What question did this study set out to answer?

This research aims to analyze the expression landscape of antibody-drug conjugate targets in gliomas to identify potential therapeutic candidates.

March 12, 2026Open Access

8P Expression landscape of antibody-drug conjugates in gliomas

MHM.K. HashkiJordan University of Science and Technology MAM.A. Al-AsadiJordan University of Science and Technology MGM.B. GhanamehJordan University of Science and Technology

Key Points

This research aims to analyze the expression landscape of antibody-drug conjugate targets in gliomas to identify potential therapeutic candidates.
Conducted a search for ADC targets through Clinical-Trials.gov
Analyzed bulk transcriptomic data from TCGA-GBM and TCGA-LGG
Performed differential expression analysis comparing tumor and normal brain tissues
Evaluated single-cell RNA sequencing data for malignant-specific markers
Identified correlations between ADC targets and patient survival using sensitivity and resistance markers.
Identified 60 ADC targets, with 23 significantly upregulated in GBM and LGG tissues
Single-cell analysis revealed 8 malignant cell markers, including DLL3 and EGFR
MUC1, FOLR1, and FN1 were positively correlated with ADC sensitivity markers
EGFR correlated with resistance markers associated with payloads
Expression of MUC1, FOLR1, and FN1 linked to worse survival outcomes in LGG and GBM.

Abstract

Background: Antibody-drug conjugates (ADCs) are an emerging therapeutic modality that enable targeted delivery of cytotoxic chemotherapy to tumor cells, thereby improving antitumor specificity while minimizing systemic toxicity.Here, we investigate the expression and landscape of ADC targets in gliomas. Methods:A comprehensive search for ADC targets was performed using Clinical-Trials.gov.Bulk transcriptomic data were obtained from TCGA-GBM (n=391) and TCGA-LGG (n=534), with normal brain samples from GTEx (n=400).Single-cell RNAseq data (GSE131928) were retrieved from TISCH2.0.Differential expression analysis (DEA) was conducted for GBM vs normal and LGG vs normal tissues.DEA of the single-cell dataset identified malignant cell marker genes, and bulk tumor-upregulated targets were filtered against these markers to identify malignant-specific ADC candidates.Correlation analyses were then performed using literature-validated sensitivity and resistance markers for ADC payloads, including topoisomerase inhibitors, maytansinoids, and auristatin derivatives.Finally, malignant-expressed ADC targets were evaluated for associations with patient survival.Results: A total of 60 ADC targets were retrieved, out of these targets 23 were significantly upregulated in both GBM and LGG (log2FC>0.5,p<0.05).Single-cell DEA identified 8 (DLL3, EGFR, CD38, FN1, SLC39A6, FOLR1, and CDH6) malignant cell cluster-upregulated targets.MUC1, FOLR1, and FN1 were significantly positively correlated with ADC sensitivity markers, including CTSB, CTSL, CTSA, and CTSC, which are lysosomal proteases that facilitate intracellular payload release.The other ADC targets showed significant negative correlation with most sensitivity markers.EGFR showed significant positive correlation to ABCB1 and ABCG2 resistance marker, known to confer resistance to auristatin and camptothecin payloads.Elevated expression of MUC1, FOLR1, and FN1 were significantly associated with worse survival outcomes in both LGG and GBM (p<0.05).Conclusions: MUC1, FOLR1, and FN1 emerge as key ADC targets in gliomas, showing malignant-specific expression, strong association with ADC payload sensitivity markers, and links to poor survival, supporting their therapeutic potential.

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