Cost-efficacy of currently applied treatments is an issue in overall cancer management challenging healthcare and causing tremendous economic burden to societies around the world. Consequently, complex treatment models presenting concepts of predictive diagnostics followed by targeted prevention and treatments tailored to the personal patient profiles earn global appreciation as benefiting the patient, healthcare economy, and the society at large. In this context, application of flavonoids as a spectrum of compounds and their nano-technologically created derivatives is extensively under consideration, due to their multi-faceted anti-cancer effects applicable to the overall cost-effective cancer management, primary, secondary, and even tertiary prevention. This article analyzes most recently updated data focused on the potent capacity of flavonoids to promote anti-cancer therapeutic effects and interprets all the collected research achievements in the frame-work of predictive, preventive, and personalized (3P) medicine. Main pillars considered are: - Predictable anti-neoplastic, immune-modulating, drug-sensitizing effects; - Targeted molecular pathways to improve therapeutic outcomes by increasing sensitivity of cancer cells and reversing their resistance towards currently applied therapeutic modalities.

• Klíčová slova
• Anthocyanidins, Anti-bacterial, Anti-cancer agents, Anti-inflammation, Anti-viral, COVID-19, Chalcones, Chemotherapy, Disease management, Drug-sensitizing effect, Flavanols, Flavanones, Flavones, Flavonoids, Flavonols, Health economy, Health policy, Immunotherapy, Isoflavonoids, Nano-carrier delivery, Phytochemicals, Predictive preventive personalized medicine (3PM/PPPM), Radiotherapy, Signalling pathways, Targeted therapy, Therapy efficacy, Therapy resistance,
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• časopisecké články MeSH
• přehledy MeSH

Biobanking is entering the new era-era of big data. New technologies, techniques, and knowledge opened the potential of the whole domain of biobanking. Biobanks collect, analyse, store, and share the samples and associated data. Both samples and especially associated data are growing enormously, and new innovative approaches are required to handle samples and to utilize the potential of biobanking data. The data reached the quantity and quality of big data, and the scientists are facing the questions how to use them more efficiently, both retrospectively and prospectively with the aim to discover new preventive methods, optimize treatment, and follow up and to optimize healthcare processes. Biobanking in the era of big data contribute to the development of predictive, preventive, and personalised medicine, for every patient providing the right treatment at the right time. Biobanking in the era of big data contributes to the paradigm shift towards personalising of healthcare.

• Klíčová slova
• Artificial intelligence, Big data, Biobanks, Biomedical research, Cancer, Computation analysis, Diabetes, Economy, Healthcare, Implementation, Information technologies, Innovations, Liquid biopsy, Machine learning, Patient benefits, Personalised treatment algorithms, Population screening, Predictive preventive personalised medicine, Services, Stroke,
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Colorectal cancer (CRC) belongs to the most common cancers. The liver is a predominant site of CRC dissemination. Novel biomarkers for predicting the survival of CRC patients with liver metastases (CLM) undergoing metastasectomy are needed. We examined KRAS mutated circulating cell-free tumor DNA (ctDNA) in CLM patients as a prognostic biomarker, independently or in combination with carcinoembryonic antigen (CEA). Thereby, a total of 71 CLM were retrospectively analyzed. Seven KRAS G12/G13 mutations was analyzed by a ddPCR™ KRAS G12/G13 Screening Kit on QX200 Droplet Digital PCR System (Bio-Rad Laboratories, Hercules, CA, USA) in liver metastasis tissue and preoperative and postoperative plasma samples. CEA were determined by an ACCESS CEA assay with the UniCel DxI 800 Instrument (Beckman Coulter, Brea, CA, USA). Tissue KRAS positive liver metastases was detected in 33 of 69 patients (47.8%). Preoperative plasma samples were available in 30 patients and 11 (36.7%) were KRAS positive. The agreement between plasma- and tissue-based KRAS mutation status was 75.9% (22 in 29; kappa 0.529). Patients with high compared to low levels of preoperative plasma KRAS fractional abundance (cut-off 3.33%) experienced shorter overall survival (OS 647 vs. 1392 days, p = 0.003). The combination of high preoperative KRAS fractional abundance and high CEA (cut-off 3.33% and 4.9 µg/L, resp.) best predicted shorter OS (HR 13.638, 95%CI 1.567-118.725) in multivariate analysis also (OS HR 44.877, 95%CI 1.59-1266.479; covariates: extend of liver resection, biological treatment). KRAS mutations are detectable and quantifiable in preoperative plasma cell-free DNA, incompletely overlapping with tissue biopsy. KRAS mutated ctDNA is a prognostic factor for CLM patients undergoing liver metastasectomy. The best prognostic value can be reached by a combination of ctDNA and tumor marker CEA.

• Klíčová slova
• CEA, cell-free DNA, circulating tumor DNA, colorectal cancer, ctDNA, liquid biopsy, liver metastasis,
• Publikační typ
• časopisecké články MeSH

The aim of the study was to evaluate the ability of following biomarkers as diagnostic tools and risk predictors of AAA: C-reactive protein, interleukin-6, pentraxin-3, galectin-3, procollagen type III N-terminal peptide, C-terminal telopeptide of type I collagen, high-sensitive troponin I, and brain natriuretic peptide. Seventy-two patients with an AAA and 100 healthy individuals were enrolled into the study. We assessed individual biomarker performance and correlation between the AAA diameter and biomarker levels, and also, a multivariate logistic regression was used to design a possible predictive model of AAA growth and rupture risk. We identified following four parameters with the highest potential to find a useful place in AAA diagnostics: galectin-3, pentraxin-3, interleukin-6, and C-terminal telopeptide of type I. The best biomarkers in our evaluation (galectin-3 and pentraxin-3) were AAA diameter-independent. With the high AUC and AAA diameter correlation, the high-sensitive troponin I can be used as an independent prognostic biomarker of the upcoming heart complications in AAA patients. Authors recommend to add biomarkers as additional parameters to the current AAA patient management. Main addition value of biomarkers is in the assessment of the AAA with the smaller diameter. Elevated biomarkers can change the treatment decision, which would be done only based on AAA diameter size. The best way how to manage the AAA patients is to create a reliable predictive model of AAA growth and rupture risk. A created multiparameter model gives very promising results with the significantly higher efficiency compared with the use of the individual biomarkers.

• Klíčová slova
• Abdominal aortic aneurism, Biomarker panel, Brain natriuretic peptide, C-Terminal telopeptide of type I collagen, Galectin-3, High-sensitive troponin I, Interleukin-6, Multivariate model, Multivariate stepwise logistic regression, Patient stratification, Pentraxin-3, Predictive preventive personalized medicine, Procollagen type III N-terminal peptide,
• Publikační typ
• časopisecké články MeSH