Biomarker Studies Research Articles

P07-06 Exposure assessment of children to mycotoxins: A preliminary biomarker study conducted in Ribeirão Preto, São Paulo, Brazil

P07-06 Exposure assessment of children to mycotoxins: A preliminary biomarker study conducted in Ribeirão Preto, São Paulo, Brazil

Multiple Inputs and Mixed Data for Alzheimer’s Disease Classification Based on 3D Vision Transformer

The current methods for diagnosing Alzheimer’s Disease using Magnetic Resonance Imaging (MRI) have significant limitations. Many previous studies used 2D Transformers to analyze individual brain slices independently, potentially losing critical 3D contextual information. Region of interest-based models often focus on only a few brain regions despite Alzheimer’s affecting multiple areas. Additionally, most classification models rely on a single test, whereas diagnosing Alzheimer’s requires a multifaceted approach integrating diverse data sources for a more accurate assessment. This study introduces a novel methodology called the Multiple Inputs and Mixed Data 3D Vision Transformer (MIMD-3DVT). This method processes consecutive slices together to capture the feature dimensions and spatial information, fuses multiple 3D ROI imaging data inputs, and integrates mixed data from demographic factors, cognitive assessments, and brain imaging. The proposed methodology was experimentally evaluated using a combined dataset that included the Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Australian Imaging, Biomarker, and Lifestyle Flagship Study of Ageing (AIBL), and the Open Access Series of Imaging Studies (OASIS). Our MIMD-3DVT, utilizing single or multiple ROIs, achieved an accuracy of 97.14%, outperforming the state-of-the-art methods in distinguishing between Normal Cognition and Alzheimer’s Disease.

Patient-Reported Experiences of Persistent Post-COVID-19 Conditions After Hospital Discharge During the Second and Third Waves of the Pandemic in Switzerland: Cross-Sectional Questionnaire Study.

Hospitalized patients infected with SARS-CoV-2 should recover within a few weeks. However, even those with mild versions can experience symptoms lasting 4 weeks or longer. These post-COVID-19 condition (PCC) comprise various new, returning, or ongoing symptoms that can last for months or years and cause disability. Few studies have investigated PCC using self-reports from discharged patients infected with SARS-CoV-2 to complement clinical and biomarker studies. This study aimed to investigate self-reported, persistent PCC among patients infected with SARS-CoV-2 who were discharged during the second and third waves of the COVID-19 pandemic. We designed, pretested, and posted an ad hoc paper questionnaire to all eligible inpatients discharged between October 2020 and April 2021. At 4 months post discharge, we collected data on PCC and scores for the Multidimensional Fatigue Inventory (MFI), the Patient Health Questionnaire-4 (PHQ-4), a Brief Memory Screening Scale (Q3PC), and a posttraumatic stress disorder scale (PCL-5). Descriptive, inferential, and multivariate linear regression statistics assessed PCC symptomatology, associations, and differences regarding sociodemographic characteristics and hospital length of stay (LOS). We examined whether our variables of interest significantly predicted MFI scores. Of the 1993 valid questionnaires returned, 245 were from discharged patients with SARS-CoV-2 (median age 71, IQR 62.7-77 years). Only 28.2% (69/245) of respondents were symptom-free after 4 months. Women had significantly more persistent PCC symptoms than men (P≤.001). Patients with a hospital LOS ≥11 days had more PCC symptoms as well (P<.001)-women had more symptoms and longer LOS. No significant differences were found between age groups (18-64, 65-74, and ≥75 years old; P=.50) or between intensive care units and other hospitalization units (P=.09). Patients self-reported significantly higher PHQ-4 scores during their hospitalization than at 4 months later (P<.001). Three-fourth (187/245, 76.4%) of the respondents reported memory loss and concentration disorders (Q3PC). No significant differences in the median MFI score (56, IQR 1-3, range 50-60]) were associated with sociodemographic variables. Patients with a hospital LOS of ≥11 days had a significantly higher median PCL-5 score (P<.001). Multivariate linear regression allowed us to calculate that the combination of PHQ-4, Q3PC, and PCL-5 scores, adjusted for age, sex, and LOS (of either ≥11 days [median 2 symptoms, IQR 1-5] or <11 days), did not significantly predict MFI scores (R2=0.09; F4,7 =1.5; P=.22; adjusted R2=0.06). The majority of inpatients infected with SARS-CoV-2 presented with PCC 4 months after discharge, with complex clinical pictures. Only one-third of them were symptom-free during that time. Based on our findings, MFI scores were not directly related to self-reported depression, anxiety, or posttraumatic scores adjusted for age, sex, or LOS. Further research is needed to explore PCC and fatigue based on self-reported health experiences of discharged inpatients infected with SARS-CoV-2.

Blood DNA methylomic signatures associated with CSF biomarkers of Alzheimer's disease in the EMIF-AD study.

We investigated blood DNA methylation patterns associated with 15 well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) pathophysiology, neuroinflammation, and neurodegeneration. We assessed DNA methylation in 885 blood samples from the European Medical Information Framework for Alzheimer's Disease (EMIF-AD) study using the EPIC array. We identified Bonferroni-significant differential methylation associated with CSF YKL-40 (five loci) and neurofilament light chain (NfL; seven loci) levels, with two of the loci associated with CSF YKL-40 levels correlating with plasma YKL-40 levels. A co-localization analysis showed shared genetic variants underlying YKL-40 DNA methylation and CSF protein levels, with evidence that DNA methylation mediates the association between genotype and protein levels. Weighted gene correlation network analysis identified two modules of co-methylated loci correlated with several amyloid measures and enriched in pathways associated with lipoproteins and development. We conducted the most comprehensive epigenome-wide association study (EWAS) of AD-relevant CSF biomarkers to date. Future work should explore the relationship between YKL-40 genotype, DNA methylation, and protein levels in the brain. Blood DNA methylation was assessed in the EMIF-AD MBD study. Epigenome-wide association studies (EWASs) were performed for 15 Alzheimer's disease (AD)-relevant cerebrospinal fluid (CSF) biomarker measures. Five Bonferroni-significant loci were associated with YKL-40 levels and seven with neurofilament light chain (NfL). DNA methylation in YKL-40 co-localized with previously reported genetic variation. DNA methylation potentially mediates the effect ofsingle-nucleotide polymorphisms (SNPs) in YKL-40 on CSF protein levels.

Electronic health record biobank cohort recapitulates an association between the MUC5B promoter polymorphism and ARDS in critically ill adults.

Large population-based DNA biobanks linked to electronic health records (EHRs) may provide advantages over traditional study designs for identifying genetic drivers of ARDS. Can ARDS be identified in an EHR biobank, and can this approach validate a previously reported genetic risk factor for ARDS? We analyzed two genotyped cohorts from one academic medical center: a prospective biomarker study of critically ill adults (VALID cohort), and hospitalized participants in a de-identified EHR biobank (BioVU). ARDS status was assessed by clinician-investigator review in VALID and an EHR-derived algorithm in BioVU (EHR-ARDS). We tested the association between the MUC5B promoter polymorphism (rs35705950) with development of ARDS/EHR-ARDS in each cohort. In VALID, 2,795 patients were included, age was 55 [43, 66] (median [IQR]) years, and 718 (25.7%) developed ARDS. In BioVU, 9,025 hospitalized participants were included, age was 60 [48, 70] , and 1,056 (11.7%) developed EHR-ARDS. We observed a significant interaction between age and rs35705950 on ARDS risk in VALID: in older patients rs35705950 was associated with increased ARDS risk (OR: 1.44; 95%CI 1.08-1.92; p=0.012) whereas among younger patients this effect was attenuated (OR: 0.84; 95%CI: 0.62-1.14; p=0.26). In BioVU, rs35705950 was associated with increased risk for EHR-ARDS among all participants (OR: 1.20; 95%CI: 1.00-1.43, p=0.043) and this relationship did not vary by age. The polymorphism was also associated with more severe oxygenation impairment among BioVU participants who required mechanical ventilation. The MUC5B promoter polymorphism was associated with ARDS in two cohorts of at-risk hospitalized adults. Although age-related effect modification was observed only in the prospective biomarker cohort, the EHR cohort identified a consistent association between MUC5B and ARDS risk regardless of age and a novel association with oxygenation impairment. Our study highlights the potential for EHR biobanks to enable precision-medicine ARDS studies.

Systematic review and meta-analysis of biomarkers predicting decompensation in patients with compensated cirrhosis

Background and aimsThe transition from compensated to decompensated cirrhosis is crucial, drastically reducing prognosis from a median survival of over 10 years to 2 years. There is currently an unmet...

A Comprehensive Review of Protein Biomarkers for Invasive Lung Cancer.

Invasion and metastasis are important hallmarks of lung cancer, and affect patients' survival. Early diagnostics of metastatic potential are important for treatment management. Recent findings suggest that the transition to an invasive phenotype causes changes in the expression of 700-800 genes. In this context, the biomarkers restricted to the specific type of cancer, like lung cancer, are often overlooked. Some well-known protein biomarkers correlate with the progression of the disease and the immunogenicity of the tumor. Most of these biomarkers are not exclusive to lung cancer because of their significant role in tumorigenesis. The dysregulation of others does not necessarily indicate cell invasiveness, as they play an active role in cell division. Clinical studies of lung cancer use protein biomarkers to assess the invasiveness of cancer cells for therapeutic purposes. However, there is still a need to discover new biomarkers for lung cancer. In the future, minimally invasive techniques, such as blood or saliva analyses, may be sufficient for this purpose. Many researchers suggest unconventional biomarkers, like circulating nucleic acids, exosomal proteins, and autoantibodies. This review paper aims to discuss the advantages and limitations of protein biomarkers of invasiveness in lung cancer, to assess their prognostic value, and propose novel biomarker candidates.

Evidence for Altered White Matter Organization After Mild Traumatic Brain Injury: A Scoping Review on the Use of Diffusion Magnetic Resonance Imaging and Blood-Based Biomarkers to Investigate Acute Pathology and Relationship to Persistent Post-Concussion Symptoms.

Mild traumatic brain injury (mTBI) is the most common form of traumatic brain injury. Post-concussive symptoms typically resolve after a few weeks although up to 20% of people experience these symptoms for >3 months, termed persistent post-concussive symptoms (PPCS). Subtle white matter (WM) microstructural damage is thought to underlie neurological and cognitive deficits experienced post-mTBI. Evidence suggests that diffusion magnetic resonance imaging (dMRI) and blood-based biomarkers could be used as surrogate markers of WM organization. We conducted a scoping review according to PRISMA-ScR guidelines, aiming to collate evidence for the use of dMRI and/or blood-based biomarkers of WM organization, in mTBI and PPCS, and document relationships between WM biomarkers and symptoms. We focused specifically on biomarkers of axonal or myelin integrity post-mTBI. Biomarkers excluded from this review therefore included the following: astroglial, perivascular, endothelial, and inflammatory markers. A literature search performed across four databases, EMBASE, Scopus, Google Scholar, and ProQuest, identified 100 records: 68 analyzed dMRI, 28 assessed blood-based biomarkers, and 4 used both. Blood biomarker studies commonly assessed axonal cytoskeleton proteins (i.e., tau); dMRI studies assessed measures of WM organization (i.e., fractional anisotropy). Significant biomarker alterations were frequently associated with heightened symptom burden and prolonged recovery time post-injury. These data suggest that dMRI and blood-based biomarkers may be useful proxies of WM organization, although few studies assessed these complementary measures in parallel, and the relationship between modalities remains unclear. Further studies are warranted to assess the benefit of a combined biomarker approach in evaluating alterations to WM organization after mTBI.

Tumor immune microenvironmental characteristics in Human Epidermal Growth Factor-2 (HER2) positive esophageal adenocarcinoma: A comparative analysis and biomarker study

BackgroundHER2 targeting in esophageal adenocarcinoma (EAC) has shown potential, but often fails to show durable response. Given the contributions of the tumor immune microenvironment (TIME) to therapeutic responses, we aimed to chart the TIME characteristics of HER2 positive tumors. Methods84 biopsies were taken from the TRAP cohort (neoadjuvant chemoradiotherapy (nCRT) according to CROSS with trastuzumab and pertuzumab; n = 40; HER2+n = 40) and a control cohort with nCRT only (n = 44; HER2- n = 40, HER2+n = 4) before treatment. Biopsies were analysed using targeted gene expression analysis (Nanostring immune-oncology panel, 750 genes). Differential gene expression was assessed between HER2 positive (n = 44) vs. negative biopsies (n = 40), and non-responders (n = 17) vs. responders (n = 23) to anti-HER2 treatment. Statistical significance was determined as p-value <0.05, adjusted for multiple testing correction. Results83 biopsies were eligible for analyses following quality control (TRAP cohort n = 40; control cohort n = 43); there were no significant differences in clinical characteristics between the TRAP vs. control the cohort or HER2 positive vs. HER2 negative biopsies. HER2 expression was found to associate with epithelial markers (EPCAM p < 0.001; E-cadherin p < 0.001). Moreover, HER2 expression was associated with a lower expression of immune cell infiltration, such as NK-cells (p < 0.001) and CD8 T-cells (p < 0.001), but also lower expression of immune exhaustion markers (PDCD1LG2, CTLA4; p < 0.001). In non-responders to anti-HER2 treatment, baseline biopsies showed increased expression of immune exhaustion markers, as well as hypoxia and VEGF signalling. DiscussionHER2 expression was associated with epithelial tumor characteristics. The HER2 positive TIME showed reduced immune cell infiltration but also lower expression of inhibitory signals associated with immune exhaustion, questioning the mechanism behind potential clinical benefit of co-administration of anti-HER2 agents and checkpoint inhibitors. As limited response was associated with increased VEGF signalling, studies could investigate potential synergism of targeting VEGF and HER2.

Decabromodiphenyl ether and thyroid hormone disruption: A detailed mapping of human biomarker studies to uncover heterogeneity

Decabromodiphenyl ether and thyroid hormone disruption: A detailed mapping of human biomarker studies to uncover heterogeneity

Quaternary floodings in the Zanzibar Channel (NW Indian Ocean, Tanzania) – Identifying palaeoceanographic patterns and palaeoenvironment using a multiproxy study

Multiproxy palaeoenvironmental analyses represent a promising tool for complex reconstructions of continent-sea or air-sea interactions in shallow marine environments. This is in particular illustrated by the case of strong climatic variations in the late Pleistocene to mid-Holocene. A unique combination of geochemical proxies (143Nd/144Nd, 87Sr/86Sr, δ18O and δ13C isotope analyses, n-alkane analysis and biomarker study) together with micropalaeontological data (foraminifera, calcareous nannoplankton and diatoms) allowed to precisely characterise two marine floodings (mid-Holocene and late Pleistocene) in the Zanzibar Channel (NW Indian Ocean, Tanzania). The climate of the late Pleistocene interval was arid compared to the Holocene. The fully oligotrophic environment characteristic of the late Pleistocene flooding (∼115–130 ka) was episodically interrupted by intervals of intense rainfall with episodes of increased nutrient input during the mid-Holocene (∼5–10 ka). The dominance of seaweed meadows in the Holocene and late Pleistocene contrasts with the modern environment dominated by seagrass ecosystems. Relatively non-radiogenic εNd signatures in the Zanzibar Channel during the Holocene and late Pleistocene indicate a strong influence of riverine input draining the Precambrian basement on the African mainland. The main inflow of seawater was from the south, consistent with the flow direction of the East African Coastal Current and the directions of the March to October monsoon winds. A promising tool for future applications as indicators of seagrass/seaweed meadow type ecosystems may be the presence of specific diatom taxa.

Evaluation of reference genes suitable for studying mRNAs and microRNAs expression in thyroid neoplasms

Analysis of gene expression is a pivotal method at the core of biomarkers studies and cancer research. Currently, RT-qPCR is the most commonly used technique to investigate the expression of certain genes. The accurate and reliable result relies on an effective normalization step using suitable reference genes. The present study was designed to evaluate the eligibility of a set of candidate mRNAs and snoRNA as reference genes in the most common human thyroid neoplasms. We tested the expression levels of eleven mRNA and small RNA housekeeping genes in thyroid samples. The stability of the candidate genes was examined in different thyroid lesions and under different experimental conditions. Results were compared to the reported data in the TCGA database. Our results suggested HPRT1 and ACTB as the best mRNA reference genes, SNORD96A, and SNORD95 as the best miRNA reference genes in thyroid tissues. These genes showed the most stable expression pattern among different thyroid lesions as well as different experimental conditions. The findings in this study highlight the effect of reference genes selection on data interpretation and emphasize the importance of testing for suitable reference genes to be used in specific types of cells and experimental conditions to ensure the validity and accuracy of results.

Comparative study of bioconcentration potential and biomarkers in Biomphalaria glabrata exposed to ZnO nanoparticles and bulk ZnO

Comparative study of bioconcentration potential and biomarkers in Biomphalaria glabrata exposed to ZnO nanoparticles and bulk ZnO

Predictors of Resolution of Meningitis Symptoms in Tuberculous Meningitis: A Clinical, Magnetic Resonance Imaging, and Biomarker Study.

In tuberculous meningitis (TBM), the meningeal symptoms and their resolution after treatment may be dependent on clinical-radiological severity, cerebrospinal fluid (CSF), and proinflammatory cytokines, and these findings may be associated with outcome. There is a paucity of studies on the resolution of meningitis symptoms in TBM. We report on associations of clinical, magnetic resonance imaging (MRI), laboratory, and proinflammatory cytokines [tumor necrosis factor (TNF)-α and interleukin 6 (IL-6)] findings with the resolution of meningitis symptoms (RMS), and the impact of RMS duration on the outcome in TBM. Seventy-one patients with TBM were included, and their clinical, laboratory, and MRI findings at baseline were recorded. mRNA profiling of TNF-α and IL-6 was done by reverse transcriptase polymerase chain reaction. The day of RMS (fever, headache, and vomiting) after treatment was noted. Predictors of long duration of RMS (>3 weeks) were evaluated by univariate followed by multivariate analysis. The impact of RMS on 6-month mortality and outcome was analyzed. Patients' median age was 25 years, and 45 (63.4%) were males. After antitubercular treatment, meningeal symptoms resolved in 35 (50.70%) by 21 days and in 90% of patients by 49 days. Longer time of RMS was associated with TBM stage, pretreatment duration, seizure, and hydrocephalus but not with TNF-α and IL-6. Seven (9.8%) patients died at 6 months, and duration of RMS predicted death (hazard ratio = 25.55, 95% CI: 1.108-589.40; P = 0.04).

Multi-Omics Analysis of Primary Prostate Cancer Datasets Reveals Novel Biomarkers.

Prostate cancer (PCa) ranks second in cancer-related deaths in men. Current screenings used in the diagnosis are not sufficient enough in the early stages therefore, more diagnostic biomarker studies are needed. We performed a meta-analysis on the biomarker potential of miRNAs, mRNAs, and methylation for the early stages of PCa by searching available microarrays from the GEO dataset for PCa tissue and benign prostatic hyperplasia (BPH) or normal adjacent to PCa. Target genes of miRNAs were determined using the miRWalk and miRDB datasets. The results were visualized using network analysis. qPCR quantification of potential miRNA and genes was performed in human prostate epithelial cell line (RWPE-1) and human prostate carcinoma epithelial cell line (22RV1). Our meta-analysis of potential biomarkers for the diagnosis of PCa identified several candidates. It was shown that miR-7-5p is overexpressed. CAMKK2, TMEM97 expression were upregulated and CLIP1 expression was downregulated and these genes were shown to be targets of miR-7-5p. CAMKK2, TMEM97, and CLIP1 genes were found to be hypermethylated. Although the changes in the expression levels of miR-7-5p and CAMKK2, TMEM97, and CLIP1 in the two cell lines used in our study were not consistent with the significant expression differences observed in the meta-analysis, our meta-analysis results would be promising in human prostate tissue or different human tumor cell line studies. This highlights the importance of our meta-analysis results in prostate cancer biomarker research, given the difficulty of experimental validation of our large-scale data meta-analysis results using a specific cell line.

Study of Inflammatory Biomarkers in Treatment-Naive HIV Patients and Their Correlation With Clusters of Differentiation 4 (CD4) Count.

Introduction The human immunodeficiency virus (HIV) primarily targets clusters of differentiation 4 (CD4)+ T cells and other immune cells, leading to immune dysfunction. Cytokines such as interleukin (IL)-23 and IL-27 have complex roles in HIV-associated disease progression, affecting viral replication and immune responses. This study aimed to explore the correlation between HIV-related CD4 lymphopenia and the inflammatory cytokines IL-23 and IL-27 in treatment-naive HIV patients. Materials and methods This is a single-center, prospective, observational study conducted at the Antiretroviral Treatment (ART) Center of Jawaharlal Nehru Medical College and Hospital, Aligarh Muslim University, Aligarh, Uttar Pradesh, India. Sixty-five treatment-naive HIV seropositive patients were recruited in this study. Quantitative estimation of inflammatory biomarkers (IL-23 and IL-27) was performed using enzyme-linked immunosorbent assay (ELISA). The fluorescent-activated cell sorter count (FACSCount) technology was used to determine the CD4+ T-cell count. Results Our study revealed that HIV-infected individuals had significantly higher levels of IL-23 (868.9±246.7 pg/mL vs 98.3±86.6 pg/mL, p < 0.01) and IL-27 (1629.5±518.5 pg/mL vs 291.3±225.2 pg/mL, p < 0.01) compared to healthy controls. Additionally, we found a strong positive correlation between CD4 count and IL-23 titers (r = 0.93, p < 0.01), as well as between CD4 count and IL-27 titers (r = 0.92, p < 0.01) in HIV-positive individuals. Conclusion The findings suggest that these cytokines respond to HIV infection and may potentially play a crucial role in restraining HIV replication and slowing down the progression of the disease.

Using data processing to understand inconsistency in smartphone behavior among patients with serious mental illness: Results of a digital phenotyping biomarker study

BackgroundSmartphone-based digital phenotyping can provide novel transdiagnostic markers of mental illness including circadian routines and anhedonia. In proposing transdiagnostic digital phenotypes for circadian routines and anhedonia in depression and bipolar disorder patients, this paper explores their derivation, comparison to naive models, and replicability across two different research sites/teams. Methods84 participants (bipolar disorder, depression, controls) used the mindLAMP app for 12 weeks to capture digital phenotypes on their personal smartphones. mindLAMP was used to deliver surveys about mood symptoms while collecting device acceleration, geolocation, and screen on/off state. Participant chronotype was derived from this sensor data. Within-participant and between-participant models were created to assess how time-varying features collected through digital phenotyping could predict weekly anhedonia survey responses. ResultsWithin-person models outperformed between-person models in predicting anhedonia. Chronotype was the strongest predictor of weekly anhedonia scores as indicated by Shapley scores. Shapley scores also revealed that many of the time-varying predictor variables are significant but differ in their direction of action. DiscussionThis analysis reveals the meaningful but potentially misleading nature of digital phenotyping signals. Results suggest that each participant has a unique set of relationships between time-varying digital phenotype variables; therefore, it is challenging to predict trends between participants. Bayesian models, with appropriate population priors, may offer the next step for improving the potential of personalized digital phenotyping insights.

Quantitative Comparison of Deparaffinization, Rehydration, and Extraction Methods for FFPE Tissue Proteomics and Phosphoproteomics.

Formalin-fixed paraffin-embedded (FFPE) tissues are suitable for proteomic and phosphoproteomic biomarker studies by data-independent acquisition mass spectrometry. The choice of the sample preparation method influences the number, intensity, and reproducibility of identifications. By comparing four deparaffinization and rehydration methods, including heptane, histolene, SubX, and xylene, we found that heptane and methanol produced the lowest coefficients of variation (CVs). Using this, five extraction methods from the literature were modified and evaluated for their performance using kidney, leg muscle, lung, and testicular rat organs. All methods performed well, except for SP3 due to insufficient tissue lysis. Heat n' Beat was the fastest and most reproducible method with the highest digestion efficiency and lowest CVs. S-Trap produced the highest peptide yield, while TFE produced the best phosphopeptide enrichment efficiency. The quantitation of FFPE-derived peptides remains an ongoing challenge with bias in UV and fluorescence assays across methods, most notably in SPEED. Functional enrichment analysis demonstrated that each method favored extracting some gene ontology cellular components over others including chromosome, cytoplasmic, cytoskeleton, endoplasmic reticulum, membrane, mitochondrion, and nucleoplasm protein groups. The outcome is a set of recommendations for choosing the most appropriate method for different settings.

Molecular biomarkers of progression in non-muscle-invasive bladder cancer - beyond conventional risk stratification.

The global incidence of bladder cancer is more than half a million diagnoses each year. Bladder cancer can be categorized into non-muscle-invasive bladder cancer (NMIBC), which accounts for ~75% of diagnoses, and muscle-invasive bladder cancer(MIBC). Up to 45% of patients with NMIBC develop disease progression to MIBC, which is associated with a poor outcome, highlighting a clinical need to identify these patients. Current risk stratification has a prognostic value, but relies solely on clinicopathological parameters that might not fully capture the complexity of disease progression. Molecular research has led to identification of multiple crucial players involved in NMIBC progression. Identified biomarkers of progression are related to cell cycle, MAPK pathways, apoptosis, tumour microenvironment, chromatin stability and DNA-damage response. However, none of these biomarkers has been prospectively validated. Reported gene signatures of progression do not improve NMIBC risk stratification. Molecular subtypes of NMIBC have improved our understanding of NMIBC progression, but these subtypes are currently unsuitable for clinical implementation owing to a lack of prospective validation, limited predictive value as a result of intratumour subtype heterogeneity, technical challenges, costs and turnaround time. Future stepsinclude thedevelopment of consensus molecular NMIBC subtypes that mightimprove conventional clinicopathological risk stratification. Prospective implementation studies of biomarkers and the design ofbiomarker-guided clinical trials are required for the integration of molecular biomarkersinto clinical practice.

Age-Dependent Signature of Serum Inflammatory Cytokines in Healthy Children and Young Adults.

The study of sensitive and specific biomarkers, such as blood inflammatory cytokines, could provide an answer to the challenges faced in the differential diagnosis of patients with systemic inflammation. Limited data exist on the impact of age on serum levels of inflammatory cytokines. We collected serum samples of 42 healthy children and young adults (1 month to 21 years). Serum levels of interleukin 1 receptor antagonist (IL-1Ra), IL-1β, IL-6, IL-18, tumor necrosis factor-alpha (TNF-α), CXCL9, and CXCL10 were measured. Data were analyzed for three different age groups (<6, 6-17, and 18-21 years). IL-18, TNF-α, and CXCL9 values varied significantly according to age group. Median values of IL-18 and TNF-α decline with age, whereas CXCL9 and CXCL10 are lowest at 6-17 years. IL-1Ra is stable among age groups. In the majority of cases, IL-1β and IL-6 are not measurable above the lower limit of quantification. A scoping literature review revealed highly variable data on IL-1Ra, IL-18, TNF-α, and CXCL10. For CXCL9, pediatric reference data are scarce. In conclusion, we report an age-dependent signature of multiple inflammatory cytokines measured in the serum of healthy children and young adults, suggesting the need to use age-specific reference values in future pediatric studies.