Relevant Biomarkers Research Articles

PET Study of Microglial Activation in Kleine-Levin Syndrome.

Kleine-Levin syndrome (KLS) is a rare recurrent hypersomnolence disorder associated with cognitive and behavioral disturbances, of unknown origin, but inflammatory mechanisms could be involved. We aimed to explore in vivo microglia activation using [18F]DPA-714 PET imaging in patients with KLS compared with controls, and during symptomatic vs asymptomatic periods. Patients with KLS and controls underwent a standardized clinical evaluation and PET imaging, using a radiolabeled ligand specific to the 18 kDa translocator protein. Images were processed on the PMOD (peripheral module) interface using a standard uptake value (SUV). Five regions of interest (ROIs) were analyzed: hypothalamus, thalamus, frontal area, cerebellum, and whole brain. SUV ratios (SUVr) were calculated by normalizing SUV with cerebellum uptake. Images of 17 consecutive patients with KLS (7 during episodes, 10 out of episodes) and 14 controls were analyzed. We found no SUV/SUVr difference between KLS and controls, between patients in and out episodes in all ROIs, and no correlation between SUVr and episode duration at the time of PET scan. No association was found between SUVr and sex, disease duration, or orexin levels. Our findings do not support the presence of neuroinflammation in KLS. Further research is needed to identify relevant biomarkers in KLS.

Enhancing Breast Cancer Subtype Classification through GediNET: Integrating Disease- Disease Association Data with a Grouping-Scoring-Modeling Approach

The development of sequencing technology and the increase in biological data repositories have allowed for a more thorough understanding of the complex molecular aspects of diseases like cancer. This paper evaluates GediNET, an integrative machine learning approach that employs a Grouping-Scoring-Modeling (GSM) approach to classify different molecular subtypes of breast cancer using the BRCA LumAB_Her2Basal dataset against different feature selection approaches and machine learning classifiers. GediNET distinguishes itself from traditional feature selection methods by analyzing groups of genes to identify relevant disease-disease associations and potential biomarkers. The results of our study show that GediNET performs better than traditional approaches in terms of accuracy and Area Under the Curve (AUC) metrics. This demonstrates that GediNET is effective in understanding the genetic intricacies of breast cancer. This approach improves the identification of molecular subtypes and promotes the development of targeted medicines and customized medicine.

Haemostatic Gene Expression in Cancer-Related Immunothrombosis: Contribution for Venous Thromboembolism and Ovarian Tumour Behaviour.

Ovarian cancer (OC) is the deadliest gynaecological malignancy. Identifying new prognostic biomarkers is an important research field. Haemostatic components together with leukocytes can drive cancer progression while increasing the susceptibility to venous thromboembolism (VTE) through immunothrombosis. Unravelling the underlying complex interactions offers the prospect of uncovering relevant OC prognostic biomarkers, predictors of cancer-associated thrombosis (CAT), and even potential targets for cancer therapy. Thus, this study evaluated the expression of F3, F5, F8, F13A1, TFPI1, and THBD in peripheral blood cells (PBCs) of 52 OC patients. Those with VTE after tumour diagnosis had a worse overall survival (OS) compared to their counterparts (mean OS of 13.8 ± 4.1 months and 47.9 ± 5.7 months, respectively; log-rank test, p = 0.001). Low pre-chemotherapy F3 and F8 expression levels were associated with a higher susceptibility for OC-related VTE after tumour diagnosis (χ2, p < 0.05). Regardless of thrombogenesis, patients with low baseline F8 expression had a shorter progression-free survival (PFS) than their counterparts (adjusted hazard ratio (aHR) = 2.54; p = 0.021). Among those who were not under platelet anti-aggregation therapy, low F8 levels were also associated with a shorter OS (aHR = 6.16; p = 0.006). Moving forward, efforts should focus on external validation in larger cohorts.

Time-course cross-species transcriptomics reveals conserved hepatotoxicity pathways induced by repeated administration of cyclosporine A

Cyclosporine A (CsA) has shown efficacy against immunity-related diseases despite its toxicity in various organs, including the liver, emphasizing the need to elucidate its underlying hepatotoxicity mechanism. This study aimed to capture the alterations in genome-wide expression over time and the subsequent perturbations of corresponding pathways across species. Six data from humans, mice, and rats, including animal liver tissue, human liver microtissues, and two liver cell lines exposed to CsA toxic dose, were used. The microtissue exposed to CsA for 10 d was analyzed to obtain dynamically differentially expressed genes (DEGs). Single-time points data at 1, 3, 5, 7, and 28 d of different species were used to provide additional evidence. Using liver microtissue-based longitudinal design, DEGs that were consistently up- or down-regulated over time were captured, and the well-known mechanism involved in CsA toxicity was elucidated. Thirty DEGs that consistently changed in longitudinal data were also altered in 28-d rat in-house data with concordant expression. Some genes (e.g. TUBB2A, PLIN2, APOB) showed good concordance with identified DEGs in 1-d and 7-d mouse data. Pathway analysis revealed up-regulations of protein processing, asparagine N-linked glycosylation, and cargo concentration in the endoplasmic reticulum. Furthermore, the down-regulations of pathways related to biological oxidations and metabolite and lipid metabolism were elucidated. These pathways were also enriched in single-time-point data and conserved across species, implying their biological significance and generalizability. Overall, the human organoids-based longitudinal design coupled with cross-species validation provides temporal molecular change tracking, aiding mechanistic elucidation and biologically relevant biomarker discovery.

NOTCH1 fusions in pediatric T-cell lymphoblastic lymphoma: Ahigh-risk subgroup with CCL17 (TARC) levels as diagnostic biomarker.

Twenty percent of children with T-cell lymphoblastic lymphoma (T-LBL) will relapse and have an extremely poor outcome. Currently, we can identify a genetically low-risk subgroup in pediatric T-LBL, yet these high-risk patients who need intensified or alternative treatment options remain undetected. Therefore, there is an urgent need to recognize these high-risk T-LBL patients through identification of molecular characteristics and biomarkers. By using RNA sequencing which was performed in 29/49 T-LBL patients who were diagnosed in the Princess Maxima Center for Pediatric Oncology between 2018 and 2023, we discovered a previously unknown high-risk biological subgroup of children with T-LBL. This subgroup is characterized by NOTCH1 gene fusions, found in 21% of our T-LBL cohort (6/29). All patients presented with a large mediastinal mass, pleural/pericardial effusions, and absence of blasts in the bone marrow, blood, and central nervous system. Blood CCL17 (C-C Motif Chemokine Ligand 17, TARC) levels were measured at diagnosis in 26/29 patients, and all six patients with NOTCH1 gene fusions patients exclusively expressed highly elevated blood CCL17 levels, defining a novel and previously not known clinically relevant biomarker for T-cell lymphoblastic lymphoma. Four out of these six patients relapsed during therapy, a fifth developed a therapy-related acute myeloid leukemia during maintenance therapy. These data indicate that T-LBL patients with a NOTCH1 fusion have a high risk of relapse which can be easily identified using a blood CCL17 screening at diagnosis. Further molecular characterization through NOTCH1 gene fusion analysis offers these patients the opportunity for treatment intensification or new treatment strategies.

Sarcopenia-related changes in serum GLP-1 level affect myogenic differentiation.

Sarcopenia, a group of muscle-related disorders, leads to the gradual decline and weakening of skeletal muscle over time. Recognizing the pivotal role of gastrointestinal conditions in maintaining metabolic homeostasis within skeletal muscle, we hypothesize that the effectiveness of the myogenic programme is influenced by the levels of gastrointestinal hormones in the bloodstream, and this connection is associated with the onset of sarcopenia. We first categorized 145 individuals from the Emergency Room of Taipei Veterans General Hospital into sarcopenia and non-sarcopenia groups, following the criteria established by the Asian Working Group for Sarcopenia. A thorough examination of specific gastrointestinal hormone levels in plasma was conducted to identify the one most closely associated with sarcopenia. Techniques, including immunofluorescence, western blotting, glucose uptake assays, seahorse real-time cell metabolic analysis, flow cytometry analysis, kinesin-1 activity assays and qPCR analysis, were applied to investigate its impacts and mechanisms on myogenic differentiation. Individuals in the sarcopenia group exhibited elevated plasma levels of glucagon-like peptide 1 (GLP-1) at 1021.5±313.5pg/mL, in contrast to non-sarcopenic individuals with levels at 351.1±39.0pg/mL (P<0.05). Although it is typical for GLP-1 levels to rise post-meal and subsequently drop naturally, detecting higher GLP-1 levels in starving individuals with sarcopenia raised the possibility of GLP-1 influencing myogenic differentiation in skeletal muscle. Further investigation using a cell model revealed that GLP-1 (1, 10 and 100ng/mL) dose-dependently suppressed the expression of the myogenic marker, impeding myocyte fusion and the formation of polarized myotubes during differentiation. GLP-1 significantly inhibited the activity of the microtubule motor kinesin-1, interfering with the translocation of glucose transporter 4 (GLUT4) to the cell membrane and the dispersion of mitochondria. These impairments subsequently led to a reduction in glucose uptake to 0.81±0.04 fold (P<0.01) and mitochondrial adenosine triphosphate (ATP) production from 25.24±1.57pmol/min to 18.83±1.11pmol/min (P<0.05). Continuous exposure to GLP-1, even under insulin induction, attenuated the elevated glucose uptake. The elevated GLP-1 levels observed in individuals with sarcopenia are associated with a reduction in myogenic differentiation. The impact of GLP-1 on both the membrane translocation of GLUT4 and the dispersion of mitochondria significantly hinders glucose uptake and the production of mitochondrial ATP necessary for the myogenic programme. These findings point us towards strategies to establish the muscle-gut axis, particularly in the context of sarcopenia. Additionally, these results present the potential of identifying relevant diagnostic biomarkers.

Systemic Therapy for Metastatic Colon Cancer: New Frontiers

AbstractWe have made steady gains in improving overall survival in patients with metastatic, unresectable, colon cancer in the last 5 to 10 years. The backbone of systemic treatment for most patients remains combination chemotherapy, but the field is becoming increasingly biomarker driven, with exciting new targeted therapies on the horizon. This review is organized in sections corresponding to currently relevant biomarkers in colon cancer and will summarize first-, second-, and third-line standard of care for metastatic, unresectable, colon cancer. The last section is intended to introduce the reader to promising agents and novel therapeutic strategies currently under investigation.

Salivary Histamine Levels in Patients with Oral Lichen Planus Lesions.

Background and Objectives: An oral lichen planus (OLP) chronic lesion refers to a group of oral potentially malignant disorders (OPMDs) that still lack a proper understanding from the point of view of relevant biomarkers for diagnostics and prognosis. The aim of the study was to assess the salivary histamine levels in patients with oral lichen planus lesions. Materials and Methods: The study included a group of 76 patients with oral lichen planus. General diseases and medication taken, smoking habits, severity of pain assessed using a visual analogue scale (VAS), oral hygiene status, and duration of OLP were evaluated. ELISA diagnostics for histamines in saliva levels were assessed. Results: The histamine levels in the OLP group were higher (0.468) in comparison with the control group (0.056), without a statistically significant value p = 0.090 (Mann-Whitney U Test). The median age of 76 OLP patients was 63 years (min 22.0-max. 81), with the biological sex being 80.3% females and 15 19.7% males. The average duration of OLP lesion presence was 29.4 months (SD 37.1) and the median value was 14.5 months. The median of the VAS was 3.0. OLP assessment in accordance with the Malhotra methodology showed the highest frequency-30.3% for only two of the point areas involved and 17.1% for three points. Clinical assessment of the different OLP grades, severity, and oral site involvement and the VAS in correlation with histamine salivary levels showed a lack of statistical significance in the investigated population. Conclusions: Undertaking further research could provide further possibilities for searching for general factors in OLP development.

Cholesterol profiling reveals 7β-hydroxycholesterol as a pathologically relevant peripheral biomarker of Alzheimer's disease.

Cholesterol homeostasis is associated with Alzheimer's disease (AD). Despite the multitude of cholesterol metabolites, little is known about which metabolites are directly involved in AD pathogenesis and can serve as its potential biomarkers. To identify "hit" metabolites, steroid profiling was conducted in mice with different age, diet, and genotype and also in humans with normal cognition, mild cognitive impairment, and AD using gas chromatography-mass spectrometry. Then, using one of the "hit" molecules (7β-hydroxycholesterol; OHC), molecular and histopathological experiment and behavioral testing were conducted in normal mice following its intracranial stereotaxic injection to see whether this molecule drives AD pathogenesis and causes cognitive impairment. The serum levels of several metabolites, including 7β-OHC, were increased by aging in the 3xTg-AD unlike normal mice. Consistently, the levels of 7β-OHC were increased in the hairs of patients with AD and were correlated with clinical severity. We found that 7β-OHC directly affects AD-related pathophysiology; intrahippocampal injection of 7β-OHC induced astrocyte and microglial cell activation, increased the levels of pro-inflammatory cytokines (TNF-alpha, IL-1β, IL-6), and enhanced amyloidogenic pathway. Mice treated with 7β-OHC also exhibited deficits in memory and frontal/executive functions assessed by object recognition and 5-choice serial reaction time task, respectively. Our results suggest that 7β-OHC could serve as a convenient, peripheral biomarker of AD. As directly involved in AD pathogenesis, 7β-OHC assay may help actualize personalized medicine in a way to identify an at-risk subgroup as a candidate population for statin-based AD treatment.

Heart rate variability modulates memory function in a virtual task

Heart rate variability (HRV) is considered one of the most relevant indicators of physical well-being and relevant biomarker for preventing cardiovascular risks. More recently, a growing amount of research has tracked an association between HRV and cognitive functions (i.e., attention). Research is still scarce on spatial orientation, a basic capability in our daily lives. It is also an important indicator of memory performance, and its malfunctioning working as an early sign of dementia. In this study, a total of 43 female students (M Age = 18.76; SD = 2.02) were measured in their lnRMSSD using the photoplethysmography technique with the Welltory smartphone app. They were also tested in their spatial memory with The Boxes Room, a virtual navigation test. Measures of physical activity were obtained with the International Physical Activity Questionnaire (IPAQ). Correlation analyses and repeated measures ANOVA were performed, comparing participants with high / low lnRMSSD in their spatial performance. Results showed that, at an equal level of physical activity, participants with a higher lnRMSSD were more effective in the early trials of The Boxes Room, being more precise in estimating the correct position of the stimuli. Moreover, a subsequent simple linear regression showed that a higher lnRMSSD was related to a smaller number of errors at the beginning of the spatial task. Overly, these results outline the relationship between HRV and navigation performance in early stages of processing, where the environment is still unknown and the situation is more demanding.

Evaluation of machine learning-based classification of clinical impairment and prediction of clinical worsening in multiple sclerosis

BackgroundRobust predictive models of clinical impairment and worsening in multiple sclerosis (MS) are needed to identify patients at risk and optimize treatment strategies.ObjectiveTo evaluate whether machine learning (ML) methods can classify clinical impairment and predict worsening in people with MS (pwMS) and, if so, which combination of clinical and magnetic resonance imaging (MRI) features and ML algorithm is optimal.MethodsWe used baseline clinical and structural MRI data from two MS cohorts (Berlin: n = 125, Amsterdam: n = 330) to evaluate the capability of five ML models in classifying clinical impairment at baseline and predicting future clinical worsening over a follow-up of 2 and 5 years. Clinical worsening was defined by increases in the Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk Test (T25FW), 9-Hole Peg Test (9HPT), or Symbol Digit Modalities Test (SDMT). Different combinations of clinical and volumetric MRI measures were systematically assessed in predicting clinical outcomes. ML models were evaluated using Monte Carlo cross-validation, area under the curve (AUC), and permutation testing to assess significance.ResultsThe ML models significantly determined clinical impairment at baseline for the Amsterdam cohort, but did not reach significance for predicting clinical worsening over a follow-up of 2 and 5 years. High disability (EDSS ≥ 4) was best determined by a support vector machine (SVM) classifier using clinical and global MRI volumes (AUC = 0.83 ± 0.07, p = 0.015). Impaired cognition (SDMT Z-score ≤ −1.5) was best determined by a SVM using regional MRI volumes (thalamus, ventricles, lesions, and hippocampus), reaching an AUC of 0.73 ± 0.04 (p = 0.008).ConclusionML models could aid in classifying pwMS with clinical impairment and identify relevant biomarkers, but prediction of clinical worsening is an unmet need.

Metabolomics Analysis of Rabbit Plasma after Ocular Exposure to Vapors of Sulfur Mustard.

Sulfur mustard (SM) is a highly potent alkylating vesicant agent and remains a relevant threat to both civilians and military personnel. The eyes are the most sensitive organ after airborne SM exposure, causing ocular injuries with no antidote or specific therapeutics available. In order to identify relevant biomarkers and to obtain a deeper understanding of the underlying biochemical events, we performed an untargeted metabolomics analysis using liquid chromatography coupled to high-resolution mass spectrometry of plasma samples from New Zealand white rabbits ocularly exposed to vapors of SM. Metabolic profiles (332 unique metabolites) from SM-exposed (n = 16) and unexposed rabbits (n = 8) were compared at different time intervals from 1 to 28 days. The observed time-dependent changes in metabolic profiles highlighted the profound dysregulation of the sulfur amino acids, the phenylalanine, the tyrosine and tryptophan pathway, and the polyamine and purine biosynthesis, which could reflect antioxidant and anti-inflammatory activities. Taurine and 3,4-dihydroxy-phenylalanine (Dopa) seem to be specifically related to SM exposure and correspond well with the different phases of ocular damage, while the dysregulation of adenosine, polyamines, and acylcarnitines might be related to ocular neovascularization. Additionally, neither cysteine, N-acetylcysteine, or guanine SM adducts were detected in the plasma of exposed rabbits at any time point. Overall, our study provides an unprecedented view of the plasma metabolic changes post-SM ocular exposure, which may open up the development of potential new treatment strategies.

Current Insights in Murine Models for Breast Cancer: Present, Past and Future.

Breast cancer is an intricate disease that is increasing at a fast pace, and numerous heterogeneities within it further make it difficult to investigate. We have always used animal models to understand cancer pathology and create an in vivo microenvironment that closely resembles human cancer. They are considered an indispensable part of any clinical investigation regarding cancer. Animal models have a high potency in identifying the relevant biomarkers and genetic pathways involved in the course of disease prognosis. Researchers have previously explored a variety of organisms, including Drosophila melanogaster, zebrafish, and guinea pigs, to analyse breast cancer, but murine models have proven the most comprehensive due to their homologous nature with human chromosomes, easy availability, simple gene editing, and high adaptability. The available models have their pros and cons, and it depends on the researcher to select the one most relevant to their research question. Chemically induced models are cost-effective and simple to create. Transplantation models such as allografts and xenografts can mimic the human breast cancer environment reliably. Genetically engineered mouse models (GEMMs) help to underpin the genetic alterations involved and test novel immunotherapies. Virus-mediated models and gene knockout models have also provided new findings regarding breast cancer progression and metastasis. These mouse models have also enabled the visualization of breast cancer metastases. It is also imperative to consider the cost-effectiveness of these models. Despite loopholes, mouse models have evolved and are required for disease analysis.

Abstract PO-016: Test-the-test: Clinical utility of comprehensive whole exome sequencing (WES) and RNA-seq for lymphoma patients

Abstract Due to the rapidly evolving landscape of targeted therapies, there is an unmet need for comprehensive molecular profiling to guide treatment decisions for lymphoma patients. Here, we designed a pilot study to assess the feasibility and turnaround time (TAT) of a comprehensive clinical whole exome sequencing (WES) and transcriptome sequencing (RNA-seq) assay in large B-cell lymphoma (LBCL) patients for clinical decision-making (NCT05464823). Patients aged ≥18 years with histologically documented LBCL requiring therapy were eligible. Formalin-fixed paraffin-embedded tissues underwent WES, RNA-seq, and copy number analysis with concomitant peripheral blood or saliva for germline DNA sequencing. Samples with &amp;lt;20% tumor purity and median coverage of &amp;lt;142x for tumor and/or &amp;lt;95x for normal samples were labeled as quantity not sufficient (QNS). Genomic and transcriptomic data were profiled to uncover clinically relevant biomarkers and match patients with clinical trials on ClinicalTrials.gov. Among 84 patients analyzed to date, 71 received WES and RNA-seq, yielding 67 reports with clinical information (treatment options and clinical trial matching) and 4 QNS reports without actionable findings. The remaining 13 samples were rejected as they failed pathology quality control for next-generation sequencing. Cell of origin (COO, n=62), LymphGen (n=62), and lymphoma microenvironment (LME, n=64) classifications were applied. The median TAT was 8 days for custom reports, and 70.4% of custom reports had a TAT ≤10 days. WES identified frequent TP53 (n=22) and MYD88 (n=11) alterations. COOs were designated as activated (n=26, 41.94%) or germinal center (n=36, 58.06%) LBCL. The LymphGen classifier (Wright et al. Cancer Cell. 2020) showed subtypes EZB MYC- (n=10, 16.13%), MCD (n=8, 12.9%), and A53 (n=6, 11.5%) as the most prevalent. LME classification revealed most LMEs as mesenchymal (n=46, 71.88%). Immune-depleted (n=12, 18.75%), immune-inflamed (n=4, 6.25%), and germinal center-like (n=2, 3.13%) LMEs were less prevalent, but the immune-depleted LME was more common in patients with relapse. Clinically significant findings, such as activated COO subtype (n=27), TP53 loss (n=21), DHITsig+ (n=9), and CARD11 mutations associated with ibrutinib resistance (n=3), were identified in 52 samples. On average, 8 clinical trials were identified per full report. Our results show the clinical utility and acceptable TAT of using a comprehensive WES and RNA-seq assay on a cohort of lymphoma patients. The full test reports included findings on significant alterations, LymphGen and LME subtypes, COOs, treatment options, and clinical trial matches. These robust findings, coupled with rapid TAT, demonstrate the feasibility of using integrated WES and RNA-seq to guide clinical decision-making for lymphoma patients. Citation Format: Dai Chihara, Kumudha Balakrishnan, Gita Masand, Anna Novokreshchenova, Alexander Bagaev, Nikita Kotlov, Ekaterina Postovalova, Eduardo Shugaev-Mendosa, Yuliya Gracheva, Kelley Lauziere, Leznath Kaneunyenye, Brianna McKenna, Amber Berlinski, McKenna Walsh, Linnea Larson, Mariam Kotsinyan, Sheila T Yong, Krystle Nomie, Nathan Fowler, Christopher R. Flowers, Jason Westin. Test-the-test: Clinical utility of comprehensive whole exome sequencing (WES) and RNA-seq for lymphoma patients [abstract]. In: Proceedings of the Fourth AACR International Meeting on Advances in Malignant Lymphoma: Maximizing the Basic-Translational Interface for Clinical Application; 2024 Jun 19-22; Philadelphia, PA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(3_Suppl):Abstract nr PO-016.

The role of urine chloride in acute heart failure

In our retrospective study, we aimed to investigate the relationship between urinary chloride (uCl−) and selected clinical and laboratory biomarkers, renal function, and patient outcomes in the acute heart failure (AHF) population. We divided 248 adult patients (≥ 18 years) with AHF into two groups: low uCl− (< 115 mmol/L) and high uCl−. The mean age of the patient group was 70.2 ± 12.6, and 182 patients were male (73.4%). Clinical endpoints included in-hospital mortality, one-year mortality, and a composite endpoint of one-year mortality and rehospitalization for heart failure. Patients were followed up for at least one year. Relevant clinical and baseline biomarker data were collected, including markers concerning inflammation, liver and kidney function, perfusion and congestion, iron status, cardiac remodeling, gasometry, renin and aldosterone. Low uCl− was associated with worse in-hospital outcomes, including higher in-hospital mortality (7.7% vs. 1.4%, p = 0.014), the need for inotropic support (20.19% vs. 2.08%, p ≤ 0.001), worsening of HF during therapy (17.31% vs. 4.86%, p ≤ 0.001), and the need for treatment in an intensive cardiac care unit (33.65% vs. 15.28%, p ≤ 0.001). Low uCl− was a significant predictor of one-year mortality (40.4% vs. 16.7%, p < 0.05) and the composite outcome (HR 2.42, 95% CI 1.43–4.08, p < 0.001). In the multivariable analysis, uCl− was independently associated with the risk of one-year mortality (HR 0.92, 95% CI 0.87–0.98, p < 0.05) and the composite outcome (HR 0.95, 95% CI 0.92–0.99, p < 0.05). Our findings suggest that low uCl− is a marker of more advanced heart failure, activation of the renin–angiotensin–aldosterone system and is related to worse one-year outcomes.

Wearable Aptalyzer Integrates Microneedle and Electrochemical Sensing for In Vivo Monitoring of Glucose and Lactate in Live Animals.

Continuous monitoring of clinically relevant biomarkers within the interstitial fluid (ISF) using microneedle (MN)-based assays, has the potential to transform healthcare. This study introduces the Wearable Aptalyzer, an integrated system fabricated by combining biocompatible hydrogel MN arrays for ISF extraction with an electrochemical aptamer-based biosensor for in situ monitoring of blood analytes. The use of aptamers enables continuous monitoring of a wide range of analytes, beyond what is possible with enzymatic monitoring. The Wearable Aptalyzer is used for real-time and multiplexed monitoring of glucose and lactate in ISF. Validation experiments using live mice and rat models of type 1 diabetes demonstrate strong correlation between the measurements collected from the Wearable Aptalyzer in ISF and those obtained from gold-standard techniques for blood glucose and lactate, for each analyte alone and in combination. The Wearable Aptalyzer effectively addresses the limitations inherent in enzymatic detection methods as well as solid MN biosensors and the need for reliable and multiplexed bioanalytical monitoring in vivo.

NFC Smartphone-Based Electrochemical Microfluidic Device Integrated with Nanobody Recognition for C-Reactive Protein.

Point-of-care testing (POCT) devices play a crucial role as tools for disease diagnostics, and the integration of biorecognition elements with electronic components into these devices widens their functionalities and facilitates the development of complex quantitative assays. Unfortunately, biosensors that exploit large conventional IgG antibodies to capture relevant biomarkers are often limited in terms of sensitivity, selectivity, and storage stability, considerably restricting the use of POCT in real-world applications. Therefore, we used nanobodies as they are more suitable for fabricating electrochemical biosensors with near-field communication (NFC) technology. Moreover, a flow-through microfluidic device was implemented in this system for the detection of C-reactive protein (CRP), an inflammation biomarker, and a model analyte. The resulting sensors not only have high sensitivity and portability but also retain automated sequential flow properties through capillary transport without the need for an external pump. We also compared the accuracy of CRP quantitative analyses between commercial PalmSens4 and NFC-based potentiostats. Furthermore, the sensor reliability was evaluated using three biological samples (artificial serum, plasma, and whole blood without any pretreatment). This platform will streamline the development of POCT devices by combining operational simplicity, low cost, fast analysis, and portability.

Optofluidic photonic crystal fiber platform for sensitive and reliable fluorescence based biosensing.

Biosensing plays a pivotal role in various scientific domains, offering significant contributions to medical diagnostics, environmental monitoring, and biotechnology. Fluorescence biosensing relies on the fluorescence emission from labelled biomolecules to enable sensitive and selective identification and quantification of specific biological targets in various samples. Photonic crystal fibers (PCFs) have led to the development of optofluidic fibers enabling efficient light-liquid interaction within small liquid volume. Herein, we present the development of a user-friendly optofluidic-fiber platform with simple hardware requirements for sensitive and reliable fluorescence biosensing with high measurement repeatability. We demonstrate a sensitivity improvement of the fluorescence emission up to 17 times compared to standard cuvette measurement, with a limit of detection of Cy5 fluorophore as low as 100 pM. The improvement in measurement repeatability is exploited for detecting haptoglobin protein, a relevant biomarker to diagnose several diseases, by using commercially available Cy5 labelled antibodies. The study aims to showcase an optofluidic platform leveraging the benefits provided by optofluidic fibers, which encompass easy light injection, robustness, and high sensitivity.

Upconversion Nanoparticle-Based Dot-Blot Immunoassay for Quantitative Biomarker Detection.

Dot-blot immunoassays are widely used for the user-friendly detection of clinical biomarkers. However, the majority of dot-blot assays have only limited sensitivity and are only used for qualitative or semiquantitative analysis. To overcome this limitation, we have employed labels based on photon-upconversion nanoparticles (UCNPs) that exhibit anti-Stokes luminescence and can be detected without optical background interference. First, the dot-blot immunoassay on a nitrocellulose membrane was optimized for the quantitative analysis of human serum albumin (HSA), resulting in a limit of detection (LOD) of 0.19 ng/mL and a signal-to-background ratio (S/B) of 722. Commercial quantum dots were used as a reference label, reaching the LOD of 4.32 ng/mL and the S/B of 3, clearly indicating the advantages of UCNPs. In addition, the potential of UCNP-based dot-blot for real sample analysis was confirmed by analyzing spiked urine samples, reaching the LOD of 0.24 ng/mL and recovery rates from 79 to 123%. Furthermore, we demonstrated the versatility and robustness of the assay by adapting it to the detection of two other clinically relevant biomarkers, prostate-specific antigen (PSA) and cardiac troponin (cTn), reaching the LODs in spiked serum of 9.4 pg/mL and 0.62 ng/mL for PSA and cTn, respectively. Finally, clinical samples of patients examined for prostate cancer were analyzed, achieving a strong correlation with the reference electrochemiluminescence immunoassay (recovery rates from 89 to 117%). The achieved results demonstrate that UCNPs are highly sensitive labels that enable the development of dot-blot immunoassays for quantitative analysis of low-abundance biomarkers.

Multiplexed Profiling of CDK Kinase Activities in Tumor Biopsies with Fluorescent Peptide Biosensors.

Detection of disease biomarkers constitutes a major challenge for the development of personalized and predictive diagnostics as well as companion assays. Protein kinases (PKs) involved in the coordination of cell cycle progression and proliferation that are hyperactivated in human cancers constitute attractive pharmacological targets and relevant biomarkers. Although it is relatively straightforward to assess the relative abundance of PKs in a biological sample, there is not always a direct correlation with enzymatic activity, which is regulated by several posttranslational mechanisms. Studies of relative abundance therefore convey limited information, and the lack of selective, sensitive, and standardized tools together with the inherent complexity of biological samples makes it difficult to quantify PK activities in physio-pathological tissues. To address this challenge, we have developed a toolbox of fluorescent biosensors that report on CDK activities in a sensitive, selective, dose-dependent, and quantitative fashion, which we have implemented to profile CDK activity signatures in cancer cell lines and biopsies from human tumors. In this study, we report on a standardized and calibrated biosensing approach to quantify CDK1,2,4, and 6 activities simultaneously through a combination of four different biosensors in a panel of 40 lung adenocarcinoma and 40 follicular lymphoma samples. CDK activity profiling highlighted two major patterns which were further correlated with age, sex of patients, tumor size, grade, and genetic and immunohistochemical features of the biopsies. Multiplex CDKACT biosensing technology provides new and complementary information relative to current genetic and immunohistochemical characterization of tumor biopsies, which will be useful for diagnostic purposes, potentially guiding therapeutic decision. These fluorescent peptide biosensors offer promise for personalized diagnostics based on kinase activity profiling.