Glioblastoma (GBM) is the most aggressive primary brain tumor in adult patients and is characterized by significant cellular heterogeneity and complex interactions between tumor cells and the tumor microenvironment. Extracellular vesicles (EVs) and the microRNAs (miRNAs) they carry are important mediators of intercellular signaling and, at the same time, a potential source of biomarkers useful in the diagnosis of gliomas. Experimental models capable of preserving the biological properties of the original tumor are essential for studying these processes. In this study, we prepared glioblastoma organoids (GBOs) derived from patient tumor tissue and analyzed extracellular miRNAs present in EVs isolated from conditioned media. Concurrently, we analyzed miRNAs contained in EVs isolated from cerebrospinal fluid (CSF) of patients with gliomas of varying degrees of malignancy. A total of 12 GBOs cultures were successfully established, long-term cultured, and cryopreserved. Immunohistochemical analysis confirmed the presence of markers typical of glioblastoma cells (Nestin, GFAP, Sox2). In early-stage organoids, cell populations representing the tumor microenvironment were also detected, including endothelial cells (CD31) and microglia (CD163). In some cases, reactive astrocytes and neurons were also present. Highly abundant miRNAs were identified in EVs isolated from conditioned media of GBO and primary GBM cultures, including hsa-miR-21-5p, members of the let-7 family, hsa-miR-16-5p, hsa-miR-125b-5p, and others. These miRNAs were simultaneously detected in EVs isolated from the CSF of patients with GBM and high-grade gliomas. In contrast, miR-204-5p, which was predominantly present in CSF samples, was minimally represented in EVs from tumor cultures, suggesting a possible origin of this miRNA in non-tumor brain tissue. The presented data support the use of GBOs derived from patient tumor tissue as a suitable model for studying intercellular communication and extracellular signaling in GBM and simultaneously demonstrate the potential of EV-associated miRNAs as biomarkers of the tumor microenvironment.

In the context of oncological diseases of (not only) the gastrointestinal tract and the oral cavity, the role of microorganisms is being increasingly discussed and investigated. A growing body of evidence supports the significance of specific microbial strains and their products both in the etiopathogenesis of certain cancers and in their prevention and therapy.

Microbiome analysis in cancer research has experienced a surge in interest comparable to the introduction of microarrays for tumor gene expression profiling 25 years ago. Associative studies investigating the composition of the microbiome in stool, tumor tissue swabs and tumor biopsies of oncology patients have been conducted across most cancer types, and their number continues to grow. Screening approaches based on non-invasive or minimally invasive sampling, including the analysis of stool, saliva, urine, and buccal and rectal swabs, are from a clinical perspective among the most promising, owing in part to simpler logistics and the possibility of repeated sampling. These types of specimens are commonly used in microbiome studies, making the microbiome an attractive target for both screening and diagnostic applications.

Microplastics and nanoplastics are ubiquitous environmental contaminants, and human exposure via ingestion and inhalation is increasingly recognized. Numerous studies report microplastics in human tissues and biological fluids, yet the biological relevance and robustness of these findings remain uncertain. This critical work evaluates current evidence on microplastics in the human body, focusing on exposure pathways, particle size relevance, and analytical limitations. Mechanistic data indicate that translocation across intestinal and pulmonary barriers is likely restricted to small microplastics (< 10 µm) and nanoplastics, raising questions about reports of larger particles in human tissues. Key challenges include secondary contamination, size-dependent detection limits, and methodological artifacts associated with common analytical techniques. Experimental evidence for biological effects, including inflammation, microbiome disruption, and cancer-related pathways, is discussed in the context of physiological relevance.

Cancer risk is predominantly shaped by environmental exposures interacting with genetic susceptibility, yet modifiable non-genetic determinants remain insufficiently characterised. The human exposome framework promotes a comprehensive, life-course approach to studying chemical, biological, and physical exposures alongside socioeconomic and psychosocial factors, but it is underutilised in cancer research. Systematically mapping biomarkers of exposure to each hallmark of cancer could provide a powerful strategy to identify modifiable risk factors with translational relevance. Czechia, with its pronounced geographic variation in cancer incidence and strong research infrastructure, provides an ideal setting to pioneer such "functional exposomics" approaches. Integrating these methods into cancer research could help identify actionable environmental drivers and generate mechanistic insights to advance precision cancer prevention.

Obesity is a major and modifiable risk factor influencing both the incidence and prognosis of malignant tumors.

Smoking is responsible for approximately 25-30% of all oncological diseases. The link with lung cancer, which is the strongest, and is therefore well known, has been demonstrated first. Unfortunately, smoking also contributes to other types of cancer, practically all kinds except endometrial cancer. However, due to the carcinogenic and other toxic effects of several thousand substances in tobacco smoke, smoking has been increasingly replaced in recent years by smoke-free forms of nicotine. Nicotine itself is not carcinogenic; on the contrary, some forms of nicotine replacement therapy are among the World Health Organization's essential medicines.

Early detection of cancer is one of the key factors influencing patient prognosis and overall cancer-related mortality. However, current population--based screening programs are limited to only a few selected diagnoses, and many highly lethal malignancies still lack an effective option for early detection. Multicancer early detection (MCED) tests represent a new group of blood-based screening methods aimed at identifying the presence of early-stage cancer across multiple primary sites through a single peripheral blood sample. They mainly rely on the analysis of circulating tumor DNA, including its methylation and fragmentation characteristics, or on combinations with protein markers or the detection of circulating tumor cells. These tests offer high specificity and are able to estimate the most likely site of origin of the tumor, which is crucial for guiding subsequent diagnostic workup. At present, the largest body of evidence is available for methylation-based and multiomic platforms. Prospective studies conducted so far in asymptomatic individuals suggest that MCED tests may enable the detection of cancers at clinically relevant stages, with a relatively low false-positive rate and an acceptable burden of follow-up investigations. At the same time, important limitations remain particularly lower sensitivity in the earliest stages of disease, the absence of standardized diagnostic algorithms following a positive result, and the lack of evidence for an effect on cancer-specific mortality and the incidence of advanced-stage disease. MCED tests therefore cannot yet be considered a replacement for established organ-specific screening programs. However, they appear to be a promising complement to current screening strategies, particularly for the detection of cancers for which no established screening exists. Their future clinical role will depend on the results of large prospective and randomized studies demonstrating their true benefit for both the population and healthcare systems. In addition to strong evidence of clinical benefit, widespread implementation into clinical practice will also require standardization of downstream diagnostic pathways and careful health-economic evaluation.

Polygenic risk score (PRS) has the ability to stratify inherited susceptibility to cancer and, as a complement to monogenic testing, can identify individuals at increased genetic risk even when no pathogenic variant is detected in high- or moderate-penetrance genes. It reflects the combined additive effects of a large number of low-penetrance variants across the genome, and represents a continuum of genetic susceptibility with an approximately normal distribution. Clinically relevant differences are typically observed in individuals in the highest and lowest percentiles of the PRS distribution, while relative risk gradients depend on the cancer type, the specific PRS model, and the reference population used. PRS is not a single test but rather a family of statistical models that differ in their design, predictive performance, and transferability across populations, underscoring the need for external validation and population-specific calibration of absolute risk. Broader implementation is thus still held back by differences between individual PRS models, limited transferability, and the lack of harmonized guidance on indication, reporting, and clinical decision-making. Consequently, clinical use in the European Union remains largely confined to pilot studies and local projects. Within these initiatives, PRS is most commonly applied in two main ways - either as a triage tool for intensified diagnostics or screening in higher-risk groups, or as a component of multifactorial absolute-risk models (e. g. BOADICEA/CanRisk) that integrate PRS with other risk factors such as pathogenic variants in moderate-penetrance genes (e. g. ATM or CHEK2), family history, or lifestyle factors. By refining absolute-risk estimates, PRS may shift individuals across clinical decision thresholds for more intensive surveillance and preventive strategies.