tozasertib (MK-0457)

The signature independently predicted prognosis (AUC: 0.70-0.84) and treatment response: LR patients favored immunotherapy (lower TIDE, higher IPS), while HR patients were sensitive to chemotherapy (e.g., Bosutinib, Tozasertib). This transcriptome-derived m6A-associated prognostic model can effectively predict clinical survival outcomes and therapeutic response in LUAD patients. Combined with immune landscape, genomic mutation profiles and single-cell transcriptomic evidence, this signature provides a reliable basis for personalized risk stratification and rational treatment choice.

According to the pharmacogenomic analysis from GDSC2 dataset, tumor cells that express higher DNA2 are more sensitive to Tozasertib, and Daporinad. DNA2 is at the core of several interrelated modules, including flap processing, telomerase extension, and cell-cycle progression, according to the enrichment study. These findings have suggested DNA2 as a therapeutic vulnerability in cancer, a context-dependent biomarker with implications for treatment response, prognosis, and immunity.

Pharmacogenomic analysis identified nine compounds (Shikonin, Bicalutamide, Bryostatin-1, Epothilone-B, JNK-9L, LFM-A13, QS11, VX-680, and Z-LLNle-CHO) exhibiting differential sensitivity between the dichotomous risk strata. This study yields findings that hold significant clinical implications for refining prognostic stratification and deciphering the immune landscape in ESCC. Moreover, they offer novel perspectives that may pave the way for more precise prognostic assessment and the formulation of targeted therapeutic interventions.

Drug sensitivity analysis indicated that tozasertib, savolitinib, AZD4547, IWP-2, and GSK591 may have potential therapeutic value. Multi-omics analyses revealed that these key genes are regulated by DNA methylation and transcription factor networks. The actin cytoskeleton-based gene signature serves as an independent indicator of poor prognosis and may support precise prognostic assessment and personalized therapeutic strategies for GBM.

This work set up a prognostic model for LUAD based on 8 MDRGs, pinpointing promising biomarkers and targets for LUAD treatment.

In summary, aurora kinase inhibitor combined with CDDP could suppress the ERK pathway to affect the biological process of esophageal carcinoma cells. Versus a simple drug, a drug combination could effectively inhibit the proliferation and migration of esophageal carcinoma cells, promote apoptosis, reduce angiogenesis, and induce cell cycle arrest.

Everolimus (EVER) and tozasertib (TOZA) encapsulated in NP and targeted with dinutuximab β (DTX-β). DTX-β/EVER-TOZA@PEG-b-PLGA may exert cytotoxic and apoptotic effects in NB. The use of targeted nanocarriers in NB treatment may enhance cytotoxic and apoptotic responses specifically in the tumor region.

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.