Integrating Proteomics and Lipidomics for Evaluating the Risk of Breast Cancer Progression: A Pilot Study

Omics in Keratoconus: From Molecular to Clinical Practice

Keratoconus (KC) is a progressive ocular disorder marked by structural and functional alterations of the cornea, leading to significant visual impairment. Recent studies indicate that these corneal changes are linked to molecular and cellular mechanisms that disrupt and degrade the extracellular matrix. This degradation is influenced by proteinases that contribute to a loss of homeostasis and an imbalance in the antioxidant/oxidative state within the cornea, fostering oxidative stress, inflammation, and apoptosis. Although these biological processes have been identified primarily through molecular biology research, omics technologies have significantly advanced our understanding of the physiological and pathological phenomena associated with KC. Omics studies encompassing genomics, transcriptomics, proteomics, epigenomics, and metabolomics, have emerged as critical tools in elucidating the complex biological landscape of various diseases, including ocular conditions. The integrative application of these studies has demonstrated their potential in personalizing medicine across diverse fields such as oncology, neurology, and ophthalmology. This review aims to describe findings from omics research applied to keratoconus, highlighting the genomic, transcriptomic, proteomic, epigenomic, and metabolomic aspects derived from ocular and other biological samples. Notably, the molecular insights gained from these studies hold promise for identifying biomarkers of keratoconus, which could enhance diagnostic accuracy and therapeutic strategies. The exploration of these biomarkers may facilitate improved management and treatment options for patients, contributing to personalized care in keratoconus management.

First-Trimester Preeclampsia-Induced Disturbance in Maternal Blood Serum Proteome: A Pilot Study

Preeclampsia (PE) is a complex and multifaceted obstetric syndrome characterized by several distinct molecular subtypes. It complicates up to 5% of pregnancies and significantly contributes to maternal and newborn morbidity, thereby diminishing the long-term quality of life for affected women. Due to the widespread dissatisfaction with the effectiveness of existing approaches for assessing PE risk, there is a pressing need for ongoing research to identify newer, more accurate predictors. This study aimed to investigate early changes in the maternal serum proteome and associated signaling pathways. The levels of 125 maternal serum proteins at 11-13 weeks of gestation were quantified using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with the BAK-125 kit. Ten serum proteins emerged as potential early markers for PE: Apolipoprotein M (APOM), Complement C1q subcomponent subunit B (C1QB), Lysozyme (LYZ), Prothrombin (F2), Albumin (ALB), Zinc-alpha-2-glycoprotein (AZGP1), Tenascin-X (TNXB), Alpha-1-antitrypsin (SERPINA1), Attractin (ATRN), and Apolipoprotein A-IV (APOA4). Notably, nine of these proteins have previously been associated with PE in prior research, underscoring the consistency and reliability of our findings. These proteins play key roles in critical molecular processes, including complement and coagulation cascades, platelet activation, and insulin-like growth factor pathways. To improve the early prediction of PE, a highly effective Support Vector Machine (SVM) model was developed, analyzing 19 maternal serum proteins from the first trimester. This model achieved an area under the curve (AUC) of 0.91, with 87% sensitivity and 95% specificity, and a hazard ratio (HR) of 13.5 (4.6-40.8) with p < 0.001. These findings demonstrate that serum protein-based SVM models possess significantly higher predictive power compared to the routine first-trimester screening test, highlighting their superior utility in the early detection and risk stratification of PE.

From Lipid Signatures to Cellular Responses: Unraveling the Complexity of Melanoma and Furthering Its Diagnosis and Treatment

Recent advancements in mass spectrometry have significantly enhanced our understanding of complex lipid profiles, opening new avenues for oncological diagnostics. This review highlights the importance of lipidomics in the comprehension of certain metabolic pathways and its potential for the detection and characterization of various cancers, in particular melanoma. Through detailed case studies, we demonstrate how lipidomic analysis has led to significant breakthroughs in the identification and understanding of cancer types and its potential for detecting unique biomarkers that are instrumental in its diagnosis. Additionally, this review addresses the technical challenges and future perspectives of these methodologies, including their potential expansion and refinement for clinical applications. The discussion underscores the critical role of lipidomic profiling in advancing cancer diagnostics, proposing a new paradigm in how we approach this devastating disease, with particular emphasis on its application in comparative oncology.

Diagnostic Value of Menstrual Blood Lipidomics in Endometriosis: A Pilot Study

Endometriosis is a prevalent chronic inflammatory disease characterized by a considerable delay between initial symptoms and diagnosis through surgery. The pressing need for a timely, non-invasive diagnostic solution underscores the focus of current research efforts. This study examines the diagnostic potential of the menstrual blood lipidome. The lipid profile of 39 samples (23 women with endometriosis and 16 patients in a control group) was acquired using reverse-phase high-performance liquid chromatography-mass spectrometry with LipidMatch processing and identification. Profiles were normalized based on total ion counts. Significant differences in lipids were determined using the Mann-Whitney test. Lipids for the diagnostic model, based on logistic regression, were selected using a combination of variance importance projection filters and Akaike information criteria. Levels of ceramides, sphingomyelins, cardiolipins, triacylglycerols, acyl- and alkenyl-phosphatidylethanolamines, and alkenyl-phosphatidylcholines increased, while acyl- and alkyl-phosphatidylcholines decreased in cases of endometriosis. Plasmenylphosphatidylethanolamine PE P-16:0/18:1 and cardiolipin CL 16:0_18:0_22:5_22:6 serve as marker lipids in the diagnostic model, exhibiting a sensitivity of 81% and specificity of 85%. The diagnostic approach based on dried spots of menstrual blood holds promise as an alternative to traditional non-invasive methods for endometriosis screening.

A Multiomics, Molecular Atlas of Breast Cancer Survivors

Breast cancer imposes a significant burden globally. While the survival rate is steadily improving, much remains to be elucidated. This observational, single time point, multiomic study utilizing genomics, proteomics, targeted and untargeted metabolomics, and metagenomics in a breast cancer survivor (BCS) and age-matched healthy control cohort (N = 100) provides deep molecular phenotyping of breast cancer survivors. In this study, the BCS cohort had significantly higher polygenic risk scores for breast cancer than the control group. Carnitine and hexanoyl carnitine were significantly different. Several bile acid and fatty acid metabolites were significantly dissimilar, most notably the Omega-3 Index (O3I) (significantly lower in BCS). Proteomic and metagenomic analyses identified group and pathway differences, which warrant further investigation. The database built from this study contributes a wealth of data on breast cancer survivorship where there has been a paucity, affording the ability to identify patterns and novel insights that can drive new hypotheses and inform future research. Expansion of this database in the treatment-naïve, newly diagnosed, controlling for treatment confounders, and through the disease progression, can be leveraged to profile and contextualize breast cancer and breast cancer survivorship, potentially leading to the development of new strategies to combat this disease and improve the quality of life for its victims.

Alpha-2-Macroglobulin Is a Novel Anticancer Agent

INTRODUCTION

Melanoma is the most aggressive skin cancer, with an increasing occurrence. Despite the recent important improvements due to novel immunotherapy approaches, when late diagnosed, melanoma prognosis is poor due to the metastatic progression and drug-resistance onset. Therefore, there is an urgent need to identify additional therapeutic targets. Melanoma invasive behavior is related to the activity of metalloproteases, able to degrade extracellular matrix leading to tumor dissemination. A recent study suggested that the most potent proteases inhibitor alpha-2-macroglobulin (A2MG) from plasma of hibernating fishes exerts potent antiproliferative effects. Our previous studies showed a significant reduction of A2MG in sera from mice/human melanoma models.

METHODS

Gene and protein expression studies have been performed by using platforms and databases available online containing expression data from thousands of patients and healthy controls.

RESULTS

We carried out an extensive bioinformatics analysis to evaluate the A2MG gene/protein expression on a large cohort of patients affected by many different cancer types, compared to healthy control subjects, and we found a highly significant difference of A2MG expression in 20 out of 31 cancer types (including melanoma) compared to healthy controls. Similar results were also confirmed at the proteomic level using another platform available online. Further, we found that higher A2MG expression is significantly related to overall survival in different cancers including melanoma.

CONCLUSION

Our results strongly suggest A2MG as a novel molecular target in melanoma therapy, as well as in other cancer types.

Quantitative Proteomics of Maternal Blood Plasma in Isolated Intrauterine Growth Restriction

Intrauterine growth restriction (IUGR) remains a significant concern in modern obstetrics, linked to high neonatal health problems and even death, as well as childhood disability, affecting adult quality of life. The role of maternal and fetus adaptation during adverse pregnancy is still not completely understood. This study aimed to investigate the disturbance in biological processes associated with isolated IUGR via blood plasma proteomics. The levels of 125 maternal plasma proteins were quantified by liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with corresponding stable isotope-labeled peptide standards (SIS). Thirteen potential markers of IUGR (Gelsolin, Alpha-2-macroglobulin, Apolipoprotein A-IV, Apolipoprotein B-100, Apolipoprotein(a), Adiponectin, Complement C5, Apolipoprotein D, Alpha-1B-glycoprotein, Serum albumin, Fibronectin, Glutathione peroxidase 3, Lipopolysaccharide-binding protein) were found to be inter-connected in a protein-protein network. These proteins are involved in plasma lipoprotein assembly, remodeling, and clearance; lipid metabolism, especially cholesterol and phospholipids; hemostasis, including platelet degranulation; and immune system regulation. Additionally, 18 proteins were specific to a particular type of IUGR (early or late). Distinct patterns in the coagulation and fibrinolysis systems were observed between isolated early- and late-onset IUGR. Our findings highlight the complex interplay of immune and coagulation factors in IUGR and the differences between early- and late-onset IUGR and other placenta-related conditions like PE. Understanding these mechanisms is crucial for developing targeted interventions and improving outcomes for pregnancies affected by IUGR.

Identification of Metabolomic Signatures for Ischemic Hypoxic Encephalopathy Using a Neonatal Rat Model

A study was performed to determine early metabolomic markers of ischemic hypoxic encephalopathy (HIE) using a Rice-Vannucci model for newborn rats. Dried blood spots from 7-day-old male and female rat pups, including 10 HIE-affected animals and 16 control animals, were analyzed by liquid chromatography coupled with mass spectrometry (HPLC-MS) in positive and negative ion recording modes. Multivariate statistical analysis revealed two distinct clusters of metabolites in both HPLC-MS modes. Subsequent univariate statistical analysis identified 120 positive and 54 negative molecular ions that exhibited statistically significant change in concentration, with more than a 1.5-fold difference after HIE. In the HIE group, the concentrations of steroid hormones, saturated mono- and triglycerides, and phosphatidylcholines (PCs) were significantly decreased in positive mode. On the contrary, the concentration of unsaturated PCs was increased in the HIE group. Among negatively charged molecular ions, the greatest variations were found in the categories of phosphatidylcholines, phosphatidylinositols, and triglycerides. The major metabolic pathways associated with changed metabolites were analyzed for both modes. Metabolic pathways such as steroid biosynthesis and metabolism fatty acids were most affected. These results underscored the central role of glycerophospholipid metabolism in triggering systemic responses in HIE. Therefore, lipid biomarkers' evaluation by targeted HPLC-MS research could be a promising approach for the early diagnosis of HIE.