Abstract Background Patients with highly aggressive breast cancers, such as triple-negative breast cancer (TNBC) and inflammatory breast cancer (IBC)—face clinical challenges, due to advanced stage at diagnosis, high risk for development of metastasis, and limited treatment options. Therefore, the development of novel treatment strategies is an urgent unmet need. We previously demonstrated that MELK is highly expressed in TNBC and IBC, and plays a key role in promoting stemness, epithelial-mesenchymal transition (EMT), and metastasis in a xenograft model. The inhibition of MELK reduced fibronectin (FN1) expression in vitro and in a xenograft mouse model, impairing the formation of extracellular fibronectin fibrils and ultimately decreasing cancer cell motility in TNBC/IBC cells. In the current study, we extended our investigation to patient samples to assess MELK expression, EMT markers, and macrophage infiltration in the tumor microenvironment. Additionally, to support clinical translation, we evaluated the efficacy of MELK inhibitors in combination with standard-of-care agents—paclitaxel (PT) and eribulin (ERB) in TNBC/IBC xenograft models. Materials and Methods We evaluated the efficacy and toxicity of MELK-inhibitors (MELK-In-17, MELK-In-30e, and OTS167), alone or in combination with paclitaxel or eribulin, using the 4T1(TNBC) and SUM149 (TN-IBC) mouse models. The multiplex immunofluorescence (mIF) staining was performed on tissue microarrays from 179-TNBC and 278-invasive breast cancer samples from the MD Anderson Breast Tumor Tissue Bank. The panel of markers included MELK, N-cadherin, E-cadherin, vimentin, fibronectin, PANCK, arginase1, CD163, IBA-1, CD206, and PD-L1. Results In the 4T1 model, MELK inhibitors alone or in combination with paclitaxel significantly reduced tumor growth compared to vehicle. MELK-In-30e was more effective than OTS167, though no synergistic effect was observed with paclitaxel combinations. All treatment groups showed reduction in FN1 and Ki67expression, with the greatest decrease in 30e and 30e+paclitaxel groups. In the SUM149 tumor model, treatment with 30e plus eribulin resulted in significantly greater tumor suppression compared to 30e alone (p = 0.02), while 30e plus paclitaxel did not demonstrate synergy. OTS167 showed modest tumor growth inhibition as a monotherapy and in combination with paclitaxel or eribulin showed limited effect. Survival was improved with 30e+paclitaxel and 30e+eribulin combinations. Ki-67 expression was reduced across all treatment groups, with the most substantial decrease in the 30e+eribulin group. 30e alone or 30e+eribulin also led to decreased expression of MELK, FN1, and vimentin. No significant toxicity was observed in the monotherapy or combination treatments. mIF staining of patient tissues revealed variable expression of MELK and EMT markers, with consistent moderate to high PDL1 expression and frequent infiltration of macrophages exhibiting immunosuppressive “M2”-like phenotypes frequently noted. Conclusions and Future Directions MELK-In-30e combined with eribulin significantly inhibited tumor growth and suppressed EMT and proliferative markers. mIF analysis of patient samples revealed a tumor microenvironment enriched in PD-L1 expression and M2 macrophages, suggesting immune evasion mechanisms. These findings provide a rationale for further investigation into MELK-targeted combination therapies to enhance the efficacy of existing therapies and immune activation in aggressive cancers. We plan to assess the prognostic value of MELK, EMT, and immune markers based on mIF analysis of patient samples. Citation Format: M. Mughees, R. Pathania, N. Fowlkes, J. Wang, S. Krishnamurthy, S. Damodaran, W. Woodward, K. Hunt, A. Sahin, K. Dalby, B. Chandra. Combination of a novel MELK inhibitor with standard of care treatment results in tumor regression and improved survival in a triple-negative inflammatory breast cancer xenograft model abstract. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-09-30.
Building similarity graph...
Analyzing shared references across papers
Loading...
Mohd Mughees
Rajneesh Pathania
Natalie W. Fowlkes
Clinical Cancer Research
The University of Texas at Austin
The University of Texas MD Anderson Cancer Center
Building similarity graph...
Analyzing shared references across papers
Loading...
Mughees et al. (Tue,) studied this question.
www.synapsesocial.com/papers/699a9de0482488d673cd417b — DOI: https://doi.org/10.1158/1557-3265.sabcs25-ps2-09-30