Characterization of Total RNA, CD44, FASN, and PTEN mRNAs from Extracellular Vesicles as Biomarkers in Gastric Cancer Patients

Recent research on material-based methods for isolation of extracellular vesicles

Extracellular vesicles (EVs) are nanoparticles secreted by cells with a closed phospholipid bilayer structure, which can participate in various physiological and pathological processes and have significant clinical value in disease diagnosis, targeted therapy and prognosis assessment. EV isolation methods currently include differential ultracentrifugation, ultrafiltration, size exclusion chromatography, immunoaffinity, polymer co-precipitation and microfluidics. In addition, material-based biochemical or biophysical approaches relying on intrinsic properties of the material or its surface-modified functionalized monomers, demonstrated unique advantages in the efficient isolation of EVs. In order to provide new ideas for the subsequent development of material-based EV isolation methods, this review will focus on the principle, research status and application prospects of material-based EV isolation methods based on different material carriers and functional monomers.

Extracellular vesicle-based liquid biopsy biomarkers and their application in precision immuno-oncology

While the field of precision oncology is rapidly expanding and more targeted options are revolutionizing cancer treatment paradigms, therapeutic resistance particularly to immunotherapy remains a pressing challenge. This can be largely attributed to the dynamic tumor-stroma interactions that continuously alter the microenvironment. While to date most advancements have been made through examining the clinical utility of tissue-based biomarkers, their invasive nature and lack of a holistic representation of the evolving disease in a real-time manner could result in suboptimal treatment decisions. Thus, using minimally-invasive approaches to identify biomarkers that predict and monitor treatment response as well as alert to the emergence of recurrences is of a critical need. Currently, research efforts are shifting towards developing liquid biopsy-based biomarkers obtained from patients over the course of disease. Liquid biopsy represents a unique opportunity to monitor intercellular communication within the tumor microenvironment which could occur through the exchange of extracellular vesicles (EVs). EVs are lipid bilayer membrane nanoscale vesicles which transfer a plethora of biomolecules that mediate intercellular crosstalk, shape the tumor microenvironment, and modify drug response. The capture of EVs using innovative approaches, such as microfluidics, magnetic beads, and aptamers, allow their analysis via high throughput multi-omics techniques and facilitate their use for biomarker discovery. Artificial intelligence, using machine and deep learning algorithms, is advancing multi-omics analyses to uncover candidate biomarkers and predictive signatures that are key for translation into clinical trials. With the increasing recognition of the role of EVs in mediating immune evasion and as a valuable biomarker source, these real-time snapshots of cellular communication are promising to become an important tool in the field of precision oncology and spur the recognition of strategies to block resistance to immunotherapy. In this review, we discuss the emerging role of EVs in biomarker research describing current advances in their isolation and analysis techniques as well as their function as mediators in the tumor microenvironment. We also highlight recent lung cancer and melanoma studies that point towards their application as predictive biomarkers for immunotherapy and their potential clinical use in precision immuno-oncology.

Survey of organ-derived small extracellular vesicles and particles (sEVPs) to identify selective protein markers in mouse serum

Extracellular vesicles and particles (EVPs) are secreted by organs across the body into different circulatory systems, including the bloodstream, and reflect pathophysiologic conditions of the organ. However, the heterogeneity of EVPs in the blood makes it challenging to determine their organ of origin. We hypothesized that small (s)EVPs (<100 nm in diameter) in the bloodstream carry distinctive protein signatures associated with each originating organ, and we investigated this possibility by studying the proteomes of sEVPs produced by six major organs (brain, liver, lung, heart, kidney, fat). We found that each organ contained distinctive sEVP proteins: 68 proteins were preferentially found in brain sEVPs, 194 in liver, 39 in lung, 15 in heart, 29 in kidney, and 33 in fat. Furthermore, we isolated sEVPs from blood and validated the presence of sEVP proteins associated with the brain (DPP6, SYT1, DNM1L), liver (FABPL, ARG1, ASGR1/2), lung (SFPTA1), heart (CPT1B), kidney (SLC31), and fat (GDN). We further discovered altered levels of these proteins in serum sEVPs prepared from old mice compared to young mice. In sum, we have cataloged sEVP proteins that can serve as potential biomarkers for organ identification in serum and show differential expression with age.

Overview of miR-106a Regulatory Roles: from Cancer to Aging

MicroRNAs (miRNAs) comprise a class of non-coding RNA with extensive regulatory functions within cells. MiR-106a is recognized for its super-regulatory roles in vital processes. Hence, the analysis of its expression in association with diseases has attracted considerable attention for molecular diagnosis and drug development. Numerous studies have investigated miR-106 target genes and shown that this miRNA regulates the expression of some critical cell cycle and apoptosis factors, suggesting miR-106a as an ideal diagnostic and prognostic biomarker with therapeutic potential. Furthermore, the reported correlation between miR-106a expression level and cancer drug resistance has demonstrated the complexity of its functions within different tissues. In this study, we have conducted a comprehensive review on the expression levels of miR-106a in various cancers and other diseases, emphasizing its target genes. The promising findings surrounding miR-106a suggest its potential as a valuable biomolecule. However, further validation assessments and overcoming existing limitations are crucial steps before its clinical implementation can be realized.

A critical appraisal of the relative contribution of tissue architecture, genetics, epigenetics and cell metabolism to carcinogenesis

Here we contrast several carcinogenesis models. The somatic-mutation-theory posits mutations as main causes of malignancy. However, inconsistencies led to alternative explanations. For example, the tissue-organization-field-theory considers disrupted tissue-architecture as main cause. Both models can be reconciled using systems-biology-approaches, according to which tumors hover in states of self-organized criticality between order and chaos, are emergent results of multiple deviations and are subject to general laws of nature: inevitable variation(mutation) explainable by increased entropy(second-law-of-thermodynamics) or indeterminate decoherence upon measurement of superposed quantum systems(quantum mechanics), followed by Darwinian-selection. Genomic expression is regulated by epigenetics. Both systems cooperate. So cancer is neither just a mutational nor an epigenetic problem. Rather, epigenetics links environmental cues to endogenous genetics engendering a regulatory machinery that encompasses specific cancer-metabolic-networks. Interestingly, mutations occur at all levels of this machinery (oncogenes/tumor-suppressors, epigenetic-modifiers, structure-genes, metabolic-genes). Therefore, in most cases, DNA mutations may be the initial and crucial cancer-promoting triggers.

Identification of Metabolism-Related Proteins as Biomarkers of Insulin Resistance and Potential Mechanisms of m6A Modification

BACKGROUND

Insulin resistance (IR) is a major contributing factor to the pathogenesis of metabolic syndrome and type 2 diabetes mellitus (T2D). Adipocyte metabolism is known to play a crucial role in IR. Therefore, the aims of this study were to identify metabolism-related proteins that could be used as potential biomarkers of IR and to investigate the role of N⁶-methyladenosine (m⁶A) modification in the pathogenesis of this condition.

METHODS

RNA-seq data on human adipose tissue were retrieved from the Gene Expression Omnibus database. The differentially expressed genes of metabolism-related proteins (MP-DEGs) were screened using protein annotation databases. Biological function and pathway annotations of the MP-DEGs were performed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Key MP-DEGs were screened, and a protein-protein interaction (PPI) network was constructed using STRING, Cytoscape, MCODE, and CytoHubba. LASSO regression analysis was used to select primary hub genes, and their clinical performance was assessed using receiver operating characteristic (ROC) curves. The expression of key MP-DEGs and their relationship with m⁶A modification were further verified in adipose tissue samples collected from healthy individuals and patients with IR.

RESULTS

In total, 69 MP-DEGs were screened and annotated to be enriched in pathways related to hormone metabolism, low-density lipoprotein particle and carboxylic acid transmembrane transporter activity, insulin signaling, and AMPK signaling. The MP-DEG PPI network comprised 69 nodes and 72 edges, from which 10 hub genes (FASN, GCK, FGR, FBP1, GYS2, PNPLA3, MOGAT1, SLC27A2, PNPLA3, and ELOVL6) were identified. FASN was chosen as the key gene because it had the highest maximal clique centrality (MCC) score. GCK, FBP1, and FGR were selected as primary genes by LASSO analysis. According to the ROC curves, GCK, FBP1, FGR, and FASN could be used as potential biomarkers to detect IR with good sensitivity and accuracy (AUC = 0.80, 95% CI: 0.67-0.94; AUC = 0.86, 95% CI: 0.74-0.94; AUC = 0.83, 95% CI: 0.64-0.92; AUC = 0.78, 95% CI: 0.64-0.92). The expression of FASN, GCK, FBP1, and FGR was significantly correlated with that of IGF2BP3, FTO, EIF3A, WTAP, METTL16, and LRPPRC (p < 0.05). In validation clinical samples, the FASN was moderately effective for detecting IR (AUC = 0.78, 95% CI: 0.69-0.80), and its expression was positively correlated with the methylation levels of FASN (r = 0.359, p = 0.001).

CONCLUSION

Metabolism-related proteins play critical roles in IR. Moreover, FASN and GCK are potential biomarkers of IR and may be involved in the development of T2D via their m⁶A modification. These findings offer reliable biomarkers for the early detection of T2D and promising therapeutic targets.

Multi-Omics Integrative Approach of Extracellular Vesicles: A Future Challenging Milestone

In the era of multi-omic sciences, dogma on singular cause-effect in physio-pathological processes is overcome and system biology approaches have been providing new perspectives to see through. In this context, extracellular vesicles (EVs) are offering a new level of complexity, given their role in cellular communication and their activity as mediators of specific signals to target cells or tissues. Indeed, their heterogeneity in terms of content, function, origin and potentiality contribute to the cross-interaction of almost every molecular process occurring in a complex system. Such features make EVs proper biological systems being, therefore, optimal targets of omic sciences. Currently, most studies focus on dissecting EVs content in order to either characterize it or to explore its role in various pathogenic processes at transcriptomic, proteomic, metabolomic, lipidomic and genomic levels. Despite valuable results being provided by individual omic studies, the categorization of EVs biological data might represent a limit to be overcome. For this reason, a multi-omic integrative approach might contribute to explore EVs function, their tissue-specific origin and their potentiality. This review summarizes the state-of-the-art of EVs omic studies, addressing recent research on the integration of EVs multi-level biological data and challenging developments in EVs origin.