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Pathological Biomarkers in Precision Medicine
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Pathological Biomarkers in Precision Medicine

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cell Biology and Pathology".

Deadline for manuscript submissions: closed (31 October 2025) | Viewed by 34292

Special Issue Editors

Prof. Dr. Ovidiu Constantin Baltatu

E-Mail Website
Guest Editor
Center of Innovation, Technology and Education (CITE) at Anhembi Morumbi University—Anima Institute, Sao Jose dos Campos, Brazil
Interests: cardiovascular disease; innovative diagnostics; disease prevention strategies
Special Issues, Collections and Topics in MDPI journals
Dr. Mirela A. Dobre

E-Mail Website
Guest Editor
Division of Nephrology and Hypertension, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
Interests: nephrology; kidney disease
Dr. Tudor Groza

E-Mail Website
Guest Editor
Rare Care Centre, Perth Children's Hospital, Nedlands, WA 6009, Australia
Interests: natural language processing; knowledge graphs; ontologies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the dynamic landscape of precision medicine, this Special Issue seeks to comprehensively explore pathological biomarkers via multifaceted methods. The identification and validation of pathological biomarkers have emerged as critical components in tailoring therapeutic interventions for individual patients. This Special Issue invites contributions spanning a broad spectrum of research areas, including but not limited to the following:

  • Biomarker Discovery and Validation: Research focusing on the identification, validation, and clinical translation of pathological biomarkers for various diseases, such as cancer, cardiovascular disorders, neurodegenerative diseases, and infectious diseases.
  • Digital Biomarkers: Advancements in the identification and application of digital biomarkers, leveraging technologies for precise diagnostics and tailored therapeutic approaches.
  • Omics Data Integration: Innovations in integrating multi-omics data (genomics, transcriptomics, proteomics, metabolomics, and phenomics) and clinical data for a holistic understanding of disease mechanisms and personalized treatment strategies.
  • Digital Imaging Technologies: Advancements in medical imaging technologies, including radiomics, functional imaging, molecular imaging, computational pathology, and their role in refining diagnostics and biomarker detection.

We welcome original research articles and review papers that contribute to the deeper understanding of the importance of exploring more pathological biomarkers, with the ultimate goal of advancing precision medicine and improving patient outcomes.

Prof. Dr. Ovidiu Constantin Baltatu
Dr. Mirela A. Dobre
Dr. Tudor Groza
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • pathological biomarkers
  • precision medicine
  • artificial intelligence
  • medical imaging
  • omics data analysis
  • personalized medicine
  • biomarker discovery
  • digital pathology

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Published Papers (10 papers)

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Research

Jump to: Review

22 pages, 3713 KB  
Article
Exploratory Analysis of Autophagy–Lysosomal Pathway Proteins in Dermal Fibroblasts as Potential Peripheral Biomarkers for Alzheimer’s Disease: A Pilot Study
by Myung Shin Lee, Sang Joon Son, Juyeong Kim, Seungbeom Go, Chang Hyung Hong, Hyun Woong Roh and Jaerak Chang
Biomedicines 2026, 14(1), 34; https://doi.org/10.3390/biomedicines14010034 - 23 Dec 2025
Viewed by 270
Abstract
Background/Objectives: Alzheimer’s disease (AD) is characterized by accumulation of abnormal intracellular substances and autophagy–lysosomal pathway (ALP) dysfunction. While current diagnostic methods rely on cerebrospinal fluid biomarkers and neuroimaging, minimally invasive peripheral biomarkers are needed. Dermal fibroblasts could serve as accessible reporters of AD-related [...] Read more.
Background/Objectives: Alzheimer’s disease (AD) is characterized by accumulation of abnormal intracellular substances and autophagy–lysosomal pathway (ALP) dysfunction. While current diagnostic methods rely on cerebrospinal fluid biomarkers and neuroimaging, minimally invasive peripheral biomarkers are needed. Dermal fibroblasts could serve as accessible reporters of AD-related molecular changes. This exploratory pilot study investigated whether ALP-associated proteins in patient-derived fibroblasts could serve as potential peripheral biomarkers for AD diagnosis. Methods: We analyzed dermal fibroblasts from 9 AD patients (amyloid Positron emission tomography (PET)-positive) and 9 age-matched controls (amyloid PET-negative). Comprehensive immunoblot analysis assessed expression profiles of 16 AD- and ALP-associated proteins. Autophagic flux and lysosomal function were evaluated using bafilomycin A1 treatment and LysoTracker staining. Diagnostic performance was assessed through receiver operating characteristic (ROC) curve analysis and multivariable logistic regression. Results: AD fibroblasts showed significantly reduced Beta-site APP cleaving enzyme 1 (BACE1) (p = 0.022) and elevated Tax1-binding protein 1 (TAX1BP1) (p = 0.035) expression. BCL2-associated athanogene proteins 2 (BAG2) and OPTN demonstrated consistent directional changes across patients. Preliminary ROC analysis showed promising performance for protein combinations, with BAG2 + OPTN achieving Area under the curve (AUC) = 0.963 (sensitivity 77.8%, specificity 88.9%). Integration with Apolipoprotein E4 (APOE4) status further enhanced diagnostic accuracy (APOE4 + BACE1: AUC = 0.914). Notably, baseline autophagic flux and lysosomal acidification were preserved, suggesting pathway-specific rather than systemic ALP dysfunction. Conclusions: This exploratory study provides preliminary evidence that dermal fibroblast-derived ALP proteins show disease-associated alterations in AD and may represent potential peripheral biomarkers. However, given the small sample size (n = 18) and lack of independent validation, these findings require confirmation in larger multi-center cohorts before clinical translation. Full article
(This article belongs to the Special Issue Pathological Biomarkers in Precision Medicine)
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Graphical abstract

12 pages, 5027 KB  
Article
Clinical Utility of Multiplex Ligation-Dependent Probe Amplification in the Genetic Assessment of Patients with Myelodysplastic Syndrome
by Radostina Valeva, Maria Levkova, Dinnar Yahya, Mari Hachmeriyan and Ilina Micheva
Biomedicines 2025, 13(12), 2985; https://doi.org/10.3390/biomedicines13122985 - 5 Dec 2025
Viewed by 367
Abstract
Background/Objectives: Genetic abnormalities are critical for the diagnosis, prognosis, and therapeutic management of myelodysplastic syndromes (MDS). This study aims to evaluate the clinical utility of Multiplex Ligation-dependent Probe Amplification (MLPA) as a rapid and cost-effective method, determining its place alongside Next-Generation Sequencing [...] Read more.
Background/Objectives: Genetic abnormalities are critical for the diagnosis, prognosis, and therapeutic management of myelodysplastic syndromes (MDS). This study aims to evaluate the clinical utility of Multiplex Ligation-dependent Probe Amplification (MLPA) as a rapid and cost-effective method, determining its place alongside Next-Generation Sequencing (NGS) for the initial genetic assessment of patients with MDS. Methods: Bone marrow samples from 68 patients newly diagnosed with MDS were analyzed. Genomic DNA was investigated using the SALSA MLPA P414-C1 MDS probe mix to detect common copy number variations (CNVs). Results: MLPA detected genetic variants in 25 patients (36.8%). The most common finding was a single chromosomal abnormality (26.5%). Multiple pathological findings were observed in only 1.5% of patients, and a JAK2 mutation was observed in 8.8% of the cohort. However, the presence of these aberrations did not show a statistically significant association with overall survival (OS) in the cohort. Patient sex was identified as the only variable that was associated with a marginal level of statistical significance regarding OS, indicating a worse prognosis for males. Conclusions: MLPA is a valuable, rapid, and cost-effective tool for initial genetic screening in low-resource settings. This was highlighted by our finding that sex was the sole significant prognostic factor, while the MLPA-detected variants were not found to be significant. The findings suggest that comprehensive risk stratification aligned with international standards requires more advanced molecular technologies. Full article
(This article belongs to the Special Issue Pathological Biomarkers in Precision Medicine)
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23 pages, 2243 KB  
Article
Explaining Risk Stratification in Differentiated Thyroid Cancer Using SHAP and Machine Learning Approaches
by Mallika Khwanmuang, Watcharaporn Cholamjiak and Pasa Sukson
Biomedicines 2025, 13(12), 2964; https://doi.org/10.3390/biomedicines13122964 - 2 Dec 2025
Viewed by 539
Abstract
Background/Objectives: Differentiated thyroid cancer (DTC) represents over 90% of all hyroid malignancies and typically has a favorable prognosis. However, approximately 30% of patients experience recurrence within 10 years after initial treatment. Conventional risk classification frameworks such as the American Thyroid Association (ATA) [...] Read more.
Background/Objectives: Differentiated thyroid cancer (DTC) represents over 90% of all hyroid malignancies and typically has a favorable prognosis. However, approximately 30% of patients experience recurrence within 10 years after initial treatment. Conventional risk classification frameworks such as the American Thyroid Association (ATA) and AJCC TNM systems rely heavily on pathological interpretation, which may introduce observer variability and incomplete documentation. This study aimed to develop an interpretable machine-learning framework for risk stratification in DTC and to identify major clinical predictors using SHapley Additive exPlanations (SHAP). Methods: A retrospective dataset of 345 patients was obtained from the UCI Machine Learning Repository. Thirteen clinicopathological features were analyzed, including Age, Gender, T, N, M, Hx Radiotherapy, Focality, Adenopathy, Pathology, and Response. Statistical analysis and feature selection (ReliefF and mRMR) were applied to identify the most influential variables. Two modeling scenarios were tested using an optimizable neural network classifier: (1) all 10 core features and (2) reduced features selected from machine learning criteria. SHAP analysis was used to explain model predictions and determine feature impact for each risk category. Results: Reducing the input features from 10 to 6 led to improved performance in the explainable neural network model (AUC = 0.94, accuracy = 92%), confirming that T, N, Response, Age, M, and Hx Radiotherapy were the most informative predictors. SHAP analysis highlighted N and T as the dominant drivers of high-risk classification, while Response enhanced postoperative biological interpretation. Notably, when Response was excluded (Scenario III), the optimizable tree model still achieved strong predictive performance (AUC = 0.93–0.96), demonstrating that accurate preoperative risk estimation can be achieved using only clinical baseline features. Conclusions: The proposed interpretable neural network model effectively stratifies recurrence risk in DTC while reducing dependence on subjective pathological interpretation. SHAP-based feature attribution enhances clinical transparency, supporting integration of explainable machine learning into thyroid cancer follow-up and personalized management. Full article
(This article belongs to the Special Issue Pathological Biomarkers in Precision Medicine)
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15 pages, 766 KB  
Article
Photobiomodulation Therapy Reduces Oxidative Stress and Inflammation to Alleviate the Cardiotoxic Effects of Doxorubicin in Human Stem Cell-Derived Ventricular Cardiomyocytes
by Guilherme Rabelo Nasuk, Leonardo Paroche de Matos, Allan Luís Barboza Atum, Bruna Calixto de Jesus, Julio Gustavo Cardoso Batista, Gabriel Almeida da Silva, Antonio Henrique Martins, Maria Laura Alchorne Trivelin, Cinthya Cosme Gutierrez Duran, Ana Paula Ligeiro de Oliveira, Renato de Araújo Prates, Rodrigo Labat Marcos, Stella Regina Zamuner, Ovidiu Constantin Baltatu and José Antônio Silva, Jr.
Biomedicines 2025, 13(7), 1781; https://doi.org/10.3390/biomedicines13071781 - 21 Jul 2025
Viewed by 1608
Abstract
Background/Objectives: Doxorubicin (DOX), a widely used anthracycline chemotherapeutic agent, is recognized for its efficacy in treating various malignancies. However, its clinical application is critically limited due to dose-dependent cardiotoxicity, predominantly induced by oxidative stress and compromised antioxidant defenses. Photobiomodulation (PBM), a non-invasive intervention [...] Read more.
Background/Objectives: Doxorubicin (DOX), a widely used anthracycline chemotherapeutic agent, is recognized for its efficacy in treating various malignancies. However, its clinical application is critically limited due to dose-dependent cardiotoxicity, predominantly induced by oxidative stress and compromised antioxidant defenses. Photobiomodulation (PBM), a non-invasive intervention that utilizes low-intensity light, has emerged as a promising therapeutic modality in regenerative medicine, demonstrating benefits such as enhanced tissue repair, reduced inflammation, and protection against oxidative damage. This investigation sought to evaluate the cardioprotective effects of PBM preconditioning in human-induced pluripotent stem cell-derived ventricular cardiomyocytes (hiPSC-vCMs) subjected to DOX-induced toxicity. Methods: Human iPSC-vCMs were allocated into three experimental groups: control cells (untreated), DOX-treated cells (exposed to 2 μM DOX for 24 h), and PBM+DOX-treated cells (preconditioned with PBM, utilizing 660 nm ±10 nm LED light at an intensity of 10 mW/cm2 for 500 s, delivering an energy dose of 5 J/cm2, followed by DOX exposure). Cell viability assessments were conducted in conjunction with evaluations of oxidative stress markers, including antioxidant enzyme activities and malondialdehyde (MDA) levels. Furthermore, transcriptional profiling of 40 genes implicated in cardiac dysfunction was performed using TaqMan quantitative polymerase chain reaction (qPCR), complemented by analyses of protein expression for markers of cardiac stress, inflammation, and apoptosis. Results: Exposure to DOX markedly reduced the viability of hiPSC-vCMs. The cells exhibited significant alterations in the expression of 32 out of 40 genes (80%) after DOX exposure, reflecting the upregulation of markers associated with apoptosis, inflammation, and adverse cardiac remodeling. PBM preconditioning partially restored the cell viability, modulating the expression of 20 genes (50%), effectively counteracting a substantial proportion of the dysregulation induced by DOX. Notably, PBM enhanced the expression of genes responsible for antioxidant defense, augmented antioxidant enzyme activity, and reduced oxidative stress indicators such as MDA levels. Additional benefits included downregulating stress-related mRNA markers (HSP1A1 and TNC) and apoptotic markers (BAX and TP53). PBM also demonstrated gene reprogramming effects in ventricular cells, encompassing regulatory changes in NPPA, NPPB, and MYH6. PBM reduced the protein expression levels of IL-6, TNF, and apoptotic markers in alignment with their corresponding mRNA expression profiles. Notably, PBM preconditioning showed a diminished expression of BNP, emphasizing its positive impact on mitigating cardiac stress. Conclusions: This study demonstrates that PBM preconditioning is an effective strategy for reducing DOX-induced chemotherapy-related cardiotoxicity by enhancing cell viability and modulating signaling pathways associated with oxidative stress, as well as inflammatory and hypertrophic markers. Full article
(This article belongs to the Special Issue Pathological Biomarkers in Precision Medicine)
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17 pages, 1030 KB  
Article
Analysis of Brain Age Gap across Subject Cohorts and Prediction Model Architectures
by Lara Dular, Žiga Špiclin, for the Alzheimer’s Disease Neuroimaging Initiative and the Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing
Biomedicines 2024, 12(9), 2139; https://doi.org/10.3390/biomedicines12092139 - 20 Sep 2024
Cited by 6 | Viewed by 4139
Abstract
Background: Brain age prediction from brain MRI scans and the resulting brain age gap (BAG)—the difference between predicted brain age and chronological age—is a general biomarker for a variety of neurological, psychiatric, and other diseases or disorders. Methods: This study examined the differences [...] Read more.
Background: Brain age prediction from brain MRI scans and the resulting brain age gap (BAG)—the difference between predicted brain age and chronological age—is a general biomarker for a variety of neurological, psychiatric, and other diseases or disorders. Methods: This study examined the differences in BAG values derived from T1-weighted scans using five state-of-the-art deep learning model architectures previously used in the brain age literature: 2D/3D VGG, RelationNet, ResNet, and SFCN. The models were evaluated on healthy controls and cohorts with sleep apnea, diabetes, multiple sclerosis, Parkinson’s disease, mild cognitive impairment, and Alzheimer’s disease, employing rigorous statistical analysis, including repeated model training and linear mixed-effects models. Results: All five models consistently identified a statistically significant positive BAG for diabetes (ranging from 0.79 years with RelationNet to 2.13 years with SFCN), multiple sclerosis (2.67 years with 3D VGG to 4.24 years with 2D VGG), mild cognitive impairment (2.13 years with 2D VGG to 2.59 years with 3D VGG), and Alzheimer’s dementia (5.54 years with ResNet to 6.48 years with SFCN). For Parkinson’s disease, a statistically significant BAG increase was observed in all models except ResNet (1.30 years with 2D VGG to 2.59 years with 3D VGG). For sleep apnea, a statistically significant BAG increase was only detected with the SFCN model (1.59 years). Additionally, we observed a trend of decreasing BAG with increasing chronological age, which was more pronounced in diseased cohorts, particularly those with the largest BAG, such as multiple sclerosis (−0.34 to −0.2), mild cognitive impairment (−0.37 to −0.26), and Alzheimer’s dementia (−0.66 to −0.47), compared to healthy controls (−0.18 to −0.1). Conclusions: Consistent with previous research, Alzheimer’s dementia and multiple sclerosis exhibited the largest BAG across all models, with SFCN predicting the highest BAG overall. The negative BAG trend suggests a complex interplay of survival bias, disease progression, adaptation, and therapy that influences brain age prediction across the age spectrum. Full article
(This article belongs to the Special Issue Pathological Biomarkers in Precision Medicine)
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Review

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41 pages, 5959 KB  
Review
Biomarker-Driven Approaches to Bone Metastases: From Molecular Mechanisms to Clinical Applications
by Youssef Elshimy, Abdul Rahman Alkhatib, Bilal Atassi and Khalid S. Mohammad
Biomedicines 2025, 13(5), 1160; https://doi.org/10.3390/biomedicines13051160 - 10 May 2025
Cited by 4 | Viewed by 5124
Abstract
Bone metastases represent a critical complication in oncology, frequently indicating advanced malignancy and substantially reducing patient quality of life. This review provides a comprehensive analysis of the complex interactions between tumor cells and the bone microenvironment, emphasizing the relevance of the “seed and [...] Read more.
Bone metastases represent a critical complication in oncology, frequently indicating advanced malignancy and substantially reducing patient quality of life. This review provides a comprehensive analysis of the complex interactions between tumor cells and the bone microenvironment, emphasizing the relevance of the “seed and soil” hypothesis, the RANK/RANKL/OPG signaling axis, and Wnt signaling pathways that collectively drive metastatic progression. The molecular and cellular mechanisms underlying the formation of osteolytic and osteoblastic lesions are examined in detail, with a particular focus on their implications for bone metastases associated with breast, prostate, lung, and other cancers. A central component of this review is the categorization of pathological biomarkers into four types: diagnostic, prognostic, predictive, and monitoring. We provide a comprehensive evaluation of circulating tumor cells (CTCs), bone turnover markers (such as TRACP-5b and CTX), advanced imaging biomarkers (including PET/CT and MRI), and novel genomic signatures. These biomarkers offer valuable insights for early detection, enhanced risk stratification, and optimized therapeutic decision-making. Furthermore, emerging strategies in immunotherapy and bone-targeted treatments are discussed, highlighting the potential of biomarker-guided precision medicine to enhance personalized patient care. The distinctiveness of this review lies in its integrative approach, combining fundamental pathophysiological insights with the latest developments in biomarker discovery and therapeutic innovation. By synthesizing evidence across various cancer types and biomarker categories, we provide a cohesive framework aimed at advancing both the scientific understanding and clinical management of bone metastases. Full article
(This article belongs to the Special Issue Pathological Biomarkers in Precision Medicine)
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17 pages, 805 KB  
Review
Personalized Nutrition in Chronic Kidney Disease
by Nishigandha Pradhan, Jennifer Kerner, Luciana A. Campos and Mirela Dobre
Biomedicines 2025, 13(3), 647; https://doi.org/10.3390/biomedicines13030647 - 6 Mar 2025
Cited by 5 | Viewed by 9296
Abstract
A personalized approach to nutrition in patients with chronic kidney disease (CKD) represents a promising paradigm shift in disease management, moving beyond traditional one-size-fits-all dietary recommendations. Patients with CKD often have other comorbidities and face unique nutritional challenges, including protein-energy wasting (PEW), sarcopenia, [...] Read more.
A personalized approach to nutrition in patients with chronic kidney disease (CKD) represents a promising paradigm shift in disease management, moving beyond traditional one-size-fits-all dietary recommendations. Patients with CKD often have other comorbidities and face unique nutritional challenges, including protein-energy wasting (PEW), sarcopenia, and impaired renal excretion of nutrients, which complicate dietary planning. Current guidelines focus primarily on nutrient restrictions—such as limiting protein, sodium, potassium, and phosphorus. However, these generalized recommendations often result in suboptimal adherence and outcomes. Personalized nutrition, which adapts dietary recommendations to individual characteristics, such as genotype, phenotype, and socio-cultural preferences, has gained traction across various chronic diseases. However, its application in nephrology remains underexplored, and despite promising results from studies such as Food4Me, questions remain about the real-world impact of such strategies. The aims of this review are (1) to summarize the evidence on the current state of nutritional recommendations in CKD, (2) to discuss the emerging role of multi-omics approaches in informing personalized nutrition advice in CKD, and (3) to provide an opinion on nutritional challenges faced by patients with CKD and the importance of collaboration with the renal dietician. We conclude that despite barriers, such as the cost and data integration, personalized nutrition holds the potential to improve CKD outcomes, enhance quality of life, and empower patients through tailored dietary strategies for better disease management. Full article
(This article belongs to the Special Issue Pathological Biomarkers in Precision Medicine)
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21 pages, 1883 KB  
Review
Non-Invasive Retinal Biomarkers for Early Diagnosis of Alzheimer’s Disease
by Snježana Kaštelan, Antonela Gverović Antunica, Velibor Puzović, Ana Didović Pavičić, Samir Čanović, Petra Kovačević, Pia Antonia Franciska Vučemilović and Suzana Konjevoda
Biomedicines 2025, 13(2), 283; https://doi.org/10.3390/biomedicines13020283 - 24 Jan 2025
Cited by 7 | Viewed by 6178
Abstract
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder of the brain associated with ageing and is the most prevalent form of dementia, affecting an estimated 55 million people worldwide, with projections suggesting this number will exceed 150 million by 2050. With its increasing [...] Read more.
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder of the brain associated with ageing and is the most prevalent form of dementia, affecting an estimated 55 million people worldwide, with projections suggesting this number will exceed 150 million by 2050. With its increasing prevalence, AD represents a significant global health challenge with potentially serious social and economic consequences. Diagnosing AD is particularly challenging as it requires timely recognition. Currently, there is no effective therapy for AD; however, certain medications may help slow its progression. Existing diagnostic methods such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and biomarker analysis in cerebrospinal fluid tend to be expensive and invasive, making them impractical for widespread use. Consequently, research into non-invasive biomarkers that enable early detection and screening for AD is a crucial area of contemporary clinical investigation. One promising approach for the early diagnosis of AD may be retinal imaging. As an extension of the central nervous system, the retina offers a distinctive opportunity for non-invasive brain structure and function assessment. Considering their shared embryological origins and the vascular and immunological similarities between the eye and brain, alterations in the retina may indicate pathological changes in the brain, including those specifically related to AD. Studies suggest that structural and vascular changes in the retina, particularly within the neuronal network and blood vessels, may act as markers of cerebral changes caused by AD. These retinal alterations have the potential to act as biomarkers for early diagnosis. Since AD is typically diagnosed only after a significant neuronal loss has occurred, identifying early diagnostic markers could enable timely intervention and help prevent disease progression. Non-invasive retinal imaging techniques, such as optical coherence tomography (OCT) and OCT angiography, provide accessible methods for the early detection of changes linked to AD. This review article focuses on the potential of retinal imaging as a non-invasive biomarker for early diagnosis of AD. Investigating the ageing of the retina and its connections to neurodegenerative processes could significantly enhance the diagnosis, monitoring, and treatment of AD, paving the way for new diagnostic and therapeutic approaches. Full article
(This article belongs to the Special Issue Pathological Biomarkers in Precision Medicine)
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18 pages, 4077 KB  
Review
Mucins as Precision Biomarkers in Glioma: Emerging Evidence for Their Potential in Biospecimen Analysis and Outcome Prediction
by Anna Erickson, Luke R. Jackson, Kevin Camphausen and Andra V. Krauze
Biomedicines 2024, 12(12), 2806; https://doi.org/10.3390/biomedicines12122806 - 11 Dec 2024
Cited by 2 | Viewed by 1916
Abstract
Despite attempts at improving survival by employing novel therapies, progression in glioma is nearly universal. Precision biomarkers are critical to advancing outcomes; however, biomarkers for glioma are currently unknown. Most data on which the field can draw for biomarker identification comprise tissue-based analysis [...] Read more.
Despite attempts at improving survival by employing novel therapies, progression in glioma is nearly universal. Precision biomarkers are critical to advancing outcomes; however, biomarkers for glioma are currently unknown. Most data on which the field can draw for biomarker identification comprise tissue-based analysis requiring the biospecimen to be removed from the tumor. Non-invasive specimen-based precision biomarkers are needed. Mucins are captured in tissue and blood and are increasingly studied in cancer, with several studies exploring their role as biomarkers to detect disease and monitor disease progression. CA125, also known as MUC16, is implemented as a biomarker in the clinic for ovarian cancer. Similarly, several mucins are membrane-bound, facilitating downstream signaling associated with tumor resistance and hallmarks of cancer. Evidence supports mucin expression in glioma cells with relationships to tumor detection, progression, resistance, and patient outcomes. The differential expression of mucins across tissues and organs could also provide a means of attributing signals measured in serum or plasma. In this review, we compiled existing research on mucins as candidate precision biomarkers in glioma, focusing on promising mucins in relationship to glioma and leading to a framework for mucin analysis in biospecimens as well as avenues for validation as data evolve. Full article
(This article belongs to the Special Issue Pathological Biomarkers in Precision Medicine)
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14 pages, 1568 KB  
Review
Evaluation of PAGE-B Score for Hepatocellular Carcinoma Development in Chronic Hepatitis B Patients: Reliability, Validity, and Responsiveness
by Evanthia Tourkochristou, Maria Kalafateli, Christos Triantos and Ioanna Aggeletopoulou
Biomedicines 2024, 12(6), 1260; https://doi.org/10.3390/biomedicines12061260 - 5 Jun 2024
Cited by 1 | Viewed by 3198
Abstract
Chronic hepatitis B (CHB) constitutes a major global public health issue, affecting millions of individuals. Despite the implementation of robust vaccination programs, the hepatitis B virus (HBV) significantly influences morbidity and mortality rates. CHB emerges as one of the leading causes of hepatocellular [...] Read more.
Chronic hepatitis B (CHB) constitutes a major global public health issue, affecting millions of individuals. Despite the implementation of robust vaccination programs, the hepatitis B virus (HBV) significantly influences morbidity and mortality rates. CHB emerges as one of the leading causes of hepatocellular carcinoma (HCC), introducing a major challenge in the effective management of CHB patients. Therefore, it is of utmost clinical importance to diligently monitor individuals with CHB who are at high risk of HCC development. While various prognostic scores have been developed for surveillance and screening purposes, their accuracy in predicting HCC risk may be limited, particularly in patients under treatment with nucleos(t)ide analogues. The PAGE-B model, incorporating age, gender, and platelet count, has exhibited remarkable accuracy, validity, and reliability in predicting HCC occurrence among CHB patients receiving HBV treatment. Its predictive performance stands out, whether considered independently or in comparison to alternative HCC risk scoring systems. Furthermore, the introduction of targeted adjustments to the calculation of the PAGE-B score might have the potential to further improve its predictive accuracy. This review aims to evaluate the efficacy of the PAGE-B score as a dependable tool for accurate prediction of the development of HCC in CHB patients. The evidence discussed aims to provide valuable insights for guiding recommendations on HCC surveillance within this specific population. Full article
(This article belongs to the Special Issue Pathological Biomarkers in Precision Medicine)
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