Angiogenesis is the process through which new blood vessels are formed from pre-existing ones. Exosomes are involved in angiogenesis in cancer progression by transporting numerous pro-angiogenic biomolecules like vascular endothelial growth factor (VEGF), matrix metalloproteinases (MMPs), and microRNAs. Exosomes promote angiogenesis by suppressing expression of factor-inhibiting hypoxia-inducible factor 1 (HIF-1). Uptake of tumor-derived exosomes (TEX) by normal endothelial cells activates angiogenic signaling pathways in endothelial cells and stimulates new vessel formation. TEX-driven cross-talk of mesenchymal stem cells (MSCs) with immune cells blocks their anti-tumor activity. Effective inhibition of tumor angiogenesis may arrest tumor progression. Bevacizumab, a VEGF-specific antibody, was the first antiangiogenic agent to enter the clinic. The most important clinical problem associated with cancer therapy using VEGF- or VEFGR-targeting agents is drug resistance. Combined strategies based on angiogenesis inhibitors and immunotherapy effectively enhances therapies in various cancers, but effective treatment requires further research.

Tumor-derived exosomes (TEX) are involved in cancer development, metastasis, and disease progression. They can modulate angiogenesis to elevate the malignant degree of tumor cells. TEX carry immunosuppressive factors affecting the antitumor activities of immune cells. Tumor cells as well as immune cells secrete immunologically active exosomes which affect intercellular communication, antigen presentation, activation of immune cells, and immune surveillance. Cell proliferation and immune response suppression create a favorable microenvironment for tumor. TEX can inhibit immune cell proliferation, induce apoptosis of activated CD8+ Teffs, suppress NK cell activity, interfere with monocyte differentiation, and promote Treg as well as MDSC expansion. Exosomes of microenvironment cells may also contribute to the development of drug resistance in cancer therapy. An important role of TEX in modulating the sensitivity of tumor cells to immunotherapy is a promising area of research to make the cancer therapy more successful.

Prostate cancer (PCa) is the second most common cause of cancer-related mortality among men in the developed world. Conventional anti-PCa therapies are not effective for patients with advanced and/or metastatic disease. In most cases, cancer therapies fail due to an incomplete depletion of tumor cells, resulting in tumor relapse. Exosomes are involved in tumor progression, promoting the angiogenesis and migration of tumor cells during metastasis. These structures contribute to the dissemination of pathogenic agents through interaction with recipient cells. Exosomes may deliver molecules that are able to induce the transdifferentiation process, known as "epithelial to mesenchymal transition". The composition of exosomes and the associated possibilities of interacting with cells make exosomes multifaceted regulators of cancer development. Extracellular vesicles have biophysical properties, such as stability, biocompatibility, permeability, low toxicity and low immunogenicity, which are key for the successful development of an innovative drug delivery system. They have an enhanced circulation stability and bio-barrier permeation ability, and they can therefore be used as effective chemotherapeutic carriers to improve the regulation of target tissues and organs. Exosomes have the capacity to deliver different types of cargo and to target specific cells. Chemotherapeutics, natural products and RNA have been encapsulated for the treatment of prostate cancers.

An appropriate combination of biomarkers and imaging technologies will become standard practice in the future. Because the incidence of and mortality from cancers is rising, the further study of new approaches for the early detection and precise characterization of tumors is essential. Extracellular vesicles (EVs), including exosomes, prove to have great potential when it comes to diagnosis and targeted therapy. Due to their natural ability to pass through biological barriers, depending on their origin, EVs can accumulate at defined sites, including tumors, preferentially. This manuscript discusses the difficulties and simplicities of processing cell-derived materials, packaging diverse groups of agents in EVs, and activating the biological complex. Developing exosome-based diagnostic techniques to detect disease precisely and early as well as treat disease marks a new era of personalized radiology and nuclear medicine. As circulating drug delivery vehicles for novel therapeutic modalities, EVs offer a new platform for cancer theranostic.

Objective To develop an easy-to-use side-specific tool for the prediction of prostate cancer extracapsular extension (ECE) using clinical, biopsy, and MRI parameters. Materials and methods Retrospective analysis of patients who underwent radical prostatectomy preceded by staging multiparametric MRI of the prostate was performed. Multivariate logistic regression analysis was used to choose independent predictors of ECE. Continuous variables were transformed to categorical ones by choosing threshold values using spline knots or testing thresholds used in previously described models. Internal validation of the rule was carried out as well as validation of other algorithms on our group was performed. Results In the analyzed period of time, 88 out of 164 patients who underwent radical prostatectomy met inclusion criteria. ECE was evidenced at radical prostatectomy in 41 patients (46.6%) and in 53 lobes (30.1%). In the multivariate analysis PSA, total percentage of cancerous tissue in cores (%PCa) and maximum tumour diameter (MTD) of Likert 3–5 lesions on MRI were independent predictors of ECE. The following rule for predicting side-specific ECE was proposed: %PCa ≥ 15% OR MTD ≥ 15 mm OR PSA ≥ 20 ng/mL. Internal validation of the algorithm revealed safe lower confidence limits for sensitivity and NPV, proving that model offers accurate risk grouping that can be safely used in decision-making. Conclusion The rule developed in this study makes ECE prediction fast, intuitive, and side-specific. However, until validated externally it should be used with caution.