Development Of Biomarkers Research Articles

Targeted Multiplex Proteomics for the Development and Validation of Biomarkers in Primary Aldosteronism Subtyping

Abstract Objective Primary aldosteronism (PA), a significant cause of secondary hypertension affecting approximately 10% of patients with severe hypertension, exacerbates cardiovascular and cerebrovascular complications even after blood pressure control. PA is categorized into two main subtypes: unilateral aldosterone-producing adenomas (APA) and bilateral hyperaldosteronism (BHA), each requiring distinct treatment approaches. Accurate subtype classification is crucial for selecting the most effective treatment. The goal of this study was to develop novel blood-based proteomic biomarkers to differentiate between APA and BHA subtypes in patients with PA. Design and Methods Five subtyping differential protein biomarker candidates (APOC3, CD56, CHGA, KRT5, and AZGP1) were identified through targeted proteomic profiling of plasma. The subtyping efficiency of these biomarkers was assessed at both the tissue gene expression and blood protein expression levels. To explore the underlying biology of APA and BHA, significant differential pathways were investigated. Results The five-protein panel proved highly effective in distinguishing APA from BHA in both tissue and blood samples. By integrating these five protein biomarkers with aldosterone and renin, our blood-based predictive methods achieved remarkable ROC AUCs of 0.986 (95% CI: 0.963-1.000) for differentiating essential hypertension (EH) from PA, and 0.922 (95% CI: 0.846-0.998) for subtyping APA versus BHA. These outcomes surpass the performance of the existing Kobayashi score subtyping system. Furthermore, the study validated differential pathways associated with the pathophysiology of primary aldosteronism, aligning with current scientific knowledge and opening new avenues for advancing PA care. Conclusions The new blood-based biomarkers for PA subtyping hold the potential to significantly enhance clinical utility and advance the practice of PA care.

Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung Disease

Objectives: We aimed to develop imaging biomarkers to predict radiation pneumonitis (RP) in non-small cell lung cancer (NSCLC) patients undergoing thoracic radiotherapy. We hypothesized that measuring morphometric complexity in the lung using simulation computed tomography may provide objective imaging biomarkers for lung parenchyma integrity, potentially forecasting the risk of RP. Materials and Methods: A retrospective study was performed on medical records of 175 patients diagnosed with NSCLC who had received thoracic radiotherapy. Three indices were utilized to measure the morphometric complexity of the lung parenchyma: box-counting fractal dimension, lacunarity, and minimum spanning tree (MST) fractal dimension. Patients were dichotomized into two groups at median values. Cox proportional hazard models were constructed to estimate the hazard ratios for grade ≥ 2 or grade ≥ 3 RP. Results and Conclusions: We found significant associations between lung parenchymal morphometric complexity and RP incidence. In univariate Cox-proportional hazard analysis, patients with a lower MST fractal dimension had a significantly higher hazard ratio of 2.296 (95% CI: 1.348–3.910) for grade ≥ 2 RP. When adjusted for age, sex, smoking status, category of the underlying lung disease, category of radiotherapy technique, clinical stage, histology, and DLCO, patients with a lower MST fractal dimension showed a significantly higher hazard ratio of 3.292 (95% CI: 1.722–6.294) for grade ≥ 2 RP and 7.952 (95% CI: 1.722 36.733) for grade ≥ 3 RP than those with a higher MST fractal dimension. Patients with lower lacunarity exhibited a significantly lower hazard ratio of 0.091 (95% CI: 0.015–0.573) for grade ≥ 3 RP in the adjusted model. We speculated that the lung tissue integrity is captured by morphometric complexity measures, particularly by the MST fractal dimension. We suggest the MST fractal dimension as an imaging biomarker for predicting the occurrence of symptomatic RP after thoracic radiotherapy.

Differential functional change in olfactory bulb and olfactory eloquent areas in Parkinson’s disease

Abstract Olfactory dysfunction, or hyposmia, frequently occurs as a prodromal symptom and ongoing sign of Parkinson’s disease. Functional MRI is a powerful tool for studying functional changes in the olfactory brain regions in patients with Parkinson’s disease. However, existing studies show inconsistent results and no study has measured olfactory functional MRI abnormalities in the human olfactory bulb directly. This is mainly due to the well-known susceptibility artifacts in conventional functional MRI images that affect several key olfactory-eloquent brain regions, and especially the olfactory bulb. In this study, olfactory functional MRI was performed using a recently developed functional MRI approach that can minimize susceptibility artifacts and measure robust functional MRI signals in the human olfactory bulb during olfactory stimulation. Experiments were performed on high magnetic field (7T) in 24 early (< 5 years of parkinsonian symptoms) Parkinson’s disease patients and 31 matched healthy controls. Our data showed increased functional MRI signal changes (ΔS/S) in the olfactory bulb in patients with early Parkinson’s disease, which correlated with behavioral olfactory measures. Temporally, functional MRI signals in the olfactory bulb returned to the pre-stimulus state earlier after reaching peak amplitude in patients with early Parkinson’s disease, implicating a faster olfactory habituation effect. The piriform cortex showed reduced numbers of activated voxels in patients with early Parkinson’s disease, which correlated with behavioral olfactory assessment. Several secondary olfactory regions including the orbitofrontal cortex, temporal pole, and amygdala exhibited reduced numbers of activated voxels and increased functional MRI signal changes in patients with early Parkinson’s disease. Our data also showed that functional MRI results are highly dependent on voxel selection in the functional analysis. In summary, we demonstrate differential spatial and temporal characteristics of olfactory functional MRI signals between the primary and secondary olfactory regions in patients with early Parkinson’s disease. These results may assist the development of novel quantitative biomarkers (especially in the early stages of Parkinson’s disease) to track and predict disease progression, as well as potential treatment targets for early intervention.

Clinical measures in chronic neuropathic pain are related to the Kennedy and endocannabinoid pathways.

Chronic neuropathic pain (CNP) is a debilitating condition, often refractory to currently available drugs. Understanding biochemical alterations in peripheral tissues such as blood will be useful for understanding underlying pathophysiological processes relating to CNP. We collected blood from two independent cohorts of CNP and pain-free controls (CNP n = 129/Controls n = 127) in the UK and Ireland to investigate the relationship between CNP-associated molecular/biochemical alterations and a range of clinical and pain metric parameters. Multiple statistical comparisons were conducted on the data, with selected variables included in one or more of the intended inferential analyses (six models). Gene expression analysis showed that choline phosphotransferase (CHPT1) was increased (p < .001) in the CNP group compared to controls. The levels of phosphatidylcholine, a metabolite of CHPT1 in the Kennedy Pathway, were significantly (p = .008) decreased in the plasma of patients with CNP. Given the relationship between the Kennedy pathway and endocannabinoids, plasma endocannabinoids and related N-acylethanolamines were quantified in clinical samples by HPLC-Tandem Mass Spectrometry. Plasma levels of the endocannabinoid 2-arachidonoylglycerol were higher in CNP samples compared to controls, and in the statistical models applied, 2-arachidonoylglycerol significantly increased the odds of CNP (p < .001). The expression of genes related to the synthesis and catabolism of endocannabinoids also corroborated the increased plasma 2-arachidonoylglycerol levels in patients with CNP. Endocannabinoid levels, expression of genes related to endocannabinoid metabolism, age, sex, depression and anxiety state together were strong predictors of CNP. The observed molecular changes indicate that lipid metabolism is altered in CNP and thus may represent a viable target for novel analgesics or biomarker development.

Abstract A008: Adaptive immune receptor repertoire characterization highlights the importance of interplay between B and T cells in disease progression

Abstract Understanding the adaptive immune system is integral to disease progression studies, development of diagnostic biomarkers, identification of therapeutic targets, and discerning varied treatment responses. Despite growing interest in profiling B and T cells in cancer research, the interaction between these cells and also the crucial roles of γδ T cells often go overlooked. In this research project, we explored the role of crucial yet frequently ignored γδ T cells in cancer research, using immune repertoire data from bladder cancer patients. We also studied the synergy between B and T cells in the immune repertoires of COVID-19 patients.Roche has developed immunoPETE (immune repertoire Primer Extension Target Enrichment), a DNA- based target enrichment assay to capture adaptive immune repertoire data*. immunoPETE efficiently identifies the heavy chains of B cells, alongside αβ and γδ T cells in one reaction, facilitating normalized clone counts across the adaptive immune system. To explore the significance of γδ T cells, we profiled the immune repertoires of 24 Non-Muscle Invasive Bladder Cancer patients treated with Bacillus Calmette-Guerin (BCG). Additionally, we evaluated the interplay between B and T cells in 117 peripheral blood immune repertoire from healthy and COVID-19 afflicted individuals, ranging from mild to severe cases.Immune repertoire data analysis indicates that underrepresentation of T cell receptor delta locus (TRD) is associated with higher risk of bladder cancer recurrence or progress. Urine pellet DNA was available for a subset of the patients in this study. Comparing immune repertoires from PBMC and urine revealed that urine repertoires represent the tumor repertoire more accurately than PBMC. Analysis of the immune repertoires from the COVID-19 patients linked disease severity with immune repertoire measures across all three cell types, highlighting the importance of multiple lymphocyte classes in disease progression. Using immunoPETE technology, which is capable of capturing the heavy chain of multiple immune cell types simultaneously in a single reaction, we have demonstrated that both B cell and T cell compartments provide distinct and valuable information in cancer and infectious diseases, each responding uniquely to the disease. Additionally, we emphasized the significance of γδ T cells in predicting cancer prognosis. Note: immunoPETE is for Research Use Only. Not for use in diagnostic procedures. Citation Format: Hossein Asgharian, Hamid Mirebrahim, Dilduz Telman, Hahn Zhao, Ulrich Schlecht, Sylvie McNamara, Rajiv Dua, Jan Berka, Patrick Bogard, Dinesh Kumar. Adaptive immune receptor repertoire characterization highlights the importance of interplay between B and T cells in disease progression [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 A008.

BIOM-64. EXPLOITING CELL-FREE DNA TO DISSECT MECHANISMS OF RESISTANCE TO TEMOZOLOMIDE IN GLIOBLASTOMA CELLS

Abstract Temozolomide (TMZ) is a cytotoxic alkylating agent that serves as a cornerstone in glioblastoma (GBM) treatment, yet is notorious for eliciting hypermutation in recurrent tumors that have developed drug resistance by downregulating mismatch repair (MMR). We reasoned that cell-free DNA (cfDNA), a non-invasive measure for detecting tumor-derived biomarkers, could be used to temporally examine the mechanism of resistance to TMZ. We therefore designed an in-vitro experiment using the patient-derived GBM43 cell line. Over five days, batches of cells were treated with either TMZ or vehicle. Cell counts and cfDNA were collected every 24 hours. We observed an associated increase in both dead cell counts and cfDNA yield in treated cells compared to untreated cells. In TMZ-treated samples, cfDNA showed a periodic fragmentation pattern consistent with internucleosomal cleavage and TMZ-induced apoptosis. Intriguingly, higher numbers of variants were found in the cfDNA of untreated samples when compared to treated cfDNA, possibly reflecting TMZ-induced selection of resistant subclones in treated samples. This was further supported by the finding that the average variant allele frequency (VAF) increased over time in TMZ-treated samples, consistent with purifying selection. Conversely, cfDNA from vehicle-treated samples demonstrated a decrease in the average VAF over time, consistent with clonal diversification. Although we did not observe an enrichment of the TMZ-associated mutational signature SBS11, we did find higher levels of defective MMR mutation signature SBS44 in treated samples, potentially indicating the selection of subclones with defective MMR mechanisms. Overall, our preliminary findings show that cfDNA can be used to resolve mechanisms of TMZ resistance over time. We are addressing open questions by performing longer treatment times, testing other patient-derived cell lines, and performing murine xenotransplantation experiments to test TMZ-associated hypermutation in vivo. Our work will contribute to our understanding of TMZ resistance, and importantly push the development of cfDNA-based biomarkers for measuring TMZ-sensitivity in patients.

Integrative ensemble modelling of cetuximab sensitivity in colorectal cancer patient-derived xenografts.

Patient-derived xenografts (PDXs) are tumour fragments engrafted into mice for preclinical studies. PDXs offer clear advantages over simpler in vitro cancer models - such as cancer cell lines (CCLs) and organoids - in terms of structural complexity, heterogeneity, and stromal interactions. Here, we characterise 231 colorectal cancer PDXs at the genomic, transcriptomic, and epigenetic levels, along with their response to cetuximab, an EGFR inhibitor used clinically for metastatic colorectal cancer. After evaluating the PDXs' quality, stability, and molecular concordance with publicly available patient cohorts, we present results from training, interpreting, and validating the integrative ensemble classifier CeSta. This model takes in input the PDXs' multi-omic characterisation and predicts their sensitivity to cetuximab treatment, achieving an area under the receiver operating characteristics curve > 0.88. Our study demonstrates that large PDX collections can be leveraged to train accurate, interpretable drug sensitivity models that: (1) better capture patient-derived therapeutic biomarkers compared to models trained on CCL data, (2) can be robustly validated across independent PDX cohorts, and (3) could contribute to the development of future therapeutic biomarkers.

EPCO-39. MULTIOMIC AND CLINICAL ANALYSIS OF MULTIPLY RECURRENT MENINGIOMAS REVEALS RISK FACTORS, UNDERLYING BIOLOGY, AND INSIGHTS INTO EVOLUTION

Abstract Although meningiomas, the most common primary brain tumor, are often effectively treated with surgery and radiation, an important subset of meningiomas behave aggressively and are characterized by treatment resistance and multiple recurrences. Prior work has yet to specifically study multiply recurrent meningiomas (MRMs), including whether they are molecularly distinct from non-recurrent meningiomas (NRMs) at initial diagnosis and whether the molecular features of MRMs evolve with subsequent recurrences. The objective of this study was to identify clinical and molecular features associated with MRMs and determine if longitudinal molecular changes occur in paired MRM samples. In this dual institution study, clinical parameters were collected for 1,186 meningioma patients. After propensity score matching, 31 MRMs were matched to 84 NRMs. Molecular sequencing including whole exome sequencing (n=44), EPIC bead chip methylation array (n=43), and RNA-sequencing (n=66) were performed. On multivariable binomial logistic regression, MRMs were significantly associated with male sex (P=0.012), subtotal resection (P=0.001), higher number of meningiomas on presentation (P=0.017), and histopathological sheeting (P=0.002). Multiomic analysis of primary meningiomas revealed MRMs exhibit greater global copy number alternations (CNA) (P=0.0113) and increased DNA methylation (P=0.0161). Integrated methylation profiling and RNA-sequencing identified candidate driver genes of MRMs. Among these genes, we demonstrate that knockdown of EDNRB, a locus with higher promoter methylation and decreased gene expression in MRMs, leads to increased meningioma cell proliferation, suggesting a tumor suppressor function. CNAs, subclonal evolution, and methylation profiles of MRMs did not significantly change from primary tumor to recurrence, even after radiation treatment, suggesting MRMs are molecularly aggressive from initial diagnosis. Overall, we identify several novel clinical and molecular risk factors associated with MRMs. MRMs harbor unique molecular features on presentation, which do not appear to change during evolution and after treatments, which has implications for development of biomarkers and therapeutic agents for these aggressive tumors.

TMET-13. SPATIAL METABOLOMIC CHANGES OF NUCLEOTIDE IN THE BRAINS OF ORTHOTOPIC MOUSE GLIOMA MODEL AFTER BORON NEUTRON CAPTURE THERAPY (BNCT)

Abstract Glioblastoma is the most lethal primary brain tumor. Boron Neutron Capture Therapy (BNCT) is a tumor-selective particle radiation therapy, in which high-LET α-particles and recoil 7Li are produced by the capture reaction between 10B and thermal neutrons and it has extended the prognosis of glioblastomas [Kawabata S, et al., Neuro-Oncology Advances 3(1), 1–9, 2021]. Augmented synthesis and use of nucleotide triphosphates is critical and universal metabolic dependency of tumor cells [Mullen, N.J., Singh, P.K. Nat Rev Cancer 23, 275–294 (2023)]. However, the effects of BNCT on metabolism of purine and pyrimidine in brain tumors and the surrounding normal brain are unknown. We spatially investigated metabolomic change in brains of orthotopic mouse glioma model, before and 2, 7, and 14 days after BNCT using mass spectrometry imaging (MSI). By separating tumor and non-tumor areas and performing Partial Least Squares Regression calculations, we have successfully visualized tumor-specific metabolites including adenine (ATP, ADP) and uridine (UTP, UDP-glucose, UDP-GlcNAc) with MSI. Of note, the signal of top-scored tumor specific metabolite, UDP-GlcNAc dramatically decreased and disappeared as the tumor regressed. Furthermore, the signal of ADP which was supposed to be released from tumor, colocalized with invading tumors along with corpus callosum. The value of adenylate energy charge, ([ATP]+0.5[ADP]/[ATP]+[ADP]+[AMP]) in the surrounding normal brain of the untreated tumor-bearing mouse increased up to 0.37 and decreased gradually down to 0.32 with BNCT, approaching to the value of normal control mouse brain, 0.27. These metabolomic changes reflected the tumor-killing effect and restoration of energy charge of surrounding normal brain by BNCT and have potential significance for development of biomarker or diagnosis.

Assessment of response to PRRT including anatomical and molecular imaging as well as novel biomarkers.

Peptide receptor radionuclide therapy (PRRT) is an effective treatment for both oncological and hormone control and is a widely accepted standard of care treatment for patients with neuroendocrine neoplasms (NEN). Its use is anticipated to increase significantly, and this demands accurate tools and paradigms to assess treatment response post PRRT. This article outlines the current role and future developments of anatomical, molecular imaging and biomarkers for response assessment to PRRT, highlighting the challenges and provides perspectives for the need to focus on a multimodality, multidisciplinary and individualised approach for patients with this complex heterogeneous disease.

Resting state functional magnetic resonance imaging in patients with multiple sclerosis before and after high-dose immunosuppressive therapy and autologous hemopoietic stem cell transplantation

BACKGROUND: Multiple sclerosis is a chronic autoimmune disease characterized by multifocal foci of demyelination in the central nervous system, usually affecting people of working age. The disease causes damage to the blood-brain barrier, the development of multifocal inflammation, destruction of the myelin sheath of axons and various degrees of damage. It is clinically manifested by restriction of motor activity, visual acuity, as well as other symptoms leading to loss of performance and disability of the patient. AIM: determination of changes in the functional connectivity of brain neural networks in patients with multiple sclerosis before and after high-dose immunosuppressive therapy and autologous hematopoietic stem cell transplantation by performing functional magnetic resonance imaging at rest. MATERIALS AND METHODS: The data of functional magnetic resonance imaging of patients with multiple sclerosis were analyzed in dynamics before and after the use of high-dose immunosuppressive therapy followed by autologous hematopoietic stem cell transplantation. The study involved 25 patients with a verified diagnosis of multiple sclerosis. Each underwent complex magnetic resonance imaging at two time points (before and after high-dose immunosuppressive therapy followed by autologous hematopoietic stem cell transplantation) with a difference of 12 months, which included structural magnetic resonance imaging - in order to exclude the presence of pathological foci in the brain (in addition to foci of multiple sclerosis) and functional magnetic resonance imaging.-resonance imaging at rest — to assess functional connectivity. Also, according to the method generally accepted in classical neurology, a clinical neurological examination was performed. RESULTS: At the stage of comparing data on the two groups obtained using functional magnetic resonance imaging at rest, changes in functional activity were detected in various parts of the brain, presumably responsible for clinical differences in the studied groups. CONCLUSION: Currently, the links between brain structures and morphological changes that cause cognitive impairment in multiple sclerosis are being studied. To predict the progression of the disease, the development of biomarkers, including those based on functional magnetic resonance imaging, is required. Evaluating changes in the functional connectivity of brain neural networks can help personalize therapeutic and rehabilitation approaches.

Genomic, epigenomic and transcriptomic inter- and intra-tumor heterogeneity in desmoid tumors.

Desmoid tumors are bland fibroblastic tumors that do not metastasize but have a high rate of local recurrence. Previously published studies proposed two different transcriptomic signatures to predict relapse. Molecular heterogeneity has been well established in high-grade sarcomas but little is known about molecular variability within locally aggressive tumors such as desmoids. We performed transcriptomic profiling of 31 specimens from 20 primary desmoid tumors to identify genes predictive of relapse. We also performed multi-omic analysis including DNA methylation, copy number alterations, point mutations and gene expression on 24 specimens from different regions of primary and recurrent desmoid tumors from 3 patients (7-9 specimens per patient). We observed highly variable expression of transcriptomic prognostic signatures, both in patients who did or did not progress. Signatures associated with favorable and unfavorable outcome were detected in different regions within the same tumor. Further multi-omic studies showed remarkable intra- and inter-tumor heterogeneity of genomic, epigenomic and transcriptomic patterns. The transcriptomic profiles showed the highest degree of variability within tumors and between primary and recurrent tumors from the same patient. This study shows an unexpected degree of intra- and inter-tumor heterogeneity in desmoid tumors. Our analysis indicates that molecular analysis of a single tumor biopsy may underestimate the magnitude of molecular alterations in desmoid tumors. Our study also shows that recurrent desmoid tumors acquire multiple new molecular alterations. Thus, molecular heterogeneity is an important consideration in drug development and validation of prognostic and predictive biomarkers for desmoid tumors.

Intercontinental Insights into Autism Spectrum Disorder: A Synthesis of Environmental Influences and DNA Methylation

Abstract Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder characterized by a broad range of symptoms. The etiology of ASD is thought to involve complex gene-environment interactions, which are crucial to understanding its various causes and symptoms. DNA methylation is an epigenetic mechanism that potentially links genetic predispositions to environmental factors in the development of ASD. This review provides a global perspective on ASD, focusing on how DNA methylation studies may reveal gene-environment interactions characteristic of specific geographical regions. It delves into the role of DNA methylation in influencing the causes and prevalence of ASD in regions where environmental influences vary significantly. We also address potential explanations for the high ASD prevalence in North America, considering lifestyle factors, environmental toxins, and diagnostic considerations. Asian and European studies offer insights into endocrine-disrupting compounds (EDC), persistent organic pollutants (POP), maternal smoking, and their associations with DNA methylation alterations in ASD. In areas with limited data on DNA methylation and ASD, such as Africa, Oceania, and South America, we discuss prevalent environmental factors based on epidemiological studies. Additionally, the review integrates global and country-specific prevalence data from various studies, providing a comprehensive picture of the variables influencing ASD diagnoses over region and year of assessment. This prevalence data, coupled with regional environmental variables and DNA methylation studies, provides a perspective on the complexities of ASD research. Integrating global prevalence data, we underscore the need for a comprehensive global understanding of ASD’s complex etiology. Expanded research into epigenetic mechanisms of ASD is needed, particularly in underrepresented populations and locations, to enhance biomarker development for diagnosis and intervention strategies for ASD that reflect the varied environmental and genetic landscapes worldwide.

Emerging Technologies for the Assessment of Natural Killer Cell Activity

Understanding natural killer (NK) cell functionality is essential in developing more effective immunotherapeutic strategies that can enhance patient outcomes, especially in the context of cancer treatment. This review provides a comprehensive overview of both traditional and novel techniques for evaluating NK cell functionality, focusing on multiparameter assays and spatial methods that illuminate NK cell interactions within their microenvironment. We discuss the significance of standardized assays for assessing NK cell function across various research and clinical settings, including cancer immunotherapy, infectious diseases, and transplantation. Key factors influencing NK cell functionality include the origin of the sample, target–effector ratios, the functional state of NK cells, and the impact of pre-treatment conditions and their natural aging effect on NK cell activity. By emphasizing the importance of selecting a suitable technique for reliable measurements, especially for longitudinal monitoring, this review aims to give an overview on techniques to measure NK cell functionality in vitro and show the interaction with their microenvironment cells by spatial imaging. Ultimately, our understanding of NK cell functionality could be critical to biomarker development, drug design, and understanding of disease progression in the field of oncology or infectious disease.

Serum microRNA Biomarker Expression in HIV and TB: A Concise Overview.

Non-coding RNAs (ncRNAs), specifically MicroRNAs or miRNAs, are now under-stood to be essential regulators in the complex field of gene expression. By selectively bind-ing to certain mRNA targets, these tiny RNA molecules control the expression of genes., leading to mRNA degradation or translational repression. The discovery of miRNAs has sig-nificantly advanced biomedical research, particularly in elucidating the molecular mecha-nisms underlying various diseases and exploring innovative therapeutic approaches. Recent progress in miRNA research has provided insights into their biogenesis, functional roles, and potential clinical applications. Despite the absence of established methodologies for clinical implementation, miRNAs show great promise as diagnostic and therapeutic agents for a wide array of diseases. Their distinctive attributes, such as high specificity, sensitivity, and accessibility, position them as ideal candidates for biomarker development and targeted therapy. Achieving a comprehensive understanding of miRNA biology and functionality is crucial to fully harnessing their potential in medicine. Ongoing research efforts aim to un-ravel the intricate mechanisms of miRNA-mediated gene regulation and to develop novel approaches for utilizing miRNAs in disease diagnosis, prognosis, and treatment. This review provides a comprehensive analysis of current knowledge on miRNAs, focusing on their bio-genesis, regulatory mechanisms, and potential clinical applications. By synthesizing existing evidence and highlighting key research findings, this review aims to inspire further explora-tion into the diverse roles of miRNAs in health and disease. Ultimately, this endeavour could result in the development of innovative miRNA-based diagnostic and therapeutic strategies.

REAL AD-Validation of a realistic screening approach for early Alzheimer's disease.

Early diagnosis is crucial to treatment success. This is especially relevant for Alzheimer's disease (AD), with its protracted preclinical phase. Most health care systems do not have the resources to conduct large-scale AD screenings in middle-aged individuals in need of novel AD treatment options and early, accurate diagnosis. Recent developments in blood-based biomarkers and remote cognitive testing offer novel, cost-effective, and scalable methods to detect cognitive and biomarker changes that may indicate early AD. In research cohorts, promising results have been reported, but these modalities have not been validated in population-based settings. The validation of a realistic screening approach for early Alzheimer's disease (REAL AD) study aims to validate the diagnostic and prognostic performance of the combined use of blood-based biomarkers and remote cognitive testing as a screening approach for early AD employing an existing health care infrastructure (the Swedish Västra Götaland Region Primary Healthcare). REAL AD aims to provide a concrete, individualized diagnostic framework, which could significantly improve AD prognosis. HIGHLIGHTS: In Sweden, most Alzheimer's disease (AD) diagnoses are made in primary care, where access to AD biomarkers is almost non-existent. Most health care systems have limited resources for the screening of middle-aged adults for early evidence of AD pathology. Blood-based biomarkers and remote cognitive testing offer novel, cost-effective, and scalable methods for detecting cognitive and biomarker changes that may indicate early AD. The REAL AD study aims to validate the diagnostic and prognostic performance of blood-based biomarkers and remote cognitive testing as a screening approach for early AD in an existing primary health care infrastructure in the Västra Götaland Region in Sweden. Studies such as REAL AD will play a vital role in helping to move the field toward concrete implementation of biomarkers in AD diagnostic workup at all care levels, eventually providing more comprehensive treatments options for the large and growing AD population, and for those at risk.

Identification of extracellular matrix proteins in plasma as a potential biomarker for intervertebral disc degeneration.

Recently, there has been significant focus on extracellular matrix proteolysis due to its importance in the pathological progression of intervertebral disc degeneration (IVDD). The present study investigates the circulating levels of extracellular matrix proteins in the plasma of IVDD and determines their potential relevance as biomarkers in disc degeneration. Global proteomic analysis was performed in the plasma samples of 10 healthy volunteers (HV) and 10 diseased subjects (DS) after depletion of highly abundant proteins such as albumin and IgG. We identified 144 and 135 matrix-associated proteins in plasma samples from healthy volunteers (HV) and patients with disc degeneration (DS), respectively. Among these, 49 of the matrix-associated proteins were identical to the proteins found in intervertebral disc (IVD) tissues retrieved from the in-house library. Applying stringent parameters, we selected 28 proteins, with 26 present in DS and 21 in HV. 19 proteins were found common between the groups, two of which-aggrecan (ACAN) and fibulin 1 (FBLN1) - showed statistically significant differences. Specifically, ACAN was up-regulated and FBLN1 was down-regulated in the DS-plasma. In particular, DS-plasma exhibited specific expression of collagen type 2a1 (COL2A1), native to the nucleus pulposus. The distinct presence of collagen type 2a1 and the elevated expression of aggrecan in IVDD plasma may serve as the basis for the development of a potential biomarker for monitoring the progression of disc degeneration.

Quantification of Replacement Fibrosis in Aortic Stenosis: A Narrative Review on the Utility of Cardiovascular Magnetic Resonance Imaging.

Aortic stenosis (AS) is associated with the development of replacement myocardial fibrosis/scar. Given the dose-dependent relationship between scar and clinical outcomes after aortic valve replacement (AVR) surgery, scar quantity may serve as an important risk-stratification tool to aid decision-making on the optimal timing of AVR. Scar is non-invasively assessed and quantified by cardiovascular magnetic resonance (CMR) imaging. Several quantification techniques exist, and consensus on the optimal technique is lacking. These techniques range from a visual manual method to fully automated ones. This review describes the different scar quantification techniques used and highlights their strengths and shortfalls within the context of AS. The two most commonly used techniques in AS include the semi-automated signal threshold versus reference mean (STRM) and full-width half-maximum (FWHM) techniques. The accuracy and reproducibility of these techniques may be hindered in AS by the coexistence of diffuse interstitial fibrosis and the presence of relatively small, non-bright scars. The validation of these techniques against histology, which is the current gold standard for scar quantification in AS, is limited. Based on the best current evidence, the STRM method using a threshold of three standard deviations above the mean signal intensity of remote myocardium is recommended. The high reproducibility of the FWHM technique in non-AS cohorts has been shown and merits further evaluation within the context of AS. Future directions include the use of quantitative T1 mapping for the detection and quantification of scar, as well as the development of serum biomarkers that reflect the fibrotic status of the myocardium in AS.

Analysis of population heterogeneity in CHO cells by genome-wide DNA methylation analysis and by multi-modal single-cell sequencing

CHO cells are major hosts for the industrial production of therapeutic proteins and their production stability is of considerable economic significance. It is widely known that CHO cells can rapidly acquire genetic alterations, which affects their genetic homogeneity over time. However, the role of non-genetic mechanisms, including epigenetic mechanisms such as DNA methylation, remains poorly understood. We have now used whole-genome bisulfite sequencing to establish single-base methylation maps of eight independent CHO cell lines. Our results identify CpG islands and low-methylated regions as conserved elements with dynamic DNA methylation. Interestingly, methylation patterns were found to cluster clearly along the three main branches of CHO evolution, with no directional changes over short culture periods. Furthermore, multi-ome single-cell sequencing of 9833 nuclei from three independent cultures revealed dynamic subpopulation structures characterized by robust expression differences in pathways related to protein production. Our findings thus provide novel insights into the epigenetic landscape and heterogeneity of CHO cells and support the development of epigenetic biomarkers that trace the emergence of subpopulations in CHO cultures.

AI-Enabled Ultra-large Virtual Screening Identifies Potential Inhibitors of Choline Acetyltransferase for Theranostic Purposes.

Alzheimer's disease (AD) and related dementias are among the primary neurological disorders and call for the urgent need for early-stage diagnosis to gain an upper edge in therapeutic intervention and increase the overall success rate. Choline acetyltransferase (ChAT) is the key acetylcholine (ACh) biosynthesizing enzyme and a legitimate target for the development of biomarkers for early-stage diagnosis and monitoring of therapeutic responses. It is also a theranostic target for tackling colon and lung cancers, where overexpression of non-neuronal ChAT leads to the production of acetylcholine, which acts as an autocrine growth factor for cancer cells. Theranostics is a hybrid of diagnostics and therapeutics that can be used to locate cancer cells using radiotracers and kill them without affecting other healthy tissues. Traditional virtual screening protocols have a lot of limitations; given the current rate of chemical database expansion exceeding billions, much faster screening protocols are required. Deep docking (DD) is one such platform that leverages the power of deep neural network (DNN)-based virtual screening, empowering researchers to dock billions of molecules in a speedy, yet explicit manner. Here, we have screened 1.3 billion compounds library from the ZINC20 database, identifying the best-performing hits. With each iteration run where the first iteration gave ∼116 million hits, the second iteration gave ∼3.7 million hits, and the final third iteration gave 168,447 hits from which further refinement gave us the top 5 compounds as potential ChAT inhibitors. The discovery of novel ChAT inhibitors will enable researchers to develop new probes that can be used as novel theranostic agents against cancer and as early-stage diagnostics for the onset of AD, for timely therapeutic intervention to halt the further progression of AD.