Mass spectrometry analysis of human tear fluid biomarkers specific for ocular and systemic diseases in the context of 3P medicine

Tear Protein Markers for Diabetic Retinopathy and Diabetic Macular Edema - Towards an Early Diagnosis and Better Prognosis

BACKGROUND

Diabetic eye disease is a highly prevalent and sight-threatening disorder. It is a disease of neuro-vascular unit of the retina, if left untreated can cause blindness. Therapeutic approaches followed for its treatment can only restrict the progression of the disease with highly variable results. There is no known biomarker for an early diagonsis of this disease, therefore by the time it is detected it goes beyond repair. This creates a massive demand for development of such biomarkers that help detect disease in its earlier stages.

METHODS

PUBMED (https://pubmed.ncbi.nlm.nih.gov/) was searched for articles relevant to the topic published till November 2023. The search was made using keywords such as Diabetic Retinopathy, inflammation, tear, biomarker, proteomics etc. The studies providing relevant information to prove the importance of biomarker discovery were chosen. After compiling the data, the manuscript writing was planned under relevant headings and sub-headings.

RESULTS

The review provides a comprehensive overview of all the tear protein biomarker studies in the field of DR and DME. Briefly, their potential in other diseases is also elucidated. While there are many studies pertaining to DR biomarkers, the identified markers lack validations which has restricted their usage in clinics. In case of DME, there was no such study towards biomarker discovery for its diagnosis and prognosis.

CONCLUSIONS

The review highlights major studies and their lacunae in the field of biomarkers discovery for DR and DME.

Tear biomarkers

An extensive exploration of lacrimal fluid molecular biomarkers in understanding and diagnosing a spectrum of ocular and systemic diseases is presented. The chapter provides an overview of lacrimal fluid composition, elucidating the roles of proteins, lipids, metabolites, and nucleic acids within the tear film. Pooled versus single-tear analysis is discussed to underline the benefits and challenges associated with both approaches, offering insights into optimal strategies for tear sample analysis. Subsequently, an in-depth analysis of tear collection methods is presented, with a focus on Schirmer's test strips and microcapillary tubes methods. Alternative tear collection techniques are also explored, shedding light on their applicability and advantages. Variability factors, including age, sex, and diurnal fluctuations, are examined in the context of their impact on tear biomarker analysis. The main body of the chapter is dedicated to discussing specific biomarkers associated with ocular discomfort and a wide array of ocular diseases. From dry eye disease and thyroid-associated ophthalmopathy to keratoconus, age-related macular degeneration, diabetic retinopathy, and glaucoma, the intricate relationship between molecular biomarkers and these conditions is thoroughly dissected. Expanding beyond ocular pathologies, the chapter explores the applicability of tear biomarkers in diagnosing systemic diseases such as multiple sclerosis, amyotrophic lateral sclerosis, Alzheimer's disease, Parkinson's disease, and cancer. This broader perspective underscores the potential of lacrimal fluid analysis in offering non-invasive diagnostic tools for conditions with far-reaching implications.

Comparative analysis of human tear fluid and aqueous humor proteomes

PURPOSE

Technological advancements allowing for the analysis of low-volume samples have led to the investigation of human tear fluid and aqueous humor (AH) as potential biomarker sources. However, acquiring AH samples poses significant challenges, making human tear fluid a more accessible alternative. This study aims to compare the protein compositions of these two biofluids to evaluate their suitability for biomarker discovery.

METHODS

Paired tear and AH samples were collected from 20 patients undergoing cataract surgery. Tear samples were collected using Schirmer strips prior to surgery, and AH samples were collected from the anterior chamber immediately after corneal incision. Proteins were extracted and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

A total of 481 proteins were identified in greater than 50% of the tear samples, and 191 proteins were detected in greater than 50% of the AH samples. Of these proteins, 82 were found to be common between the two biofluids, with ALB, LTF, TF, LCN1, and IGKC being the most abundant.

CONCLUSION

Although tear fluid and the AH are functionally independent and physically separated, many of the proteins detected in AH were also detected in tears. This direct comparison of the proteomic content of tear fluid and AH may aid in further investigation of tear fluid as a source of readily accessible biomarkers for various human diseases.

The paradigm change from reactive medical services to 3PM in ischemic stroke: a holistic approach utilising tear fluid multi-omics, mitochondria as a vital biosensor and AI-based multi-professional data interpretation

Worldwide stroke is the second leading cause of death and the third leading cause of death and disability combined. The estimated global economic burden by stroke is over US$891 billion per year. Within three decades (1990-2019), the incidence increased by 70%, deaths by 43%, prevalence by 102%, and DALYs by 143%. Of over 100 million people affected by stroke, about 76% are ischemic stroke (IS) patients recorded worldwide. Contextually, ischemic stroke moves into particular focus of multi-professional groups including researchers, healthcare industry, economists, and policy-makers. Risk factors of ischemic stroke demonstrate sufficient space for cost-effective prevention interventions in primary (suboptimal health) and secondary (clinically manifested collateral disorders contributing to stroke risks) care. These risks are interrelated. For example, sedentary lifestyle and toxic environment both cause mitochondrial stress, systemic low-grade inflammation and accelerated ageing; inflammageing is a low-grade inflammation associated with accelerated ageing and poor stroke outcomes. Stress overload, decreased mitochondrial bioenergetics and hypomagnesaemia are associated with systemic vasospasm and ischemic lesions in heart and brain of all age groups including teenagers. Imbalanced dietary patterns poor in folate but rich in red and processed meat, refined grains, and sugary beverages are associated with hyperhomocysteinaemia, systemic inflammation, small vessel disease, and increased IS risks. Ongoing 3PM research towards vulnerable groups in the population promoted by the European Association for Predictive, Preventive and Personalised Medicine (EPMA) demonstrates promising results for the holistic patient-friendly non-invasive approach utilising tear fluid-based health risk assessment, mitochondria as a vital biosensor and AI-based multi-professional data interpretation as reported here by the EPMA expert group. Collected data demonstrate that IS-relevant risks and corresponding molecular pathways are interrelated. For examples, there is an evident overlap between molecular patterns involved in IS and diabetic retinopathy as an early indicator of IS risk in diabetic patients. Just to exemplify some of them such as the 5-aminolevulinic acid/pathway, which are also characteristic for an altered mitophagy patterns, insomnia, stress regulation and modulation of microbiota-gut-brain crosstalk. Further, ceramides are considered mediators of oxidative stress and inflammation in cardiometabolic disease, negatively affecting mitochondrial respiratory chain function and fission/fusion activity, altered sleep-wake behaviour, vascular stiffness and remodelling. Xanthine/pathway regulation is involved in mitochondrial homeostasis and stress-driven anxiety-like behaviour as well as molecular mechanisms of arterial stiffness. In order to assess individual health risks, an application of machine learning (AI tool) is essential for an accurate data interpretation performed by the multiparametric analysis. Aspects presented in the paper include the needs of young populations and elderly, personalised risk assessment in primary and secondary care, cost-efficacy, application of innovative technologies and screening programmes, advanced education measures for professionals and general population-all are essential pillars for the paradigm change from reactive medical services to 3PM in the overall IS management promoted by the EPMA.

Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological Insight

Human tear fluid contains numerous compounds, which are present in highly variable amounts owing to the dynamic and multipurpose functions of tears. A better understanding of the level and sources of variance is essential for determining the functions of the different tear components and the limitations of tear samples as a potential biomarker source. In this study, a quantitative proteomic method was used to analyze variations in the tear protein profiles of healthy volunteers. High day-to-day and inter-eye personal variances were observed in the tear volumes, protein content, and composition of the tear samples. Several normalization and outlier exclusion approaches were evaluated to decrease variances. Despite the intrapersonal variances, statistically significant differences and cluster analysis revealed that proteome profile and immunoglobulin composition of tear fluid present personal characteristics. Using correlation analysis, we could identify several correlating protein clusters, mainly related to the source of the proteins. Our study is the first attempt to achieve more insight into the biochemical background of human tears by statistical evaluation of the experimentally observed dynamic behavior of the tear proteome. As a pilot study for determination of personal protein profiles of the tear fluids of individual patients, it contributes to the application of this noninvasively collectible body fluid in personal medicine.

Significance of flavonoids targeting PI3K/Akt/HIF-1α signaling pathway in therapy-resistant cancer cells - A potential contribution to the predictive, preventive, and personalized medicine

BACKGROUND

Cancer management faces multiple obstacles, including resistance to current therapeutic approaches. In the face of challenging microenvironments, cancer cells adapt metabolically to maintain their supply of energy and precursor molecules for biosynthesis and thus sustain rapid proliferation and tumor growth. Among the various metabolic adaptations observed in cancer cells, the altered glucose metabolism is the most widely studied. The aberrant glycolytic modification in cancer cells has been associated with rapid cell division, tumor growth, cancer progression, and drug resistance. The higher rates of glycolysis in cancer cells, as a hallmark of cancer progression, is modulated by the transcription factor hypoxia inducible factor 1 alpha (HIF-1α), a downstream target of the PI3K/Akt signaling, the most deregulated pathway in cancer.

AIM OF REVIEW

We provide a detailed overview of current, primarily experimental, evidence on the potential effectiveness of flavonoids to combat aberrant glycolysis-induced resistance of cancer cells to conventional and targeted therapies. The manuscript focuses primarily on flavonoids reducing cancer resistance via affecting PI3K/Akt, HIF-1α (as the transcription factor critical for glucose metabolism of cancer cells that is regulated by PI3K/Akt pathway), and key glycolytic mediators downstream of PI3K/Akt/HIF-1α signaling (glucose transporters and key glycolytic enzymes).

KEY SCIENTIFIC CONCEPTS OF REVIEW

The working hypothesis of the manuscript proposes HIF-1α - the transcription factor critical for glucose metabolism of cancer cells regulated by PI3K/Akt pathway as an attractive target for application of flavonoids to mitigate cancer resistance. Phytochemicals represent a source of promising substances for cancer management applicable to primary, secondary, and tertiary care. However, accurate patient stratification and individualized patient profiling represent crucial steps in the paradigm shift from reactive to predictive, preventive, and personalized medicine (PPPM / 3PM). The article is focused on targeting molecular patterns by natural substances and provides evidence-based recommendations for the 3PM relevant implementation.

A review of biological targets and therapeutic approaches in the management of triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is a heterogeneous, aggressive phenotype of breast cancer with associated chemoresistance. The development of chemo- or radioresistance could be attributed to diverse tumor microenvironments, overexpression of membrane proteins (transporters), epigenetic changes, and alteration of the cell signaling pathways/genes associated with the development of cancer stem cells (CSCs).

AIM OF REVIEW

Due to the diverse and heterogeneous nature of TNBC, therapeutic response to the existing modalities offers limited scope and thus results in reccurance after therapy. To establish landmark therapeutic efficacy, a number of novel therapeutic modalities have been proposed. In addition, reversal of the resistance that developed during treatment may be altered by employing appropriate therapeutic modalities. This review aims to discuss the plethora of investigations carried out, which will help readers understand and make an appropriate choice of therapy directed toward complete elimination of TNBC.

KEY SCIENTIFIC CONCEPTS OF REVIEW

This manuscript addresses the major contributory factors from the tumor microenvironment that are responsible for the development of chemoresistance and poor prognosis. The associated cellular events and molecular mechanism-based therapeutic interventions have been explained in detail. Inhibition of ABC transporters, cell signaling pathways associated with CSCs, and epigenetic modification offers promising results in this regard. TNBC progression, invasion, metastasis and recurrence can also be inhibited by blocking multiple cell signaling pathways, targeting specific receptors/epigenetic targets, disrupting bioenergetics and generating reactive oxygen species (ROS).

Smart Contact Lenses as Wearable Ophthalmic Devices for Disease Monitoring and Health Management

The eye contains a complex network of physiological information and biomarkers for monitoring disease and managing health, and ocular devices can be used to effectively perform point-of-care diagnosis and disease management. This comprehensive review describes the target biomarkers and various diseases, including ophthalmic diseases, metabolic diseases, and neurological diseases, based on the physiological and anatomical background of the eye. This review also includes the recent technologies utilized in eye-wearable medical devices and the latest trends in wearable ophthalmic devices, specifically smart contact lenses for the purpose of disease management. After introducing other ocular devices such as the retinal prosthesis, we further discuss the current challenges and potential possibilities of smart contact lenses.

Ubiquitinomics revealed disease- and stage-specific patterns relevant for the 3PM approach in human sigmoid colon cancers

Objective

The patients with sigmoid colorectal cancer commonly show high mortality and poor prognosis. Increasing evidence has demonstrated that the ubiquitinated proteins and ubiquitination-mediated molecular pathways influence the growth and aggressiveness of colorectal cancer. It emphasizes the scientific merits of quantitative ubiquitinomics in human sigmoid colon cancer. We hypothesize that the ubiquitinome and ubiquitination-mediated pathway networks significantly differ in sigmoid colon cancers compared to controls, which offers the promise for in-depth insight into molecular mechanisms, discovery of effective therapeutic targets, and construction of reliable biomarkers in the framework of predictive, preventive, and personalized medicine (PPPM; 3P medicine).

Methods

The first ubiquitinome analysis was performed with anti-K-ε-GG antibody beads (PTMScan ubiquitin remnant motif [K-ε-GG])-based label-free quantitative proteomics and bioinformatics to identify and quantify ubiquitination profiling between sigmoid colon cancer tissues and para-carcinoma tissues. A total of 100 human sigmoid colon cancer samples that included complete clinical information and the corresponding gene expression data were obtained from The Cancer Genome Atlas (TCGA). Ubiquitination was the main way of protein degradation; the relationships between differentially ubiquitinated proteins (DUPs) and their differently expressed genes (DEGs) and between DUPs and their differentially expressed proteins (DEPs) were analyzed between cancer tissues and control tissues. The overall survival of those DUPs was obtained with Kaplan-Meier method.

Results

A total of 1249 ubiquitinated sites within 608 DUPs were identified in human sigmoid colon cancer tissues. KEGG pathway network analysis of these DUPs revealed 35 statistically significant signaling pathways, such as salmonella infection, glycolysis/gluconeogenesis, and ferroptosis. Gene Ontology (GO) analysis of 608 DUPs revealed that protein ubiquitination was involved in 98 biological processes, 64 cellular components, 51 molecule functions, and 26 immune system processes. Protein-protein interaction (PPI) network of 608 DUPs revealed multiple high-combined scores and co-expressed DUPs. The relationship analysis between DUPs and their DEGs found 4 types of relationship models, including DUP-up (increased ubiquitination level) and DEG-up (increased gene expression), DUP-up and DEG-down (decreased gene expression), DUP-down (decreased ubiquitination level) and DEG-up, and DUP-down and DEG-down. The relationship analysis between DUPs and their DEPs found 4 types of relationship models, including DUP-up and DEP-up (increased protein expression), DUP-up and DEP-down (decreased protein expression), DUP-down and DEP-up, and DUP-down and DEP-down. Survival analysis found 46 overall survival-related DUPs in sigmoid colon cancer, and the drug sensitivity of overall survival-related DUPs were identified.

Conclusion

The study provided the first differentially ubiquitinated proteomic profiling, ubiquitination-involved signaling pathway network changes, and the relationship models between protein ubiquitination and its gene expression and between protein ubiquitination and its protein expression, in human sigmoid colon cancer. It offers the promise for deep insights into molecular mechanisms of sigmoid colon cancer, and discovery of effective therapeutic targets and biomarkers for patient stratification, predictive diagnosis, prognostic assessment, and personalized treatment in the context of 3P medicine.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00328-2.

Machine learning-couched treatment algorithms tailored to individualized profile of patients with primary anterior chamber angle closure predisposed to the glaucomatous optic neuropathy

Background

Primary angle closure glaucoma (PACG) is still one of the leading causes of irreversible blindness, with a trend towards an increase in the number of patients to 32.04 million by 2040, an increase of 58.4% compared with 2013. Health risk assessment based on multi-level diagnostics and machine learning-couched treatment algorithms tailored to individualized profile of patients with primary anterior chamber angle closure are considered essential tools to reverse the trend and protect vulnerable subpopulations against health-to-disease progression.

Aim

To develop a methodology for personalized choice of an effective method of primary angle closure (PAC) treatment based on comparing the prognosis of intraocular pressure (IOP) changes due to laser peripheral iridotomy (LPI) or lens extraction (LE).

Methods

The multi-parametric data analysis was used to develop models predicting individual outcomes of the primary angle closure (PAC) treatment with LPI and LE. For doing this, we suggested a positive dynamics in the intraocular pressure (IOP) after treatment, as the objective measure of a successful treatment. Thirty-seven anatomical parameters have been considered by applying artificial intelligence to the prospective study on 30 (LE) + 30 (LPI) patients with PAC.

Results and data interpretation in the framework of 3P medicine

Based on the anatomical and topographic features of the patients with PAC, mathematical models have been developed that provide a personalized choice of LE or LPI in the treatment. Multi-level diagnostics is the key tool in the overall advanced approach. To this end, for the future application of AI in the area, it is strongly recommended to consider the following:Clinically relevant phenotyping applicable to advanced population screeningSystemic effects causing suboptimal health conditions considered in order to cost-effectively protect affected individuals against health-to-disease transitionClinically relevant health risk assessment utilizing health/disease-specific molecular patterns detectable in body fluids with high predictive power such as a comprehensive tear fluid analysis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00337-1.

Quantitative phosphoproteomics reveals molecular pathway network alterations in human early-stage primary hepatic carcinomas: potential for 3P medical approach

Objective

Hepatic carcinoma is one of the most common types of malignant tumors in the digestive system, and its biological characteristics determine its high rate of metastasis and recurrence after radical resection, leading to a poor prognosis for patients. Increasing evidence demonstrates that phosphoproteins and phosphorylation-mediated molecular pathways influence the occurrence and development of hepatic carcinoma. It is urgent need to develop early-stage biomarkers for improving diagnosis, therapy, medical service, and prognostic assessment. We hypothesize that phosphoproteome and phosphorylation-mediated signaling pathway networks significantly differ in human early-stage primary hepatic carcinomas relative to control liver tissues, which will identify the key differentially phosphorylated proteins and phosphorylation-mediated signaling pathway network alterations in human early-stage primary hepatic carcinoma to innovate predictive diagnosis, prognostic assessment, and personalized medical services and progress beyond the state of the art in the framework of predictive, preventive, and personalized medicine (PPPM).

Methods

Tandem mass tag (TMT)-based quantitative proteomics coupled with TiO2 enrichment of phosphopeptides was used to identify phosphorylation profiling, and bioinformatics was used to analyze the pathways and biological functions of phosphorylation profiling between early-stage hepatic carcinoma tissues and tumor-adjacent normal control tissues. Furthermore, the integrative analysis with transcriptomic data from TCGA database obtained differently expressed genes (DEGs) corresponding to differentially phosphorylated proteins (DPPs) and overall survival (OS)-related DPPs.

Results

A total of 1326 phosphopeptides derived from 858 DPPs in human early-stage primary hepatic carcinoma were identified. KEGG pathway network analysis of 858 DPPs revealed 33 statistically significant signaling pathways, including spliceosome, glycolysis/gluconeogenesis, B-cell receptor signaling pathway, HIF-1 signaling pathway, and fatty acid degradation. Gene Ontology (GO) analysis of 858 DPPs revealed that protein phosphorylation was involved in 57 biological processes, 40 cellular components, and 37 molecular functions. Protein-protein interaction (PPI) network constructed multiple high-combined scores and co-expressed DPPs. Integrative analysis of transcriptomic data and DPP data identified 105 overlapped molecules (DPPs; DEGs) between hepatic carcinoma tissues and control tissues and 125 OS-related DPPs. Overlapping Venn plots showed 14 common molecules among datasets of DPPs, DEGs, and OS-related DDPs, including FTCD, NDRG2, CCT2, PECR, SLC23A2, PNPLA7, ANLN, HNRNPM, HJURP, MCM2, STMN1, TCOF1, TOP2A, and SSRP1. The drug sensitivities of OS-related DPPs were identified, including LMOD1, CAV2, UBE2E2, RAPH1, ANXA5, HDLBP, CUEDC1, APBB1IP, VCL, SRSF10, SLC23A2, EPB41L2, ESR1, PLEKHA4, SAFB2, SMARCAD1, VCAN, PSD4, RDH16, NOP56, MEF2C, BAIAP2L2, NAGS, SRSF2, FHOD3, and STMN1.

Conclusions

Identification and annotation of phosphoproteomes and phosphorylation-mediated signaling pathways in human early-stage primary hepatic carcinoma tissues provided new directions for tumor prevention and treatment, which (i) helps to enrich phosphorylation functional research and develop new biomarkers; (ii) enriches phosphorylation-mediated signaling pathways to gain a deeper understanding of the underlying mechanisms of early-stage primary hepatic carcinoma; and (iii) develops anti-tumor drugs that facilitate targeted phosphorylated sites. We recommend quantitative phosphoproteomics in early-stage primary hepatic carcinoma, which offers great promise for in-depth insight into the molecular mechanism of early-stage primary hepatic carcinoma, the discovery of effective therapeutic targets/drugs, and the construction of reliable phosphorylation-related biomarkers for patient stratification, predictive diagnosis, prognostic assessment, and personalized medical services in the framework of PPPM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00335-3.

An Uncharacterised lncRNA Coded by the ASAP1 Locus Is Downregulated in Serum of Type 2 Diabetes Mellitus Patients

Diabetes mellitus (DM) is a complex and multifactorial disease characterised by high blood glucose. Type 2 Diabetes (T2D), the most frequent clinical condition accounting for about 90% of all DM cases worldwide, is a chronic disease with slow development usually affecting middle-aged or elderly individuals. T2D represents a significant problem of public health today because its incidence is constantly growing among both children and adults. It is also estimated that underdiagnosis prevalence would strongly further increase the real incidence of the disease, with about half of T2D patients being undiagnosed. Therefore, it is important to increase diagnosis accuracy. The current interest in RNA molecules (both protein- and non-protein-coding) as potential biomarkers for diagnosis, prognosis, and treatment lies in the ease and low cost of isolation and quantification with basic molecular biology techniques. In the present study, we analysed the transcriptome in serum samples collected from T2D patients and unaffected individuals to identify potential RNA-based biomarkers. Microarray-based profiling and subsequent validation using Real-Time PCR identified an uncharacterised long non-coding RNA (lncRNA) transcribed from the ASAP1 locus as a potential diagnostic biomarker. ROC curve analysis showed that a molecular signature including the lncRNA and the clinicopathological parameters of T2D patients as well as unaffected individuals showed a better diagnostic performance compared with the glycated haemoglobin test (HbA1c). This result suggests that the application of this biomarker in clinical practice would help to improve the diagnosis, and therefore the clinical management, of T2D patients. The proposed biomarker would be useful in the context of predictive, preventive, and personalised medicine (3PM/PPPM).

Remote Measurements of Tear Electrolyte Concentrations on Both Sides of an Inserted Contact Lens

In this paper, a method is described to perform ion concentration measurements on both sides of an inserted contact lens, without physical contact with the eye or the contact lens. The outer surface of an eye is covered with a tear film that has multiple layers. The central aqueous layer contains electrolytes and proteins. When a contact lens is inserted, it becomes localized in the central layer, which creates two layers known as the pre-lens tear film (PLTF) and the post-lens tear film (PoLTF). The PoLTF is in direct contact with the sensitive corneal epithelial cells which control electrolyte concentrations in tears. It is difficult to measure the overall electrolyte concentration in tears because of the small 7 μL volume of bulk tears. No methods are known, and no method has been proposed, to selectively measure the concentrations of electrolytes in the smaller volumes of the PLTF and the PoLTF. In this paper, we demonstrate the ability to localize fluorophores on each side of a contact lens without probe mixing or diffusion across the lens. We measured the concentration of sodium in the region of the PoLTF using a sodium-sensitive fluorophore positioned on the inner surface of a contact lens. The fluorescence measurements do not require physical contact and are mostly independent of eye motion and fluorophore concentration. The method is generic and can be combined with ion-sensitive fluorophores for the other electrolytes in tears. Instrumentation for non-contact measurements is likely to be inexpensive with modern opto-electronic devices. We expect these lenses to be used for measurements of other ions in the PLTF and the PoLTF, and thus become useful for both research and in the diagnosis of infections, keratitis and biomarkers for diseases.

Protein profile analysis of tear fluid with hyphenated HPLC-UV LED-induced fluorescence detection for the diagnosis of dry eye syndrome

Tear fluid contains organic and inorganic constituents, variations in their relative concentrations could provide valuable information and can be useful for the detection of several ophthalmological diseases. This report describes the application of the lab-assembled light-emitting diode (LED)-based high-performance liquid chromatography system for protein profiling of tear fluids to diagnose dry eye disease. Principal Component Analysis (PCA), match/no-match, and Artificial Neural Network (ANN) based binary classification of protein profile data were performed for disease diagnosis. Results from the match/no-match test of the protein profile data showed 94.4% sensitivity and 87.8% specificity. ANN with the leaving one out procedure has given 91.6% sensitivity and 93.9% specificity.

Molecular Mechanisms Behind Vascular Mimicry as the Target for Improved Breast Cancer Management

Introduction

Breast cancer has a high incidence and mortality rate in women due to metastasis and drug resistance which is associated with vasculogenic mimicry (VM). We purposed to explore VM formulation in breast cancer and mechanism of which is involved in EphA2/PIK3R1/CTNNB1 in the present study.

Methods

The expression of EphA2/PIK3R1/CTNNB1 and breast cancer patient prognosis was analyzed from TCGA data, both gene and protein expression as well as VM were measured in human breast cancer tissue samples collected in our study. The relationship between EphA2/PIK3R1/CTNNB1 and the formation of VM in breast cancer and its possible regulatory mechanism was explored.

Results

The results of the bioinformatics analysis based on TCGA showed that the expression of PIK3R1/ CTNNB1/ PECAM1 (CD31) in tumor tissues was significantly lower than that in normal tissues. EphA2 was positively correlated with PIK3R1, PIK3R1 with CTNNB1, and CTNNB1 with PECAM1 expression in breast cancer tissues. The results of detection in breast cancer and adjacent tissues indicated that the expression of EphA2/PIK3R1/CTNNB1 in cancer tissues was significantly lower than that in adjacent tissues. The expression of PIK3R1 was positively correlated with EphA2 and CTNNB1 expression, respectively, as well as EphA2 expression correlated with CTNNB1 expression positively. VM formation was significantly increased in breast cancer tissues compared with adjacent tissues.

Conclusion

Our results suggested that the formation of VM in breast cancer may be related to the EphA2/PIK3R1/CTNNB1 molecular signaling pathway.

Tear Cytokine Levels in Sicca Syndrome-Related Dry Eye: A Meta-Analysis

Sjogren's syndrome (SS) is an autoimmune disease that affects exocrine glands, mainly salivary and lacrimal glands. Several studies have investigated cytokine profiles in tears in order to understand the pathogenesis of SS and find additional diagnostic markers. This systematic review and meta-analysis aimed to analyze cytokines in tears of SS patients. A systematic literature search of the Cochrane, Medline via PubMed, Scopus, and Web of Science databases was conducted using key terms related to "Sjögren's syndrome" and "tears" combined with "biomarker", "cytokines", "interleukin", and "chemokines", following PRISMA guidelines. Article selection was subjected to certain eligibility criteria. A total of 17 articles (from 1998 and 2022) were selected for the quantitative and qualitative analysis. When compared to controls, concentrations of IFN-γ, TNF-α, IL-1α, IL-1 Ra, IL-4, IL-6, IL-8, IL-10, IL-17, IL-21 and IL-22 were consistently higher; however, IL-23 was significantly lower in patients with SS compared to the controls. Tear levels of some cytokines were significantly elevated among SS groups compared to control groups. Therefore, these cytokines could be potential biomarkers of SS. However, standardization of sample collection and analytical methods is necessary in order to translate these findings into clinical practice.

Underexplored reciprocity between genome-wide methylation status and long non-coding RNA expression reflected in breast cancer research: potential impacts for the disease management in the framework of 3P medicine

Breast cancer (BC) is the most common female malignancy reaching a pandemic scale worldwide. A comprehensive interplay between genetic alterations and shifted epigenetic regions synergistically leads to disease development and progression into metastatic BC. DNA and histones methylations, as the most studied epigenetic modifications, represent frequent and early events in the process of carcinogenesis. To this end, long non-coding RNAs (lncRNAs) are recognized as potent epigenetic modulators in pathomechanisms of BC by contributing to the regulation of DNA, RNA, and histones' methylation. In turn, the methylation status of DNA, RNA, and histones can affect the level of lncRNAs expression demonstrating the reciprocity of mechanisms involved. Furthermore, lncRNAs might undergo methylation in response to actual medical conditions such as tumor development and treated malignancies. The reciprocity between genome-wide methylation status and long non-coding RNA expression levels in BC remains largely unexplored. Since the bio/medical research in the area is, per evidence, strongly fragmented, the relevance of this reciprocity for BC development and progression has not yet been systematically analyzed. Contextually, the article aims at:consolidating the accumulated knowledge on both-the genome-wide methylation status and corresponding lncRNA expression patterns in BC andhighlighting the potential benefits of this consolidated multi-professional approach for advanced BC management. Based on a big data analysis and machine learning for individualized data interpretation, the proposed approach demonstrates a great potential to promote predictive diagnostics and targeted prevention in the cost-effective primary healthcare (sub-optimal health conditions and protection against the health-to-disease transition) as well as advanced treatment algorithms tailored to the individualized patient profiles in secondary BC care (effective protection against metastatic disease). Clinically relevant examples are provided, including mitochondrial health control and epigenetic regulatory mechanisms involved.

Clarifying the effect of gut microbiota on allergic conjunctivitis risk is instrumental for predictive, preventive, and personalized medicine: a Mendelian randomization analysis

Background

Allergic conjunctivitis is an ocular immune disease which affects the conjunctiva, eyelids, and cornea. Growing evidence implicates the gut microbiota in balancing and modulating immunity response, and in the pathogenesis of allergic disease. As a result, gut microbial imbalance could be a useful indicator for allergic conjunctivitis. From the perspective of predictive, preventive, and personalized medicine (PPPM), clarifying the role of gut microbial imbalance in the development of allergic conjunctivitis could provide a window of opportunity for primary prediction, targeted prevention, and personalized treatment of the disease.

Working hypothesis and methodology

In our study, we hypothesized that individuals with microbial dysbiosis may be more susceptible to allergic conjunctivitis due to an increased inflammatory response. To verify the working hypothesis, our analysis selected genetic variants linked with gut microbiota features (N = 18,340) and allergic conjunctivitis (4513 cases, 649,376 controls) from genome-wide association studies. The inverse-variance weighted (IVW) estimate, Mendelian randomization (MR)-Egger, weighted median estimator, maximum likelihood estimator (MLE), and MR robust adjusted profile score (MR.RAPS) were employed to analyze the impact of gut microbiota on the risk of allergic conjunctivitis and identify allergic conjunctivitis-related gut microbes. Ultimately, these findings may enable the identification of individuals at risk of allergic conjunctivitis through screening of gut microbial imbalances, and allow for new targeted prevention and personalized treatment strategies.

Results

Genetic liability to Ruminococcaceae_UCG_002 (OR, 0.83; 95% CI, 0.70-0.99; P = 4.04×10^-2), Holdemanella (OR, 0.78; 95% CI, 0.64-0.96; P = 2.04×10^-2), Catenibacterium (OR, 0.69; 95% CI, 0.56-0.86; P = 1.09×10^-3), Senegalimassilia (OR, 0.71; 95% CI, 0.55-0.93; P = 1.23×10^-2) genus were associated with a low risk of allergic conjunctivitis with IVW. Besides, we found suggestive associations of a genetic-driven increase in the Oscillospira (OR, 1.41; 95% CI, 1.00-2.00; P = 4.63×10^-2) genus with a higher risk of allergic conjunctivitis. Moreover, MLE and MR.RAPS show consistent results with IVW after further validation and strengthened confidence in the true causal associations. No heterogeneity and pleiotropy was detected.

Conclusions

Our study suggests that gut microbiota may play a causal role in the development of allergic conjunctivitis and provides new insights into the microbiota-mediated mechanism of the disease. Gut microbiota may serve as a target for future predictive diagnostics, targeted prevention, and individualized therapy in allergic conjunctivitis, facilitating the transition from reactive medical services to PPPM in the management of the disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-023-00321-9.

Tear nanoDSF Denaturation Profile Is Predictive of Glaucoma

Primary open-angle glaucoma (POAG) is a frequent blindness-causing neurodegenerative disorder characterized by optic nerve and retinal ganglion cell damage most commonly due to a chronic increase in intraocular pressure. The preservation of visual function in patients critically depends on the timeliness of detection and treatment of the disease, which is challenging due to its asymptomatic course at early stages and lack of objective diagnostic approaches. Recent studies revealed that the pathophysiology of glaucoma includes complex metabolomic and proteomic alterations in the eye liquids, including tear fluid (TF). Although TF can be collected by a non-invasive procedure and may serve as a source of the appropriate biomarkers, its multi-omics analysis is technically sophisticated and unsuitable for clinical practice. In this study, we tested a novel concept of glaucoma diagnostics based on the rapid high-performance analysis of the TF proteome by differential scanning fluorimetry (nanoDSF). An examination of the thermal denaturation of TF proteins in a cohort of 311 ophthalmic patients revealed typical profiles, with two peaks exhibiting characteristic shifts in POAG. Clustering of the profiles according to peaks maxima allowed us to identify glaucoma in 70% of cases, while the employment of artificial intelligence (machine learning) algorithms reduced the amount of false-positive diagnoses to 13.5%. The POAG-associated alterations in the core TF proteins included an increase in the concentration of serum albumin, accompanied by a decrease in lysozyme C, lipocalin-1, and lactotransferrin contents. Unexpectedly, these changes were not the only factor affecting the observed denaturation profile shifts, which considerably depended on the presence of low-molecular-weight ligands of tear proteins, such as fatty acids and iron. Overall, we recognized the TF denaturation profile as a novel biomarker of glaucoma, which integrates proteomic, lipidomic, and metallomic alterations in tears, and monitoring of which could be adapted for rapid non-invasive screening of the disease in a clinical setting.

Short communication: unique metabolic signature of proliferative retinopathy in the tear fluid of diabetic patients with comorbidities - preliminary data for PPPM validation

Type 2 diabetes (T2DM) defined as the adult-onset type that is primarily not insulin-dependent, comprises over 95% of all diabetes mellitus (DM) cases. According to global records, 537 million adults aged 20-79 years are affected by DM that means at least 1 out of 15 persons. This number is projected to grow by 51% by the year 2045. One of the most common complications of T2DM is diabetic retinopathy (DR) with an overall prevalence over 30%. The total number of the DR-related visual impairments is on the rise, due to the growing T2DM population. Proliferative diabetic retinopathy (PDR) is the progressing DR and leading cause of preventable blindness in working-age adults. Moreover, PDR with characteristic systemic attributes including mitochondrial impairment, increased cell death and chronic inflammation, is an independent predictor of the cascading DM-complications such as ischemic stroke. Therefore, early DR is a reliable predictor appearing upstream of this "domino effect". Global screening, leading to timely identification of DM-related complications, is insufficiently implemented by currently applied reactive medicine. A personalised predictive approach and cost-effective targeted prevention shortly - predictive, preventive and personalised medicine (PPPM / 3PM) could make a good use of the accumulated knowledge, preventing blindness and other severe DM complications. In order to reach this goal, reliable stage- and disease-specific biomarker panels are needed characterised by an easy way of the sample collection, high sensitivity and specificity of analyses. In the current study, we tested the hypothesis that non-invasively collected tear fluid is a robust source for the analysis of ocular and systemic (DM-related complications) biomarker patterns suitable for differential diagnosis of stable DR versus PDR. Here, we report the first results of the comprehensive ongoing study, in which we correlate individualised patient profiles (healthy controls versus patients with stable D as well as patients with PDR with and without co-morbidities) with their metabolic profiles in the tear fluid. Comparative mass spectrometric analysis performed has identified following metabolic clusters which are differentially expressed in the groups of comparison: acylcarnitines, amino acid & related compounds, bile acids, ceramides, lysophosphatidyl-choline, nucleobases & related compounds, phosphatidyl-cholines, triglycerides, cholesterol esters, and fatty acids. Our preliminary data strongly support potential clinical utility of metabolic patterns in the tear fluid indicating a unique metabolic signature characteristic for the DR stages and PDR progression. This pilot study creates a platform for validating the tear fluid biomarker patterns to stratify T2DM-patients predisposed to the PDR. Moreover, since PDR is an independent predictor of severe T2DM-related complications such as ischemic stroke, our international project aims to create an analytical prototype for the "diagnostic tree" (yes/no) applicable to healthrisk assessment in diabetes care.

New insight of metabolomics in ocular diseases in the context of 3P medicine

Metabolomics refers to the high-through untargeted or targeted screening of metabolites in biofluids, cells, and tissues. Metabolome reflects the functional states of cells and organs of an individual, influenced by genes, RNA, proteins, and environment. Metabolomic analyses help to understand the interaction between metabolism and phenotype and reveal biomarkers for diseases. Advanced ocular diseases can lead to vision loss and blindness, reducing patients' quality of life and aggravating socio-economic burden. Contextually, the transition from reactive medicine to the predictive, preventive, and personalized (PPPM / 3P) medicine is needed. Clinicians and researchers dedicate a lot of efforts to explore effective ways for disease prevention, biomarkers for disease prediction, and personalized treatments, by taking advantages of metabolomics. In this way, metabolomics has great clinical utility in the primary and secondary care. In this review, we summarized much progress achieved by applying metabolomics to ocular diseases and pointed out potential biomarkers and metabolic pathways involved to promote 3P medicine approach in healthcare.

Diabetic retinopathy as the leading cause of blindness and early predictor of cascading complications-risks and mitigation

Proliferative diabetic retinopathy (PDR) the sequel of diabetic retinopathy (DR), a frequent complication of diabetes mellitus (DM), is the leading cause of blindness in the working-age population. The current screening process for the DR risk is not sufficiently effective such that often the disease is undetected until irreversible damage occurs. Diabetes-associated small vessel disease and neuroretinal changes create a vicious cycle resulting in the conversion of DR into PDR with characteristic ocular attributes including excessive mitochondrial and retinal cell damage, chronic inflammation, neovascularisation, and reduced visual field. PDR is considered an independent predictor of other severe diabetic complications such as ischemic stroke. A "domino effect" is highly characteristic for the cascading DM complications in which DR is an early indicator of impaired molecular and visual signaling. Mitochondrial health control is clinically relevant in DR management, and multi-omic tear fluid analysis can be instrumental for DR prognosis and PDR prediction. Altered metabolic pathways and bioenergetics, microvascular deficits and small vessel disease, chronic inflammation, and excessive tissue remodelling are in focus of this article as evidence-based targets for a predictive approach to develop diagnosis and treatment algorithms tailored to the individual for a cost-effective early prevention by implementing the paradigm shift from reactive medicine to predictive, preventive, and personalized medicine (PPPM) in primary and secondary DR care management.

Association between Serum Total Bilirubin Level and Patients with Primary Open-Angle Glaucoma in China: A Cross-Sectional, Case-Control Study

Objective

To investigate the relationship between peripheral blood total bilirubin (TBIL) levels and the risk of primary open-angle glaucoma (POAG).

Methods

This study was a cross-sectional, case-control study design. Between April 2021 and January 2022, 198 POAG patients and 205 healthy subjects were recruited from the EENT Hospital of Fudan University. Their clinical information (intraocular pressure, central corneal thickness, vertical cup-disk ratios (VCDR), and axial length) and demographic data were collected. Serum levels of TBIL were measured in enzymes using a Roche C702 biochemical analyzer. The POAG subgroups were classified by gender and VCDR: mild (VCDR ≤ 0.64), moderate (VCDR ≤ 0.85), and severe (VCDR > 0.85). Univariate and multivariate logistic regression analyses were performed.

Results

The level of TBIL (11.58 ± 5.16 μmol/L) in the POAG group was higher than that in the control group (10.18 ± 3.38 μmol/L; p < 0.05). In the male subgroup, TBIL was also significantly higher than in the normal control group; TBIL levels were lower in the mild subgroup (10.82 ± 4.48 μmol/L), followed by the moderate subgroup (12.00 ± 5.55 μmol/L) and the severe subgroup (14.47 ± 5.45 μmol/L). The results of the multivariate logistic regression analysis showed that high TBIL levels were a risk factor for male POAG, at 1.126 (95% CI 1.009-1.256). Pearson's analysis revealed that TBIL was positively correlated with intraocular pressure (r = 0.134, p = 0.012), VCDR (r = 0.142, p = 0.046), anterior chamber depth (r = 0.190, p = 0.014), and axial length (r = 0.179, p = 0.019) in the patients. However, no statistical difference (p < 0.05) was observed in the female patients with POAG.

Conclusion

The results showed that high levels of TBIL may be related to the pathogenesis of POAG and that the severity of the disease is positively correlated, especially in male patients.

DNA and histone modifications as potent diagnostic and therapeutic targets to advance non-small cell lung cancer management from the perspective of 3P medicine

Lung cancer has a very high mortality in females and males. Most (~ 85%) of lung cancers are non-small cell lung cancers (NSCLC). When lung cancer is diagnosed, most of them have either local or distant metastasis, with a poor prognosis. In order to achieve better outcomes, it is imperative to identify the molecular signature based on genetic and epigenetic variations for different NSCLC subgroups. We hypothesize that DNA and histone modifications play significant roles in the framework of predictive, preventive, and personalized medicine (PPPM; 3P medicine). Epigenetics has a significant impact on tumorigenicity, tumor heterogeneity, and tumor resistance to chemotherapy, targeted therapy, and immunotherapy. An increasing interest is that epigenomic regulation is recognized as a potential treatment option for NSCLC. Most attention has been paid to the epigenetic alteration patterns of DNA and histones. This article aims to review the roles DNA and histone modifications play in tumorigenesis, early detection and diagnosis, and advancements and therapies of NSCLC, and also explore the connection between DNA and histone modifications and PPPM, which may provide an important contribution to improve the prognosis of NSCLC. We found that the success of targeting DNA and histone modifications is limited in the clinic, and how to combine the therapies to improve patient outcomes is necessary in further studies, especially for predictive diagnostics, targeted prevention, and personalization of medical services in the 3P medicine approach. It is concluded that DNA and histone modifications are potent diagnostic and therapeutic targets to advance non-small cell lung cancer management from the perspective of 3P medicine.

Recent Advances in Proteomics-Based Approaches to Studying Age-Related Macular Degeneration: A Systematic Review

Age-related macular degeneration (AMD) is a common ocular disease characterized by degeneration of the central area of the retina in the elderly population. Progression and response to treatment are influenced by genetic and non-genetic factors. Proteomics is a powerful tool to study, at the molecular level, the mechanisms underlying the progression of the disease, to identify new therapeutic targets and to establish biomarkers to monitor progression and treatment effectiveness. In this work, we systematically review the use of proteomics-based approaches for the study of the molecular mechanisms underlying the development of AMD, as well as the progression of the disease and on-treatment patient monitoring. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) reporting guidelines were followed. Proteomic approaches have identified key players in the onset of the disease, such as complement components and proteins involved in lipid metabolism and oxidative stress, but also in the progression to advanced stages, including factors related to extracellular matrix integrity and angiogenesis. Although anti-vascular endothelial growth factor (anti-VEGF)-based therapy has been crucial in the treatment of neovascular AMD, it is necessary to deepen our understanding of the underlying disease mechanisms to move forward to next-generation therapies for later-stage forms of this multifactorial disease.

Proteomics-Based Identification of Dysregulated Proteins in Breast Cancer

Immunohistochemistry (IHC) is still widely used as a morphology-based assay for in situ analysis of target proteins as specific tumor antigens. However, as a very heterogeneous collection of neoplastic diseases, breast cancer (BC) requires an accurate identification and characterization of larger panels of candidate biomarkers, beyond ER, PR, and HER2 proteins, for diagnosis and personalized treatment, without the limited availability of antibodies that are required to identify specific proteins. Top-down, middle-down, and bottom-up mass spectrometry (MS)-based proteomics approaches complement traditional histopathological tissue analysis to examine expression, modification, and interaction of hundreds to thousands of proteins simultaneously. In this review, we discuss the proteomics-based identification of dysregulated proteins in BC that are essential for the following issues: discovery and validation of new biomarkers by analysis of solid and liquid/non-invasive biopsies, cell lines, organoids and xenograft models; identification of panels of biomarkers for early detection and accurate discrimination between cancer, benign and normal tissues; identification of subtype-specific and stage-specific protein expression profiles in BC grading and measurement of disease progression; characterization of new subtypes of BC; characterization and quantitation of post-translational modifications (PTMs) and aberrant protein-protein interactions (PPI) involved in tumor development; characterization of the global remodeling of BC tissue homeostasis, diagnosis and prognostic information; and deciphering of molecular functions, biological processes and mechanisms through which the dysregulated proteins cause tumor initiation, invasion, and treatment resistance.

Development of the Breast Cancer Survivors Symptom Checklist for Use in Follow-Up Multidisciplinary Appointments

Background

Breast cancer survivors are primarily followed up to monitor the effectiveness of treatment and complications and to detect recurrences. Many breast cancer survivors may experience prolonged adverse physical and psychological effects, which should also be addressed at follow-ups. The objective of this study was to develop a brief symptom assessment tool for breast cancer survivors to be used as a guideline for the survivors and all health care professionals conducting the routine follow-up. The second objective was to describe the women's individual experiences with follow-ups.

Methods

A literature review, a focus group of 6 healthcare professionals using a nominal group technique process, and the experience and feedback via qualitative interviews with 16 breast cancer survivors was used to develop the Breast Cancer Survivors Symptom Assessment Checklist (BCS-SC).

Results

The BCS-SC consists of a set of 13 symptoms/burdens and one question. On a scale from 0 (no symptom) to 10 (worst imaginable), survivors indicated the extent to which they experience each symptom. All survivors perceived the annual follow-ups as important, but none prepared for them. Eight of the 16 survivors reported that they had 2 or more of the symptoms/burdens listed in the BCS-SC. However, only one of the survivors had mentioned her symptom to the doctor at follow-up.

Conclusion

The BCS-SC is a comprehensive assessment tool for symptoms/burdens that are common among breast cancer survivors and can aid efforts to optimize their follow-up. Furthermore, the BCS-SC allows for a more patient-initiated and focused consultation, leading to more patient-centered quality care.

Quantitative brain-derived neurotrophic factor lateral flow assay for point-of-care detection of glaucoma

Glaucoma, a ruinous group of eye diseases with progressive degeneration of the optic nerve and vision loss, is the leading cause of irreversible blindness. Accurate and timely diagnosis of glaucoma is critical to promote secondary prevention and early disease-modifying therapies. Reliable, cheap, and rapid tests for measuring disease activities are highly required. Brain-derived neurotrophic factor (BDNF) plays an important role in maintaining the function and survival of the central nervous system. Decreased BDNF levels in tear fluid can be seen in glaucoma patients, which indicates that BDNF can be regarded as a novel biomarker for glaucoma. Conventional ELISA is the standard method to measure the BDNF level, but the multi-step operation and strict storage conditions limit its usage in point-of-care settings. Herein, a one-step and a portable glaucoma detection method was developed based on the lateral flow assay (LFA) to quantify the BDNF concentration in artificial tear fluids. The results of the LFA were analyzed by using a portable and low-cost system consisting of a smartphone camera and a dark readout box fabricated by 3D printing. The concentration of BDNF was quantified by analyzing the colorimetric intensity of the test line and the control line. This assay yields reliable quantitative results from 25 to 300 pg mL^-1 with an experimental detection limit of 14.12 pg mL^-1. The LFA shows a high selectivity for BDNF and high stability in different pH environments. It can be readily adapted for sensitive and quantitative testing of BDNF in a point-of-care setting. The BDNF LFA strip shows it has great potential to be used in early glaucoma detection.

Oculomics for sarcopenia prediction: a machine learning approach toward predictive, preventive, and personalized medicine

Aims

Sarcopenia is characterized by a gradual loss of skeletal muscle mass and strength with increased adverse outcomes. Recently, large-scale epidemiological studies have demonstrated a relationship between several chronic disorders and ocular pathological conditions using an oculomics approach. We hypothesized that sarcopenia can be predicted through eye examinations, without invasive tests or radiologic evaluations in the context of predictive, preventive, and personalized medicine (PPPM/3PM).

Methods

We analyzed data from the Korean National Health and Nutrition Examination Survey (KNHANES). The training set (80%, randomly selected from 2008 to 2010) data were used to construct the machine learning models. Internal (20%, randomly selected from 2008 to 2010) and external (from the KNHANES 2011) validation sets were used to assess the ability to predict sarcopenia. We included 8092 participants in the final dataset. Machine learning models (XGBoost) were trained on ophthalmological examinations and demographic factors to detect sarcopenia.

Results

In the exploratory analysis, decreased levator function (odds ratio [OR], 1.41; P value <0.001), cataracts (OR, 1.31; P value = 0.013), and age-related macular degeneration (OR, 1.38; P value = 0.026) were associated with an increased risk of sarcopenia in men. In women, an increased risk of sarcopenia was associated with blepharoptosis (OR, 1.23; P value = 0.038) and cataracts (OR, 1.29; P value = 0.010). The XGBoost technique showed areas under the receiver operating characteristic curves (AUCs) of 0.746 and 0.762 in men and women, respectively. The external validation achieved AUCs of 0.751 and 0.785 for men and women, respectively. For practical and fast hands-on experience with the predictive model for practitioners who may be willing to test the whole idea of sarcopenia prediction based on oculomics data, we developed a simple web-based calculator application (https://knhanesoculomics.github.io/sarcopenia) to predict the risk of sarcopenia and facilitate screening, based on the model established in this study.

Conclusion

Sarcopenia is treatable before the vicious cycle of sarcopenia-related deterioration begins. Therefore, early identification of individuals at a high risk of sarcopenia is essential in the context of PPPM. Our oculomics-based approach provides an effective strategy for sarcopenia prediction. The proposed method shows promise in significantly increasing the number of patients diagnosed with sarcopenia, potentially facilitating earlier intervention. Through patient oculometric monitoring, various pathological factors related to sarcopenia can be simultaneously analyzed, and doctors can provide personalized medical services according to each cause. Further studies are needed to confirm whether such a prediction algorithm can be used in real-world clinical settings to improve the diagnosis of sarcopenia.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00292-3.

An Extensive Study of Phenol Red Thread as a Novel Non-Invasive Tear Sampling Technique for Proteomics Studies: Comparison with Two Commonly Used Methods

Tear samples are considered in recent publications as easily, noninvasively collectible information sources for precision medicine. Their complex composition may aid the identification of biomarkers and the monitoring of the effectiveness of treatments for the eye and systemic diseases. Sample collection and processing are key steps in any analytical method, especially if subtle personal differences need to be detected. In this work, we evaluate the usability of a novel sample collection technique for human tear samples using phenol red threads (cotton thread treated with the pH indicator phenol red), which are efficiently used to measure tear volume in clinical diagnosis. The low invasiveness and low discomfort to the patients have already been demonstrated, but their applicability for proteomic sample collection has not yet been compared to other methods. We have shown, using various statistical approaches, the qualitative and quantitative differences in proteomic samples collected with this novel and two traditional methods using either glass capillaries or Schirmer’s paper strips. In all parameters studied, the phenol red threads proved to be equally or even more suitable than traditional methods. Based on detectability using different sampling methods, we have classified proteins in tear samples.

Derivative Three-Dimensional Synchronous Fluorescence Analysis of Tear Fluid and Their Processing for the Diagnosis of Glaucoma

Background: Sensitive and rapid diagnosis of the early stages of glaucoma from tear fluid is a great challenge for researchers. Methods: Tear fluid was analyzed using three-dimensional synchronous fluorescence spectroscopy (3D-SFS). Our previously published results briefly describe the main methods which applied the second derivative to a selected synchronous spectrum Δλ = 110 nm in distinguishing between healthy subjects (CTRL) and patients with glaucoma (POAG). Results: In this paper, a novel strategy was used to evaluate three-dimensional spectra from the tear fluid database of our patients. A series of synchronous excitation spectra were processed as a front view and presented as a single curve showcasing the overall fluorescence profile of the tear fluid. The second derivative spectrum provides two parameters that can enhance the distinction between CTRL and POAG tear fluid. Conclusions: Combining different types of 3D-SFS data can offer interesting and useful diagnostic tools and it can be used as input for machine learning and process automation.

Clinical Tear Fluid Proteomics—A Novel Tool in Glaucoma Research

Tear fluid forms the outermost layer of the ocular surface and its characteristics and composition have been connected to various ocular surface diseases. As tear proteomics enables the non-invasive investigation of protein levels in the tear fluid, it has become an increasingly popular approach in ocular surface and systemic disease studies. Glaucoma, which is a set of multifactorial diseases affecting mainly the optic nerve and retinal ganglion cells, has also been studied using tear proteomics. In this condition, the complete set of pathophysiological changes occurring in the eye is not yet fully understood, and biomarkers for early diagnosis and accurate treatment selection are needed. More in-depth analyses of glaucoma tear proteomics have started to emerge only more recently with the implementation of LC-MS/MS and other modern technologies. The aim of this review was to examine the published data of the tear protein changes occurring during glaucoma, its topical treatment, and surgical interventions.

Characterization of oral and gut microbiome and plasma metabolomics in COVID-19 patients after 1-year follow-up

BACKGROUND

Due to the outbreak and rapid spread of coronavirus disease 2019 (COVID-19), more than 160 million patients have become convalescents worldwide to date. Significant alterations have occurred in the gut and oral microbiome and metabonomics of patients with COVID-19. However, it is unknown whether their characteristics return to normal after the 1-year recovery.

METHODS

We recruited 35 confirmed patients to provide specimens at discharge and one year later, as well as 160 healthy controls. A total of 497 samples were prospectively collected, including 219 tongue-coating, 129 stool and 149 plasma samples. Tongue-coating and stool samples were subjected to 16S rRNA sequencing, and plasma samples were subjected to untargeted metabolomics testing.

RESULTS

The oral and gut microbiome and metabolomics characteristics of the 1-year convalescents were restored to a large extent but did not completely return to normal. In the recovery process, the microbial diversity gradually increased. Butyric acid-producing microbes and Bifidobacterium gradually increased, whereas lipopolysaccharide-producing microbes gradually decreased. In addition, sphingosine-1-phosphate, which is closely related to the inflammatory factor storm of COVID-19, increased significantly during the recovery process. Moreover, the predictive models established based on the microbiome and metabolites of patients at the time of discharge reached high efficacy in predicting their neutralizing antibody levels one year later.

CONCLUSIONS

This study is the first to characterize the oral and gut microbiome and metabonomics in 1-year convalescents of COVID-19. The key microbiome and metabolites in the process of recovery were identified, and provided new treatment ideas for accelerating recovery. And the predictive models based on the microbiome and metabolomics afford new insights for predicting the recovery situation which benefited affected individuals and healthcare.

The Predictive Effect of the 8th AJCC Pathological Prognostic Staging on the Benefit of Postmastectomy Radiotherapy in N2/N3 Breast Cancer

Background

The role of the 8th American Joint Committee on Cancer (AJCC) pathological prognostic staging (PPS) on treatment-decision making of breast cancer (BC) remains unclear. This study aimed to investigate the predictive effect of the 8th AJCC PPS on the benefit of postmastectomy radiotherapy (PMRT) in N2/N3 BC.

Methods

We included women with stage N2/3 BC diagnosed between 2010 and 2018 from the Surveillance, Epidemiology, and End Results database. The effect of PMRT on breast cancer-specific survival (BCSS) was evaluated using the multivariate Cox proportional-hazards models.

Results

A total of 13,445 patients were identified, including 10,547 (78.4%) patients treated with PMRT. All patients had reassigned stages based on the 8th AJCC PPS. There were 7102 patients (52.8%) that had stage changed, including 1160 patients (8.6%) were upstaged and 5942 patients (44.2%) were downstaged from the 7th AJCC anatomical staging (AS) to the 8th AJCC PPS. Regarding the 7th AJCC AS, 7603 (56.5%), 948 (7.1%), and 4895 (36.4%) were stage IIIA, IIIB, and IIIC diseases, respectively. Using the 8th AJCC PPS, 3525 (26.2%), 460 (3.4%), 1335 (9.9%), 3457 (25.7%), 2169 (19.1%), and 2100 (15.6%) patients were restaged as IB, IIA, IIB, IIIA, IIIB, and IIIC diseases, respectively. The PPS displayed increased prognostic accuracy and improved model fit with respect to BCSS compared to the 7th AS (C-index, 0.731 vs 0.605, P < 0.001; Akaike Information Criterion, 42141 vs 43118). Regarding the AS, the receipt of PMRT was associated with a better BCSS in those with stage IIIA (P = 0.004), IIIB (P = 0.003), and IIIC (P < 0.001) diseases. Using the PPS, the receipt of PMRT was not associated with a better BCSS among patients with stage IB (P = 0.446), IIA (P = 0.140), and IIB (P = 0.248) disease, while the receipt of PMRT was associated with a better BCSS for those with stage IIIA (P = 0.009), IIIB (P < 0.001), and IIIC (P < 0.001) disease.

Conclusion

The 8th AJCC staging provides superior risk stratification and a better tool to predict the benefit of PMRT in N2/3 BC.

Anti-breast cancer effects of phytochemicals: primary, secondary, and tertiary care

Breast cancer incidence is actually the highest one among all cancers. Overall breast cancer management is associated with challenges considering risk assessment and predictive diagnostics, targeted prevention of metastatic disease, appropriate treatment options, and cost-effectiveness of approaches applied. Accumulated research evidence indicates promising anti-cancer effects of phytochemicals protecting cells against malignant transformation, inhibiting carcinogenesis and metastatic spread, supporting immune system and increasing effectiveness of conventional anti-cancer therapies, among others. Molecular and sub-/cellular mechanisms are highly complex affecting several pathways considered potent targets for advanced diagnostics and cost-effective treatments. Demonstrated anti-cancer affects, therefore, are clinically relevant for improving individual outcomes and might be applicable to the primary (protection against initial cancer development), secondary (protection against potential metastatic disease development), and tertiary (towards cascading complications) care. However, a detailed data analysis is essential to adapt treatment algorithms to individuals’ and patients’ needs. Consequently, advanced concepts of patient stratification, predictive diagnostics, targeted prevention, and treatments tailored to the individualized patient profile are instrumental for the cost-effective application of natural anti-cancer substances to improve overall breast cancer management benefiting affected individuals and the society at large.

Applications of Tandem Mass Spectrometry (MS/MS) in Protein Analysis for Biomedical Research

Mass Spectrometry (MS) allows the analysis of proteins and peptides through a variety of methods, such as Electrospray Ionization-Mass Spectrometry (ESI-MS) or Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry (MALDI-MS). These methods allow identification of the mass of a protein or a peptide as intact molecules or the identification of a protein through peptide-mass fingerprinting generated upon enzymatic digestion. Tandem mass spectrometry (MS/MS) allows the fragmentation of proteins and peptides to determine the amino acid sequence of proteins (top-down and middle-down proteomics) and peptides (bottom-up proteomics). Furthermore, tandem mass spectrometry also allows the identification of post-translational modifications (PTMs) of proteins and peptides. Here, we discuss the application of MS/MS in biomedical research, indicating specific examples for the identification of proteins or peptides and their PTMs as relevant biomarkers for diagnostic and therapy.

Prostate cancer treatment costs increase more rapidly than for any other cancer—how to reverse the trend?

According to GLOBOCAN, about 1.41 million new prostate cancer (PCa) cases were registered in the year 2020 globally. The corresponding socio-economic burden is enormous. Anti-cancer mRNA-based therapy is a promising approach, the principle of which is currently applied for anti-COVID-19 vaccination, undergoing a detailed investigation in populations considering its short- and long-term effectiveness and potential side effects. Pragmatically considered, it will take years or even decades to make mRNA therapy working for any type of cancers, and if possible, for individual malignancy sub-types which are many specifically for the PCa. Actually, the costs of treating PCa are increasing more rapidly than those of any other cancer. The trend has to be reversed now, not in a couple of years. In general, two main components are making currently applied reactive (management of clinically manifested disease) PCa treatment particularly expensive. On one hand, it is rapidly increasing incidence of the disease and metastatic PCa as its subtype. To this end, rapidly increasing PCa incidence rates in young and middle-aged male sub-populations should be taken into account as a long-term contributor to the metastatic disease potentially developed later on in life. On the other hand, patient stratification to differentiate between non-metastatic PCa (no need for an extensive and costly treatment) and particularly aggressive cancer subtypes requiring personalised treatment algorithms is challenging. Considering current statistics, it becomes obvious that reactive medicine got at its limit in PCa management. Multi-professional expertise is unavoidable to create and implement anti-PCa programmes in the population. In our strategic paper, we exemplify challenging PCa management by providing detailed expert recommendations for primary (health risk assessment), secondary (prediction and prevention of metastatic disease in PCa) and tertiary (making palliative care to the management of chronic disease) care in the framework of predictive, preventive and personalised medicine.

Metabolic phenotyping of tear fluid as a prognostic tool for personalised medicine exemplified by T2DM patients

Background/aims

Concerning healthcare approaches, a paradigm change from reactive medicine to predictive approaches, targeted prevention, and personalisation of medical services is highly desirable. This raises demand for biomarker signatures that support the prediction and diagnosis of diseases, as well as monitoring strategies regarding therapeutic efficacy and supporting individualised treatments. New methodological developments should preferably rely on non-invasively sampled biofluids like sweat and tears in order to provide optimal compliance, reduce costs, and ensure availability of the biomaterial. Here, we have thus investigated the metabolic composition of human tears in comparison to finger sweat in order to find biofluid-specific marker molecules derived from distinct secretory glands. The comprehensive investigation of numerous biofluids may lead to the identification of novel biomarker signatures. Moreover, tear fluid analysis may not only provide insight into eye pathologies but may also be relevant for the prediction and monitoring of disease progression and/ or treatment of systemic disorders such as type 2 diabetes mellitus.

Methods

Sweat and tear fluid were sampled from 20 healthy volunteers using filter paper and commercially available Schirmer strips, respectively. Finger sweat analysis has already been successfully established in our laboratory. In this study, we set up and evaluated methods for tear fluid extraction and analysis using high-resolution mass spectrometry hyphenated with liquid chromatography, using optimised gradients each for metabolites and eicosanoids. Sweat and tears were systematically compared using statistical analysis. As second approach, we performed a clinical pilot study with 8 diabetic patients and compared them to 19 healthy subjects.

Results

Tear fluid was found to be a rich source for metabolic phenotyping. Remarkably, several molecules previously identified by us in sweat were found significantly enriched in tear fluid, including creatine or taurine. Furthermore, other metabolites such as kahweol and various eicosanoids were exclusively detectable in tears, demonstrating the orthogonal power for biofluid analysis in order to gain information on individual health states. The clinical pilot study revealed that many endogenous metabolites that have previously been linked to type 2 diabetes such as carnitine, tyrosine, uric acid, and valine were indeed found significantly up-regulated in tears of diabetic patients. Nicotinic acid and taurine were elevated in the diabetic cohort as well and may represent new biomarkers for diabetes specifically identified in tear fluid. Additionally, systemic medications, like metformin, bisoprolol, and gabapentin, were readily detectable in tears of patients.

Conclusions

The high number of identified marker molecules found in tear fluid apparently supports disease development prediction, developing preventive approaches as well as tailoring individual patients’ treatments and monitoring treatment efficacy. Tear fluid analysis may also support pharmacokinetic studies and patient compliance control.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00272-7.

Oxidative Stress in the Pathogenesis of Aorta Diseases as a Source of Potential Biomarkers and Therapeutic Targets, with a Particular Focus on Ascending Aorta Aneurysms

Aorta diseases, such as ascending aorta aneurysm (AsAA), are complex pathologies, currently defined as inflammatory diseases with a strong genetic susceptibility. They are difficult to manage, being insidious and silent pathologies whose diagnosis is based only on imaging data. No diagnostic and prognostic biomarkers or markers of outcome have been known until now. Thus, their identification is imperative. Certainly, a deep understanding of the mechanisms and pathways involved in their pathogenesis might help in such research. Recently, the key role of oxidative stress (OS) on the pathophysiology of aorta disease has emerged. Here, we describe and discuss these aspects by revealing some OS pathways as potential biomarkers, their underlying limitations, and potential solutions and approaches, as well as some potential treatments.

Cancer glycomics offers potential biomarkers and therapeutic targets in the framework of 3P medicine

Glycosylation is one of the most important post-translational modifications (PTMs) in a protein, and is the most abundant and diverse biopolymer in nature. Glycans are involved in multiple biological processes of cancer initiation and progression, including cell-cell interactions, cell-extracellular matrix interactions, tumor invasion and metastasis, tumor angiogenesis, and immune regulation. As an important biomarker, tumor-associated glycosylation changes have been extensively studied. This article reviews recent advances in glycosylation-based biomarker research, which is useful for cancer diagnosis and prognostic assessment. Truncated O-glycans, sialylation, fucosylation, and complex branched structures have been found to be the most common structural patterns in malignant tumors. In recent years, immunochemical methods, lectin recognition-based methods, mass spectrometry (MS)-related methods, and fluorescence imaging-based in situ methods have greatly promoted the discovery and application potentials of glycomic and glycoprotein biomarkers in various cancers. In particular, MS-based proteomics has significantly facilitated the comprehensive research of extracellular glycoproteins, increasing our understanding of their critical roles in regulating cellular activities. Predictive, preventive and personalized medicine (PPPM; 3P medicine) is an effective approach of early prediction, prevention and personalized treatment for different patients, and it is known as the new direction of medical development in the 21st century and represents the ultimate goal and highest stage of medical development. Glycosylation has been revealed to have new diagnostic, prognostic, and even therapeutic potentials. The purpose of glycosylation analysis and utilization of biology is to make a fundamental change in health care and medical practice, so as to lead medical research and practice into a new era of 3P medicine.

PKC-mediated phosphorylation and activation of the MEK/ERK pathway as a mechanism of acquired trastuzumab resistance in HER2-positive breast cancer

Protein expression, activation and stability are regulated through inter-connected signal transduction pathways resulting in specific cellular states. This study sought to differentiate between the complex mechanisms of intrinsic and acquired trastuzumab resistance, by quantifying changes in expression and activity of proteins (phospho-protein profile) in key signal transduction pathways, in breast cancer cellular models of trastuzumab resistance. To this effect, we utilized a multiplex, bead-based protein assay, DigiWest^®, to measure around 100 proteins and protein modifications using specific antibodies. The main advantage of this methodology is the quantification of multiple analytes in one sample, utilising input volumes of a normal western blot. The intrinsically trastuzumab-resistant cell line JIMT-1 showed the largest number of concurrent resistance mechanisms, including PI3K/Akt and RAS/RAF/MEK/ERK activation, β catenin stabilization by inhibitory phosphorylation of GSK3β, cell cycle progression by Rb suppression, and CREB-mediated cell survival. MAPK (ERK) pathway activation was common to both intrinsic and acquired resistance cellular models. The overexpression of upstream RAS/RAF, however, was confined to JIMT 1; meanwhile, in a cellular model of acquired trastuzumab resistance generated in this study (T15), entry into the ERK pathway seemed to be mostly mediated by PKCα activation. This is a novel observation and merits further investigation that can lead to new therapeutic combinations in HER2-positive breast cancer with acquired therapeutic resistance.