Product Description

Ixabepilone is an orally bioavailable microtubule inhibitor, which binds to tubulin and promotes tubulin polymerization and microtubule stabilization, thereby arrests cells in the G2-M phase of the cell cycle and induces tumor cell apoptosis.

Screeningbio‘s K562/ Ixabepilone resistance cell line generated by exposing to increasing concentration of drug for certain period of time. After stable acquire resistance, cells were harvested and characterized for drug resistance by 7 days proliferation assay.

Data

Target Background

Ixabepilone is a semisynthetic epothilone B analog that stabilizes microtubules and promotes tubulin polymerization, leading to mitotic arrest and apoptosis in rapidly dividing cancer cells. Unlike paclitaxel, ixabepilone retains activity against certain β‑tubulin mutations and alterations in tubulin isotypes that confer taxane resistance, making it particularly useful in patients with taxane‑resistant breast cancer and other solid tumors. Nevertheless, acquired resistance remains a clinical challenge limiting its long‑term efficacy.

Mechanistically, ixabepilone resistance arises through multiple cellular adaptations. Upregulation of efflux transporters such as P‑glycoprotein (MDR1/ABCB1) decreases intracellular drug accumulation, although ixabepilone is a relatively poor substrate for some ABC transporters compared to taxanes. Mutations or altered expression of β‑tubulin isotypes—especially class III β‑tubulin (TUBB3)—can reduce drug–microtubule binding. Activation of survival signaling pathways including PI3K/Akt, MAPK, and NF‑κB promotes anti‑apoptotic responses. Additionally, changes in microtubule‑associated proteins (MAPs, e.g., tau and MAP4), enhanced autophagic flux, and epithelial–mesenchymal transition (EMT) contribute to reduced drug sensitivity.

Understanding these resistance mechanisms is critical for designing strategies to overcome them, such as combining ixabepilone with efflux transporter inhibitors, targeting compensatory PI3K/Akt or MAPK pathways, or using patient‑derived resistant models to guide personalized combination regimens.