Definition of an Inflammatory Biomarker Signature in Plasma-Derived Extracellular Vesicles of Glioblastoma Patients

Glioblastoma (GB) is an aggressive type of tumour for which therapeutic options and biomarkers are limited. GB diagnosis mostly relies on symptomatic presentation of the tumour and, in turn, brain imaging and invasive biopsy that can delay its diagnosis. Description of easily accessible and effective biomarkers present in biofluids would thus prove invaluable in GB diagnosis. Extracellular vesicles (EVs) derived from both GB and stromal cells are essential to intercellular crosstalk in the tumour bulk, and circulating EVs have been described as a potential reservoir of GB biomarkers. Therefore, EV-based liquid biopsies have been suggested as a promising tool for GB diagnosis and follow up. To identify GB specific proteins, sEVs were isolated from plasma samples of GB patients as well as healthy volunteers using differential ultracentrifugation, and their content was characterised through mass spectrometry. Our data indicate the presence of an inflammatory biomarker signature comprising members of the complement and regulators of inflammation and coagulation including VWF, FCGBP, C3, PROS1, and SERPINA1. Overall, this study is a step forward in the development of a non-invasive liquid biopsy approach for the identification of valuable biomarkers that could significantly improve GB diagnosis and, consequently, patients’ prognosis and quality of life.

Predictive biomarker modeling of pediatric atopic dermatitis severity based on longitudinal serum collection

The pathogenesis of atopic dermatitis (AD) results from complex interactions between environmental factors, barrier defects, and immune dysregulation resulting in systemic inflammation. Therefore, we sought to characterize circulating inflammatory profiles in pediatric AD patients and identify potential signaling nodes which drive disease heterogeneity and progression. We analyzed a sample set of 87 infants that were at high risk for atopic disease based on atopic dermatitis diagnoses. Clinical parameters, serum, and peripheral blood mononuclear cells (PBMCs) were collected upon entry, and at one and four years later. Within patient serum, 126 unique analytes were measured using a combination of multiplex platforms and ultrasensitive immunoassays. We assessed the correlation of inflammatory analytes with AD severity (SCORAD). Key biomarkers, such as IL-13 (rmcorr=0.47) and TARC/CCL17 (rmcorr=0.37), among other inflammatory signals, significantly correlated with SCORAD across all timepoints in the study. Flow cytometry and pathway analysis of these analytes implies that CD4 T cell involvement in type 2 immune responses were enhanced at the earliest time point (year 1) relative to the end of study collection (year 5). Importantly, forward selection modeling identified 18 analytes in infant serum at study entry which could be used to predict change in SCORAD four years later. We have identified a pediatric AD biomarker signature linked to disease severity which will have predictive value in determining AD persistence in youth and provide utility in defining core systemic inflammatory signals linked to pathogenesis of atopic disease.

Characteristics of Bipolar Patients with Cognitive Impairment of Suspected Neurodegenerative Origin: A Multicenter Cohort

Bipolar disorder is associated with an increased risk of dementia with aging. Little is known regarding this association, limiting appropriate diagnosis and management. We aimed to describe the characteristics of bipolar patients with late cognitive impairment for whom the hypothesis of an underlying neurodegenerative disease had been raised. We performed a retrospective multicenter study, recruiting bipolar patients over 50 years old from five French tertiary memory centers who had undergone cerebrospinal fluid (CSF) biomarker assessment for Alzheimer’s disease (AD). Clinical, neuropsychological, and paraclinical characteristics were analyzed and 78 patients were included. The mean age at the onset of cognitive impairment was 62.4 years (±9.2). The mean MMSE score was 22.8 (±4.5), the mean FAB was 11.7 (±3.9), and the mean FCRST was 15.8 (±7.4)/36.8 (±9.7) (free/total recall). A total of 48.6% of the patients displayed cognitive fluctuations, and 38.2% showed cognitive improvement during follow-ups; and 56.3% of the patients showed Parkinsonism, of which 12.7% had never received antipsychotics. Among patients who underwent DAT-scans, 35.3% displayed dopaminergic denervation; 10.3% of patients had CSF AD biological signature (“A+ T+” profile), while 56.4% had other abnormal CSF profiles. Thus, clinical presentation was dominated by executive dysfunction, episodic memory impairment, fluctuating cognition, and a high frequency of Parkinsonism. Specifically, high frequency of delusional episodes suggests limited tolerance of psychotropic drugs. Most patients had abnormal CSF biomarker profiles, but only a minority displayed AD’s specific biomarker signature. Therefore, while our results unveil shared common neurocognitive features in bipolar patients with cognitive impairment of suspected neurodegenerative origin they suggest a participation of various underlying pathologies rather than a common degenerative mechanism in the pathophysiology of this condition.

A dry immersion model of microgravity modulates platelet phenotype, miRNA signature, and circulating plasma protein biomarker profile

Ground based research modalities of microgravity have been proposed as innovative methods to investigate the aetiology of chronic age-related conditions such as cardiovascular disease. Dry Immersion (DI), has been effectively used to interrogate the sequelae of physical inactivity (PI) and microgravity on multiple physiological systems. Herein we look at the causa et effectus of 3-day DI on platelet phenotype, and correlate with both miRomic and circulating biomarker expression. The miRomic profile of platelets is reflective of phenotype, which itself is sensitive and malleable to the exposome, undergoing responsive transitions in order to fulfil platelets role in thrombosis and haemostasis. Heterogeneous platelet subpopulations circulate at any given time, with varying degrees of sensitivity to activation. Employing a DI model, we investigate the effect of acute PI on platelet function in 12 healthy males. 3-day DI resulted in a significant increase in platelet count, plateletcrit, platelet adhesion, aggregation, and a modest elevation of platelet reactivity index (PRI). We identified 15 protein biomarkers and 22 miRNA whose expression levels were altered after DI. A 3-day DI model of microgravity/physical inactivity induced a prothrombotic platelet phenotype with an unique platelet miRNA signature, increased platelet count and plateletcrit. This correlated with a unique circulating protein biomarker signature. Taken together, these findings highlight platelets as sensitive adaptive sentinels and functional biomarkers of epigenetic drift within the cardiovascular compartment.

The Identification of Blood Biomarkers of Chronic Neuropathic Pain by Comparative Transcriptomics

In this study, we recruited 50 chronic pain (neuropathic and nociceptive) and 43 pain-free controls to identify specific blood biomarkers of chronic neuropathic pain (CNP). Affymetrix microarray was carried out on a subset of samples selected 10 CNP and 10 pain-free control participants. The most significant genes were cross-validated using the entire dataset by quantitative real-time PCR (qRT-PCR). In comparative analysis of controls and CNP patients, WLS (P = 4.80 × 10–7), CHPT1 (P = 7.74 × 10–7) and CASP5 (P = 2.30 × 10–5) were highly significant, whilst FGFBP2 (P = 0.00162), STAT1 (P = 0.00223), FCRL6 (P = 0.00335), MYC (P = 0.00335), XCL2 (P = 0.0144) and GZMA (P = 0.0168) were significant in all CNP patients. A three-arm comparative analysis was also carried out with control as the reference group and CNP samples differentiated into two groups of high and low S-LANSS score using a cut-off of 12. STAT1, XCL2 and GZMA were not significant but KIR3DL2 (P = 0.00838), SH2D1B (P = 0.00295) and CXCR31 (P = 0.0136) were significant in CNP high S-LANSS group (S-LANSS score > 12), along with WLS (P = 8.40 × 10–5), CHPT1 (P = 7.89 × 10–4), CASP5 (P = 0.00393), FGFBP2 (P = 8.70 × 10–4) and FCRL6 (P = 0.00199), suggesting involvement of immune pathways in CNP mechanisms. None of the genes was significant in CNP samples with low (< 12) S-LANSS score. The area under the receiver operating characteristic (AUROC) analysis showed that combination of MYC, STAT1, TLR4, CASP5 and WLS gene expression could be potentially used as a biomarker signature of CNP (AUROC − 0.852, (0.773, 0.931 95% CI)).

A highly predictive autoantibody-based biomarker panel for prognosis in early-stage NSCLC with potential therapeutic implications

Background Lung cancer is the leading cause of cancer-related death worldwide. Surgical resection remains the definitive curative treatment for early-stage disease offering an overall 5-year survival rate of 62%. Despite careful case selection, a significant proportion of early-stage cancers relapse aggressively within the first year post-operatively. Identification of these patients is key to accurate prognostication and understanding the biology that drives early relapse might open up potential novel adjuvant therapies. Methods We performed an unsupervised interrogation of >1600 serum-based autoantibody biomarkers using an iterative machine-learning algorithm. Results We identified a 13 biomarker signature that was highly predictive for survivorship in post-operative early-stage lung cancer; this outperforms currently used autoantibody biomarkers in solid cancers. Our results demonstrate significantly poor survivorship in high expressers of this biomarker signature with an overall 5-year survival rate of 7.6%. Conclusions We anticipate that the data will lead to the development of an off-the-shelf prognostic panel and further that the oncogenic relevance of the proteins recognised in the panel may be a starting point for a new adjuvant therapy.

Serum Biomarker Profile Including CCL1, CXCL10, VEGF, and Adenosine Deaminase Activity Distinguishes Active From Remotely Acquired Latent Tuberculosis

IntroductionThere is an urgent medical need to differentiate active tuberculosis (ATB) from latent tuberculosis infection (LTBI) and prevent undertreatment and overtreatment. The aim of this study was to identify biomarker profiles that may support the differentiation between ATB and LTBI and to validate these signatures.Materials and MethodsThe discovery cohort included adult individuals classified in four groups: ATB (n = 20), LTBI without prophylaxis (untreated LTBI; n = 20), LTBI after completion of prophylaxis (treated LTBI; n = 20), and healthy controls (HC; n = 20). Their sera were analyzed for 40 cytokines/chemokines and activity of adenosine deaminase (ADA) isozymes. A prediction model was designed to differentiate ATB from untreated LTBI using sparse partial least squares (sPLS) and logistic regression analyses. Serum samples of two independent cohorts (national and international) were used for validation.ResultssPLS regression analyses identified C-C motif chemokine ligand 1 (CCL1), C-reactive protein (CRP), C-X-C motif chemokine ligand 10 (CXCL10), and vascular endothelial growth factor (VEGF) as the most discriminating biomarkers. These markers and ADA(2) activity were significantly increased in ATB compared to untreated LTBI (p ≤ 0.007). Combining CCL1, CXCL10, VEGF, and ADA2 activity yielded a sensitivity and specificity of 95% and 90%, respectively, in differentiating ATB from untreated LTBI. These findings were confirmed in the validation cohort including remotely acquired untreated LTBI participants.ConclusionThe biomarker signature of CCL1, CXCL10, VEGF, and ADA2 activity provides a promising tool for differentiating patients with ATB from non-treated LTBI individuals.

Searching for a technology-driven acute rheumatic fever test: the START study protocol

IntroductionThe absence of a diagnostic test for acute rheumatic fever (ARF) is a major impediment in managing this serious childhood condition. ARF is an autoimmune condition triggered by infection with group A Streptococcus. It is the precursor to rheumatic heart disease (RHD), a leading cause of health inequity and premature mortality for Indigenous peoples of Australia, New Zealand and internationally.Methods and analysis‘Searching for a Technology-Driven Acute Rheumatic Fever Test’ (START) is a biomarker discovery study that aims to detect and test a biomarker signature that distinguishes ARF cases from non-ARF, and use systems biology and serology to better understand ARF pathogenesis. Eligible participants with ARF diagnosed by an expert clinical panel according to the 2015 Revised Jones Criteria, aged 5–30 years, will be recruited from three hospitals in Australia and New Zealand. Age, sex and ethnicity-matched individuals who are healthy or have non-ARF acute diagnoses or RHD, will be recruited as controls. In the discovery cohort, blood samples collected at baseline, and during convalescence in a subset, will be interrogated by comprehensive profiling to generate possible diagnostic biomarker signatures. A biomarker validation cohort will subsequently be used to test promising combinations of biomarkers. By defining the first biomarker signatures able to discriminate between ARF and other clinical conditions, the START study has the potential to transform the approach to ARF diagnosis and RHD prevention.Ethics and disseminationThe study has approval from the Northern Territory Department of Health and Menzies School of Health Research ethics committee and the New Zealand Health and Disability Ethics Committee. It will be conducted according to ethical standards for research involving Indigenous Australians and New Zealand Māori and Pacific Peoples. Indigenous investigators and governance groups will provide oversight of study processes and advise on cultural matters.

Lipocalin-2 and calprotectin as stool biomarkers for predicting necrotizing enterocolitis in premature neonates

Background Necrotizing enterocolitis (NEC) is a major challenge for premature infants in neonatal intensive care units and efforts toward the search for indicators that could be used to predict the development of the disease have given limited results until now. Methods In this study, stools from 132 very low birth weight infants were collected daily in the context of a multi-center prospective study aimed at investigating the potential of fecal biomarkers for NEC prediction. Eight infants (~6%) received a stage 3 NEC diagnosis. Their stools collected up to 10 days before diagnosis were included and matched with 14 non-NEC controls and tested by ELISA for the quantitation of eight biomarkers. Results Biomarkers were evaluated in all available stool samples leading to the identification of lipocalin-2 and calprotectin as the two most reliable predicting markers over the 10-day period prior to NEC development. Pooling the data for each infant confirmed the significance of lipocalin-2 and calprotectin, individually and in combination 1 week in advance of the NEC clinical diagnosis. Conclusions The lipocalin-2 and calprotectin tandem represents a significant biomarker signature for predicting NEC development. Although not yet fulfilling the “perfect biomarker” criteria, it represents a first step toward it. Impact Stool biomarkers can be used to predict NEC development in very low birth weight infants more than a week before the diagnosis. LCN2 was identified as a new robust biomarker for predicting NEC development, which used in conjunction with CALPRO, allows the identification of more than half of the cases that will develop NEC in very low birth weight infants. Combining more stool markers with the LCN2/CALPRO tandem such as PGE2 can further improve the algorithm for the prediction of NEC development.