patupilone (EPO 906)

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.

P1/2, N=75, Completed, University of Southern California | Unknown status --> Completed

P2, N=349, Active, not recruiting, National Cancer Institute (NCI) | Trial completion date: Mar 2026 --> Mar 2027

Although less potent than the nanomolar-range reference drug Epothilone B (IC50 < 0.1 μM), rugulosin A showed submicromolar-to-low micromolar efficacy with notable selectivity toward cancer cells, which is considered significant for an unoptimized natural product scaffold. Its antiproliferative activity against K562 cells (GI50 = 3.69 μM), benchmarked against Imatinib (GI50 = 0.373 μM), also falls within the active range of natural product leads...Molecular docking revealed strong binding energies (-10.1, -9.8, and -11.0 kcal/mol), along with a stable molecular dynamics simulations data. These findings highlight rugulosin A (3) as a promising anticancer lead that modulates major apoptosis signaling pathways.

P1, N=22, Active, not recruiting, National Cancer Institute (NCI) | Trial completion date: Mar 2026 --> Mar 2027

Furthermore, therapeutic vulnerabilities were explored by integrating drug sensitivity prediction, AI-assisted cMAP screening, and molecular docking validation, which identified Epothilone B as a promising agent targeting HBEGF. Overall, this research shows that understanding the heterogeneity of CAFs with AI-enabled multi-omics modeling can reveal prognostic biomarkers and therapeutic targets for overcoming resistance, with the ultimate goal of improving precision oncology for HNSCC.

Drug sensitivity analysis indicated that bortezomib, docetaxel, and epothilone B were more effective in the high-risk group. The exosome-related risk model constructed in this study can effectively predict the prognosis of patients with STAD.

The present study developed a PRS using 101 machine learning combination algorithms, which could aid in risk stratification and prognosis for LUAD patients. The candidate drugs and target may provide new insights in the treatment of high PRS group patients.

The level of released LDH of HepG-2 cells was increased exponentially with the Epothilone concentration, ensuring their negative effect on the plasma membrane permeability. From the docking results, the binding energy of Epothilone B with the tubulin-β was -9.96 kcal/mol, that was lower than Taxol (-7.87 kcal/mol), ensuring the higher affinity of Epothilone B to bind with the β-tubulin protein.

Furthermore, drug sensitivity analysis indicated that high-risk patients were more sensitive to Thapsigargin, Docetaxel, AKT inhibitor VIII, Pyrimethamine, and Epothilone B, while showing higher resistance to drugs such as I-BET-762, PHA-665752, and Belinostat. This study provides a comprehensive analysis of NRGs in BC and establishes reliable ML-based diagnostic and prognostic models. The findings highlight the clinical relevance of NRGs in BC progression, immune regulation, and therapy response, offering potential targets for personalized treatment strategies.

This study successfully developed a prognostic model based on SRGs, effectively predicting the prognosis and drug response of KIRC patients. The model demonstrated significant predictive performance and potential clinical application value. Furthermore, the study highlighted the critical role of sialylation in KIRC, offering new insights into its underlying mechanisms in tumor biology. These findings could guide personalized treatment strategies for KIRC patients, emphasizing the importance of sialylation in cancer prognosis and therapy.

P2, N=349, Active, not recruiting, National Cancer Institute (NCI) | Trial completion date: Mar 2025 --> Mar 2026