Exosomes and prostate cancer management

Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications

Prostate cancer (PCa) is a significant global contributor to mortality, predominantly affecting males aged 65 and above. The field of omics has recently gained traction due to its capacity to provide profound insights into the biochemical mechanisms underlying conditions like prostate cancer. This involves the identification and quantification of low-molecular-weight metabolites and proteins acting as crucial biochemical signals for early detection, therapy assessment, and target identification. A spectrum of analytical methods is employed to discern and measure these molecules, revealing their altered biological pathways within diseased contexts. Metabolomics and proteomics generate refined data subjected to detailed statistical analysis through sophisticated software, yielding substantive insights. This review aims to underscore the major contributions of multi-omics to PCa research, covering its core principles, its role in tumor biology characterization, biomarker discovery, prognostic studies, various analytical technologies such as mass spectrometry and Nuclear Magnetic Resonance, data processing, and recent clinical applications made possible by an integrative "omics" approach. This approach seeks to address the challenges associated with current PCa treatments. Hence, our research endeavors to demonstrate the valuable applications of these potent tools in investigations, offering significant potential for understanding the complex biochemical environment of prostate cancer and advancing tailored therapeutic approaches for further development.

Advances of machine learning-assisted small extracellular vesicles detection strategy

Detection of extracellular vesicles (EVs), particularly small EVs (sEVs), is of great significance in exploring their physiological characteristics and clinical applications. The heterogeneity of sEVs plays a crucial role in distinguishing different types of cells and diseases. Machine learning, with its exceptional data processing capabilities, offers a solution to overcome the limitations of conventional detection methods for accurately classifying sEV subtypes and sources. Principal component analysis, linear discriminant analysis, partial least squares discriminant analysis, XGBoost, support vector machine, k-nearest neighbor, and deep learning, along with some combined methods such as principal component-linear discriminant analysis, have been successfully applied in the detection and identification of sEVs. This review focuses on machine learning-assisted detection strategies for cell identification and disease prediction via sEVs, and summarizes the integration of these strategies with surface-enhanced Raman scattering, electrochemistry, inductively coupled plasma mass spectrometry and fluorescence. The performance of different machine learning-based detection strategies is compared, and the advantages and limitations of various machine learning models are also evaluated. Finally, we discuss the merits and limitations of the current approaches and briefly outline the perspective of potential research directions in the field of sEV analysis based on machine learning.

Exosomal noncoding RNAs in gynecological cancers: implications for therapy resistance and biomarkers

Gynecologic cancers, including ovarian cancer (OC), cervical cancer (CC), and endometrial cancer (EC), pose a serious threat to women's health and quality of life due to their high incidence and lethality. Therapeutic resistance in tumors refers to reduced sensitivity of tumor cells to therapeutic drugs or radiation, which compromises the efficacy of treatment or renders it ineffective. Therapeutic resistance significantly contributes to treatment failure in gynecologic tumors, although the specific molecular mechanisms remain unclear. Exosomes are nanoscale vesicles released and received by distinct kinds of cells. Exosomes contain proteins, lipids, and RNAs closely linked to their origins and functions. Recent studies have demonstrated that exosomal ncRNAs may be involved in intercellular communication and can modulate the progression of tumorigenesis, aggravation and metastasis, tumor microenvironment (TME), and drug resistance. Besides, exosomal ncRNAs also have the potential to become significant diagnostic and prognostic biomarkers in various of diseases. In this paper, we reviewed the biological roles and mechanisms of exosomal ncRNAs in the drug resistance of gynecologic tumors, as well as explored the potential of exosomal ncRNAs acting as the liquid biopsy molecular markers in gynecologic cancers.

The regulatory process and practical significance of non-coding RNA in the dissemination of prostate cancer to the skeletal system

Prostate cancer is a major contributor to male cancer-related mortality globally. It has a particular affinity for the skeletal system with metastasis to bones seriously impacting prognosis. The identification of prostate cancer biomarkers can significantly enhance diagnosis and patient monitoring. Research has found that cancer and metastases exhibit abnormal expression of numerous non-coding RNA. Some of these RNA facilitate prostate cancer bone metastasis by activating downstream signaling pathways, while others inhibit this process. Elucidating the functional processes of non-coding RNA in prostate cancer bone metastasis will likely lead to innovative treatment strategies for this malignant condition. In this review, the mechanistic role of the various RNA in prostate cancer is examined. Our goal is to provide a new avenue of approach to the diagnosis and treatment of bone metastasis in this cancer.

Tumor-derived systems as novel biomedical tools-turning the enemy into an ally

Cancer is a complex illness that presents significant challenges in its understanding and treatment. The classic definition, "a group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body," fails to convey the intricate interaction between the many entities involved in cancer. Recent advancements in the field of cancer research have shed light on the role played by individual cancer cells and the tumor microenvironment as a whole in tumor development and progression. This breakthrough enables the utilization of the tumor and its components as biological tools, opening new possibilities. This article delves deeply into the concept of "tumor-derived systems", an umbrella term for tools sourced from the tumor that aid in combatting it. It includes cancer cell membrane-coated nanoparticles (for tumor theranostics), extracellular vesicles (for tumor diagnosis/therapy), tumor cell lysates (for cancer vaccine development), and engineered cancer cells/organoids (for cancer research). This review seeks to offer a complete overview of the tumor-derived materials that are utilized in cancer research, as well as their current stages of development and implementation. It is aimed primarily at researchers working at the interface of cancer biology and biomedical engineering, and it provides vital insights into this fast-growing topic.

Advances in early detection methods for solid tumors

During the last decade, non-invasive methods such as liquid biopsy have slowly replaced traditional imaging and invasive pathological methods used to diagnose and monitor cancer. Improvements in the available detection methods have enabled the early screening and diagnosis of solid tumors. In addition, advances in early detection methods have made the continuous monitoring of tumor progression using repeat sampling possible. Previously, the focus of liquid biopsy techniques included the following: 1) the isolation of circulating tumor cells, circulating tumor DNA, and extracellular tumor vesicles from solid tumor cells in the patient's blood; in addition to 2) analyzing genomic and proteomic data contained within the isolates. Recently, there has been a rapid devolvement in the techniques used to isolate and analyze molecular markers. This rapid evolvement in detection techniques improves their accuracy, especially when few samples are available. In addition, there is a tremendous expansion in the acquisition of samples and targets for testing; solid tumors can be detected from blood and other body fluids. Test objects have also expanded from samples taken directly from cancer to include indirect objects affected in cancer development. Liquid biopsy technology has limitations. Even so, this detection technique is the key to a new phase of oncogenetics. This review aims to provide an overview of the current advances in liquid biopsy marker selection, isolation, and detection methods for solid tumors. The advantages and disadvantages of liquid biopsy technology will also be explored.

Exosomes from prostate cancer cell lines: Isolation optimisation and characterisation

Exosomes are considered to be a rich source of biomarkers, hence in this article we examine the best procedure for their isolation. We examine several isolation procedures, exosome storage conditions and other conditions affecting exosome production by prostate cell lines. We selected four different commercially available kits based on different principles to achieve exosome isolation, the best being magnetic-based. In addition, we found storage at - 20 °C to be good for storing isolated exosomes and that exosomes were produced from the cancerous prostate cell line 22Rv1 in much greater amounts than the non-cancerous prostate cell line RWPE1. We also found differences in the response of both cell lines in the production of exosomes as a result of stress, i.e. exposure to hydrogen peroxide and starvation. The effect of Triton X-100 on exosome lysis was examined using two different surfactant concentrations by analysis of the exosome count and change in the exosome size. The final part of the article details the advantages of the use of a 2D biochip prepared in-house over a commercially available 3D biochip for monitoring the interaction of exosomes via its surface receptors (CD63) with an immobilised ligand (anti-CD63 antibodies) using surface plasmon resonance. The final experiment shows the potential of lectin fluorescent microarrays for the analysis of glycans present in lysed exosomes.