Introduction: The POU class 1 homeobox 1 transcription factor (POU1F1, also known as Pit-1) is expressed in the mammary gland and its overexpression induces profound phenotypic changes in proteins involved in cell proliferation, apoptosis, and invasion. Patients with breast cancer and elevated expression of Pit-1 show a positive correlation with the occurrence of distant metastasis. In this study we evaluate the relationship between Pit-1 and two collagenases: matrix metalloproteinase-1 (MMP-1) and matrix metalloproteinase-13 (MMP-13), which have been related to metastasis in breast cancer. Methods: We began by transfecting the MCF-7 and MDA-MB-231 human breast adenocarcinoma cell lines with the Pit-1 overexpression vector (pRSV-hPit-1). Afterward, the mRNA, protein, and transcriptional regulation of both MMP-1 and MMP-13 were evaluated by real-time PCR, Western blot, chromatin immunoprecipitation (ChIP), and luciferase reporter assays. We also evaluated Pit-1 overexpression with MMP-1 and MMP-13 knockdown in a severe combined immunodeficiency (SCID) mouse tumor xenograft model. Finally, by immunohistochemistry we correlated Pit-1 with MMP-1 and MMP-13 protein expression in 110 human breast tumors samples. Results: Our data show that Pit-1 increases mRNA and protein of both MMP-1 and MMP-13 through direct transcriptional regulation. In SCID mice, knockdown of MMP-13 completely blocked lung metastasis in Pit-1-overexpressing MCF-7 cells injected into the mammary fat pad. In breast cancer patients, expression of Pit-1 was found to be positively correlated with the presence of both MMP-1 and MMP-13. Conclusions: Our data indicates that Pit-1 regulates MMP-1 and MMP-13, and that inhibition of MMP-13 blocked invasiveness to lung in Pit-1-overexpressed breast cancer cells.

Preterm delivery affects approximately 10% of pregnancies worldwide and remains a major clinical challenge due to the lack of reliable early predictive tools. Existing strategies are often invasive, relying on blood or amniotic fluid samples and requiring complex processing. In this study, we describe a novel non-invasive approach based on the multiplex detection of inflammatory cytokines in small urine volumes from pregnant women. To account for clinical and temporal variability, we applied Generalized Additive Models for Location, Scale, and Shape (GAMLSS) to adjust for gestational age at sampling and obstetric factors. Correlation network analyses revealed cytokine interactions that distinguished preterm from term deliveries, with macrophage-derived cytokines—MIP-1α, MIP-1β, IL-15, and IL-22—emerging as central nodes. These findings highlight the involvement of the IL-1 pathway in the pathophysiology of preterm labor. Furthermore, urinary IL-5 and IL-31 levels correlated positively with pregnancy duration, whereas IL-1β and IL-1Ra in urine and TNFα in amniotic fluid showed inverse associations. Altogether, this non-invasive methodology provides insight into immune dynamics during pregnancy and offers a foundation for future studies focused on biomarker discovery and mechanistic understanding of preterm birth.