Diagnosing and staging epithelial ovarian cancer by serum glycoproteomic profiling

BACKGROUND

There is a need for diagnostic tests for screening, triaging and staging of epithelial ovarian cancer (EOC). Glycoproteomics of blood samples has shown promise for biomarker discovery.

METHODS

We applied glycoproteomics to serum of people with EOC or benign pelvic masses and healthy controls. A total of 653 analytes were quantified and assessed in multivariable models, which were tested in an independent cohort. Additionally, we analyzed glycosylation patterns in serum markers and in tissues.

RESULTS

We identified a biomarker panel that distinguished benign lesions from EOC with sensitivity and specificity of 83.5% and 90.1% in the training set, and of 86.7 and 86.7% in the test set, respectively. ROC analysis demonstrated strong performance across a range of cutoffs. Fucosylated multi-antennary glycopeptide markers were higher in late-stage than in early-stage EOC. A comparable pattern was found in late-stage EOC tissues.

CONCLUSIONS

Blood glycopeptide biomarkers have the potential to distinguish benign from malignant pelvic masses, and early- from late-stage EOC. Glycosylation of circulating and tumor tissue proteins may be related. This study supports the hypothesis that blood glycoproteomic profiling can be used for EOC diagnosis and staging and it warrants further clinical evaluation.

Mass Spectrometry Analysis of Glycopeptides Enriched by Anion Exchange-Mediated Methods Reveals PolyLacNAc-Extended N-Glycans in Integrins and Tetraspanins in Melanoma Cells

Glycosylation is a key modulator of the functional state of proteins. Recent developments in large-scale analysis of intact glycopeptides have enabled the identification of numerous glycan structures that are relevant in pathophysiological processes. However, one motif found in N-glycans, poly-N-acetyllactosamine (polyLacNAc), still poses a substantial challenge to mass spectrometry-based glycoproteomic analysis due to its relatively low abundance and large size. In this work, we developed approaches for the systematic mapping of polyLacNAc-elongated N-glycans in melanoma cells. We first evaluated five anion exchange-based matrices for enriching intact glycopeptides and selected two materials that provided better overall enrichment efficiency. We then tested the robustness of the methodology by quantifying polyLacNAc-containing glycopeptides as well as changes in protein fucosylation and sialylation. Finally, we applied the optimal enrichment methods to discover glycopeptides containing polyLacNAc motifs in melanoma cells and found that integrins and tetraspanins are substantially modified with these structures. This study demonstrates the feasibility of glycoproteomic approaches for identification of glycoproteins with polyLacNAc motifs.

Plasma glycoproteomic biomarkers identify metastatic melanoma patients with reduced clinical benefit from immune checkpoint inhibitor therapy

The clinical success of immune-checkpoint inhibitors (ICI) in both resected and metastatic melanoma has confirmed the validity of therapeutic strategies that boost the immune system to counteract cancer. However, half of patients with metastatic disease treated with even the most aggressive regimen do not derive durable clinical benefit. Thus, there is a critical need for predictive biomarkers that can identify individuals who are unlikely to benefit with high accuracy so that these patients may be spared the toxicity of treatment without the likely benefit of response. Ideally, such an assay would have a fast turnaround time and minimal invasiveness. Here, we utilize a novel platform that combines mass spectrometry with an artificial intelligence-based data processing engine to interrogate the blood glycoproteome in melanoma patients before receiving ICI therapy. We identify 143 biomarkers that demonstrate a difference in expression between the patients who died within six months of starting ICI treatment and those who remained progression-free for three years. We then develop a glycoproteomic classifier that predicts benefit of immunotherapy (HR=2.7; p=0.026) and achieves a significant separation of patients in an independent cohort (HR=5.6; p=0.027). To understand how circulating glycoproteins may affect efficacy of treatment, we analyze the differences in glycosylation structure and discover a fucosylation signature in patients with shorter overall survival (OS). We then develop a fucosylation-based model that effectively stratifies patients (HR=3.5; p=0.0066). Together, our data demonstrate the utility of plasma glycoproteomics for biomarker discovery and prediction of ICI benefit in patients with metastatic melanoma and suggest that protein fucosylation may be a determinant of anti-tumor immunity.

Glycoproteomics as a powerful liquid biopsy-based screening tool for non-small cell lung cancer

e21148

Background: Protein glycosylation is the most abundant and complex form of post-translational protein modification. Glycosylation profoundly affects protein structure, conformation, and function. The elucidation of the potential role of differential protein glycosylation as biomarkers has so far been limited by the technical complexity of generating and interpreting this information. We have recently established a novel, powerful platform that combines liquid chromatography/mass spectrometry with a proprietary artificial-intelligence-based data processing engine that allows, for the first time, highly scalable interrogation of the glycoproteome. Methods: Using this platform, we interrogated 694 glycopeptide (GP) and non-glycosylated peptide transitions derived from 74 serum proteins in pre-treatment peripheral blood samples from a cohort of 316 individuals with non-small-cell lung cancer (NSCLC) (128 females, 187 males, 1 with unknown sex, median age 66 years, age range 31-89 years, stage 0-4 N’s: 1 / 99 / 80 / 84 / 49, 3 missing) and a comparison cohort of 194 healthy control samples (102 females, 92 males, median age 52 years, age range 30-63 years). Age- and sex-adjusted differential expression analysis for 596 normalized biomarkers were performed to evaluate statistically significant differential abundances using an FDR-adjusted q-value of 0.05 as a cutoff. Repeated five-fold cross-validated LASSO-regularized logistic regression was performed to create a multivariable classifier that predicts whether a serum sample belongs to the healthy or NSCLC cohort. Results: We identified 432 biomarkers with significant abundance differences at FDR ≤ 0.05 between samples with NSCLC and healthy controls. Using 70% of the complete cohort (balanced by case/control membership, NSCLC stage, sex, and age quartile) as a training set, we selected a total of 375 glycopeptide and non-glycosylated peptide biomarker features that remained differentially expressed at FDR-adjusted q-value ≤ 0.05 as input into a LASSO-regularized multivariable classifier. This resulting in a 19-biomarker model exhibiting an accuracy of 94.8% (96.9% sensitivity, 91.2% specificity) and AUC of 0.989. This classifier was validated in an independent test set comprising the remaining 30% of subjects, yielding an accuracy of 94.5% (95.5% sensitivity, 93.0% specificity) and AUC of 0.975. Sensitivity in the test set was 100% / 96% / 99% / 96% / 94% / 10%, in stages 0-4 and missing, respectively. Conclusions: Our results indicate that glycoproteomic biomarkers can be leveraged as a strong liquid biopsy-based screening tool for patients at high risk of NSCLC, as an alternative to imaging modalities.

Serum glycoproteomic signatures and association with survival in patients with bone and soft tissue sarcoma treated with immune-checkpoint inhibitor therapy

11546

Background: Glycosylation is one of the most ubiquitous and functionally important forms of post-translational modification. The role of differential glycosylation in serum proteins has so far been limited by the technical complexity inherent in generating and interpreting this information. InterVenn has built a novel platform that combines liquid chromatography/mass spectrometry with a proprietary artificial-intelligence-based data processing engine, allowing for highly scalable and reproducible interrogation of glycoproteins with site- and glycan-specificity. Methods: Using this platform, we interrogated 519 glycopeptide (GP) biomarkers derived from 70 serum proteins in pre-treatment samples from a cohort of 103 individuals (56 females, 47 males, age ranging from 18 to 84 years) presenting with one of 20 solid cancer types. All patients were treated with durvalumab and tremelimumab immune checkpoint inhibitor (ICI) therapy. Median follow-up for overall survival (OS) was 11.4 months, with 70 events total observed. OS associations were assessed for individual GPs via Cox regression models and leave-one-out-cross-validation (LOOCV) was employed to generate penalized multivariable prediction scores. Notably, 43 patients had a primary diagnosis of bone and soft tissue sarcoma, and stratified analyses were carried out in this population. Results: We identified 154 biomarkers significantly associated with OS in the full dataset after adjusting for multiple comparisons (FDR < 0.05). Of these, 7 were statistically significant at p < 0.01 in the sarcoma-only subset. LOOCV models built in all cancer types resulted in held-out scores that discriminated those likely to exhibit long-term survival post-ICI therapy from those unlikely to benefit (HR = 4.0, p = 4.91E-08, with 4 GPs included in the final model). Furthermore, LOOCV models including only sarcoma patients demonstrated even stronger predictive attributes (HR = 8.22, p = 2.10E-05, employing 2 glycopeptides). All 9 sarcoma patients with extreme glycosylation signatures for prediction of poor survival displayed quick clinical progression with little benefit from ICI therapy. Relative signal strength and comparative analyses demonstrated strong histotype-specificity inherent in the biomarkers employed for sarcoma vs all cancers. Conclusions: Our results indicate that glycoproteomic liquid biopsy holds potential as a predictive biomarker for identifying sarcoma patients who will derive the greatest benefit from ICI therapy.

Identifying potential glycoproteomic biomarkers for diagnosis of colorectal cancer (CRC)

e15529

Background: Excluding skin cancers, colorectal cancer is the third most common cancer diagnosed in both men and women in the United States. Colorectal cancer (CRC) affects men and women of all racial and ethnic groups and is most often found in people who are 50 years old or older. To aid diagnosis and improve screening for CRC, this study focuses on identifying glycoprotein biomarkers using blood serum. Methods: Novel methods including liquid-chromatography/mass-spectrometry (LC-MS) with in-house peak integration software PB-Net were used to identify glycoprotein biomarkers by analyzing blood serum. Samples were sourced from different biorepositories including 245 CRC, 38 adenoma and 196 healthy controls. The data were split into 75% training and 25% hold-out test set for multivariable predictions. Statistical analysis was performed on normalized data to identify potential biomarkers differentiating adenoma and different stages of CRC samples from the healthy controls. Results: There were 419 significantly differentially expressed glycopeptides/peptides from comparisons between CRC and adenoma samples against the healthy control samples with an FDR < 0.05. A subset of these biomarkers were assessed, generating a 21-biomarker multivariable classifier model. We observed a test set AUC of 0.926, and the sensitivity for all stages of CRC was 90% (87% early stage, 92% late stage). Notably, sensitivity for adenomas was 79%, a large improvement upon the state of the art in adenoma diagnosis. Conclusions: Identification of these key glycopeptides/peptides in blood serum could prove to be a promising non-invasive diagnostic tool that can help improve screening and aid in early detection of advanced adenomas and CRC.

Predicting breast cancer in women using liquid biopsy-derived glycoproteomic markers

e12545

Background: Breast cancer is the most common cancer among women worldwide.Traditional methods of cancer detection such as tissue biopsy are invasive, costly, time consuming and not amenable for repetition. As a result, minimally invasive liquid biopsies, especially blood-based biomarkers show potential value for breast cancer risk prediction and early detection. In this study, we investigated the use of serum glycoproteins circulating in blood to identify a panel of potential prognostic markers that may aid in predicting breast cancer in women. Methods: We applied a novel platform for characterizing blood glycoproteomic biomarkers, combining liquid-chromatography/mass spectrometry (LC-MS) with artificial intelligence/neural networks (AI-NN) to analyze serum samples from 279 breast cancer patients (median age 56 years, with stage 0-4 N’s: 1 / 83 / 114 / 56 / 25) and 102 healthy control samples (median age 52 years). A panel of 596 serum glycosylated and non-glycosylated peptides, representing 71 serum proteins, were analyzed. Age-adjusted differential expression analysis for 596 normalized biomarkers were performed to evaluate statistically significant differential abundances using an FDR q-value of 0.05 as a cutoff. Using the top differentially expressed markers as input, a LASSO penalized logistic regression model with 5-fold repeated cross validation was applied to identify the top biomarkers contributing to the separation between healthy controls and breast cancer patients. Results: We identified 243 out of 596 markers that were differentially expressed (FDR <<0.05) between breast cancer samples and healthy controls. Out of those, 11 markers were obtained as the top predictors in classifying breast cancer patients and healthy controls. The classification algorithm yielded an accuracy of 94% (95.9% sensitivity, 88.7% specificity) and an AUC of 0.983 on the training set. This classifier was validated on an independent test set with 30% of the subjects, yielding an accuracy of 93% (96.4% sensitivity, 83.9% specificity) and an AUC of 0.974. Test sensitivity was high across stages, at 96% / 90% / 95% / 90% in stages 1-4, respectively. Conclusions: Based on the results, we conclude that circulating glycoproteins in serum may be useful in screening applications in breast cancer, and strongly demonstrates the utility of glycoprotein profiles as a powerful non-invasive diagnostic tool.

Liquid-biopsy-derived glycoproteomic profiling as a novel means for noninvasive diagnosis of ovarian cancer

e17604

Background: Ovarian cancer (OC) is the fifth- leading cause of cancer-related deaths among women, and the most lethal gynecological cancer. Currently available biomarkers, including CA-125 and HE4, show suboptimal diagnostic performance for differentiating among benign and malignant pelvic tumors, and the early recognition of OC. Differentiation of benign and malignant pelvic tumors is required for proper patient triaging and management, yet non-invasive methods remain a largely unmet medical need. Methods: We applied a novel platform for characterizing peripheral blood glycoproteomic biomarkers, combining liquid-chromatography/mass spectrometry (LC-MS) with artificial intelligence/neural networks (AI-NN) for the targeted quantification of serum protein glycosylation at intact glycopeptide level to analyze serum samples from 296 treatment-naïve women with histopathology-confirmed diagnosis of either benign (n = 151) or malignant (n = 145) tumors, and from 55 healthy control subjects, procured from a commercial biobank. Using data-dependent acquisition, a panel of 683 serum glycosylated and non-glycosylated peptides, representing 71 serum proteins, was interrogated. Samples were randomly divided into a training and a testing set for multivariable analysis. Data processing was performed using PB-Net, an in-house-developed high-throughput peak integration software. Raw data were normalized, processed by statistical analysis, and applied to machine learning models. Results: Comparison of glycopeptide abundances among patients with OC and benign pelvic tumors yielded 428 statistically significantly differentially expressed glycopeptides/peptides (at FDR < 0.05). A subpanel of these markers used to generate a score for predicting OC yielded areas under the receiver-operating-characteristic of 0.955 and 0.894 in the training and testing sets, respectively. The predicted probability of malignancy increased with cancer stage, and probability distributions were similar across training and test sets. Applying the model to healthy subjects, not utilized in training, resulted in few misclassifications and a spread nearly equivalent to that of the benign tumor cases. This indicates the signature robustly predicts malignancy and severity of disease. Conclusions: Our novel approach exhibited impressive levels of accuracy for the noninvasive differentiation of benign and malignant pelvic masses, compared with existing biomarkers and algorithms, thereby demonstrating the utility of glycoprotein profiles as a powerful, noninvasive new diagnostic modality.

Glycoproteomics as a powerful liquid biopsy-based predictor of checkpoint inhibitor treatment benefit in metastatic malignant melanoma

9545

Background: Protein glycosylation is the most abundant and complex form of post-translational protein modification. Glycosylation profoundly affects protein structure, conformation, and function. The elucidation of the potential role of differential protein glycosylation as biomarkers has so far been limited by the technical complexity of generating and interpreting this information. We have recently established a novel, powerful platform that combines liquid chromatography/mass spectrometry with a proprietary artificial-intelligence-based data processing engine that allows, for the first time highly scalable interrogation of the glycoproteome. Methods: Using this platform, we interrogated 526 glycopeptide (GP) signatures derived from 75 serum proteins in pretreatment blood samples from a cohort of 205 individuals (66 females, 139 males, age range 24 to 97 years) with metastatic malignant melanoma treated either with nivolumab plus ipilimumab (95 patients) or pembrolizumab (110 patients) immune-checkpoint inhibitor (ICI) therapy. Results: In an optimized assay containing 27 glycopeptides and 20 non-glycosylated peptides, we identified 14 GPs with abundance differences at FDR q≤0.05 with regard to PFS. Using 40% of the cohort as a training set and selecting 12 glycopeptide and non-glycosylated peptide biomarker features of the 47 total by LASSO shrinkage, we created a multivariable-model-based classifier for PFS that yielded a hazard ratio (HR) for prediction of likely ICI benefit of 7.5 at p < 0.0001. This classifier was validated in the test set comprised of the held-out 60% of patients, yielding a HR of 4.7 at a similar p-value for separating patients likely benefiting from ICI therapy and those likely not benefiting from ICI therapy (50% PFS of 18 months vs. 3 months based on classifier score above/below cutoff). This classifier has a sensitivity of > 99% to predict likely ICI benefit, while still performing at a specificity of 26%, thus helping to safely reduce ultimately unnecessary and non-beneficial exposure to these agents of one in four who otherwise would unnecessarily be exposed to them. Conclusions: Our results indicate that glycoproteomics holds a strong promise as a predictor for checkpoint inhibitor treatment benefit that appears to significantly outperform other currently pursued biomarker approaches in this context.

Developing guideline-based key performance indicators for recurrent miscarriage care: lessons from a multi-stage consensus process with a diverse stakeholder group

BACKGROUND

Standardised care pathways tailored to women/couples who experience recurrent miscarriage are needed; however, clinical practice is inconsistent and poorly organised. In this paper, we outline our processes and experiences of developing guideline-based key performance indicators (KPIs) for recurrent miscarriage care with a diverse stakeholder group which will be used to evaluate national services. To date, such exercises have generally only involved clinicians, with the need for greater stakeholder involvement highlighted.

METHODS

Our study involved six stages: (i) identification and synthesis of recommendations for recurrent miscarriage care through a systematic review of clinical practice guidelines; (ii) a two-round modified e-Delphi survey with stakeholders to develop consensus on recommendations and outcomes; (iii) four virtual meetings to develop this consensus further; (iv) development of a list of candidate KPIs; (v) survey to achieve consensus on the final suite of KPIs and a (vi) virtual meeting to agree on the final set of KPIs. Through participatory methods, participants provided feedback on the process of KPI development.

RESULTS

From an initial list of 373 recommendations and 14 outcomes, 110 indicators were prioritised for inclusion in the final suite of KPIs: (i) structure of care (n = 20); (ii) counselling and supportive care (n = 7); (iii) investigations (n = 30); treatment (n = 34); outcomes (n = 19). Participants' feedback on the process comprised three main themes: accessibility, richness in diversity, streamlining the development process.

CONCLUSIONS

It is important and feasible to develop guideline-based KPIs with a diverse stakeholder group. One hundred and ten KPIs were prioritised for inclusion in a suite of guideline-based KPIs for recurrent miscarriage care. Insights into our experiences may help others undertaking similar projects, particularly those undertaken in the absence of a clinical guideline and/or involving a range of stakeholders.

Serum Glycoprotein Markers in Nonalcoholic Steatohepatitis and Hepatocellular Carcinoma

Fatty liver disease progresses through stages of fat accumulation and inflammation to nonalcoholic steatohepatitis (NASH), fibrosis and cirrhosis, and eventually hepatocellular carcinoma (HCC). Currently available diagnostic tools for HCC lack sensitivity and specificity. In this study, we investigated the use of circulating serum glycoproteins to identify a panel of potential prognostic markers that may be indicative of progression from the healthy state to NASH and further to HCC. Serum samples were processed and analyzed using a novel high-throughput glycoproteomics platform. Our initial dataset contained healthy, NASH, and HCC serum samples. We analyzed 413 glycopeptides, representing 57 abundant serum proteins, and compared among the three phenotypes. We studied the normalized abundance of common glycoforms and found 40 glycopeptides with statistically significant differences in abundances in NASH and HCC compared to controls. Summary level relative abundances of core-fucosylated, sialylated, and branched glycans containing glycopeptides were higher in NASH and HCC as compared to controls. We replicated some of our findings in an independent set of samples of individuals with benign liver conditions and HCC. Our results may be of value in the management of liver diseases. Data generated in this work can be downloaded from MassIVE (https://massive.ucsd.edu) with identifier MSV000088809.

A proximity labeling method for protein–protein interactions on cell membrane

Modified catalytic antibodies targeting specific antigens are employed to investigate protein interactions and antigen interaction sites.

30 Blood-based glycoprotein signatures in advanced non-small-cell lung carcinoma (NSCLC) receiving first-line immune checkpoint blockade

Background

Immune checkpoint blockade is an integral component of first-line therapy for most patients with ad-vanced non-small cell lung cancer (NSCLC), however individual patient outcomes are highly variable and improved biomarkers are needed. Protein glycosylation is an emerging mechanism of immune evasion in cancer. We examined blood-based glycopeptide signatures in a cohort of advanced NSCLC patients treated with first-line immune checkpoint blockade.

Methods

Pretreatment blood samples were obtained from 46 advanced NSCLC patients treated with first line pembrolizumab or pembrolizumab + carboplatin + pemetrexed. All patients provided written in-formed consent to the institutional review board–approved protocols (#02–180 and 13–367) at the Da-na-Farber/Harvard Cancer Center (Boston, MA), and the study was conducted in accordance with the Declaration of Helsinki. Samples were analyzed using an advanced glycoproteomics platform (Inter-Venn Biosciences) that combines ultra-high-performance liquid chromatography coupled to triple quadrupole mass spectrometry with a proprietary neural-network-based data processing engine. 409 individual glycopeptide (GP) signatures derived from 67 abundant serum proteins were analyzed and correlated with overall survival (OS) and other clinical outcomes.

Results

We identified 30 GPs with abundance differences using a False Discovery Rate (FDR) threshold of 0.05. Using the 5 most predictive GP markers, we created a multivariable model for OS by generating leave-one-out cross-validation (LOOCV) scores and determining an optimized cutoff value of -0.83 (range: -2.2 - 3.4) for these scores using Harrell’s concordance index. The median overall survival was 2.8 years for patients (n=14) whose GP classifier value was above the cutoff and 0.8 years for patients (n=32) whose GP classifier value was below the cutoff (HR 7.4, 95% CI 1.7–32.1, p=0.007) The model’s perfor-mance was not affected by sex, age, or treatment regimen.

Conclusions

Blood-based glycopeptide signatures may represent novel, non-invasive biomarkers of clinical out-come to first-line immune checkpoint blockade in advanced NSCLC. Additional research is needed to validate these findings in larger cohorts and to explore potential applications relevant to clinical decision-making.

Ethics Approval

The study obtained ethics approval from the institutional review board (approved protocol #02–180 and 13–367) at the Dana-Farber/Harvard Cancer Center (Boston, MA), and the study was conducted in accordance with the Declaration of Helsinki.

Consent

All patients provided written informed consent to the institutional review board–approved protocols (#02–180 and 13–367) at the Dana-Farber/Harvard Cancer Center (Boston, MA), and the study was conducted in accordance with the Declaration of Helsinki.

Abstract 387: Glycoproteomics as a powerful liquid biopsy-based predictor of checkpoint-inhibitor treatment response

Introduction: Protein glycosylation is the most abundant and most complex form of post-translational protein modification. Glycosylation profoundly affects protein structure, conformation, and function. The elucidation of the potential role of differential protein glycosylation as biomarkers has so far been limited by the technical complexity of generating and interpreting this information. We have recently established a novel, powerful platform that combines ultra-high-performance liquid chromatography coupled to triple quadrupole mass spectrometry with a proprietary machine learning and neural-network-based data processing engine that allows, for the first time, high-throughput, highly scalable interrogation of the glycoproteome.

Experimental Procedures: Using this platform we interrogated 413 individual glycopeptide (GP) signatures derived from 69 abundant serum proteins in pretreatment blood samples from a cohort of 36 individuals (11 females, 25 males, age range 28 to 90 years) with metastatic malignant melanoma treated either with nivolumab plus ipilimumab (12 patients) or pembrolizumab (24 patients). Progression-free survival (PFS) data with follow-up of up to 3.7 years (median: 0.8 years) were used as clinical endpoint phenotype against which the predictive power of differential abundance of GPs was assessed. PFS data were analyzed using Cox Proportional Hazards models, and Kaplan Meier curves were generated for GP markers that showed statistically significant differential abundances using an FDR-adjusted p-value of ≤0.1 as a cutoff.

Summary of Results: We identified 27 GPs with abundance differences at FDR p≤0.1, and among them 8 at p≤0.001. Using the latter 8 markers, we created a multivariable model for PFS by generating leave-one-out cross-validation (LOOCV) scores and determining an optimized cutoff value for these scores using Harrel's concordance index. Dichotomizing the LOOCV scores using this cutoff value demonstrated the model to yield a hazard ratio of 9.2 at a p-value of 10-5 for separating treatment responders and non-responders (70% vs. 0% PFS, respectively, at 18 months based on LOOCV score above/below cutoff), as compared to a hazard ratio of 1.5, p=0.5 for PDL1 expression. Conclusions: Our results indicate that glycoproteomics holds a strong promise as a response predictor to checkpoint inhibitor treatment that appears to significantly outperform other currently pursued biomarker approaches in this context.

Citation Format: Gege Xu, Rachel Rice, Hector Huang, Klaus Lindpaintner, Jillian M. Prendergast, Karl Normington, Dennie Frederick, Genevieve M. Boland, Daniel Serie. Glycoproteomics as a powerful liquid biopsy-based predictor of checkpoint-inhibitor treatment response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 387.

The prevention of obesity starting from the kindergarten by means of peer educator mothers and WhatsApp messages

Study design

Experimental approach.

Background

Early-life diet plays a crucial role in the development of body weight issues. We therefore investigated the effectiveness of a peer-education intervention, aiming at encouraging the intake of fruits and vegetables and of a healthy mid-morning snack, targeting the mothers of 3-8 years old children attending kindergarten and primary school.

Methods

The study involved 924 children (intervention group) and 450 children (control group). The intervention was carried out by organizing three meetings at school with the participation of healthcare professionals, mothers and teachers in a maieutic way. The meetings focused on i) discussing the issues that mothers face with their children's nutrition; ii) possible solutions; iii) identification of "leading mothers" playing as peer-educators. As control a similar intervention targeting only the teachers, without involving the mothers, was also carried out. The effectiveness of such interventions was evaluated by external evaluators, before, the interventions and 3 and 9 months after the interventions.

Results

The check, carried out 3 months after the intervention, showed a significant improvement with respect to the mid-morning snack, and the consumption of the main dishes as well as fruits; the check carried out 9 months after the intervention, showed that such improvements were maintained in the case of the midmorning snack and the fruit intake. No improvement was observed in relation to the control group.

Conclusions

This is the first example of an intervention promoting a healthy diet involving mothers of children attending kindergarten and primary school as peer educators and it actually improved the dietary habits.

Clinical practice guidelines for recurrent miscarriage in high-income countries: a systematic review

Recurrent miscarriage affects 1-2% of women of reproductive age, depending on the definition used. A systematic review was conducted to identify, appraise and describe clinical practice guidelines (CPG) published since 2000 for the investigation, management, and/or follow-up of recurrent miscarriage within high-income countries. Six major databases, eight guideline repositories and the websites of 11 professional organizations were searched to identify potentially eligible studies. The quality of eligible CPG was assessed using the Appraisal of Guidelines for Research and Evaluation (AGREE II) Tool. A narrative synthesis was conducted to describe, compare and contrast the CPG and recommendations therein. Thirty-two CPG were included, from which 373 recommendations concerning first-trimester recurrent miscarriage were identified across four sub-categories: structure of care (42 recommendations, nine CPG), investigations (134 recommendations, 23 CPG), treatment (153 recommendations, 24 CPG), and counselling and supportive care (46 recommendations, nine CPG). Most CPG scored 'poor' on applicability (84%) and editorial independence (69%); and to a lesser extent stakeholder involvement (38%) and rigour of development (31%). Varying levels of consensus were found across CPG, with some conflicting recommendations. Greater efforts are required to improve the quality of evidence underpinning CPG, the rigour of their development and the inclusion of multi-disciplinary perspectives, including those with lived experience of recurrent miscarriage.

The general populations' understanding of first trimester miscarriage: a cross sectional survey

OBJECTIVES

Miscarriage is a common, yet for many, devastating adverse pregnancy outcome. However, despite this the level of public knowledge on the topic is sub-optimal. We aimed to examine the general public's knowledge of miscarriage as well as their health information seeking behaviours associated with this topic.

STUDY DESIGN

We commissioned a national cross-sectional telephone survey of adults in the Republic of Ireland. 967 members of the general public consented to participate to this anonymised telephone survey. Sampling procedures ensured proportionality as per national standards. We examined respondents' definitions of miscarriage, its incidence and clinical findings, as well as the information seeking behaviours of the general population surrounding miscarriage.

RESULTS

699 (72%) of respondents provided an estimate of miscarriage frequency, with 28% of respondents correctly estimating that miscarriage occurs in 21-30% of pregnancies, with 61% under-estimating the incidence. Men were three times more likely than women to under-estimate (aOR3.5; 95% CI 2.4-4.9), as were those without children (aOR 1.7; 95% CI 1.2-2.6), or those living in urban areas (aOR 1.6; 95%CI 1.0-2.4. One third of respondents (33%) believed that the risk of miscarriage was higher following only one miscarriage. While 83% of respondents knew someone who had experienced a miscarriage, just over one third had discussed the topic of miscarriage with a family member/friend.

CONCLUSIONS

The general populations' knowledge of miscarriage, its incidence and associated factors is concerning, as are their health information seeking behaviours. Improving the level of knowledge of the general public could be achieved by adopting the topic into existing public health and education strategies. This will allow those experiencing miscarriage to frame their experience and expectations.

Parents and clinicians: partners in perinatal bereavement research -experiences from the International Stillbirth Alliance Conference 2017

In recent years, there has been a global call to reduce the numbers of preventable stillbirths and increase public awareness about the incidence and impact of pregnancy loss. The lived experiences of bereaved parents have much to contribute to developing the research agenda and clinical care in pregnancy loss. The multidisciplinary Pregnancy Loss Research Group (PLRG) based at the INFANT Centre at University College Cork and Cork University Maternity Hospital, has an established practice of active engagement and participation of patient members. This partnership provided the catalyst to model a similar collaborative approach between clinicians, researchers and bereaved parents when the PLRG was successful in their bid to host the International Stillbirth Alliance (ISA) annual conference in 2017. Over 400 hundred delegates from around the globe attended the conference, of which one quarter were bereaved parents. Establishing a culture of collaboration, support and mutual respect in the field of pregnancy loss, requires scientists, clinicians and parents to be brought together so each can be informed by the other in the efforts to prevent stillbirth and improve bereavement care. As part of ISA 2017 conference, a sub-committee of staff and parents was established to ensure that the voice of parents could contribute to the research agenda and developments in clinical and bereavement care. A creative workshop specifically for parents, followed by a parent assembly were organised to facilitate this. Remembrance activities, organised by the parent committee, were central to the conference and actively engaged in by parents, clinicians and researchers. This commentary, written collaboratively by a parent, a chaplain, a bereavement and loss specialist midwife and a consultant obstetrician, gives voice to this experience, identifying four key messages that arose from our reflection on the conference. These include; the value of active partnership between clinicians and patients, the use of creativity as a unifying expression of grief and as a means to facilitate learning, the value of collaboration with global stakeholders in raising awareness about stillbirth, and the importance of facilitating meaningful patient/public engagement in scientific research. The potential for education and learning opportunities are also explored, highlighting the connection between parents, researchers and clinicians as central stakeholders in the prevention of stillbirth and in improving bereavement care.

University students' awareness of causes and risk factors of miscarriage: a cross-sectional study

Background

Spontaneous miscarriage is the most common complication of pregnancy, occurring in up to 20% of pregnancies. Despite the prevalence of miscarriage, little is known regarding peoples’ awareness and understanding of causes of pregnancy loss. The aim of this study was to explore university students’ understanding of rates, causes and risk factors of miscarriage.

Methods

A cross-sectional study including university students. An online questionnaire was circulated to all students at the University College Cork using their university email accounts in April and May 2016. Main outcomes included identification of prevalence, weeks of gestation at which miscarriage occurs and causative risk factors for miscarriage.

Results

A sample of 746 students were included in the analysis. Only 20% (n = 149) of students correctly identified the prevalence of miscarriage, and almost 30% (n = 207) incorrectly believed that miscarriage occurs in less than 10% of pregnancies. Female were more likely to correctly identify the rate of miscarriage than men (21.8% versus 14.5%). However, men tended to underestimate the rate and females overestimate it. Students who did not know someone who had a miscarriage underestimated the rate of miscarriage, and those who were aware of some celebrities who had a miscarriage overestimated the rate. Almost 43% (n = 316) of students correctly identified fetal chromosomal abnormalities as the main cause of miscarriage. Females, older students, those from Medical and Health disciplines and those who were aware of a celebrity who had a miscarriage were more likely to identify chromosomal abnormalities as a main cause. However, more than 90% of the students believed that having a fall, consuming drugs or the medical condition of the mother was a causative risk factor for miscarriage. Finally, stress was identified as a risk factor more frequently than advanced maternal age or smoking.

Conclusion

Although almost half of the participants identified chromosomal abnormalities as the main cause of miscarriage, there is still a lack of understanding about the prevalence and most important risk factors among university students. University represents an ideal opportunity for health promotion strategies to increase awareness of potential adverse outcomes in pregnancy.

Electronic supplementary material

The online version of this article (10.1186/s12905-018-0682-1) contains supplementary material, which is available to authorized users.

Early clinical failure of the ACCIS® metal on metal hip arthroplasty system - A metal on metal hip with a difference

The ACCIS hip system has been marketed with a unique bearing surface which the manufacturers claim to reduce wear below the level of other MoM bearings and consequently less metal ion release. The cobalt-chrome-molybdenum alloy is heat treated to reduce the number and size of block carbides and the surface is modified with titanium-niobium-nitride to create a ceramic-like surface. We present our experience with ACCIS. 148 surgical procedures were carried out in 126 patients using the ACCIS hip resurfacing (77) or large head MOM total hip replacement(71). Patients were followed up with regular clinical and radiological assessment. In addition, metal ion levels were obtained. There have been 27 revision procedures carried out for a variety of indications with a current revision rate of 18%. Seven failures could not be attributed to the prosthesis itself, still leaving a failure rate of 13.5%. The mean survival time of these is 33 months, ranging from 1 to 72 months. 13 revisions were -performed for pain and revision demonstrated poor cup integration. 7 were revised because of high ion levels but this was patient choice despite remaining asymptomatic. Whilst the testing phases indicated benefits in wear characteristics, this is not apparent in our group. We have demonstrated an unacceptably high revision rate due to unknown causes and have ceased implanting the ACCIS.

Ethanol-induced conditioned partner preference in female mice

Drinking behavior and social context are intimately intertwined. Peer relations can promote drinking. Conversely, alcohol promotes social interaction. The present study tested female mice for ethanol-induced conditioned partner preference. Ovariectomized (OVX) C57Bl/6 females with chronic estradiol replacement (OVX+E) received saline or ethanol (1, 2 or 4 g/kg) ip and were paired 4 × for 30 min each with 1 of 2 stimulus females. The test female was paired with the CS- stimulus female following saline, and was paired with the CS+ female following ethanol. After pairing, we measured proximity of the test female to the CS+ and CS- females in a 10' test. In a second study, OVX and OVX+E females were tested for conditioned partner preference (CS+ vs. CS-) in response to 2.5 g/kg ethanol. In separate groups of mice, both test and stimulus females (IS+) received ethanol during pairing to determine if test mice develop conditioned partner preference for another intoxicated mouse. OVX+E test females showed conditioned partner preference for the CS+ female in response to ethanol at 2g/kg (change in preference score for CS+: +86.6 ± 30.0 s/10 min), but not at 0, 1 or 4 g/kg. At 2.5 g/kg ethanol, OVX+E females developed conditioned partner preference for either IS+ (+63.6 ± 24.0 s) or CS+ females (+93.8 ± 27.1 s). OVX test females demonstrated ethanol-induced conditioned partner preference only for the IS+ female (+153.8 ± 32.0 s). These data demonstrate that ethanol promotes social preference in female mice, and that estradiol enhances this effect.

Longitudinally-graded optical fibers

Optical fibers have become ubiquitous tools for the creation, propagation, manipulation, and detection of light. However, while the intensity of light propagating through the fiber can increase or decrease along the length through amplification or attenuation, respectively, the properties of the fiber itself generally do not, thus removing an opportunity to further control the behavior of light and performance of fiber-based devices. Shown here are optical fibers that exhibit significant changes in their longitudinal optical properties, specifically a tailored longitudinal numerical aperture change of about 12% over less than 20 meters of length. This is about 1900 times greater than previously reported. The Brillouin gain coefficient was found to decrease by over 6 dB relative to a standard commercial single mode fiber. Next generation analogs are expected to exhibit more than a 10 dB reduction in SBS gain using larger, yet still reasonably manufacturable gradients over practical lengths.

Intraoperative cell salvage versus postoperative autologous blood transfusion in hip arthroplasty: a retrospective service evaluation

INTRODUCTION

A number of ways of reducing blood loss in arthroplasty have been explored, including preoperative autologous transfusion, intraoperative cell salvage and postoperative autologous transfusions. Both intraoperative blood salvage and postoperative retransfusion drains have been shown to be effective in reducing blood loss in total hip arthroplasty. In our department there was a change in practice from using postoperative retransfusion drains to intraoperative cell salvage. To our knowledge no study has directly compared using intraoperative blood salvage and postoperative retransfusion drains alone in total hip arthroplasty.

METHODS

This was a retrospective service evaluation including all primary hip arthroplasty performed under our care between January 2006 and December 2008. Patients were divided into two groups: Group A used a postoperative autologous blood transfusion (ABT) drain and Group B used intraoperative cell salvage.

RESULTS

A total of 144 patients were included in this study: 84 in Group A and 60 in Group B. The mean haemoglobin difference for Group A was 3.96g/dl (standard deviation [SD]: 1.52) and for Group B it was 3.46g/dl (SD: 1.42). The mean haematocrit difference for Group A was 0.12% (SD: 0.05) and for Group B it was 0.10% (SD: 0.04). Using an independent t-test for the comparison of means, a significant difference was found between Group A and B both in regards to haemoglobin difference (p=0.009) and haematocrit difference (p=0.046).

CONCLUSIONS

We feel that intraoperative cell salvage provides a more efficient method of reducing blood loss than postoperative retransfusion in primary total hip replacement. A prospective randomised study would be useful to ascertain any clinical difference between the two methods.

Silica-clad crystalline germanium core optical fibers

Silica-clad optical fibers comprising a core of crystalline germanium were drawn using a molten core technique. With respect to previous fibers drawn using a borosilicate cladding, the present fibers exhibit negligible oxygen despite being fabricated at more than twice the melting point of the germanium. The counterintuitive result of less oxygen when the fiber is drawn at a higher temperatures is discussed. The measured propagation loss for the fiber was 0.7 dB/cm at 3.39 μm, which is the lowest loss reported to date.

Toward a photoconducting semiconductor RF optical fiber antenna array

Recently, optical fibers comprising a crystalline semiconductor core in a silica cladding have been successfully drawn by a conventional drawing process. These fibers are expected to exhibit a photoconductive response when illuminated by photons more energetic than the band gap of the core. In the photoconducting state, such a fiber can be expected to support driven RF currents so as to function as an antenna element, much as a plasma antenna. In this paper, we report the first device-related results on a crystalline semiconductor core optical fiber potentially useful in a photoconducting optical fiber antenna array; namely, optically induced changes to the electrical conductivity of a glass-clad germanium-core optical fiber. Since DC photoconduction measurements were masked by a photovoltaic effect, RF measurements at 5 MHz were used to determine the magnitude of the induced photoconductive effect. The observed photoconductivity, though not large in the present experiment, was comparable to that measured for the bulk crystals from which the fibers were drawn. The absorbed pumping light generated photo-carriers, thereby transforming the core from a dielectric material to a conductor. This technology could thus enable a class of transient antenna elements useful in low observable and reconfigurable antenna array applications.

Glass-clad single-crystal germanium optical fiber

Long lengths (250 meters) of a flexible 150 microm diameter glass-clad optical fiber containing a 15 microm diameter crystalline and phase-pure germanium core was fabricated using conventional optical fiber draw techniques. X-ray diffraction and spontaneous Raman scattering measurements showed the core to be very highly crystalline germanium with no observed secondary phases. Elemental analysis confirmed a very well-defined core-clad interface with a step-profile in composition and nominally 4 weight-percent oxygen having diffused into the germanium core from the glass cladding. For this proof-of-concept fiber, polycrystalline n-type germanium of unknown dopant concentration was used. The measured infrared transparency of the starting material was poor and, as a likely outcome, the attenuation of the resultant fiber was too high to be measured. However, the larger Raman cross-section, infrared and terahertz transparency of germanium over silicon should make these fibers of significant value for fiber-based mid- to long-wave infrared and terahertz waveguides and Raman-shifted infrared light sources once high-purity, high-resistivity germanium is employed.