Expert Review of Molecular Diagnostics最新文献

Introduction: Accurate prediction of short-term mortality is crucial for optimizing clinical prognosis and providing treatment decisions. Conventional metrics, including physiological indicators, laboratory indexes and scoring systems, suffer from limitations in comprehensiveness, accuracy, and dynamism. In contrast, the metabolomic aging score, as an emerging biomarker, offers substantial promise in short-term mortality prediction.

Areas covered: By integrating multiple metabolites associated with aging and mortality, the score captures dynamic metabolic shifts, providing a real-time reflection of an individual's health status. This approach enables a more precise assessment of short-term mortality risk across diverse diseases, setting it apart from traditional, disease-specific biomarkers. In addition, the metabolic aging score also shows great application prospects in identifying susceptible populations and providing individualized precision medication. This article discusses the novel role of the metabolomic aging score in mortality prediction, highlighting its superior accuracy compared to conventional metrics.

Expert opinion: This score has broad application prospects in the future and also faces challenges such as large-scale validation and standardization. Furthermore, the integration of artificial intelligence (AI) is poised to enhance the clinical utility of the metabolomic aging score, advancing its potential to transform healthcare practices.

Introduction: Pancreatic Cancer (PC) is a highly aggressive tumor that is mainly diagnosed at later stages. Various imaging technologies, such as CT, MRI, and EUS, possess limitations in early PC diagnosis. Therefore, this review article explores the various innovative biomarkers for PC detection, such as DNA methylation, Noncoding RNAs, and proteomic biomarkers, and the role of AI in PC detection at early stages.

Area covered: Innovative biomarkers, such as DNA methylation genes, show higher specificity and sensitivity in PC diagnosis. Additionally, various non-coding RNAs, such as long non-coding RNAs (lncRNAs) and microRNAs, show high diagnostic accuracy and serve as diagnostic and prognostic biomarkers. Additionally, proteomic biomarkers retain higher diagnostic accuracy in different body fluids. Apart from this, the utilization of AI showed that AI surpassed the radiologist's diagnostic performance in PC detection.

Expert opinion: The combination of AI and advanced biomarkers can revolutionize early PC detection. However, large-scale, prospective studies are needed to validate its clinical utility. Further. standardization of biomarker panels and AI algorithms is a vital step toward their reliable applications in early PC detection, ultimately improving patient outcomes. [Figure: see text].

Introduction: Biomarkers have transformed fungal diagnostics by enabling early detection, risk assessment and treatment monitoring. Their clinical value depends on factors e.g. sensitivity, specificity, host immune status and technical standardization.

Area covered: This review covers antigen- and DNA-based methods for detecting invasive fungal infections, focusing on Aspergillus spp., Candida spp. and Mucorales.

Expert opinion: The selection of fungal biomarkers should be tailored to patient populations, clinical setting, and suspected infections. Combining biomarkers enhances diagnostic accuracy, particularly in high-risk patients. While biomarkers indicate fungal presence, they support diagnosis and guide decisions, but must be interpreted alongside clinical context and guidelines (EORTC/MSG). [Figure: see text].

Introduction: Saliva has emerged as an important biological fluid for diagnostics, particularly hormone analysis. Its noninvasive collection and accessibility make it a compelling alternative to traditional blood-based diagnostics, enabling detection of biomarkers reflecting physiological and pathological conditions.

Areas covered: This review examines hormones measurable in saliva, including cortisol, testosterone, progesterone, estradiol, dehydroepiandrosterone (DHEA), and others. It highlights methods such as Enzyme-Linked Immunosorbent Assay (ELISA), Radioimmunoassay, and Liquid Chromatography coupled with Tandem Mass Spectrometry (LC-MS/MS) for hormonal analysis, focusing on their sensitivity and challenges. The discussion addresses the advantages and limitations of saliva as a diagnostic medium, including practicality and susceptibility to external influences. Clinical applications are explored, including stress monitoring, hormonal dysfunction diagnosis, and applications in personalized medicine.

Expert opinion: Salivary diagnostics holds significant potential in clinical and research contexts, particularly for hormone analysis. Despite challenges such as hormonal variability and technical limitations, advances are steadily overcoming these barriers. The noninvasive and accessible nature of saliva collection positions it as a promising medium for diagnostic innovation. Continued research, coupled with standardization of techniques, will be critical to fully harnessing saliva-based diagnostics for advancing personalized medicine, influencing the detection, diagnosis, and prognosis of certain conditions.

Introduction: The aim of this review is to summarize the advances of the last 5 years in the field of biomarker-guided therapeutic approach in sepsis through prognostic, predictive, and adaptive enrichment strategies.

Areas covered: A thorough search of the literature was done based on the existing biomarkers for which clinical trials of integration in the inclusion criteria are available. The authors reviewed the accessible completed and ongoing studies, which use IL-6, ferritin, IL-7, sTREM-1, IL-15, HLA-DR, DPP-3 and/or bioADM for diagnosis of sepsis or septic shock, prognosis of outcome of interest or/and personalized treatment tailored to each patient's endotype classification.

Expert opinion: Inconclusive sepsis trial outcomes highlight the need for strategic protocol design, patient stratification, and biomarker-guided immunomodulatory therapies. Future advancements should focus on real-time biomarker monitoring, personalized treatment, and point-of-care diagnostics to optimize therapeutic efficacy and patient outcomes.

Background: Ameloblastic carcinoma (AC), malignancy originating from the odontogenic epithelium, shows histological overlap with ameloblastoma (AM). In order to unravel mechanisms driving AC, it is imperative to understand the molecular distinction between these two entities. This systematic review aims to highlight molecular and immunohistochemical markers involved in the pathogenesis of AC and to distinguish it from its histological mimic, AM.

Research design and methods: Literature search across three databases including PubMed, Web of Sciences, and Scopus was carried out from year 1999 to 2023 for original human case control studies involving AM, AC, and controls as study groups. Various biological markers studied in the literature were grouped based on principal molecular pathways. Joanna Briggs Institute (JBI), a critical appraisal tool for case control studies, was used to assess the risk of bias (RoB).

Results: Out of the 277 studies identified during the initial search, 28 studies were found eligible. These studies reported expression of various immunohistochemical (IHC), genetic and epigenetic markers in AC, AM, and controls through immunohistochemistry and gene sequencing.

Conclusion: Stem cells, epigenetics, and growth factors define the pathways involved in pathogenesis of AC and may prove to be a potential therapeutic target in the future.

Introduction: Encephalitis has a broad etiology, including infectious and auto-immune causes. In infectious encephalitis, the breadth of causative organisms results in incomplete testing and low diagnostic yields.Metagenomics sequences all DNA and RNA allowing untargeted detection of all organisms in a single specimen; this is of particular use in diagnosis of encephalitis with a broad etiology.

Areas covered: We review the literature and discuss metagenomics workflows, host depletion and pathogen enrichment methods, bioinformatics analysis and potential analysis of the host transcriptome to aid diagnosis. We discuss the clinical use of metagenomics for diagnosis of neurological infection including time to result, cost, quality assurance, patient cohorts in whom metagenomics adds the most value, recommended specimen types, limitations and review published cases in which metagenomics has been used to diagnose encephalitis.

Expert opinion: There is good evidence for the utility of metagenomics to diagnose infection in encephalitis. Due to infections with rare, unexpected or novel pathogens, metagenomics adds most value to diagnosis in immunocompromised patients and the greatest diagnostic yield is in brain biopsies. Technical advances are needed to reduce the complexity, cost and time to result which will enable wider adoption in clinical laboratories and use as a first-line test.

Introduction: In recent years, circulating tumor DNA (ctDNA) has emerged as a promising method for detection of minimal or molecular residual disease (MRD) among patients with breast cancer.

Areas covered: In this narrative review, we provide a summary of currently available studies assessing use of ctDNA in detection of MRD in patients after completion of curative therapy. Additionally, we discuss limitations of present studies, future considerations, and an overview of ongoing trials evaluating the clinical utility of MRD-directed therapy interventions.

Expert opinion: While the clinical utility of MRD-directed therapy guidance remains under investigation, collective data from studies overwhelmingly confirm the prognostic value of ctDNA status across various stages and subtypes of breast cancer. Results from ongoing clinical trials in the coming years will provide more clarity on the overall clinical benefit of MRD-directed interventions for breast cancer patients.