tozasertib (MK-0457)

Drug sensitivity analysis indicates that the RORC gene is responsive to agents such as VX-680, MG-132, and Sunitinib. Cell biology experiments have confirmed that RORC overexpression significantly diminishes the proliferation, invasion, and migration capabilities of gastric cancer cells. Integrating bioinformatics and cell biology experiments suggests that RORC, a gene associated with rhythm regulation, acts as a tumor suppressor gene that is underexpressed in gastric cancer, thereby serving as a potential biomarker and therapeutic target for this malignancy.

To explore therapeutic implications, transcriptomics-guided drug repositioning combined with molecular docking analysis identified five candidate compounds-celastrol, fedratinib, pevonedistat, tozasertib, and withaferin A-predicted to target key network hubs. Overall, this in silico study provides a ceRNA-centered regulatory framework for GC and prioritizes biologically informed biomarkers and repositioned drug candidates with potential applicability across other malignancies to converge precision oncology.

Drug sensitivity prediction indicated that high-risk patients may respond better to agents such as Tozasertib and Navitoclax. This study establishes a robust, demethylation-driven six-gene signature that effectively stratifies HCC patients into distinct prognostic groups. The model integrates multi-omic insights into tumor biology and therapeutic vulnerability, providing a clinically actionable framework for personalized risk assessment and treatment planning in hepatocellular carcinoma.

Selumetinib, entinostat, and erlotinib were identified as candidate drugs for cluster 2, whereas tozasertib, alpelisib, and cediranib showed higher suitability for cluster 1. Ten potential biomarkers, 13 transcription factors, and 2 miRNAs were characterized. This study elucidates the role of UPS in ESCC progression and provides a framework for personalized treatment strategies.

Lastly, MMPBSA showed a higher negative free energy in the presence of Jervine than VX-680 when complexed with AURKB. Finally, our results suggest that Jervine is a potent, dual-targeting kinase inhibitor with favourable pharmacokinetic and therapeutic properties, warranting further experimental validation for anticancer drug development.

High MCMBP expression was ass-ociated with sensitivity to Gemcitabine combined with Paclitaxel, as well as small mo-lecules such as Tozasertib and Motesanib. Overexpression of MCMBP may serve as a prognostic biomarker and p-otential therapeutic target in PAAD. It drives PAAD progression by activating the JAK-STAT3 pathway to upregulate PD-L1.

This validated mitochondrial risk model delivers a clinically actionable biomarker for BLCA prognosis stratification and guides personalized therapeutic selection, enabling precision treatment intensification.

Drug sensitivity analysis identified BX-795 and tozasertib as potential treatments for tumors with high IGSF8 expression. Knockdown of IGSF8 significantly inhibited the proliferation ability of prostate cancer cells. Our findings indicated that IGSF8 might be used as a potential prognostic marker and therapeutic target for various cancers.

Finally, seven repurposed candidate drugs ENTRECTINIB, SORAFENIB, CHEMBL1765740, TOZASERTIB, NERVIANO, AZD-1152-HQPA, and SELICICLIB were proposed through molecular docking analysis. In conclusion, the findings of this study have the potential to significantly impact the early diagnosis, prognosis, and treatment of NSCLC.

Finally, dasatinib and tozasertib were identified as drug candidates capable of converting cold pancreatic adenocarcinoma tumors into hot tumors. In this study, we developed a framework for discerning clinically significant immune subtypes across various cancer types, further identifying several potential targets for converting cold tumors into hot tumors to enhance anticancer treatment efficacy.

Both docking studies revealed perfect binding of all identified ligands in active site pockets of AAK protein with similar amino acids of active sites as compared with standard BindingDB_50433632 compound and co-crystal ligand VX-680 binding mode of AAK protein. Therefore, it can be concluded that computational drug discovery approaches are meticulously implemented to identify potential AAKs inhibitors/modulators, and credential of the work was substantiated through the identification of three potential AAKs inhibitors/modulators that may hold significant promise for improving cancer management, however, need extensive biological assays or pre-clinical trials for assessing the efficacy profile of the identified compounds.

The IC50 values of predicted drugs, in the case of Tozasertib 1096 and WIKI4 1940, were significantly variant between risk groups...The study established an ARG prognosis model of ESCC. It provided a reference for the research of ARGs in ESCC.