Chronic myeloid leukemia (CML) is a well-characterized oncological disease in which virtually all patients possess a translocation (9;22) that generates the tyrosine kinase BCR::ABL1 protein. This translocation represents one of the milestones in molecular oncology in terms of both diagnostic and prognostic evaluations. The molecular detection of the BCR::ABL1 transcription is a required factor for CML diagnosis, and its molecular quantification is essential for assessing treatment options and clinical approaches. In the CML molecular context, point mutations on the ABL1 gene are also a challenge for clinical guidelines because several mutations are responsible for tyrosine kinase inhibitor resistance, indicating that a change may be necessary in the treatment protocol. So far, the European LeukemiaNet and the National Comprehensive Cancer Network (NCCN) have presented international guidelines on CML molecular approaches, especially those related to BCR::ABL1 expression. In this study, we show almost three years’ worth of data regarding the clinical treatment of CML patients at the Erasto Gaertner Hospital, Curitiba, Brazil. These data primarily comprise 155 patients and 532 clinical samples. BCR::ABL1 quantification by a duplex-one-step RT-qPCR and ABL1 mutations detection were conducted. Furthermore, digital PCR for both BCR::ABL1 expression and ABL1 mutations were conducted in a sub-cohort. This manuscript describes and discusses the clinical importance and relevance of molecular biology testing in Brazilian CML patients, demonstrating its cost-effectiveness.

Chronic myeloid leukemia (CML) is a type of leukemia whose main genetic marker is the reciprocal translocation that leads to the production of the BCR::ABL1 oncoprotein. The expression of some genes may interfere with the progression and development of leukemias. MicroRNAs are small non-coding RNAs that have the potential to alter the expression of some genes and may be correlated with some types of leukemia and could be used as biomarkers in the diagnosis and prognosis of patients. Therefore, this project carried out an analysis of microRNA-type plasma biomarkers in patients with chronic myeloid leukemia at unique points, including follow-up analysis of patients from the Erasto Gaertner Hospital. 35 microRNAs were analyzed in different cohorts. Inside those groups, 70 samples were analyzed at unique points and 11 patients in a follow-up analysis. Statistically different results were found for microRNA-7-5p, which was found to be upregulated in patients with high expression of the BCR::ABL1 transcript when compared to healthy controls. This microRNA also had evidence of behavior related to BCR::ABL1 when analyzed in follow-up, but strong evidence was not found. In this way, this work obtained results that may lead to manifestations of a relationship between miR-7-5p and chronic myeloid leukemia, and evaluations of possible microRNAs that are not related to this pathology.

This study aimed to identify the cytokine expression profile in prostate cancer (PCa) patients compared to healthy individuals. Plasma samples from 75 PCa patients and 14 healthy controls were analyzed using Multiplex ELISA (Luminex) to measure the expression levels of 12 cytokines: IL-4, IL-5, IL-6, IL-10, IL-1β, IL-17A, IL-12p70, MCP-1/CCL2, MIP-1α/CCL3, MIP-1β/CCL4, TNF-α, and IFN-γ. Differences in cytokine expression levels were analyzed using the Mann–Whitney test, Wilcoxon’s rank-sum test, Spearman’s rank correlation, and K-means Clustering unsupervised machine learning to validate cytokine expression patterns. In PCa patients, MIP-1α/CCL3, MIP-1β/CCL4, IFN-γ, and interleukins exhibited significantly higher expression levels; conversely, TNF-α and MCP-1/CCL2 both had decreased expression compared to healthy individuals. The clustering analysis confirmed that PCa patients exclusively exhibit the highest associations with MIP-1α/CCL3, IFN- γ, IL-12p70, IL-4, and IL-5. Furthermore, specific correlations between IL-4 and MIP-1 beta, IL-4 and IFN-gamma, IL-5 and IL-12p70, and IL-5 and IFN-gamma in PCa patients did not occur in healthy individuals. Such results will guide forthcoming in vitro and in vivo human prostate cancer-drug treatment models, paving the way for exploration of future drug targets and candidates with potential to predict FDA-approved prostate cancer treatment responses by targeting cytokine levels and the oncogenesis pathways.