AURKB (Aurora Kinase B)

SP-2-067 is a novel, selective AKA degrader that modulates IC expression by upregulating PD-L1 and downregulating LAG3, indicating its potential for immunomodulation through AUNIP- and NINEIN-mediated mechanisms. Additionally, AKA, AUNIP, and NINEIN are linked to a distinct immune cell profile, presenting an opportunity to reshape the tumor immune microenvironment and support combinatorial strategies with IC inhibitors in prostate cancer.

This defect was associated with diminished autophagy. Together, these findings establish Aurkb as a key regulator of microglial development, homeostasis, and responses to remyelination.

Given their unique properties and clinical relevance, PGCCs represent a promising frontier in cancer biology with the potential to overcome therapeutic resistance and prevent tumor recurrence through targeted interventions. This review seeks to elucidate the role of PGCCs across multiple cancer types and highlights their emerging potential as novel targets for future cancer therapies.

The results of the receiver operating characteristic (ROC) curve, area under the ROC curve, calibration plot, net reclassification index, integrated discrimination improvement index, and decision curve analysis revealed that the model had good discriminating ability, predictive ability, and clinical utility. In conclusion, AURKA, BUB1, and CDK1 are potential prognostic biomarkers of NPC, and a prediction model incorporating the expression levels of AURKA and BUB1 has good discriminating ability, predictive ability, and clinical utility.

The integration of AH liquid biopsy in RB management may aid prognosis prediction and optimize treatment strategies. However, further research is needed to validate the prognostic significance.

In addition, we review the status of AURKA-specific inhibitors in clinical evaluation and their associated adverse effects. Finally, we cite the emerging therapeutic strategy of proteolysis targeting chimeras (PROTACs) as an innovative means to selectively degrade AURKs, offering a novel approach to targeted cancer therapy.

AURKB is a significant prognostic biomarker and potential therapeutic target, with overexpression linked to poor outcomes and chemotherapy resistance. The association with hypomethylation suggests an epigenetic role, supporting targeted therapies. AURKB's influence on immune suppression highlights its role in the tumor microenvironment. Clinical integration of AURKB analysis could enhance personalized treatment, and future research should explore combination therapies with AURKB inhibitors.

Western blot and qRT-PCR tests validated these genes in GIST-T1 cells, and ssGSEA analysis indicated a significant relationship between these hub genes and immune cell infiltration. This study revealed a set of novel signature genes with high diagnostic value, offering promising targets for the diagnosis and treatment of GIST.

Importantly, follow-up kinase selectivity profiling revealed that BDE30671203 is a highly selective PLK1 inhibitor, showing over 450-fold and 1200-fold selectivity against the closely related AURKA and AURKB kinases, respectively. Therefore, this study not only provides promising chemical starting points for PLK1-targeted drug discovery, but more significantly validates a robust screening strategy for kinase inhibitor discovery.

This study identified novel candidate risk genes for EOCRC, underscoring the role of rare variants and expanding our understanding of the genetic architecture of CRC. Future studies should include functional validation and replication studies on other ancestries to confirm and extend these results.

AURKA and AURKB are crucial regulators of tumor progression in RB and UM. Aurora kinase inhibition can be explored as a novel therapeutic strategy.

This study identifies CDC20 as a key prognostic biomarker for bladder cancer, providing novel insights for early diagnosis, clinical treatment, and prognosis assessment. The findings highlight the potential of CDC20 as a therapeutic target and underscore the value of integrated bioinformatics and experimental validation in biomarker discovery.