Evaluation of (Z)-endoxifen as a potential therapy for glioblastoma multiforme through computational and experimental analyses

Abstract

(Z)-endoxifen (endoxifen) is the active metabolite of tamoxifen. Endoxifen is a potent antiestrogen that binds and blocks estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ). Early-phase clinical trials have shown that endoxifen has promising effects in patients with hormone-resistant metastatic breast cancer and other estrogen receptor-positive (ERα+) tumors. In addition, endoxifen has known estrogen-independent effects, such as inhibiting protein kinase C beta (PKCβ1). Given its broader mechanisms and demonstrated clinical activity with potential advantages over tamoxifen in breast cancer, endoxifen warrants investigation in other cancer types. This study aimed to identify new oncology indications with high therapeutic potential for endoxifen, as monotherapy or in combination, by applying the AI-powered PandaOmics platform to analyze a wide range of cancer types based on its mechanisms of action (MOA). Glioblastoma multiforme (GBM) emerged as a top candidate for endoxifen's therapeutic potential. In vitro studies in the CRT435 GBM cell line confirmed that endoxifen treatment reduced cell proliferation and induced cell death, while in vivo studies in a subcutaneous CRT435 patient-derived xenograft (PDX) model demonstrated a tolerable safety profile but no significant tumor growth reduction, likely reflecting limitations of the model used. This study underscores the application of AI-driven computational approaches in identifying new therapeutic hypotheses and demonstrates the potential of repurposing endoxifen for GBM treatment.

Keywords: (Z)-endoxifen; Artificial intelligence; Glioblastoma multiforme; Mechanism of action.

Fig. 1

A diagram illustrating the pipeline of data integration, hypothesis generation, and deep dive analysis.

Fig. 1

A diagram illustrating the pipeline of data integration, hypothesis generation, and deep dive analysis.

Fig. 2

(A) Analysis of genes intersecting between bulk GBM and endoxifen data. The red arrow pointing up and the blue arrow pointing down describe a group of genes that were upregulated in GBM and downregulated by endoxifen in MCF7 cells. The red arrow pointing down and the blue arrow pointing up describe a group of genes that were downregulated in GBM and upregulated by endoxifen in MCF7 cells. (B) GSEA analysis for 560 genes upregulated in GBM and downregulated after endoxifen treatment in MCF7 cells. Ranking is based on adjusted p-value. Coloring is based on Combined score =  − log(p-value) * Odds Ratio. Dot size is based on the number of genes related to the pathway. All significant hallmarks are presented.

Fig. 3

TF enrichment analysis for downstream genes that were upregulated in GBM and downregulated after endoxifen treatment in MCF7 cells. (A) Scatter plot for TFs significantly enriched with downstream genes (FDR adjusted p-value < 0.05) in both GBM and endoxifen meta-analyses. The first 10 TFs with the highest proportion of downstream genes upregulated in GBM and downregulated after endoxifen treatment in breast cancer cells are labeled. (B) Graph for E2F8 downstream genes with their combined normalized log fold changes (LFC) in GBM project and in endoxifen project. Significantly (FDR corrected p-value < 0.05) upregulated and downregulated genes are colored green and red, respectively.

Fig. 4

(A) Analysis of genes intersecting between bulk GBM, scRNA-seq GBM and endoxifen data. The red arrow pointing up and the blue arrow pointing down describe a group of genes that were upregulated in bulk and scRNA-seq GBM and downregulated by endoxifen in MCF7 cells. (B) GSEA analysis for 73 genes upregulated in bulk and scRNA-seq GBM and downregulated after endoxifen treatment in MCF7 cells. Ranking is based on adjusted p-value. Coloring is based on Combined score =  − log(p-value) * Odds Ratio. Dot size is based on the number of genes related to the pathway. All significant hallmarks are presented.

Fig. 5

Results of the analysis of the genes associated with a patient’s survival and GBM subtypes. (A) Kaplan–Meier survival analysis based on the TCGA-GBM dataset. Heatmaps based on PandaOmics expression analysis in GBM (B) and (E) endoxifen meta-analyses. (C) UMAPs of HSPB1, PRA3 and NFKBIZ expression in GBM samples from GSE84465 scRNA-seq. (D) Boxplots for HSPB1, PRA3 and NFKBIZ genes from GSE84465 scRNA-seq GBM study. (F) UMAPs and boxplot of HSPB1 expression in GBM samples with Mesenchymal (MES) and Proneural/Classical (PN&CL) subtypes based on GSE159416 scRNA-seq GBM study. *p-value < 0.05, **p-value < 0.01, ***p-value < 0.0001.

Fig. 5

Results of the analysis of the genes associated with a patient’s survival and GBM subtypes. (A) Kaplan–Meier survival analysis based on the TCGA-GBM dataset. Heatmaps based on PandaOmics expression analysis in GBM (B) and (E) endoxifen meta-analyses. (C) UMAPs of HSPB1, PRA3 and NFKBIZ expression in GBM samples from GSE84465 scRNA-seq. (D) Boxplots for HSPB1, PRA3 and NFKBIZ genes from GSE84465 scRNA-seq GBM study. (F) UMAPs and boxplot of HSPB1 expression in GBM samples with Mesenchymal (MES) and Proneural/Classical (PN&CL) subtypes based on GSE159416 scRNA-seq GBM study. *p-value < 0.05, **p-value < 0.01, ***p-value < 0.0001.

Fig. 5

Results of the analysis of the genes associated with a patient’s survival and GBM subtypes. (A) Kaplan–Meier survival analysis based on the TCGA-GBM dataset. Heatmaps based on PandaOmics expression analysis in GBM (B) and (E) endoxifen meta-analyses. (C) UMAPs of HSPB1, PRA3 and NFKBIZ expression in GBM samples from GSE84465 scRNA-seq. (D) Boxplots for HSPB1, PRA3 and NFKBIZ genes from GSE84465 scRNA-seq GBM study. (F) UMAPs and boxplot of HSPB1 expression in GBM samples with Mesenchymal (MES) and Proneural/Classical (PN&CL) subtypes based on GSE159416 scRNA-seq GBM study. *p-value < 0.05, **p-value < 0.01, ***p-value < 0.0001.

Fig. 6

Summary of in vitro studies on the efficacy of endoxifen in the CRT435 GBM cell line. (A) Proliferation analysis in CRT435 cells treated with endoxifen, TMZ, or combination of both. (B) Cytotoxicity (cellular apoptosis) analysis in CRT435 cells treated with endoxifen, TMZ, or combination of both. Proliferation over time was measured by nuclear green object count per image following IncuCyte NucLight Green lentiviral transduction, while cytotoxicity (apoptosis) was assessed by red fluorescence integrated intensity (RCU × µm² per image) using IncuCyte Annexin V staining. Desired treatments were added on Day 1, after the transduced cells were confirmed to fluoresce. Scans were taken every 6 h starting on Day 0 and over an 8-day period. Vehicle control was used in equivalent to the dose of highest test agent dose. 10% DMSO was used as a cell killing positive control. For ease of visualization and perception of data in the graph, only the 5-day curves for cells treated with maximum concentrations of substances and their combinations are shown. The full versions of the proliferation graphs and apoptosis graphs can be found in Supplementary Figs. 1 and 2. Representative images of CRT435 cells from the IncuCyte S3 Live-Cell Analysis System after endoxifen treatment can be found in Supplementary Figs. 3–7.

Fig. 7

Summary of in vivo studies on the efficacy of endoxifen in the CRT435 PDX model. Tumor volume measurements in athymic nude mice inoculated with CRT435 tumor fragment and treated with endoxifen alone or in combination with TMZ. Mean tumor volume (TMV) (mm³) ± standard error (SE) are presented.