Informative Biomarkers Research Articles

Abstract 5890: Personalized detection of circulating cell-free tumor DNA in gynecologic cancer

Abstract Endometrial and ovarian cancers are among the most common gynecologic malignancies in the U.S., with 5-year overall survival rates of 81% and 50% respectively. Ovarian cancer often presents late due to asymptomatic early stages and nonspecific symptoms in advanced stages. Few markers exist for early detection, and they lack the sensitivity and specificity needed for high-risk screening. Given the absence of informative protein blood biomarkers, cell-free DNA analysis has become a promising tool for early detection, treatment evaluation, and monitoring. However, previous studies of circulating tumor DNA (ctDNA) in gynecological cancers had limited sensitivity. We adapted MASQ (Multiplex Accurate Sensitive Quantitation), originally developed to measure residual cells in leukemia, to the measurement of ctDNA in solid cancers. MASQ detects patient-specific mutations simultaneously in up to 50 loci with exceptional sensitivity, below one part per million. This study uses MASQ to measure tumor-specific variants in blood (cell-free DNA) from endometrial and ovarian cancer patients, aiming to determine the range of ctDNA signals at presentation and explore correlations with clinicopathological features and patient outcomes. We analyzed samples from 46 gynecologic cancer patients (12 ovarian, 34 endometrial) treated at Northwell Health. Samples were collected in collaboration with gynecologic oncology research coordinators and the Northwell Health Biorepository. Peripheral blood was collected at diagnosis (n=46) and post-surgery (n=14), along with surgical tumor specimens. Whole genome sequencing of tumor and blood identified thousands of somatic tumor variants per patient. For each patient, 30 representative variants were selected for MASQ sequencing. MASQ libraries were generated from cell-free DNA isolated from pre- and post-surgery plasma. Ultrasensitive variant counts across 30 loci were aggregated and analyzed for clinical correlations. ctDNA signal was detected in 35 of 46 cases at presentation, with variant allele frequencies ranging from below 10^-4 to 10^-1. ctDNA signal was higher in ovarian cancer (13/13 detected) than endometrial cancer, and higher in aggressive Type II endometrial cancer (15/16) vs. Type I (5/13). ctDNA levels correlated with tumor size and copy number imbalance, but not with total cell-free DNA. Detection of ctDNA predicted worse overall survival (p=0.023) and was the strongest predictor of survival in multivariate analysis. Post-surgery follow-up in 10 of 14 patients showed significant ctDNA reduction following treatment, highlighting MASQ’s sensitivity in tracking treatment response. This study highlights the potential of sensitive ctDNA detection for early diagnosis and monitoring in gynecologic cancers. However, limited cell-free DNA abundance necessitates even more sensitive methods to enhance clinical utility. Citation Format: Andrea B. Moffitt, Jude Kendall, Joan Alexander, Asya Stepansky, Arisa Kapedani, Zihua Wang, Dan Levy, Kenny Ye, Abba M. Krieger, Marina Frimer, Gary L. Goldberg, Michael Wigler. Personalized detection of circulating cell-free tumor DNA in gynecologic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5890.

Abstract 5879: An optimized sample-to-result workflow for detection of tumor mutations and immune sequencing in liquid biopsies

Abstract Non-invasive liquid biopsies are helping advance various aspects of disease assessment including early detection, disease monitoring, and therapy selection, while also allowing for improved patient follow-up and economic efficiency over traditional tissue biopsies. Plasma cell-free DNA (cfDNA) applications have recently been adopted in prenatal screening, tumor mutation profiling and post-transplant monitoring. Additionally, combining cfDNA profiling with paired RNA analysis of peripheral blood mononuclear cells (PBMCs) can provide useful insights into biomarkers and immune phenotypes, and present a comprehensive multiomic profile from a single blood draw. Several technical and analytical challenges persist in the liquid biopsy field including immediate preservation of draw time levels of cfDNA, minimizing PBMC lysis during storage, low concentrations of cfDNA with even lower tumor fraction, as well as the need for a higher sensitivity in downstream applications to accurately interpret clinical signals. Here, we present an efficient blood-to-result workflow for tumor-specific mutation detection and immune profiling using contrived samples spiked with known mutation controls. Whole blood was collected in Streck Nucleic Acid BCT enabling preservation of draw time concentration of cell-free nucleic acids and prevention of immune cell lysis. Nucleic acid extraction was performed on the isolated PBMCs and plasma fraction using an optimized protocol for the Monarch Mag Viral DNA/RNA Extraction Kit which features a simplified, magnetic bead-based workflow. Isolated cfDNA was used to prepare sequencing libraries using an optimized library prep workflow to maximize conversion efficiency from cfDNA. Isolated PBMC RNA was utilized to prepare RNA-seq libraries and Immune-seq libraries using the NEBNext UltraExpress RNA Library Prep Kit and NEBNext Immune Sequencing Kit, respectively. Combining these sample storage, extraction, and library prep methods resulted in a high yield of cfDNA libraries with minimal contaminating genomic DNA, enabling improved sequencing data quality, high conversion efficiency, and high sensitivity for clinical research, including detecting spike-in mutations. Transcriptome and immune repertoire profiling from the preserved PBMC in the same blood sample provided complementary biomarker information to enable a comprehensive evaluation of the disease status of these samples. Citation Format: Anagha Kadam, Margaret R. Heider, Chen Song, Jian Sun, Ariel Erijman, Nicholas M. George. An optimized sample-to-result workflow for detection of tumor mutations and immune sequencing in liquid biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5879.

Identification of patients with suspected NSTE-ACS in the observe zone: evaluating GRACE 1.0 score and a biomarker panel for risk stratification and management optimization.

Current guidelines recommend additional diagnostic work-up for patients with suspected non-ST-elevation acute coronary syndrome (NSTE-ACS) triaged in the observe zone using accelerated diagnostic protocols. This study assessed the effectiveness of combining the Global Registry of Acute Coronary Events (GRACE) 1.0 score with additional non-cardio-specific biomarkers for risk stratification in the observe zone. A total of 6789 patients with suspected NSTE-ACS were enrolled over 24months, with 961 (21.8%) assigned to the observe zone. A classification and regression tree (CART) analysis dichotomized risk using the GRACE-score and additional biomarkers beyond high-sensitivity cardiac troponin including C-reactive protein < 10mg/dL, N-terminal pro-B-type natriuretic peptide < 300ng/L, D-dimers < 5mg/L, estimated glomerular filtration rate > 30mL/min/1.73m2, Copeptin < 10pmol/L, and hemoglobin > 10g/dL. The primary endpoint was 1-year all-cause mortality, validated using the Biomarkers in Acute Cardiac Care (BACC) cohort. A low GRACE 1.0 score < 109 points was found in 37.6% of observe zone patients, showing a negative predictive value of 98.6% and sensitivity of 89.8% for death. Adding biomarker information reduced predicted 1-year-mortality from 1.38% with the GRACE-score alone to 0.46% when none of the biomarkers were above cutoff (prevalent in 22.7%). The proportion of protocol-eligible patients increased from 22.7 to 37.6%, with no events within 30days. Findings were confirmed in the BACC cohort. A low GRACE 1.0 score combined with ≤ 1 elevated biomarker significantly improves mortality prediction in the observe zone, helping identify low-risk patients for further out-of-hospital diagnostic work-up, potentially decongesting crowded emergency departments. Registration URL: https://www. gov ; Unique identifier: NCT05774431.

Enhancing Aging Biomarker Research through Large Language Models and Knowledge Graphs (Student Abstract)

Aging biomarkers play a crucial role in uncovering the biological mechanisms behind aging and in developing strategies to support healthy aging. However, the search for reliable aging biomarkers is particularly challenging due to the intricate and multifactorial nature of the aging process. Furthermore, biomarker names and categories are not well-standardized in the current literature. While, a formal definition of a biomarker is nonexistent in the current literature, formally defining biomarkers and standardizing the vocabulary for biomarkers can help accelerate AI research around this concept which can lead to better, faster and more accurate analyses of the existing data and literature. Thus, in this work, we generated Knowledge Graphs that can help us define and standardize biomarkers. We present our Knowledge Graphs (KGs) generated using both an LLM and expert-curated datasets. We compare both KGs to understand why systematic integration between these two models is needed. The integration of Knowledge Graphs (KGs) and Large Language Models (LLMs) presents a promising approach to advancing aging biomarker research through the inherent structured and standardized nature of ontology schemas in knowledge graphs. We showcase that the accuracy of LLM-generated KGs remains questionable but systematic methods such as KNARM can help us with the accuracy of these efforts. In future work, we will propose a synergistic framework where KGs and LLMs interact iteratively to improve both the comprehensiveness and accuracy of aging biomarker information.

Lung Cancer Biomarker Database (LCBD): a comprehensive and curated repository of lung cancer biomarkers

BackgroundLung cancer remains a leading cause of cancer-related mortality, primarily because of the lack of effective diagnostic and therapeutic biomarkers. To address the issue of fragmented biomarker data across numerous publications, we have developed the Lung Cancer Biomarker Database (LCBD, http://lcbd.biomarkerdb.com).MethodsWe comprehensively reviewed biomarker-related studies up to June 30, 2023, and extracted relevant biomarker information. The identified biomarkers were systematically annotated, including genes, proteins, GO terms, KEGG pathways, biomarker types, molecular types, developmental stages, discovery methods, sources, populations, and sample sizes. The LCBD online platform was developed to integrate lung cancer biomarker data, and provide search, browsing, and data download functions for researchers. To validate the data in the LCBD, we conducted three case studies comparing models with and without LCBD data.ResultsAfter deduplication and summarization, we collected 1,447 unique biomarkers that were systematically annotated. We then developed the LCBD specifically for use in lung cancer diagnosis. The validity of the biomarkers in the LCBD was confirmed using prognostic models, diagnostic models, and immune infiltration models.ConclusionThe LCBD provides a centralized platform for lung cancer biomarkers, facilitating early screening and personalized treatment. This database is poised to become a valuable resource for lung cancer research and therapeutic strategies.

Novel blood-based proteomic signatures across multiple neurodegenerative diseases.

Blood-based biomarkers have the potential to support early and accurate diagnoses of neurodegenerative diseases, which are sensitive to molecular pathology and are predictive of outcome. We evaluated a novel multiplex proteomic method in people with diverse neurodegenerative diseases. Serum from people with Alzheimer's disease (N=36), Lewy body dementia (N=34), frontotemporal dementia (N=36), and progressive supranuclear palsy (N=36) and age-matched controls (N=30) was analyzed with the nucleic acid linked immuno-sandwich assay (NULISA) central nervous system panel (≈ 120 analytes) and inflammation panel (250 analytes). Biomarkers were compared across groups and included as predictors of survival. The NULISA panels demonstrated high sensitivity and reliability for detecting multiple biomarkers across neurodegenerative disorders. There were condition-specific proteomic biomarkers, while neurofilament light chain, corticotropin-releasing hormone, CD276, and a data-driven inflammation pattern were significant transdiagnostic outcome predictors. The sensitive NULISA multiplex approach supports differential diagnosis and target identification, with prognostically informative dementia-related biomarkers. We tested the novel technology nucleic acid linked immuno-sandwich assay (NULISA) in people with diverse neurodegenerative diseases, which demonstrated high sensitivity and reliability for detecting multiple biomarkers in serum samples. We compared the NULISA central nervous system serum results to single molecule array (Simoa) plasma assays for phosphorylated tau (p-tau)217, p-tau231, neurofilament light chain (NfL), and glial fibrillary acidic protein, finding strong correlations. Increased levels of serum NfL were identified across all patient groups and most elevated in the frontotemporal dementia (FTD) and progressive supranuclear palsy (PSP) cohorts, while p-tau epitopes were the most significant markers in patients with Alzheimer's disease (AD) and Lewy body dementia. Patients with FTD and PSP showed upregulation of many inflammation markers, compared to controls and patients with AD. We found condition-specific proteomic biomarkers, while NfL, corticotropin-releasing hormone, CD276, and data-driven immune signatures were significant transdiagnostic predictors of clinical outcomes (survival rates).

The value of midregional proadrenomedullin to predict mortality in intensive care unit.

The value of midregional proadrenomedullin to predict mortality in intensive care unit.

Utilizing Structural MRI and Unsupervised Clustering to Differentiate Schizophrenia and Alzheimer's Disease in Late-onset Psychosis

Utilizing Structural MRI and Unsupervised Clustering to Differentiate Schizophrenia and Alzheimer's Disease in Late-onset Psychosis

GLASSR-Net: Glass Substrate Spectral Restoration Neural Network for Fourier Transform Infrared Microspectroscopy in the Fingerprint Region.

Fourier transform infrared (FTIR) microspectroscopy has emerged as a pivotal pathological tool, offering informative spectral biomarkers for numerous diseases. However, the dependency on specialized infrared (IR) substrates limits effective and widespread clinical translation. IR transparent bases like calcium/barium fluoride (CaF2/BaF2) are costly and fragile, while IR reflective bases cannot be used for microscopic screening due to their opacity to visible light. In comparison, 1 mm thick pathological glass substrates are cost-effective, reliable, and widely utilized in clinical pathology. Therefore, establishing a methodology for collecting high-quality FTIR spectra on glass substrates is highly desired and beneficial. Here, we develop a glass substrate spectral restoration neural network (GLASSR-Net) to restore the fingerprint absorbance spectra from glass-based spectra spanning the wavenumbers from 1800 to 1000 cm-1. The model is trained and validated by acquiring input glass-based spectra and ground truth spectra, respectively, through FTIR raster scanning on contiguous tissue sections of papillary thyroid carcinoma (PTC) mounted on glass and CaF2 substrates. The GLASSR-Net successfully restores the sample absorbance and accurately reconstructs the biochemical distribution in both the spatial and spectral domains. Furthermore, the biochemical signatures of PTC are effectively extracted and analyzed from the restored spectra with traditional spectral histology, indicating a decrease in amide I/II absorption and an accumulation of lipids and nucleic acids in cancerous regions. The proposed GLASSR-Net presents a novel framework for data collection, spectral restoration, and integration of traditional methodology in glass-based IR microspectroscopy, which facilitates the incorporation of FTIR microspectroscopy into clinical histological scenarios.

Analysis of MicroRNA Expression in Specimens From Patients With Cutaneous Melanoma

Importance: Cutaneous melanoma is regarded as the most lethal form of skin cancer. According to the literature, issues associated with accurate prognosis and early detection of relapses hinder effective treatment of melanomas. Over the past 20 years, microRNAs have been shown to modulate various biological processes. Disruption of microRNA expression and activity can contribute to the risk of cancer development, including cutaneous melanoma. Therefore, we decided to study some microRNAs as biomarkers for future use in cutaneous melanoma diagnosis.Objective: To analyze the expression of microRNA-205, microRNA-199a-3p, microRNA-146a-5p in tumor tissue of patients diagnosed with cutaneous melanoma.Materials and methods: We quantified the expression of microRNA-205, microRNA-199a-3p, microRNA-146a-5p using the realtime polymerase chain reaction in biopsy specimens from patients with melanoma (n=14). For all the specimens, the cycle threshold (Ct) value was 0.1 (qPCRsoft 3.0, Analytik Jena, Germany). Statistical analysis was performed using Statistica 7.0 (StatSoft, USA). Furthermore, we conducted a bioinformatics search for microRNA target genes using DIANA-mirPath v.3.0 (DIANA-Lab, Greece) and constructed gene interaction networks using STRING (https://string-db.org/).Results: We detected 2 of 3 microRNAs in the group of patients with cutaneous melanoma: microRNA-205 and microRNA-146a-5p. In both the control group and the group of patients with melanoma, 1 of 3 microRNAs, namely miR-146a-5p, was found. The mean ∆Ct value of microRNA-146a-5p was 3.81±2.03 in the control group and 2.26±1.34 in the patients with melanoma. Due to the wide range of values in the control group and the group of patients with cutaneous melanoma, microRNA-146a-5p cannot be considered an informative biomarker. At the same time, we found high expression of microRNA-205 in the group of patients with cutaneous melanoma.Conclusions: microRNA-205 was found to be valuable in melanoma diagnosis. However, further studies with larger sample size and additional stratification by histopathological features are needed.

Molecular and immunological features associated with long-term benefits in metastatic NSCLC patients undergoing immune checkpoint blockade

ABSTRACT Introduction Immunotherapy is firmly established as a treatment regimen in various solid tumors, driven by its exceptional benefits in a selected group of patients. Despite widespread adoption of immune checkpoint blockade (ICB) across diverse solid tumors, the quest for a clinically informative biomarker for long-term benefit remains unmet. Methods A total of 49 patients with metastatic NSCLC treated with ICB were included. Long-term (LTR) and short-term responders (STR) were defined as those with a response to ICB lasting more than 24 months or less than 6 months, respectively. Longitudinal blood specimens were collected before ICB treatment initiation and early-on treatment. Plasma ctDNA next-generation sequencing panel (NGS) and serum proteomics were performed. GeoMx DSP on baseline tumor tissue was performed in a subset of patients. Results Our analysis revealed specific characteristics of LTR compared with STR, namely higher PD-L1 in tumor cells (p = 0.005) and higher incidence of irAEs (p = 0.001). Genomic features associated with lack of benefit from ICB included co-occurring mutations in KRAS/STK11 and TP53/KMT2D (p < 0.05). At a baseline, LTR patients exhibited higher serum levels of proteins related with apoptosis (CASP8, PRKRA), chemotaxis, immune proteasome, processing of MHC class I (S100A4, PSMD9, RNF41) and immune homeostasis (HAVCR1, ARG1) (p < 0.05). Protein spatial profiling of tumor samples showed higher levels of proteins linked with the presence of immune cells (CD45), T cells (CD8), antigen presentation (HLA-DR) and immune regulation proteins (PD-L1, IDO1) within the tumor and tumor stroma component (p < 0.05) in LTR patients. Serum longitudinal analysis identified a set of proteins that presented distinct dynamics in LTR compared to STR, making them interesting candidates to evaluate as early predictors of treatment efficacy. Conclusions Our multimodal analysis of patients with metastatic NSCLC treated with ICB identified clinicopathological and immunological features associated with long-term benefits. The presence of preexisting antitumor immunity emerged as a strong predictor of long-term benefits, providing insights for potential biomarkers and therapeutic strategies for enhancing ICB outcomes in metastatic NSCLC.

Plasma Hepcidin as a potential informative biomarker of Alzheimer disease and vascular dementia

BackgroundBlood-based assays are expected to be integrated into clinical routines across various contexts, including Alzheimer’s disease (AD). Vascular dementia (VaD), which is the second most common cause leading to dementia after AD, could also significantly benefit from this advancement. However, no informative fluid biomarker has been identified for VaD. Given the disruption of iron homeostasis in both AD and VaD, this study aims to characterize the potential of the iron-related hormone Hepcidin as a biomarker for these two conditions. We will compare its added value to established AT(N) blood biomarkers.MethodsBlood biomarkers (amyloid-composite, p-Tau181, Neurofilament Light Chain [NfL] and Hepcidin) levels in blood were analyzed in two independent cohorts and compared between AD patients and non-AD individuals. Additionally, blood Hepcidin and NfL were evaluated in the contexts of VaD and CADASIL, with their relative diagnostic value assessed.ResultsBlood Hepcidin and NfL do not significantly increase the AUC obtained with both p-Tau181 and amyloid composite in the context of AD. In contrast, AUC for VaD diagnosis is significantly higher when combining these two blood biomarkers compared to NfL alone. Hepcidin was not significantly modified in CADASIL patients compared to control subjects.ConclusionBlood Hepcidin and NfL have limited interest in the clinical context of AD but determination of these biomarkers shows to be highly informative for the diagnosis of VaD. This result could have important implications for diagnosis and implementation of clinical trials.

A multicentre implementation trial of an Artificial Intelligence-driven biomarker to inform Shared decisions for androgen deprivation therapy in men undergoing prostate radiotherapy: the ASTuTE protocol

BackgroundAndrogen deprivation therapy (ADT) improves outcomes in men undergoing definitive radiotherapy for prostate cancer but carries significant toxicities. Clinical parameters alone are insufficient to accurately identify patients who will derive the most benefit, highlighting the need for improved patient selection tools to minimize unnecessary exposure to ADT’s side effects while ensuring optimal oncological outcomes. The ArteraAI Prostate Test, incorporating a multimodal artificial intelligence (MMAI)-driven digital histopathology-based biomarker, offers prognostic and predictive information to aid in this selection. However, its clinical utility in real-world settings has yet to be measured prospectively.MethodsThis multicentre implementation trial aims to collect real-world data on the use of the previously validated Artera MMAI-driven prognostic and predictive biomarkers in men with intermediate-risk prostate cancer undergoing curative radiotherapy. The prognostic biomarker estimates the 10-year risk of metastasis, while the predictive biomarker determines the likely benefit from short-term ADT (ST-ADT). A total of 800 participants considering ST-ADT in conjunction with curative radiotherapy will be recruited from multiple Australian centers. Eligible patients with intermediate-risk prostate cancer, as defined by the National Comprehensive Cancer Network, will be asked to participate. The primary endpoint is the percentage of patients for whom testing led to a change in the shared ST-ADT recommendation, analyzed using descriptive statistics and McNemar’s test comparing recommendations before and after biomarker testing. Secondary endpoints include the impact on quality of life and 5-year disease control, assessed through linkage with the Prostate Cancer Outcomes Registry. The sample size will be re-evaluated at an interim analysis after 200 patients.DiscussionASTuTE will determine the impact of a novel prognostic and predictive biomarker on shared decision-making in the short term, and both quality of life and disease control in the medium term. If the biomarker demonstrates a significant impact on treatment decisions, it could lead to more personalized treatment strategies for men with intermediate-risk prostate cancer, potentially reducing overtreatment and improving quality of life. A potential limitation is the variability in clinical practice across different centers inherent in real-world studies.Trial RegistrationAustralian New Zealand Clinical Trials Registry, ACTRN12623000713695p. Registered 5 July 2023.

A nomogram for predicting adverse perinatal outcome with fetal growth restriction: a prospective observational study

BackgroundFetal growth restriction (FGR) is a major determinant of perinatal morbidity and mortality. Our study aimed to develop a prediction model for the risk of FGR developing adverse perinatal outcome (APO) and evaluate its performance.MethodsThis was a prospective observational cohort study of consecutive singleton gestations meeting the ACOG-endorsed criteria for FGR from January 2022 to June 2023 at Obstetrics and Gynecology Hospital of Fudan University. Clinical information, ultrasound indicators and serum biomarkers were collected. The primary composite APO comprised one or more of: perinatal death, intrauterine demise, intraventricular hemorrhage, periventricular leukomalacia, seizures, necrotizing enterocolitis, neonatal respiratory distress syndrome, sepsis and the length of stay in the neonatal intensive care unit > 7 days. Least absolute shrinkage and selection operator regression was used to screen variables for nomogram model construction. The discrimination, calibration and clinical effectiveness of the nomogram were evaluated using receiver operating characteristic curve, calibration plots and decision curve analysis in training and validation cohorts.ResultsA total of 122 pregnancies were enrolled in the final statistical analysis. Five variables were identified to establish a nomogram, including gestational weeks at diagnosis, abnormal umbilical artery Doppler, abnormal uterine artery Doppler, and multiples of the median values of placental growth factor and soluble fms-like tyrosine kinase-1. The area under the receiver-operating-characteristics curve of 0.87 (95% CI, 0.75–0.99) and 0.86 (95% CI, 0.74–0.98) in the training and validation cohort respectively, indicated satisfactory discriminative ability of the nomogram. The calibration plots showed favorable consistency between the nomogram’s predictions and actual observations. Decision curve analysis supported its practical value in a clinical setting.ConclusionsA nomogram was developed and validated to possess the promising capacity of predicting APO in FGR-afflicted neonates, and may prove useful in counseling and management of pregnancies complicated by FGR.

Analysis of a mouse germ cell tumor model establishes pluripotency-associated miRNAs as conserved serum biomarkers for germ cell cancer detection

Malignant testicular germ cells tumors (TGCTs) are the most common solid cancers in young men. Current TGCT diagnostics include conventional serum protein markers, but these lack the sensitivity and specificity to serve as accurate markers across all TGCT subtypes. MicroRNAs (miRNAs) are small non-coding regulatory RNAs and informative biomarkers for several diseases. In humans, miRNAs of the miR-371-373 cluster are detectable in the serum of patients with malignant TGCTs and outperform existing serum protein markers for both initial diagnosis and subsequent disease monitoring. We previously developed a genetically engineered mouse model featuring malignant mixed TGCTs consisting of pluripotent embryonal carcinoma (EC) and differentiated teratoma that, like the corresponding human malignancies, originate in utero and are highly chemosensitive. Here, we report that miRNAs in the mouse miR-290-295 cluster, homologs of the human miR-371-373 cluster, were detectable in serum from mice with malignant TGCTs but not from tumor-free control mice or mice with benign teratomas. miR-291-293 were expressed and secreted specifically by pluripotent EC cells, and expression was lost following differentiation induced by the drug thioridazine. Notably, miR-291-293 levels were significantly higher in the serum of pregnant dams carrying tumor-bearing fetuses compared to that of control dams. These findings reveal that expression of the miR-290-295 and miR-371-373 clusters in mice and humans, respectively, is a conserved feature of malignant TGCTs, further validating the mouse model as representative of the human disease. These data also highlight the potential of serum miR-371-373 assays to improve patient outcomes through early TGCT detection, possibly even prenatally.

БИОХИМИЧЕСКИЕ МАРКЕРЫ ДИСФУНКЦИИ ГЕПАТОБИЛИАРНОЙ СИСТЕМЫ У НОВОТЕЛЬНЫХ КОРОВ

The purpose of research is to study the biochemical parameters of the blood of cows to search for informative biomarkers for assessing hepatobiliary disorders in the early lactation period. Objectives: a comprehensive biochemical study of the blood of cows in the early lactation period and determination of the activity of liver and skeletal muscle enzymes as indicators characterizing liver cell damage. Experimental studies were carried out in 7 farms of the Altai Region. A total of 87 blood samples were collected from animals during the study period. The material for research was the blood serum of cows during the period up to 45 days of lactation. As a result of research, it was found that in cows with fatty liver degeneration there is a significant increase in the concentration of bilirubin in the blood - up to 13.72 µmol/l, a decrease in the concentration of albumin beyond the standard ranges to 26.4 g/l cholesterol to 1.74 mmol/l, compared to healthy animals. The level of triglycerides in the blood of sick cows decreases to 0.33 mmol/l, compared to healthy animals (0.47 mmol/l), however, these changes are within standard intervals (0.22–0.55 mmol/l). A study of circulating liver enzymes showed that in cows with fatty degeneration there is a significant increase in the enzymatic activity of aspartate aminotransferase (AST) to 148.3 U/l, glutamyltransferase (GGT) to 30.0 U/l and creatine kinase (CK) to 667.8 U /l, which is 1.95, 1.55 and 6.71 times more than in healthy animals, respectively. Thus, changes in the concentrations of bilirubin, cholesterol, albumin, AST and GGT can be used as a diagnostic algorithm that is highly informative when testing disorders of the functional state of the liver, which will allow for timely correction.

Advances in colorectal cancer diagnosis using optimal deep feature fusion approach on biomedical images.

Colorectal cancer (CRC) is the second popular cancer in females and third in males, with an increased number of cases. Pathology diagnoses complemented with predictive and prognostic biomarker information is the first step for personalized treatment. Histopathological image (HI) analysis is the benchmark for pathologists to rank colorectal cancer of various kinds. However, pathologists' diagnoses are highly subjective and susceptible to inaccurate diagnoses. The improved diagnosis load in the pathology laboratory, incorporated with the reported intra- and inter-variability in the biomarker assessment, has prompted the quest for consistent machine-based techniques to be integrated into routine practice. In the healthcare field, artificial intelligence (AI) has achieved extraordinary achievements in healthcare applications. Lately, computer-aided diagnosis (CAD) based on HI has progressed rapidly with the increase of machine learning (ML) and deep learning (DL) based models. This study introduces a novel Colorectal Cancer Diagnosis using the Optimal Deep Feature Fusion Approach on Biomedical Images (CCD-ODFFBI) method. The primary objective of the CCD-ODFFBI technique is to examine the biomedical images to identify colorectal cancer (CRC). In the CCD-ODFFBI technique, the median filtering (MF) approach is initially utilized for noise elimination. The CCD-ODFFBI technique utilizes a fusion of three DL models, MobileNet, SqueezeNet, and SE-ResNet, for feature extraction. Moreover, the DL models' hyperparameter selection is performed using the Osprey optimization algorithm (OOA). Finally, the deep belief network (DBN) model is employed to classify CRC. A series of simulations is accomplished to highlight the significant results of the CCD-ODFFBI method under the Warwick-QU dataset. The comparison of the CCD-ODFFBI method showed a superior accuracy value of 99.39% over existing techniques.

Beta-trace protein in chronic inflammatory demyelinating polyradiculoneuropathy and Guillain-Barré syndrome - clinical utilization and a new insight into pathophysiological mechanisms.

Beta-trace protein (BTP) is primarily used as a marker for traumatic CSF leakage. Spinal leptomeningeal cells adjacent to the spinal nerve roots are a major producer of this protein, which has prompted interest in its relevance to inflammatory polyradiculoneuropathies. BTP has not previously been investigated in patients with Guillain-Barré syndrome (GBS) and chronic inflammatory demyelinating polyradiculopathy (CIDP). BTP was measured in the cerebrospinal fluid (CSF) and plasma in patients with GBS, CIDP, disease-free controls, non-inflammatory polyneuropathies, and multiple sclerosis. Pre-treatment levels of BTP in plasma were increased in patients with CIDP, but not GBS compared to all controls. Pre-treatment levels of BTP in CSF were increased in patients with CIDP compared to all controls but in patients with GBS compared only to disease-free controls. In patients with GBS and CIDP, levels of BTP in CSF were increased compared to disease-free controls irrespective of Q.alb, and the levels correlated with axonal damage markers in CSF and plasma. Elevated pre-treatment levels of BTP in CSF predicted therapy failure 3months after initiation of immunotherapy in CIDP. BTP in CSF and plasma may be a potential biomarker to aid in the diagnosis of CIDP. BTP in CSF could be a potentially more informative biomarker than albumin in a subgroup of patients with GBS and CIDP who have a normal or mildly elevated Q.alb. BTP in CSF may be predictive for therapy response in patient with CIDP, but needs to be validated in larger studies.

Plasma p-tau217 identifies cognitively normal older adults who will develop cognitive impairment in a 10-year window.

We assessed the prognostic accuracy of plasma p-tau217 in predicting the progression to mild cognitive impairment (MCI) in cognitively unimpaired (CU) individuals over a mean follow-up of 5.65 years after plasma collection (range 1.01-10.47). We included 215 participants from the PREVENT-AD cohort with plasma Aβ42/40 and p-tau217, 159 with cerebrospinal fluid (CSF) Aβ42/40 and p-tau217, and 155 with 18F-NAV4694 and 18F-flortaucipir PET scans. MCI progression was determined by multidisciplinary consensus among memory experts blind to biomarker and genetic information. Cox proportional hazard models indicated a greater progression rate in A+T+plasma and A-T+plasma compared to A-T-plasma individuals (HR=7.81 [95% CI=3.92 to 15.59] and HR=4.25 [1.60-11.31] respectively). Similar results were found with CSF (HR=3.63 [1.72-7.70]) and PET (HR=9.30 [3.67-23.55]). Plasma p-tau217 is a prognostic marker for identifying individuals who will develop cognitive impairment within ten years. Elevated plasma p-tau217 levels in CU individuals indicate future clinical progression. Adding plasma Aβ42/40 status to p-tau markers did not improve the prediction to MCI. All individuals with abnormal tau PET measured in a temporal meta-ROI progressed to MCI.

Adverse events (AEs) –derived biomarker in predicting clinical outcomes in patients with colorectal cancer (CRC) treated with immunotherapy (IC).

132 Background: There are insufficient studies evaluating the role of AEs in CRC patients treated with IC. This study aims to transform AEs from traditional toxicity evaluation tools to informative biomarkers for assessing treatment efficacy by utilizing modern analytical strategies. Methods: We analyzed a single arm study of 51 mismatch repair proficient, refractory CRC patients (NCT03712943) treated with regorafenib and nivolumab. Data for analysis included CTCAE version 5 AE data, RECIST treatment response, progression-free survival (PFS), and overall survival (OS). Analytic approach leveraged multiple AE parameters to develop a set of innovative AE biomarkers. One AE biomarker of interest was treatment related low-grade early AEs (TR-LG-AE) which was defined as frequency of all TR-LG-AEs occurring between the 1st day and day 30 after the 1st treatment. Results: TR-LG-AE was associated with treatment response (p&lt;0.001 by ANOVA trend test). Patients with higher AE events tended to be a responder, compared to PD patients with a lower frequency of AE events. The TR-LG-AE also correlated with improved PFS and OS with hazard ratio of 0.83 (p=0.01) and 0.89 (p=0.03), respectively. Accordingly, patients were grouped into high versus low TR-LG-AE based on optimal cutoff of 6 events for further analysis. The dichotomized TR-LG-AE (high vs low) showed significant association with survival outcomes (median PFS: 15.3 vs 3.7 months; p&lt;0.001; median OS: 21.9 vs 9 months; p=0.02). Further interaction analysis showed patients with high TR-LG-AE had improved PFS regardless of occurrence of high-grade AE (HG-AE) (p=0.01), suggesting its independence of HG-AE. Individual AE analysis identified patients experienced with early low-grade rash maculo-papular, lipase increased, or hypertension had improved PFS (p&lt;0.001). In biomarker analysis, one key mutation biomarker, RAS, did not show significant association with survival outcomes (PFS: p=0.66; OS: p=0.81). In contrast, integration with TR-LG-AE led to remarkable improvement. Specifically, the TR-LG-AE was able to help improve RAS classification by identifying patients with better treatment benefit. Specifically, patients with RAS mutation and high TR-LG-AE experiences had a median PFS of 15.3 months compared to others (median PFS of 3.7 months; p=0.007), and a median OS of 21.9 months compared to others (median OS of 9.4 months; p=0.04). Conclusions: The study demonstrated utility of AE in predicting clinical outcomes in CRC, similar to our previous findings in lung cancer. Moreover, it discovered that integration of AE-derived biomarkers with molecular biomarkers could produce a more robust classifier than when considered individually. This analysis is the first of its kind to identify subgroups of CRC patients that benefit from IC treatment.