Exploring the Relationship between MicroRNAs, Intratumoral Microbiota, and Breast Cancer Progression in Patients with and without Metastasis.

Breast cancer (BC) continues to pose a significant burden on global cancer-related morbidity and mortality, primarily driven by metastasis. However, the combined influence of microRNAs (miRNAs) and intratumoral microbiota on BC metastasis remains largely unexplored. In this study, we aimed to elucidate the interplay between intratumoral microbiota composition, miRNA expression profiles, and their collective influence on metastasis development in BC patients by employing 16S rRNA sequencing and qPCR methodologies. Our findings revealed an increase in the expression of miR-149-5p, miR-20b-5p, and miR-342-5p in metastatic breast cancer (Met-BC) patients. The Met-BC patients exhibited heightened microbial richness and diversity, primarily attributed to diverse pathogenic bacteria. Taxonomic analysis identified several pathogenic and pro-inflammatory species enriched in Met-BC, contrasting with non-metastatic breast cancer (NonMet-BC) patients, which displayed an enrichment in potential probiotic and anti-inflammatory species. Notably, we identified and verified a baseline prognostic signature for metastasis in BC patients, with its clinical relevance further validated by its impact on overall survival. In conclusion, the observed disparities in miRNA expression and species-level bacterial abundance suggest their involvement in BC progression. The development of a prognostic signature holds promise for metastasis risk assessment, paving the way for personalized interventions and improved clinical outcomes in BC patients.

Increased blood draws for ultrasensitive ctDNA and CTCs detection in early breast cancer patients.

Early breast cancer patients often experience relapse due to residual disease after treatment. Liquid biopsy is a methodology capable of detecting tumor components in blood, but low concentrations at early stages pose challenges. To detect them, next-generation sequencing has promise but entails complex processes. Exploring larger blood volumes could overcome detection limitations. Herein, a total of 282 high-volume plasma and blood-cell samples were collected for dual ctDNA/CTCs detection using a single droplet-digital PCR assay per patient. ctDNA and/or CTCs were detected in 100% of pre-treatment samples. On the other hand, post-treatment positive samples exhibited a minimum variant allele frequency of 0.003% for ctDNA and minimum cell number of 0.069 CTCs/mL of blood, surpassing previous investigations. Accurate prediction of residual disease before surgery was achieved in patients without a complete pathological response. A model utilizing ctDNA dynamics achieved an area under the ROC curve of 0.92 for predicting response. We detected disease recurrence in blood in the three patients who experienced a relapse, anticipating clinical relapse by 34.61, 9.10, and 7.59 months. This methodology provides an easily implemented alternative for ultrasensitive residual disease detection in early breast cancer patients.

Obstrucción intestinal alta secundaria a cálculo impactado en duodeno (síndrome de Bouveret) / Gastric outlet obstruction due to duodenal gallstone (Bouveret syndrome)

No disponible

Fractura transdiscal de bloque vertebral tras caída accidental en paciente con espondilitis anquilosante / Transdiscal fracture of the vertebrae following an accidental fall in a patient with ankylosing spondylitis

No disponible