A Crucial Angiogenesis-Associated Gene MEOX2 Could Be a Promising Biomarker Candidate for Breast Cancer

KMV-mediated cardiomyocyte-to-endothelial cell signaling drives capillary rarefaction to promote heart failure following pressure overload

Rationale: Pressure overload (PO)-induced heart failure (HF) is a global health burden with poor outcomes. Cardiomyocyte hypertrophy and capillary rarefaction are two features and drivers of PO-induced HF. Metabolism is altered in hypertrophic cardiomyocytes; however, the metabolites secreted by hypertrophic cardiomyocytes to paracrinally regulate capillary density remain to be identified. Methods: PO-induced HF was established by transverse aortic constriction in mice. Metabolite secretion was examined by nontargeted metabolomics and enzyme-linked immunosorbent assays. Gene expression was examined by RNA-sequencing and immunoblotting. Protein-promoter binding was examined by chromatin immunoprecipitation-PCR. Cardiomyocyte hypertrophy and cardiac capillary density were examined by immunostaining for -actinin and CD31, respectively. In vitro angiogenesis was indicated by proliferation, migration, tube formation, and angiogenic factor expression of endothelial cells (ECs). EC senescence was determined by SA--gal staining and p16 and p21 expression. Results: There was a negative correlation between cardiomyocyte size and capillary density in PO-induced failing hearts, and hypertrophic cardiomyocytes paracrinally inhibited angiogenesis of ECs. 3-Methyl-2-oxovaleric acid (KMV) was the most upregulated metabolite secreted by hypertrophic cardiomyocytes. Notably, KMV treatment resulted in EC senescence and angiogenesis inhibition in vitro and exaggerated PO-induced EC senescence, capillary rarefaction, and cardiac dysfunction of mice in vivo. Additionally, KMV increased expression and nuclear accumulation of mesenchyme homeobox 2 (Meox2) in ECs, whereas Meox2 knockdown diminished KMV-induced EC senescence and angiogenesis inhibition. Furthermore, Meox2 directly bound to the promoter of the senescence-related gene p21 in ECs, and this binding was enhanced by KMV. Conclusions: The data suggest that hypertrophic cardiomyocytes secrete elevated levels of KMV, which paracrinally increases nuclear accumulation of Meox2 in ECs, where Meox2 binds to the promoter of p21 and thereby triggers EC senescence and subsequent angiogenesis impairment, ultimately driving capillary rarefaction to promote PO-induced HF. The findings identified KMV as a novel metabolite secreted by hypertrophic cardiomyocytes that triggered EC senescence to drive PO-induced capillary rarefaction and subsequent HF development. Targeting this KMV-mediated cardiomyocyte-to-EC signaling has therapeutic potential in the management of PO-induced HF in patients.

MEOX2 mediates cisplatin resistance in ovarian cancer via E2F target and DNA repair pathways

Ovarian cancer (OV) is a leading cause of cancer-related mortality among women worldwide. Despite the success of platinum-based chemotherapy in treating OV, the emergence of cisplatin resistance has significantly compromised its therapeutic efficacy. Therefore, understanding the mechanisms underlying cisplatin resistance and its molecular regulation is crucial for improving patient outcomes. This study, MEOX2 was identified as a key gene significantly associated with prognosis and cisplatin resistance in OV through bioinformatics analysis. Its expression level and biological functions were validated using online databases, tissue microarrays, and cellular experiments. The results demonstrated that high MEOX2 expression was closely associated with poor survival outcomes in OV patients, while its expression was significantly reduced in cisplatin-resistant cells. Further gene silencing experiments revealed that silencing MEOX2 markedly enhanced cisplatin resistance in resistant cells and significantly reduced cisplatin-induced early apoptosis, although it had no notable effect on cell proliferation. Moreover, the study showed that MEOX2 was not associated with immune cell infiltration in OV but was positively correlated with angiogenesis-related genes. In cisplatin-resistant cells, gene set enrichment analysis of MEOX2 co-expressed genes highlighted the activation of the E2F target and DNA repair pathway. Additionally, MEOX2 exhibited a significant negative correlation with the MCM protein family. In summary, MEOX2 is highly expressed in OV and is associated with poor patient prognosis. It may confer cisplatin resistance to OV cells by activating the E2F target and DNA repair pathway to mitigate cisplatin-induced early apoptosis. Despite certain limitations, these findings provide novel insights into the potential role of MEOX2 as a prognostic biomarker and therapeutic target in OV.

Inference of differential gene regulatory networks using boosted differential trees

Summary

Diseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections remains a challenging task and would benefit from the development of novel nonparametric approaches. We develop a new ensemble method called BoostDiff (boosted differential regression trees) to infer a differential network discriminating between two conditions. BoostDiff builds an adaptively boosted (AdaBoost) ensemble of differential trees with respect to a target condition. To build the differential trees, we propose differential variance improvement as a novel splitting criterion. Variable importance measures derived from the resulting models are used to reflect changes in gene expression predictability and to build the output differential networks. BoostDiff outperforms existing differential network methods on simulated data evaluated in four different complexity settings. We then demonstrate the power of our approach when applied to real transcriptomics data in COVID-19, Crohn's disease, breast cancer, prostate adenocarcinoma, and stress response in Bacillus subtilis. BoostDiff identifies context-specific networks that are enriched with genes of known disease-relevant pathways and complements standard differential expression analyses.

Availability and implementation

BoostDiff is available at https://github.com/scibiome/boostdiff_inference.

Low expression of MEOX2 is associated with poor survival in patients with breast cancer

Aim: To investigate associations of MEOX2 expression with clinicopathological features and survival of breast cancer patients. Materials & methods: We used a breast cancer tissue microarray for immunohistochemistry. Associations between MEOX2 expression and clinicopathological features were analyzed using the χ-square test. Survival analysis was determined using a Kaplan-Meier curve. Multivariate Cox regression was used to determine associations of MEOX2 expression with overall survival. Results: We found that 74.1% of patients (100/135) had expression of MEOX2 at varying levels. MEOX2 was associated with histological grade and negatively correlated with Ki67 expression. Lower MEOX2 expression was significantly associated with decreased overall survival (p = 0.0011). Conclusion: MEOX2 expression could be a novel diagnostic and prognostic biomarker of breast cancer.