic esophagitis (EoE) patients including proteins associated with inflammation and epithelial barrier function; however, the effect of proton pump inhibitor (PPI) treatment on this signature is unknown. Herein, we used a proteomic approach to investigate: (1) whether PPI treatment alters the esophageal epithelium protein profile observed in EoE patients and (2) whether the protein signature at baseline predicts PPI response. We evaluated the protein signature of esophageal biopsies using a cohort of adult EoE (n = 25) patients and healthy controls (C) (n = 10). In EoE patients, esophageal biopsies were taken before (pre) and after (post) an 8-week PPI treatment, determining the histologic response. Eosinophil count PostPPI was used to classify the patients: ≥15 eosinophils/hpf as non-responders (non-responder) and < 15 eosinophils/hpf as responders (R). Protein signature was determined and differentially accumulated proteins were characterized to identify altered biological processes and signaling pathways. Comparative analysis of differentially accumulated proteins between groups revealed common signatures between three groups of patients with inflammation (responder-PrePPI, non-responder-PrePPI, and non-responder-PostPPI) and without inflammation (controls and responder-PostPPI). PPI therapy almost reversed the EoE specific esophageal protein signature, which is enriched in pathways associated with inflammation and epithelial barrier function, in responder-PostPPI. Furthermore, we identified a set of candidate proteins to differentiate responder-PrePPI and non-responder-PrePPI EoE patients before treatment. These findings provide evidence that PPI therapy reverses the alterations in esophageal inflammatory and epithelial proteins characterizing EoE, thereby providing new insights into the mechanism of PPI clinical response. Interestingly, our results also suggest that PPI response could be predicted at baseline in EoE.

Molina-Jiménez F ，Ugalde-Triviño L ，Arias-González L ，Armenteros E ，Relaño-Rupérez C ，Casabona S ，Moreno-Monteagudo JA ，Pérez-Fernández MT ，Martín-Domínguez V ，Fernández-Pacheco J ，Laserna-Mendieta EJ ，Muñoz-Hernández P ，García-Martínez J ，Muñoz J ，Lucendo AJ ，Santander C ，Majano P ... -  《-》

Circulating immunome fingerprint in eosinophilic esophagitis is associated with clinical response to proton pump inhibitor treatment.

The aim of the study was to characterize the circulating immunome of patients with EoE before and after proton pump inhibitor (PPI) treatment in order to identify potential non-invasive biomarkers of treatment response. PBMCs from 19 healthy controls and 24 EoE patients were studied using a 39-plex spectral cytometry panel. The plasmacytoid dendritic cell (pDC) population was differentially characterized by spectral cytometry analysis and immunofluorescence assays in esophageal biopsies from 7 healthy controls and 13 EoE patients. Interestingly, EoE patients at baseline had lower levels of circulating pDC compared with controls. Before treatment, patients with EoE who responded to PPI therapy had higher levels of circulating pDC and classical monocytes, compared with non-responders. Moreover, following PPI therapy pDC levels were increased in all EoE patients, while normal levels were only restored in PPI-responding patients. Finally, circulating pDC levels inversely correlated with peak eosinophil count and pDC count in esophageal biopsies. The number of tissue pDCs significantly increased during active EoE, being even higher in non-responder patients when compared to responder patients pre-PPI. pDC levels decreased after PPI intake, being further restored almost to control levels in responder patients post-PPI. We hereby describe a unique immune fingerprint of EoE patients at diagnosis. Moreover, circulating pDC may be also used as a novel non-invasive biomarker to predict subsequent response to PPI treatment.

Ugalde-Triviño L ，Molina-Jiménez F ，H-Vázquez J ，Relaño-Rupérez C ，Arias-González L ，Casabona S ，Pérez-Fernández MT ，Martín-Domínguez V ，Fernández-Pacheco J ，Lucendo AJ ，Bernardo D ，Santander C ，Majano P ... -  《Frontiers in Immunology》

Defining the optimum strategy for identifying adults and children with coeliac disease: systematic review and economic modelling.

Elwenspoek MM ，Thom H ，Sheppard AL ，Keeney E ，O'Donnell R ，Jackson J ，Roadevin C ，Dawson S ，Lane D ，Stubbs J ，Everitt H ，Watson JC ，Hay AD ，Gillett P ，Robins G ，Jones HE ，Mallett S ，Whiting PF ... -  《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》

Mononuclear cell composition and activation in blood and mucosal tissue of eosinophilic esophagitis.

Eosinophilic esophagitis (EoE) is a chronic, inflammatory, antigen-driven disease of the esophagus. Tissue EoE pathology has previously been extensively characterized by novel transcriptomics and proteomic platforms, however the majority of surface marker determination and screening has been performed in blood due to mucosal tissue size limitations. While eosinophils, CD4+ T cells, mast cells and natural killer (NK) T cells were previously investigated in the context of EoE, an accurate picture of the composition of peripheral blood mononuclear cells (PBMC) and their activation is missing. In this study, we aimed to comprehensively analyze the composition of peripheral blood mononuclear cells and their activation using surface marker measurements with multicolor flow cytometry simultaneously in both blood and mucosal tissue of patients with active EoE, inactive EoE, patients with gastroesophageal reflux disease (GERD) and controls. Moreover, we set out to validate our data in co-cultures of PBMC with human primary esophageal epithelial cells and in a novel inducible mouse model of eosinophilic esophagitis, characterized by extensive IL-33 secretion in the esophagus. Our results indicate that specific PBMC populations are enriched, and that they alter their surface expression of activation markers in mucosal tissue of active EoE. In particular, we observed upregulation of the immunomodulatory molecule CD38 on CD4+ T cells and on myeloid cells in biopsies of active EoE. Moreover, we observed significant upregulation of PD-1 on CD4+ and myeloid cells, which was even more prominent after corticosteroid treatment. With co-culture experiments we could demonstrate that direct cell contact is needed for PD-1 upregulation on CD4+ T cells. Finally, we validated our findings of PD-1 and CD38 upregulation in an inducible mouse model of EoE. Herein we show significant alterations in the PBMC activation profile of patients with active EoE in comparison to inactive EoE, GERD and controls, which could have potential implications for treatment. To our knowledge, this study is the first of its kind expanding the multi-color flow cytometry approach in different patient groups using in vitro and in vivo translational models.

Gruden E ，Kienzl M ，Ristic D ，Kindler O ，Kaspret DM ，Schmid ST ，Kargl J ，Sturm E ，Doyle AD ，Wright BL ，Baumann-Durchschein F ，Konrad J ，Blesl A ，Schlager H ，Schicho R ... -  《-》