Current Biomarkers Research Articles

Conditional survival to assess prognosis in patients with chronic lymphocytic leukemia

Biomarkers in chronic lymphocytic leukemia (CLL) allow assessment of prognosis. However, the validity of current prognostic biomarkers based on a single assessment point remains unclear for patients who have survived one or more years. Conditional survival (CS) studies that address how prognosis may change over time, especially in prognostic subgroups, are still rare. We performed CS analyses to estimate 5-year survival in 1-year increments, stratified by baseline disease characteristics and known risk factors in two community-based cohorts of CLL patients (Freiburg University Hospital (n = 316) and Augsburg University Hospital (n = 564)) diagnosed between 1984 and 2021. We demonstrate that 5-year CS probability is stable (app. 75%) for the entire CLL patient cohort over 10 years. While age, sex, and stage have no significant impact on CS, patients with high-risk disease features such as non-mutated IGHV, deletion 17p, and high-risk CLL-IPI have a significantly worse prognosis at diagnosis, and 5-year CS steadily decreases with each additional year survived. Our results confirm that CLL patients have a stable survival probability with excess mortality and that the prognosis of high-risk CLL patients declines over time. We infer that CS-based prognostic information is relevant for disease management and counseling of CLL patients.

Cell-cell communication network-based interpretable machine learning predicts cancer patient response to immune checkpoint inhibitors.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. However, only some patients respond to ICIs, and current biomarkers for ICI efficacy have limited performance. Here, we devised an interpretable machine learning (ML) model trained using patient-specific cell-cell communication networks (CCNs) decoded from the patient's bulk tumor transcriptome. The model could (i) predict ICI efficacy for patients across four cancer types (median AUROC: 0.79) and (ii) identify key communication pathways with crucial players responsible for patient response or resistance to ICIs by analyzing more than 700 ICI-treated patient samples from 11 cohorts. The model prioritized chemotaxis communication of immune-related cells and growth factor communication of structural cells as the key biological processes underlying response and resistance to ICIs, respectively. We confirmed the key communication pathways and players at the single-cell level in patients with melanoma. Our network-based ML approach can be used to expand ICIs' clinical benefits in cancer patients.

A study of blood myeloid-derived suppressor cells for predicting pembrolizumab efficacy in patients with metastatic urothelial carcinoma.

658 Background: Immune checkpoint inhibitors (ICIs) are crucial for treating metastatic urothelial carcinoma (mUC) patients, yet current prognostic biomarkers fail to predict ICI efficacy. Previous preclinical models have suggested myeloid-derived suppressor cells (MDSCs) as a potential therapeutic target in bladder cancer. This study aims to evaluate the predictive value of blood MDSCs in mUC patients undergoing pembrolizumab treatment. Methods: Ninety-eight mUC patients who progressed with platinum-based chemotherapy at Osaka Metropolitan University received pembrolizumab. Among them, 30 patients were assessed for blood MDSCs. Peripheral blood samples were collected from healthy individuals (n = 6) and mUC patients (n = 30) before pembrolizumab initiation. The mononuclear cell layer was isolated using density gradient centrifugation for MDSC analysis through flow cytometry. Monocytic and polymorphonuclear MDSCs were defined as CD11b+ HLADR – CD33 high CD14 + CD15 – and CD11b+ HLADR – CD33 low CD14 – CD15 +, respectively. The neutrophil-lymphocyte ratio (NLR) in blood served as a control. Treatment response was assessed via CT images using RECICT v1.1. Progression-free survival (PFS) and overall survival (OS) were calculated using the Kaplan-Meier method, with log-rank test for between-group comparison. Results: First, blood MDSCs were significantly elevated in mUC patients compared to healthy controls (p = 0.0024, Mann Whitney test). Secondly, patients with MDSClow (≤ median, n = 15) had significantly longer PFS than those with MDSChigh (> median, n = 15) (17.6 vs. 1.9 months, p = 0.0126). However, no significant difference was observed in OS. In contrast, when the NLR cutoff was set at 3.5, no significant association was found for PFS and OS. Conclusions: Blood MDSCs show promise as a predictive marker for pembrolizumab therapy efficacy.

Antibody Profiling of Pan-Cancer Viral Proteome Reveals Biomarkers for Nasopharyngeal Carcinoma Diagnosis and Prognosis

Diagnosing, predicting disease outcome, and identifying effective treatment targets for virus-related cancers are lacking. Protein biomarkers have the potential to bridge the gap between prevention and treatment for these types of cancers. While it has been shown that certain antibodies against EBV proteins could be used to detect nasopharyngeal carcinoma (NPC), antibodies targeting are solely a tiny part of the about 80 proteins expressed by the EBV genome. Furthermore, it remains unclear what role other viruses play in NPC since many diseases are the result of multiple viral infections. For the first time, this study measured both IgA and IgG antibody responses against 646 viral proteins from 23 viruses in patients with NPC and control subjects using nucleic acid programmable protein arrays. Candidate seromarkers were then validated by ELISA using 1665 serum samples from three clinical cohorts. We demonstrated that the levels of five candidate seromarkers (EBV-BLLF3-IgA, EBV-BLRF2-IgA, EBV-BLRF2-IgG, EBV-BDLF1-IgA, EBV-BDLF1-IgG) in NPC patients were significantly elevated than controls. Additional examination revealed that NPC could be successfully diagnosed by combining the clinical biomarker EBNA1-IgA with the five anti-EBV antibodies. The sensitivity of the six-antibody signature at 95% specificity to diagnose NPC was comparable to the current clinically-approved biomarker combination, VCA-IgA, and EBNA1-IgA. However, the recombinant antigens of the five antibodies are easier to produce and standardize compared to the native viral VCA proteins. This suggests the potential replacement of the traditional VCA-IgA assay with the 5-antibodies combination to screen and diagnose NPC. Additionally, we investigated the prognostic significance of these seromarkers titers in NPC. We showed that NPC patients with elevated BLLF3-IgA and BDLF1-IgA titers in their serum exhibited significantly poorer disease-free survival, suggesting the potential of these two seromarkers as prognostic indicators of NPC. These findings will help develop serological tests to detect and treat NPC in the future.

Biomarkers for Alzheimer's Disease – An Overview

AbstractAlzheimer's disease (AD) is a complex neurodegenerative disorder with a significant global impact on public health. The emergence of atypical clinical phenotypes challenges traditional diagnostic approaches, necessitating a deeper exploration of biomarkers for accurate identification. The US Food and Drug Administration (FDA) classification of biomarkers and their integration into different stages of AD provide a structured framework for their application in research and clinical settings. Within the context of AD drug development, biomarkers are essential for participant selection, target engagement evaluation, and assessment of pathological hallmarks, including Aβ and tau protein abnormalities. The incorporation of nanoparticles with a biodegradable approach introduces innovative strategies to address the complexities of AD. This paper extensively discusses biomarkers associated with synaptic dysfunction, neuroinflammation, and glial activation, recognizing their significance in elucidating disease mechanisms. Common pathologies such as synuclein and TDP‐43 further underscore the multifaceted nature of AD. Current biomarkers for AD diagnosis, encompassing cerebral spinal fluid (CSF) biomarkers and various imaging modalities, reflect the ongoing efforts to enhance early detection and monitoring. Intriguingly, novel biomarkers continue to emerge, offering promising avenues for improved understanding and intervention. Current review provides a comprehensive survey of biomarkers for AD, elucidating their diverse roles across different aspects of the disease. By highlighting their contributions to diagnosis, drug development, and mechanistic insights, this overview underscores the importance of biomarker research in the pursuit of effective AD management and treatment strategies.

Dysregulation of long non-coding RNAs in Takayasu arteritis: A proof-of-concept study.

Takayasu arteritis (TAK) is a rare systemic vasculitis primarily affecting the aorta and its major branches. Early diagnosis is critical to prevent severe vascular complications, yet current biomarkers are insufficient. This proof-of-concept study explores the potential of long non-coding RNAs (lncRNAs) in TAK, an area largely unexplored. In this cross-sectional study, 53 TAK patients, 53 healthy controls, and 10 rheumatoid arthritis (RA) patients were enrolled. Clinical evaluations, disease activity assessments, and lncRNA expression levels were analyzed. TAK patients exhibited significant dysregulation in several lncRNAs, including THRIL (19.4, 11.1-48.8 vs. 62.5, 48.6-91.4 arbitrary units [a.u.]; p < 0.0001), HIF1A-AS1 (4.5, 1.8-16.6 vs. 26.5, 19.8-33.7 a.u.; p < 0.0001), MALAT-1 (26.9, 13.8-52.5 vs. 92.1, 58.5-92.1 a.u.; p < 0.0001), and HOTAIR (8.0, 2.5-24.5 vs. 36.0, 30.0-43.8 a.u.; p < 0.0001), compared to healthy controls. Notably, HOTAIR (area under the ROC curve [AUC] = 0.825), HIF1A-AS1 (AUC = 0.820), and THRIL (AUC = 0.781) demonstrated high diagnostic potential with superior specificity (approximately 95%). While lncRNAs showed diagnostic promise, no significant correlations with TAK activity were observed. Comparative analysis with RA patients revealed distinct lncRNA expression patterns. This study unveils significant dysregulation of lncRNAs THRIL, HIF1A-AS1, and HOTAIR in TAK patients, underscoring their potential as biomarkers and opening avenues for further research into the mechanistic roles of these lncRNAs in TAK pathogenesis.

Current and Future Biomarkers in Esophagogastric Adenocarcinoma.

Biomarker-based therapies have shown improved patient outcomes across various cancer types. The purpose of this review to summarize our knowledge of current and future biomarkers in esophagogastric adenocarcinoma (EGA). In this publication, we will review current standard biomarkers in patients with upper GI cancers. We will also discuss novel biomarkers that are under investigations and their associated therapies that are currently in clinical trials. EGAa are a group of heterogeneous diseases, both anatomically and molecularly. There are several established biomarkers (HER2, PD-L1, microsattelite instability or mismatch repair protein expression) that allow for individualized treatments for patients with these cancers. There are also several emerging biomarkers for EGA, some of which have clinically relevant associated therapies. Claudin 18.2 is the furthest along among these. Anti-claudin antibody, zolbetuximab, improved overall survival in biomarker select patients with advanced GEA in two phase 3 studies. Other novel biomarkers, such as FGFR2b and DKN01, are also in the process of validation, and treatments based on the presence of these biomarkers are currently in clinical studies. Ongoing efforts to identify novel biomarkers in EGA have led to enhanced subclassification of upper GI cancers. These advances, coupled with the strategic application of targeted therapies and immunotherapy when appropriate, hold promise to further improve patients outcomes.

Role of biomarkers and molecular signaling pathways in acute lung injury.

Acute lung injury (ALI) is caused by bacterial, fungal, and viral infections. When pathogens invade the lungs, the immune system responds by producing cytokines, chemokines, and interferons to promote the infiltration of phagocytic cells, which are essential for pathogen clearance. Their excess production causes an overactive immune response and a pathological hyper-inflammatory state, which leads to ALI. Until now, there is no particular pharmaceutical treatment available for ALI despite known inflammatory mediators like neutrophil extracellular traps (NETs) and reactive oxygen species (ROS). Therefore, the primary objective of this review is to provide the clear overview on the mechanisms controlling NETs, ROS formation, and other relevant processes during the pathogenesis of ALI. In addition, we have discussed the significance of epithelial and endothelial damage indicators and several molecular signaling pathways associated with ALI. The literature review was done from Web of Science, Scopus, PubMed, and Google Scholar for ALI, NETs, ROS, inflammation, biomarkers, Toll- and nucleotide-binding oligomerization domain (NOD)-like receptors, alveolar damage, pro-inflammatory cytokines, and epithelial/endothelial damage alone or in combination. This review summarized the main clinical signs of ALI, including the regulation and distinct function of epithelial and endothelial biomarkers, NETs, ROS, and pattern recognition receptors (PRRs). However, no particular drugs including vaccine for ALI has been established. Furthermore, there is a lack of validated diagnostic tools and a poor predictive rationality of current therapeutic biomarkers. Hence, extensive and precise research is required to speed up the process of drug testing and development by the application of artificial intelligence technologies, structure-based drug design, in-silico approaches, and drug repurposing.

Screening and experimental validation of diagnostic gene in ulcerative colitis with anti-TNF-α therapy.

In clinical practice, the diagnosis of ulcerative colitis (UC) mainly relies on a comprehensive analysis of a series of signs and symptoms of patients. The current biomarkers for diagnosis of UC and prognostic prediction of anti-TNF-α therapy are inaccurate. The present study aimed to perform an integrative analysis of gene expression profiles in patients with UC. A total of seven datasets from the GEO database that met our strict inclusion criteria were included. After identifying differentially expressed genes (DEGs) between UC patients and healthy individuals, the diagnostic and prognostic utility of the DEGs were then analyzed via least absolute shrinkage and selection operator and support-vector machine recursive feature elimination. Subgroup analyses of the treated and untreated groups, as well as the treatment-response group and non-response group, were also performed. Furthermore, the relationship between the expressions of UC-related genes and infiltration of immune cells in the course of treatment was also investigated. Immunohistochemical (IHC) assay was used to verify the gene expression in inflamed UC tissues. When considering all the applied methods, DUOX2, PI3, S100P, MMP7, and S100A8 had priority to be defined as the characteristic genes among DEGs. The area under curve (AUC) of the five genes, which were all consistently over-expressed, based on an external validation dataset, were all above 0.94 for UC diagnosis. Four of the five genes (DUOX2, PI3, MMP7, and S100A8) were down-regulated between treatment-responsive and nonresponsive patients. A significant difference was also observed concerning the infiltration of immune cells, including macrophage and neutrophil, between the two groups (treatment responsive and nonresponsive). The changes in the expression of DUOX2 and MMP7 based on the IHC assay were highly consistent with the results obtained in the current study. This confirmed the mild to moderate diagnostic and predictive value of DUOX2 and MMP7 in patients with UC. The conducted analyses showed that the expression profile of the five identified biomarkers accurately detects UC, whereas four of the five genes evidently predicted the response to anti-TNF-α therapy.

P418 Lipopolysaccharide-Binding Protein (LBP) in Crohn's Disease (CD) Patients: A Promising Non-Invasive Biomarker Monitoring Disease Activity

Abstract Background Current biomarkers of inflammatory bowel disease (IBD) monitoring (serum C-reactive protein (CRP) and faecal calprotectin (FC)) have limitations in terms of specificity (SP) and sensitivity (SE), especially for Crohn’s disease (CD) patients. Lipopolysaccharide-binding protein (LBP) is a soluble acute-phase protein and is thought to partly reflect intestinal permeability by binding to bacterial lipopolysaccharides. The search for new biomarkers to monitor disease activity would improve the management of IBD patients. Methods This is a retrospective study including 69 IBD patients (43 CD and 26 ulcerative colitis (UC)) and 21 healthy controls (HC). Serum LBP levels were measured by enzyme-linked immunosorbent assay. Clinical, biological and endoscopic parameters were analysed for IBD patients. Statistical tests, including nonparametric tests and receiver operating characteristic (ROC) curve analysis, were used to evaluate the diagnostic accuracy of LBP. Results Demographics and baseline data of the overall cohort is presented in Table 1. IBD patients displayed a significantly higher LBP median (29.6 µg/mL [19.8-38.8] in CD and 22.8 [13.7-38.8] in UC) than HC (5.5 [4.4-6.5], P &amp;lt; 0.001) with no overlapping distributions, a finding supported by an AUC of 0.997 and 0.989, respectively for CD and UC patients (Figures 1A). In CD patients, LBP levels gradually increased with endoscopic severity, demonstrating a 1.7-fold rise in active patients compared to remitter patients (P=0.02) (Figure 1B). LBP levels were higher in Montreal B1 compared to B2 and B3 CD patients (P &amp;lt; 0.001) (Figure 1C). Overall, a robust correlation was observed between LBP and CRP (ρ=0.75, P &amp;lt; 0.001). The correlation increased upon the exclusion of cases with normal CRP levels but active endoscopic disease (ρ=0.79, P &amp;lt; 0.001). In those endoscopically active patients with normal CRP, LBP level was higher than in remitter patients (34.3 [29.4-37.6] vs 19.1 [10-24.7], P=0.01) with a discriminative cut-off of 25 µg/mL (SE of 100%, SP of 89%). Likewise, LBP level exhibited a positive correlation with FC (ρ=0.42, P &amp;lt; 0.01) which was further strengthened after excluding cases where FC measurements did not align with endoscopic activity (ρ=0.53, P &amp;lt; 0.01). The median LBP for those patients was 25.6 [18.5-31.5], reflecting again the interest of LBP measurement to evaluate CD activity when FC lacks sensibility. Conclusion Our study suggests that LBP might be a promising non-invasive biomarker for monitoring disease activity, especially in CD patients. Furthermore, in clinical situations where current biomarkers (CRP and FC) lack sensitivity for assessing disease activity, LBP could be discriminative and help filling the gap for reliable therapeutic decisions.

Diagnostic Challenges during Inflammation and Cancer: Current Biomarkers and Future Perspectives in Navigating through the Minefield of Reactive versus Dysplastic and Cancerous Lesions in the Digestive System.

In the setting of pronounced inflammation, changes in the epithelium may overlap with neoplasia, often rendering it impossible to establish a diagnosis with certainty in daily clinical practice. Here, we discuss the underlying molecular mechanisms driving tissue response during persistent inflammatory signaling along with the potential association with cancer in the gastrointestinal tract, pancreas, extrahepatic bile ducts, and liver. We highlight the histopathological challenges encountered in the diagnosis of chronic inflammation in routine practice and pinpoint tissue-based biomarkers that could complement morphology to differentiate reactive from dysplastic or cancerous lesions. We refer to the advantages and limitations of existing biomarkers employing immunohistochemistry and point to promising new markers, including the generation of novel antibodies targeting mutant proteins, miRNAs, and array assays. Advancements in experimental models, including mouse and 3D models, have improved our understanding of tissue response. The integration of digital pathology along with artificial intelligence may also complement routine visual inspections. Navigating through tissue responses in various chronic inflammatory contexts will help us develop novel and reliable biomarkers that will improve diagnostic decisions and ultimately patient treatment.

Early detection of liver injuries by the Serum enhanced binding test sensitive to albumin post-transcriptional modifications

Early and sensitive biomarkers of liver dysfunction and drug-induced liver injury (DILI) are still needed, both for patient care and drug development. We developed the Serum Enhanced Binding (SEB) test to reveal post-transcriptional modifications (PTMs) of human serum albumin resulting from hepatocyte dysfunctions and further evaluated its performance in an animal model. The SEB test consists in spiking serum ex-vivo with ligands having specific binding sites related to the most relevant albumin PTMs and measuring their unbound fraction. To explore the hypothesis that albumin PTMs occur early during liver injury and can also be detected by the SEB test, we induced hepatotoxicity in male albino Wistar rats by administering high daily doses of ethanol and CCl4 over several days. Blood was collected for characterization and quantification of albumin isoforms by high-resolution mass spectrometry, for classical biochemical analyses as well as to apply the SEB test. In the exposed rats, the appearance of albumin isoforms paralleled the positivity of the SEB test ligands and histological injuries. These were observed as early as D3 in the Ethanol and CCl4 groups, whereas the classical liver tests (ALT, AST, PAL) significantly increased only at D7. The behavior of several ligands was supported by structural and molecular simulation analysis. The SEB test and albumin isoforms revealed hepatocyte damage early, before the current biochemical biomarkers. The SEB test should be easier to implement in the clinics than albumin isoform profiling.

Novel rapid method for identifying and quantifying pathogenic bacteria within four hours of blood collection

Sepsis is life-threatening organ dysfunction and is considered a major cause of health loss. However, since the current biomarkers of sepsis reflect the host’s immune response to microorganisms, they would inevitably cause a time-lag. This means that there is still no truly reliable biomarker of sepsis. In the present study, we developed a novel method for identifying and quantifying unknown pathogenic bacteria within four hours of sample collection. The most important point of this study is that the novel method can be used to determine the number of bacteria in a sample as a novel biomarker of infectious diseases. Indeed, based on the number of bacteria, we were able to accurately estimate the severity of microbial infection. Furthermore, using the time-dependent changes in the number of bacteria, we were able to monitor the therapeutic effect accurately. The rapid identification and quantification of bacteria may change our approach to medical care.

Biomarkers and molecular endotypes of sarcoidosis: lessons from omics and non-omics studies.

Sarcoidosis is a chronic granulomatous disorder characterized by unknown etiology, undetermined mechanisms, and non-specific therapies except TNF blockade. To improve our understanding of the pathogenicity and to predict the outcomes of the disease, the identification of new biomarkers and molecular endotypes is sorely needed. In this study, we systematically evaluate the biomarkers identified through Omics and non-Omics approaches in sarcoidosis. Most of the currently documented biomarkers for sarcoidosis are mainly identified through conventional "one-for-all" non-Omics targeted studies. Although the application of machine learning algorithms to identify biomarkers and endotypes from unbiased comprehensive Omics studies is still in its infancy, a series of biomarkers, overwhelmingly for diagnosis to differentiate sarcoidosis from healthy controls have been reported. In view of the fact that current biomarker profiles in sarcoidosis are scarce, fragmented and mostly not validated, there is an urgent need to identify novel sarcoidosis biomarkers and molecular endotypes using more advanced Omics approaches to facilitate disease diagnosis and prognosis, resolve disease heterogeneity, and facilitate personalized medicine.

Review of the limitations of current biomarkers in acute kidney injury clinical practices.

Acute kidney injury is a prevalent disease in hospitalized patients and is continuously increasing worldwide. Various efforts have been made to define and classify acute kidney injury to understand the progression of this disease. Furthermore, deviations from structure and kidney function and the current diagnostic guidelines are not adequately placed due to baseline serum creatinine values, which are rarely known and estimated based on glomerular function rate, resulting in misclassification of acute kidney injury staging. Hence, the current guidelines are still developing to improve and understand the clinical implications of risk factors and earlier predictive biomarkers of acute kidney injury. Yet, studies have indicated disadvantages and limitations with the current acute kidney injury biomarkers, including lack of sensitivity and specificity. Therefore, the present narrative review brings together the most current evidenced-based practice and literature associated with the limitations of the gold standard for acute kidney injury diagnoses, the need for novel acute kidney injury biomarkers, and the process for biomarkers to be qualified for diagnostic use under the following sections and themes. The introduction section situates the anatomy and normal and abnormal kidney functions related to acute kidney injury disorders. Guidelines in providing acute kidney injury definitions and classification are then considered, followed by a discussion of the disadvantages of standard markers used to diagnose acute kidney injury. Characteristics of an ideal acute kidney injury biomarker are discussed concerning sensitivity, specificity, and anatomic location of injury. A particular focus on the role and function of emerging biomarkers is discussed in relation to their applications and significance to the prognosis and severity of acute kidney injury. Findings show emerging markers are early indicators of acute kidney injury prediction in different clinical settings. Finally, the process required for a biomarker to be applied for diagnostic use is explained.

Interferon-stimulated neutrophils as a predictor of immunotherapy response

Despite the remarkable success of anti-cancer immunotherapy, its effectiveness remains confined to a subset of patients-emphasizing the importance of predictive biomarkers in clinical decision-making and further mechanistic understanding of treatment response. Current biomarkers, however, lack the power required to accurately stratify patients. Here, we identify interferon-stimulated, Ly6Ehi neutrophils as a blood-borne biomarker of anti-PD1 response in mice at baseline. Ly6Ehi neutrophils are induced by tumor-intrinsic activation of the STING (stimulator of interferon genes) signaling pathway and possess the ability to directly sensitize otherwise non-responsive tumors to anti-PD1 therapy, in part through IL12b-dependent activation of cytotoxic Tcells. By translating our pre-clinical findings to a cohort of patients with non-small cell lung cancer and melanoma (n= 109), and to public data (n= 1440), we demonstrate the ability of Ly6Ehi neutrophils to predict immunotherapy response in humans with high accuracy (average AUC≈ 0.9). Overall, our study identifies a functionally active biomarker for use in both mice and humans.

Laboratory diagnosis of neurosyphilis: optimization ways. Part II. Current approaches and biomarkers

Laboratory diagnosis of neurosyphilis: optimization ways. Part II. Current approaches and biomarkers

Perspective: Sepsis Biomarker Research Requires a Move to the Emergency Department and More Collaboration

Despite years of research and multiple potential candidate biomarkers for sepsis, few have had sufficient sensitivity or specificity to be integrated into routine practice. There have been only 11 observational studies that have collected samples from patients presenting to the emergency department with suspected sepsis. This has resulted in gaps in the ability to accurately diagnose sepsis in patients presenting with infections and give an accurate prognosis for patients or their families. Recent work has shown the importance of immunothrombosis, particularly in the prognosis for patients admitted to the intensive care unit with sepsis. Significantly some of the most impactful markers are actually decreased. In this perspective we summarize the current sepsis biomarker literature, highlight the limitations, particularly in diagnosis, and suggest some strategies for moving this field forward.

PSGL-1, ADAM8, and selectins as potential biomarkers in the diagnostic process of systemic lupus erythematosus and systemic sclerosis: an observational study.

Early diagnosis and treatment of Systemic lupus erythematosus (SLE) and Systemic sclerosis (SSc) present significant challenges for clinicians. Although various studies have observed changes in serum levels of selectins between healthy donors and patients with autoimmune diseases, including SLE and SSc, their potential as biomarkers has not been thoroughly explored. We aimed to investigate serum profiles of PSGL-1 (sPSGL-1), ADAM8 (sADAM8) and P-, E- and L-selectins (sP-, sE- and sL-selectins) in defined SLE and SSc patient cohorts to identify disease-associated molecular patterns. We collected blood samples from 64 SLE patients, 58 SSc patients, and 81 healthy donors (HD). Levels of sPSGL-1, sADAM8 and selectins were analyzed by ELISA and leukocyte membrane expression of L-selectin and ADAM8 by flow cytometry. Compared to HD, SLE and SSc patients exhibited elevated sE-selectin and reduced sL-selectin levels. Additionally, SLE patients exhibited elevated sPSGL-1 and sADAM8 levels. Compared to SSc, SLE patients had decreased sL-selectin and increased sADAM8 levels. Furthermore, L-selectin membrane expression was lower in SLE and SSc leukocytes than in HD leukocytes, and ADAM8 membrane expression was lower in SLE neutrophils compared to SSc neutrophils. These alterations associated with some clinical characteristics of each disease. Using logistic regression analysis, the sL-selectin/sADAM8 ratio in SLE, and a combination of sL-selectin/sE-selectin and sE-selectin/sPSGL-1 ratios in SSc were identified and cross-validated as potential serum markers to discriminate these patients from HD. Compared to available diagnostic biomarkers for each disease, both sL-selectin/sADAM8 ratio for SLE and combined ratios for SSc provided higher sensitivity (98% SLE and and 67% SSc correctly classified patients). Importantly, the sADAM8/% ADAM8(+) neutrophils ratio discriminated between SSc and SLE patients with the same sensitivity and specificity than current disease-specific biomarkers. SLE and SSc present specific profiles of sPSGL-1, sE-, sL-selectins, sADAM8 and neutrophil membrane expression which are potentially relevant to their pathogenesis and might aid in their early diagnosis.

Strategies for translating proteomics discoveries into drug discovery for dementia.

Tauopathies, diseases characterized by neuropathological aggregates of tau including Alzheimer's disease and subtypes of frontotemporal dementia, make up the vast majority of dementia cases. Although there have been recent developments in tauopathy biomarkers and disease-modifying treatments, ongoing progress is required to ensure these are effective, economical, and accessible for the globally ageing population. As such, continued identification of new potential drug targets and biomarkers is critical. "Big data" studies, such as proteomics, can generate information on thousands of possible new targets for dementia diagnostics and therapeutics, but currently remain underutilized due to the lack of a clear process by which targets are selected for future drug development. In this review, we discuss current tauopathy biomarkers and therapeutics, and highlight areas in need of improvement, particularly when addressing the needs of frail, comorbid and cognitively impaired populations. We highlight biomarkers which have been developed from proteomic data, and outline possible future directions in this field. We propose new criteria by which potential targets in proteomics studies can be objectively ranked as favorable for drug development, and demonstrate its application to our group's recent tau interactome dataset as an example.