Complementary Biomarkers Research Articles

Identification and characterization of tumor and stromal derived liquid biopsy analytes in pancreatic ductal adenocarcinoma

BackgroundThe lack of predictive biomarkers contributes notably to the poor outcomes of patients with pancreatic ductal adenocarcinoma (PDAC). Cancer-associated fibroblasts (CAFs) are the key components of the prominent PDAC stroma. Data on clinical relevance of CAFs entering the bloodstream, known as circulating CAFs (cCAFs) are scarce. Here, we developed a combined liquid biopsy assay to detect cCAFs and circulating tumor cells (CTCs) in metastatic PDAC (mPDAC) and other metastatic gastrointestinal malignancies (mGI). In addition, we evaluated plasma hyaluronan (HA) levels as a complementary surrogate biomarker of the stromal extent in patients with PDAC.MethodsA sequential liquid biopsy assay based on a two step-enrichment, combining marker dependent and independent cell enrichment, was established for cCAF and CTC detection and validated in mPDAC and mGI patients. The enriched cells were identified by multiplex immunofluorescence. HA measurement was performed by ELISA on blood samples from healthy blood donors (HD), localized and late-stage PDAC patients.ResultscCAFs (≥ 1cCAFs/7.5 mL blood) were detected in 95.4% of mPDAC and in 78.2% of mGI patients, with significantly higher numbers in mPDAC compared to mGI patients (mean number 22.7 vs. 11.0; P = 0.0318). mPDAC patients with ≥ 15 cCAFs/7.5 mL blood had a significant shorter median overall survival (mOS 3.2 months (95% confidence interval (CI) 0.801–5.855) vs. 14.2 months (95% CI 6.055–22.332); P = 0.013), whereby CTC levels were not associated with mOS. In mGI neither cCAFs nor CTCs had a significant impact on OS. HA plasma levels in mPDAC patients were significantly higher compared to HD (mean 123.0 ng/mL vs. 74.45 ng/mL, P = 0.015). High HA in localized and late-stage PDAC were associated with a significantly shorter mOS (mOSlocalized PDAC: 12.6 months vs. 23.5 months (P = 0.008); mOSmPDAC: 1.8 months vs. 5.3 months (P = 0.004)).ConclusionsOur liquid biopsy assay provides robust detection of cCAFs in mPDAC and mGI patients. The measurement of both circulatory stromal parameters, cCAFs and HA, adds valuable clinical information as they are associated with an unfavorable outcome in PDAC. These results highlight that stromal characteristics unique to PDAC could be leveraged to fill the current gap in discovering predictive biomarkers.

CCL3 as a novel biomarker in the diagnosis of necrotizing enterocolitis

ObjectivesNeonatal necrotizing enterocolitis (NEC) is a common intestinal disease that threatens the lives of newborns and is characterized by ischemic necrosis of the small intestine and colon. As early diagnosis of NEC improves prognosis, the identification of new or complementary biomarkers is of great importance. In this study, we evaluate the diagnostic value of CCL3 in NEC and compare its effectiveness with other commonly used biomarkers, such as procalcitonin (PCT) and C-reactive protein (CRP).Participants and designSerum samples were collected from 64 patients with NEC and 38 jaundice neonatal controls. Before initiating therapy, blood samples for the whole blood count, CRP, PCT and CCL3 were obtained from all neonates. Receiver operating characteristic (ROC) curve and multivariate logistic regression analyses were performed.SettingDepartment of Clinical Laboratory, Children’s Hospital of Chongqing Medical University.ResultsThe serum CCL3 level of the NEC group was significantly higher than that of the Control group. The ROC area under the curve (AUC) was 0.8614 (95%confidence interval (CI) 0.7863–0.936; p < 0.0001) for CCL3, 0.8534 (95% CI 0.7682–0.9386; p < 0.0001) for PCT, 0.675 (95% CI 0.5625–0.788; p < 0.0001) for CRP, 0.579 (95% CI 0.4402–0.7188 p = 0.2460) for WBC, and 0.7384 (95% CI 0.6215–0.8554 p = 0.0005) for PLT. With a cut-off value of 83.33 ng/ml, the diagnostic sensitivity and negative predictive value of CCL3 were 83.33% and 80.55%, respectively. The combined use of CCL3 and PCT could significantly improve diagnostic performance for NEC (0.903; 95% CI 0.810–0.960; p < 0.0001).ConclusionsCCL3 may be used as a promising biomarker for the diagnosis of NEC, and the combined use of CCL3 and PCT could improve the diagnosis of NEC.

Systemic immune-inflammation index and long-term mortality in patients with hypertension: a cohort study.

The objective of this study was to examine the relationship between systemic inflammation and long-term mortality in patients with hypertension. The study employed a retrospective cohort design. The study population was derived from the National Health and Nutrition Examination Survey (NHANES), and the mortality data for this population was acquired from the National Death Index (NDI) database. Systemic inflammation was quantified by the Systemic Immune Inflammation Index (SII) and the Systemic Inflammatory Response Index (SIRI), which were then categorized into four groups (Q1-Q4, with Q4 representing the highest level of SII or SIRI). Weighted Cox regression models were constructed to investigate the association between mortality and SII and SIRI, with hazard ratios (HRs) subsequently calculated. A total of 7431 participants were included in the analysis. The highest quantile (Q4) of SII was associated with a higher risk of all-cause mortality (hazard ratio 1.36, 95% CI 1.1-1.69, P < 0.001). After adjustment for important covariates, the association remained significant (hazard ratio 1.70, 95% CI 1.27-2.30, P < 0.001). The highest quantile (Q4) of SIRI was also associated with the highest risk of mortality (hazard ratio 2.11, 95% CI 1.64-2.70, P < 0.001), and this association remained significant after adjustment for important covariates (hazard ratio 1.64, 95% CI 0.61-1.22, P = 0.001). Both SII and SIRI scores were found to be associated with mortality rates in patients with hypertension. The findings suggest that these scores may serve as complementary biomarkers to the neutrophil-to-lymphocyte ratio (NLR) for assessing mortality risk in patients with hypertension. Further investigation is warranted to elucidate the underlying mechanisms that underpin this association.

Developing biomarkers to estimate manure ammonia emissions from dairy cattle

Abstract This research aimed to develop biomarkers for estimating ammonia (NH3) emissions from dairy cattle manure over a 15-day in vitro incubation system. To generate different levels of NH3 emissions, the experiment utilized four manure experimental groups: 1 urinary nitrogen (U) to 1 faecal nitrogen (F) ratio (CT), 2 U to 1 F ratio (2U1F), and CT and 2U1F with lignite application (CT + L and 2U1F + L, respectively). The addition of lignite to ruminant manure aimed to enhance environmental sustainability through its beneficial properties. Three biomarkers, nitrogen (N) isotopic fractionation (δ15N), N: potassium (K) ratio, and N: phosphorus (P) ratio, were investigated. Manure δ15N increased linearly when NH3 emission increased in CT and 2U1F groups (R2 = 0.79 and 0.90, respectively; P ≤ 0.001), while manure N: P decreased when NH3 emission increased in CT + L and 2U1F + L groups (R2 = 0.73 and 0.85, respectively; P ≤ 0.001). No useful relationship was found between N: K and NH3 emission, apart from in 2U1F group (R2 = 0.84; P ≤ 0.001). The experiment found manure δ15N and N: P are complementary biomarkers to predict NH3 emissions, from non-lignite and lignite groups, respectively.

Predictive Biomarkers for the Early Detection of Anastomotic Leaks in Colorectal Surgeries: A Systematic Review.

Anastomotic leaks (ALs) remain a serious postoperative complication in colorectal surgery, often resulting in significant morbidity, prolonged hospitalization, and increased mortality risk. This systematic review aims to evaluate the role of predictive biomarkers in the early detection of ALs, focusing on their diagnostic accuracy and clinical utility. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive literature search was conducted across MEDLINE, Scopus, CENTRAL, and Web of Science, identifying studies that examined biomarkers such as C-reactive protein (CRP), procalcitonin (PCT), and white blood cell (WBC) count in the context of AL. A total of 20 studies met the inclusion criteria, with sample sizes ranging from 59 to 2,655 patients undergoing colorectal surgeries with primary anastomosis. CRP emerged as the most widely studied and reliable biomarker, with studies suggesting that elevated CRP levels, particularly on postoperative days 3-4, can effectively indicate AL risk, showing high negative predictive value. PCT has also shown promise as a complementary biomarker, offering enhanced specificity for infectious complications. Although WBC count alone was a limited predictor, it may add diagnostic value when used with other markers. In addition, innovative biomarkers, such as inflammatory indices in peritoneal fluid, demonstrated potential for further improving AL detection accuracy.

Performance evaluation of a CRISPR Cas9-based selective exponential amplification assay for the detection of KRAS mutations in plasma of patients with advanced pancreatic cancer

AimsPancreatic ductal adenocarcinoma (PDAC) is highly malignant, with shockingly mortality rates. KRAS oncoprotein is the main molecular target for PDAC. Liquid biopsies, such as the detection of circulating tumour DNA...

Abstract A010: Biofluid-Ensemble Analysis through Multi-modal Spectroscopy (BEAMS): A deep learning architecture for rapid early-stage liquid biopsy cancer diagnostics

Abstract Introduction: Head and neck cancer (HNC) is one of the most common cancer types globally without an accessible rapid screening method. Conventional screening occurs at the clinician’s office, where grading and staging of the tumors are physically performed, and the clinician’s preliminary diagnosis is usually confirmed through laborious procedures of histology and CT/PET/MR scans. Patient’s quality of life and expected outcomes can be improved through early-stage screening, yet there is no existing technology on the market that tackles this dire need. As such, we propose a rapid liquid biopsy diagnostic platform empowered by deep learning algorithms that makes early-stage non-invasive screening possible. The platform utilizes the complementary vibrational spectral biomarkers information from Fourier Transform Infrared Spectroscopy (FTIR) and Raman spectroscopy. We coupled the techniques with two biofluids: saliva and plasma, which offered information on circulating and localized metabolites. Materials and Methods: The patient’s biofluid is first drop-casted on top of a substrate and air-dried at room temperature. Using an FTIR microscope or a Raman microscope, 25 spot measurements are made in a 5 by 5 grid pattern to produce a comprehensive scan of the sample. The measured spectra are subsequently fed into the deep learning framework to perform classification. The deep machine learning framework is composed of spectrum and subject-level models. Specifically, the spectrum-level model employs cascading convolutional layers to identify the prominent features within the spectrum. This is followed by a sequence of linear layers that further extract features from the convolutional layers and carry out binary classification. For each patient, preliminary classification results of the spectral level model are then evaluated on a per- modality basis across our four modalities (FTIR/Raman measurements made on saliva/plasma) where the patient is classified as positive if any of the modality models deem it so. This framework is applied to a cohort of 96 patients, with 36 non-cancerous patients, 28 early-stage patients, and 32 late-stage patients. Results and Discussion: Our model optimized for general cancer detection has a sensitivity of 91.7%, specificity of 77.8%, and accuracy of 86.5%. Late- stage cancer has proven to be less challenging to detect since our model optimized for late-stage cancer diagnosis has a sensitivity of 93.8%, a specificity of 83.3%, and an accuracy of 88.2%. Our best early-stage model has a sensitivity of 89.3%, a specificity of 69.4%, and an accuracy of 78.1%. Conclusions: Our proposed framework has demonstrated promising capability as the preliminary screening method for high-risk patients (e.g. tobacco users) while providing further interpretability of the deep learning model that is often characterized as a “black box”. The modular nature of our model structure offers substantial flexibility, enabling effective performance even when specific biofluids or spectroscopy modalities are unavailable. Citation Format: Kwan Lun Chiu, Antonio Guillen-Perez, Rebecca Mayer, Wesley Viner, Hanna Koster, Matthew Benson, Jeremy Rowe, Maria Navas-Moreno, Andrew Birkeland, Maria-Dolores Cano, J. Sebastián Gomez-Diaz, Randy Carney. Biofluid-Ensemble Analysis through Multi-modal Spectroscopy (BEAMS): A deep learning architecture for rapid early-stage liquid biopsy cancer diagnostics [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A010.

Truncated Albumins as Novel Surrogate Biomarkers in Diabetes Therapy: Epiphenomena and Potential Clinical Applications.

Aims/Hypothesis: Among various albumin posttranslational modifications (PTMs), N- and C-terminal truncations (HSA-DA and HSA-L) have also shown biomarker potential in disease states. We examined albumin truncation longitudinal trends and correlations during diabetes therapy toward possible future clinical applications. Methods: In a preliminary longitudinal therapy investigation, mass spectrometry was employed to track PTMs of human serum albumin (HSA), including glycation (GA), cysteinylation (CA or HNA1; reversible), di/trioxidation (OA or HNA2; irreversible), and truncation (TA). These modifications were correlated with ongoing therapy in four distinct subject groups: type 1 diabetes (T1DM), type 2 diabetes (T2DM), prediabetes-obesity (PDOB), and healthy controls (NORM), observed over a follow-up period extending up to 280 days. Results: Diabetes was associated with significant reduction ("deficiency") of measured albumin truncations (For HSA-DA: T2DM = 0.32 ± 0.3%, p = 2E-08; T1DM = 1.02 ± 0.4%, p = 3E-05; PDOB = 1.61 ± 0.2%, p = 0.004; compared to NORM = 2.08 ± 0.2%). Albumin truncation reduction was more striking in T2DM (HSA-DA: T2DM vs. T1DM: p = 0.004). Improvements in glycemic control and decrease of albumin glycation during diabetes therapy were associated with concomitant increase of albumin truncations toward the "healthy" normal ranges, and vice versa ("mirror image" trends). Accordingly, albumin truncation correlated inversely with albumin glycation (HSA-DA vs. GA: R = -0.53, p = 1E-09). Conclusions: The "epiphenomenon" of albumin truncation (reflecting the severity of mean hyperglycemia and also insulin resistance) can possibly provide novel, sensitive, and complementary biomarkers (e.g., via simpler HSA-DA peptide fragment immunoassays) to monitor efficacy of diabetes therapy and also progression from "healthy" to prediabetes and type 2 diabetes, highlighting potential diagnostic and prognostic utility in clinical diabetes care.

Selenoprotein P as a prognostic biomarker of burn sepsis: A prospective cohort study

IntroductionSeverely burned patients exhibit increased nutritional requirements and are at high risk of developing sepsis. Selenium is an essential trace element supporting antioxidant and anti-inflammatory pathways, mediated by incorporation into selenoproteins. The selenium status may affect sepsis risk in burn injury. MethodsThis prospective cohort study included 90 adult patients admitted to Zurich Burn Center, Switzerland. All patients received a continuous intravenous infusion of 1000 μg sodium selenite per day during the first week as part of local standard of care. Three complementary biomarkers of serum selenium status were determined at nine time-points up to six months postburn, namely total selenium, selenoprotein P, and glutathione peroxidase 3. The resulting data were correlated to clinical parameters and outcomes, with sepsis as the primary end point. ResultsA high fraction of the patients displayed selenium deficiency already at admission, and developed sepsis during hospitalization (n = 55; 61 %). Selenium status at admission was inversely related to burn severity. Low baseline selenoprotein P was associated with sepsis incidence, irrespective of trauma severity (adjusted HR, 1.94; 95 % CI, 1.05–3.63; p = 0.035). Burn severity and baseline concentrations of selenoprotein P and white blood cells together predicted sepsis with an area under the curve of 0.84 (95 % CI, 0.75–0.93; p < 0.0001). Supplemental selenium was associated with a transient normalization of selenium status. ConclusionConsidering its rapid decline following severe burn injury, the assessment of serum selenoprotein P upon admission may contribute to an early prediction of sepsis risk.

Cardiac autonomic changes after stroke

Abstract Introduction There is a highly complex and clinically important relationship between the cardiac and the nervous system, called the heart-brain axis [1]. Therefore, acute brain damage may lead to alterations in cardiac function due to changes in the autonomic nervous system[2,3]. Novel computerised biosignal analysis techniques and advanced biosignal assessment could provide a valuable tool to sensitively analyse cardiac autonomic function (CAF). CAF can be characterized by two complementary digital biomarkers, periodic repolariation dynamics (PRD) and deceleration capacity (DC). The aim of this study was to determine CAF by means of PRD and DC in patients with acute ischemic stroke (AIS) or transient ischemic attack (TIA) and to analyze them according to their relationship with specific cardiac (high-sensitive Troponin T (hsTnT) and N-terminal pro-B-type natriuretic peptide (NT-pro BNP)) and stroke (location, type, severity) characteristics. Methoden / Methods Between February 22, 2021, and May 5, 2023, 282 patients after an AIS or TIA were enrolled in the study. During the inpatient stay, all relevant parameters were recorded and stored in a database. To assess CAF, a 30-minute biosignal measurement was performed with a high resolution (1kHz) electrocardiogram (ECG). Cardiac autonomic biomarkers, PRD and DC, were calculated semiautomatically afterwards from patients. Results Fifteen ECGs were excluded due to poor recording quality. Consequently, data from 261 AIS and 21 TIA patients were analyzed. A total of 105 patients (37.2 %) had pathological PRD (≥ 5.75 deg2) and/or DC (≤ 2.5 ms), 78 patients (27.7 %) had pathological PRD, and 57 patients (20.2 %) had pathological DC. The median PRD was 3.13 deg2 and the median DC was 5.30 ms (see Figure). There were no significant differences in the distribution of PRD and DC between male and female patients (PRD p = 0.38, DC p = 0.30), and between AIS and TIA patients (PRD p = 0.13, DC p = 0.66). Patients with middle cerebral artery (MCA) infarction had significantly higher median PRD values (3.56 deg2 [IQR 1.51 - 6.59 ] vs. 2.81 deg2 [IQR 1.15 - 5.99], p = 0.047) and lower median DC values (4.66 ms [IQR 2.65 – 7.76] vs. 6.11 ms [IQR 3.15 – 10.61], p = 0.011) than patients with stroke located in another cerebral regions (see Figure). Patients with pathological PRD or DC had significantly higher hsTnT (13.50 ng/l [IQR 9.7 – 24.1] vs. 11.05 ng/l [ IQR 7.13 – 16.23], p &amp;lt; 0.001) and NT-pro BNP (269.00 ng/l [IQR 117.50 – 687.00] vs. 125.50 ng/l [IQR 57.00 – 288.25], p &amp;lt; 0.001) values. Conclusions The study showed that a considerable proportion, more than one third of all patients, had evidence of cardiac autonomic dysfunction after acute cerebral ischaemia. Of particular interest, PRD was higher and DC was lower in patients with MCA ischaemia, reflecting a potentially higher cardiac risk profile. Cardiac autonomic dysfunction was also associated with increased hsTnT and NT-proBNP levels.

Integrative Multi-Omics Approach for Improving Causal Gene Identification.

Transcriptome-wide association studies (TWAS) have been widely used to identify thousands of likely causal genes for diseases and complex traits using predicted expression models. However, most existing TWAS methods rely on gene expression alone and overlook other regulatory mechanisms of gene expression, including DNA methylation and splicing, that contribute to the genetic basis of these complex traits and diseases. Here we introduce a multi-omics method that integrates gene expression, DNA methylation, and splicing data to improve the identification of associated genes with our traits of interest. Through simulations and by analyzing genome-wide association study (GWAS) summary statistics for 24 complex traits, we show that our integrated method, which leverages these complementary omics biomarkers, achieves higher statistical power, and improves the accuracy of likely causal gene identification in blood tissues over individual omics methods. Finally, we apply our integrated model to a lung cancer GWAS data set, demonstrating the integrated models improved identification of prioritized genes for lung cancer risk.

Clinical implications of residual normal plasma cells within bone marrow across various disease stages in multiple myeloma.

Residual normal plasma cells (NPCs), which compete with tumor plasma cells, play an important role in multiple myeloma. However, large-scale cohort studies investigating residual NPCs, especially at the minimal residual disease (MRD) phase, are currently lacking. In this study, we conducted a comprehensive investigation into the clinical significance of residual NPCs throughout the entire disease course in 1363 myeloma patients from the NICHE cohort (NCT04645199). Our results revealed that myeloma patients with high baseline NPCs ratio (≥5%) exhibited distinct indolent features, characterized by lower tumor burden, reduced frequencies of cytopenia, immunoparesis, and high-risk cytogenetics. Importantly, high residual NPCs ratio at diagnosis or relapse was independently associated with favorable survival. High absolute percentages of NPCs at undetectable MRD were related with superior clinical benefit and immune reconstitution. At MRD-positive phases, grouping based on NPCs ratio (<50%, 50-90%, ≥90%) demonstrated better risk stratification compared to residual tumor log levels. Based on the time-dependent NPCs ratio trend, we developed a dynamic MRD model that classifies patients into three groups with diverse longitudinal trends, leading to distinct prognoses. Collectively, residual NPCs serves not only as a valuable complementary biomarker for risk stratification but also provides valuable insights on reclassifications and kinetics of MRD.

Estimation of Serum Malondialdehyde (a Marker of Oxidative Stress) as a Predictive Biomarker for the Severity of Coronary Artery Disease (CAD) and Cardiovascular Outcomes.

Background Coronary artery disease (CAD) is influenced by oxidative stress, which is a critical yet often overlooked factor in disease progression. While traditional biomarkers such as cholesterol levels and blood pressure are commonly used, they do not fully capture oxidative damage. Malondialdehyde (MDA), a byproduct of lipid peroxidation, offers additional insights into oxidative stress and CAD severity. Unlike conventional markers, such as low-density lipoprotein (LDL) cholesterol, which primarily reflects lipid levels, and high-sensitivity C-reactive protein (hs-CRP), which indicates inflammation, MDA directly measures oxidative damage. This makes MDA a potentially valuable complement to these traditional biomarkers, providing a more nuanced understanding of CAD risk. Despite its potential, the role of MDA in clinical assessments remains underexplored. This study aims to address this gap by evaluating MDA's effectiveness as a complementary biomarker, enhancing the assessment of CAD risk and progression beyond what is provided by existing markers. Objective This study aims to assess serum MDA levels in relation to CAD severity to explore its potential as a non-invasive biomarker for disease progression and cardiovascular outcomes. Methodology This cross-sectional study was conducted at the Department of Cardiology, Mardan Medical Complex Teaching Hospital, Pakistan, from June 2023 to May 2024. Patients were divided into different groups with varying severity of CAD. The one-way ANOVA was used to assess differences among groups, and Pearson's correlation coefficient explored relationships between MDA and all study variables. Simple linear regression analyzed associations between MDA levels, patient groups, and other variables, controlling for covariates. MDA's potential as a predictive biomarker was assessed through ROC curve analysis, with statistical significance set at a p-value < 0.05. Results A total of 133 patients were included in the study, categorized based on CAD severity into mild (n=71), moderate (n=39), and severe (n=23) groups. Serum MDA levels significantly increased with the severity of CAD. Specifically, MDA levels were 116.61 ± 41.95in the mild group, 253.45 ± 180.29in the moderate group, and peaked at 459.91 ± 149.80in the severe group. The differences in MDA levels among these groups were statistically significant (p < 0.01), supporting the association between higher MDA levels and increased CAD severity. Factors such as BMI, heart rate, blood pressure, and smoking status also significantly influenced MDA levels. Receiver operating characteristic (ROC) curve analysis demonstrated high diagnostic accuracy of MDA for assessing CAD severity, with area under the curve (AUC) values of 0.81 for moderate and 0.94 for severe CAD. Comorbid conditions such as diabetes mellitus were associated with elevated MDA levels. Conclusion Elevated serum MDA serves as a reliable, non-invasive biomarker for predicting CAD severity, with potential applications in clinical risk assessment and management strategies. By identifying patients with elevated oxidative stress early, clinicians can implement timely interventions, potentially slowing disease progression and improving outcomes.

Influence of sex and functional status on the value of serum steroid profiling in discriminating adrenocortical carcinoma from adrenocortical adenoma.

It is challenging for clinicians to distinguish adrenocortical carcinoma (ACC) from benign adrenocortical adenomas (ACA) in their early stages. This study explored the value of serum steroid profiling as a complementary biomarker for malignancy diagnosis of ACC other than diameter and explored the influence of sex and functional status. In this retrospective study, a matched cohort of patients diagnosed with either ACC or ACA based on histopathology was meticulously paired in a 1:1 ratio according to sex, age, and functional status. Eight serum steroids including 11-deoxycortisol, 11-deoxycorticosterone, progesterone, androstenedione, dehydroepiandrosterone (DHEA), dehydroepiandrosterone sulfate (DHEAS), 17-hydroxyprogesterone, and estradiol, were quantified by liquid chromatography tandem mass spectrometry. We conducted a comparative analysis of the clinical characteristics and serum steroid profiles of patients with ACC and ACA, with further subgroup analysis. The study included 31 patients with ACC and 31 matched patients with ACA. Patients with ACC exhibited significantly larger tumor diameters, lower body mass index (BMI), and higher levels of 11-deoxycortisol, progesterone, and androstenedione than those with ACA. 11-deoxycortisol was the only valuable index for discriminating ACC from ACA, regardless of functional status and sex. Progesterone, DHEA, and DHEAS levels were higher in the functional ACC group than in the non-functional ACC group. Female ACC patients, especially in postmenopausal female exhibited higher levels of androstenedione than male patients. The area under the curve of tumor diameter, 11-deoxycortisol, and BMI was 0.947 (95% CI 0.889-1.000), with a sensitivity of 96.8% and specificity of 90.3%. Serum steroid profiling serves as a helpful discriminative marker for ACC and ACA, with 11-deoxycortisol being the most valuable marker. For other steroid hormones, consideration of sex differences and functional status is crucial.

Proteomic Profiling of Serum of Women with Bi-Rads 1 to 5: Identification of Potential Complementary Biomarkers for Early Detection of Breast Cancer

Proteomic Profiling of Serum of Women with Bi-Rads 1 to 5: Identification of Potential Complementary Biomarkers for Early Detection of Breast Cancer

Comparative analysis of neurofilaments and biomarkers of muscular damage in amyotrophic lateral sclerosis.

Diagnosis of the fatal neurodegenerative disease amyotrophic lateral sclerosis is challenging. Neurofilaments, indicative of neuronal damage, along with creatine kinase, creatinine, myoglobin, and troponin T, representing muscular damage, have been identified as promising fluid biomarkers. This study aims to comprehensively assess and compare their diagnostic and prognostic potential in a 'real-world' cohort of patients with amyotrophic lateral sclerosis. About 77 patients with amyotrophic lateral sclerosis and its clinical variants, and 26 age- and sex-matched controls with various neuromuscular and neurodegenerative diseases, were retrospectively included in this monocentric, cross-sectional study. Neurofilaments in cerebrospinal fluid and biomarkers of muscular damage in serum were measured and correlated with demographic features, motor function, survival time, clinical phenotypes, and the extent of upper and lower motor neuron involvement. Neurofilament, myoglobin, and troponin T concentrations were higher in patients with amyotrophic lateral sclerosis compared to disease controls. Higher neurofilament levels correlated with lower motor function and faster disease progression rate, while higher creatine kinase and creatinine concentrations were linked to preserved motor function. In contrast, troponin T elevation indicated poorer fine and gross motor functions. Increased neurofilament levels were associated with shorter survival, whereas biomarkers of muscular damage lacked survival correlation. Neurofilament concentrations were higher in classical amyotrophic lateral sclerosis than in progressive muscular atrophy, while myoglobin and troponin T levels were elevated in progressive muscular atrophy compared to primary lateral sclerosis. Neurofilaments were predominantly linked to upper motor neuron involvement. Our findings confirmed the robust diagnostic and prognostic value of neurofilaments in amyotrophic lateral sclerosis. Elevated neurofilament concentrations were associated with higher disease severity, faster disease progression, shorter survival, and predominant upper motor neuron degeneration. Biomarkers of muscular damage were inferior in distinguishing amyotrophic lateral sclerosis from other neuromuscular and neurodegenerative diseases. However, they may serve as complementary biomarkers and support in discriminating clinical variants of amyotrophic lateral sclerosis.

Circulating Tumor DNA Assessment for Treatment Monitoring Adds Value to PSA in Metastatic Castration-Resistant Prostate Cancer.

Enzalutamide after abiraterone progression is commonly used in metastatic castration-resistant prostate cancer despite a low rate of clinical benefit. Analyzing IMbassador250, a phase III trial assessing enzalutamide with or without atezolizumab after abiraterone, we hypothesized that baseline and early changes in circulating tumor DNA (ctDNA) tumor fraction (TF) may identify patients more likely to exhibit survival benefit from enzalutamide. ctDNA was quantified from plasma samples using a tissue-agnostic assay without buffy coat sequencing. Baseline ctDNA TF, changes in ctDNA TF from baseline to cycle 3 day 1 (C3D1), and detection at C3D1 alone were compared with overall response rate, radiographic progression-free survival (rPFS), median OS (mOS), and 50% reduction in PSA. ctDNA TF detection at baseline and/or C3D1 was associated with shorter rPFS and OS in 494 evaluable patients. Detection of ctDNA TF at C3D1, with or without detection at cycle 1 day 1, was associated with worse rPFS and mOS than lack of detection. When ctDNA TF and PSA response at C3D1 were discordant, patients with (ctDNA TF undetected/PSA not reduced) had more favorable outcomes than (ctDNA TF detected/PSA reduced; mOS 22.1 vs. 16 months; P < 0.001). In a large cohort of patients with metastatic castration-resistant prostate cancer receiving enzalutamide after abiraterone, we demonstrate the utility of a new tissue-agnostic assay for monitoring molecular response based on ctDNA TF detection and dynamics. ctDNA TF provides a minimally invasive, complementary biomarker to PSA testing and may refine personalized treatment approaches.

Activity and levels of TNF-α, IL-6 and IL-8 in saliva of children and young adults with dental caries: a systematic review and meta-analysis

BackgroundCytokines play an important role in the immunopathogenesis of dental caries. A systematic review and meta-analysis was carried out with the following three objectives: 1)To deepen and discuss through a comprehensive analysis of the literature the effects of dental caries on the activity and levels of TNF-α, IL-6 and IL-8 in saliva of children and young adults, 2)To compare the levels of this cytokines in saliva of the exposure group (moderate-severe dental caries) with the control group (caries-free or mild dental caries), and 3)To determine whether the levels of these cytokines could be used as a complementary clinical diagnostic tool to assess the severity of dental caries.MethodsThe protocol followed PRISMA and Cochrane guidelines and was registered in the Open Science Framework (OSF): https://doi.org/10.17605/OSF.IO/MF74V. A digital search was performed in PubMed/MEDLINE, Cochrane, Scopus, and Google Schoolar databases from February 15th, 2012, to January 13th, 2024. The methodological validity of the selected studies was assessed using Joanna Briggs Institute (JBI) tool. A meta-analysis was performed using a random-effects model to evaluate the association between dental caries/health, and the concentration of TNF-α, IL-6 and IL-8.ResultsThe search strategy provided a total of 126 articles, of which 15 investigations met the inclusion criteria. The total number of patients studied was 1,148, of which 743 represented the case/exposure group, and 405 represented the control group. The age of the patients ranged from 3 to 25 years. IL-6 was the most prevalent cytokine in the saliva of children and young adults with active dental caries. The meta-analysis revealed that there are significant differences between the levels of IL-6 and TNF-α in saliva of children with active dental caries compared to their control groups.ConclusionsThe findings suggest that IL-6 and TNF-α levels may have potential as complementary biomarkers for assessing dental caries severity. However, further research is needed to validate these findings in larger and more diverse populations before clinical application.

Combined MR quantitative susceptibility mapping and multi-shell diffusion in Parkinson's disease.

Quantitative susceptibility mapping (QSM), neurite orientation dispersion and density imaging (NODDI), and the g-ratio have separately shown differences between Parkinson's disease (PD) and healthy controls. The g-ratio has, however, not been studied in PD in the substantia nigra (SN) and the putamen. A combination of these methods could also potentially be a complementary imaging biomarker for PD. This study aimed to assess the diagnostic performance of QSM, NODDI, the g-ratio, and a combined QSM-NODDI imaging marker in the SN and putamen of PD patients. In this prospective study, the diagnostic performance of median region of interest values was compared in a cohort of 15 participants with PD and 14 healthy controls after manual segmentation. The diagnostic performance was assessed using the area under curve (AUC) for the receiving operator characteristic. Median QSM in the contralateral SN identified PD with AUC 0.77, and median isotropic volume fraction identified PD in the ipsilateral SN with AUC 0.68. A combined NODDI-QSM marker improved diagnostic performance (AUC 0.80). No significant differences were found in the g-ratio. A combination of median QSM and median isotropic volume fraction improves the differentiation of PD from healthy controls and is a potential biomarker in the diagnostics of PD. This confirms previously reported results indicating that combining QSM and NODDI modestly improves differentiation of PD.

Detection of cell-free tumor DNA in cerebrospinal fluid as a diagnostic biomarker for leptomeningeal melanoma metastasis: A case series.

Leptomeningeal melanoma metastases (LMM) are associated with poor survival. Diagnosis is based on clinical presentation, brain MRI and cerebrospinal fluid (CSF) analysis. Inconclusive findings at initial presentation can delay treatment. In this single-center case series, detection of BRAFV600- and NRASQ61-mutant cell-free tumor DNA (cfDNA) in CSF was evaluated as a complementary diagnostic biomarker. In 12 patients with clinical suspicion of LMM, a retrospective analysis of MRI, CSF cytology and cfDNA analysis on 1 mL of CSF using the Idylla® platform was carried out. Nine patients displayed MRI abnormalities suggesting LMM. CSF analysis identified malignant cells in three patients (including one without MRI abnormalities). BRAFV600- or NRASQ61-mutant cfDNA was detected in CSF of nine patients (eight with and one without MRI abnormalities; all patients with positive CSF cytology). Subsequent follow-up confirmed LMM in all patients with positive and in one patient with a negative CSF cfDNA analysis (sensitivity 81.8%; specificity 100%). Our findings suggest that analyzing BRAFV600- and NRASQ61-mutant cfDNA in CSF using the Idylla® platform holds promise as a sensitive and specific complementary diagnostic biomarker for LMM, particularly in case of inconsistency between imaging and CSF cytology. The 110-min analysis can facilitate urgent treatment decisions.