Christel C. Herold‐Mende

This study uses pan-cancer phosphoproteomics to identify therapeutic targets and improve precision oncology by analyzing 1,998 tumor samples and developing new scores for kinase activity and immune response.

This paper uses Raman spectroscopy and machine learning to classify brain tumor cell types at single-cell resolution, achieving high accuracy in distinguishing IDH1 mutation status and histological subtypes.

This study identifies panobinostat as an effective treatment for aggressive meningiomas through drug screening on tumor organoids and reveals a resistance mechanism involving the HDAC8-TGFβ-EMT axis.

The paper identifies PTEN loss as a driver of aggressive NF2 mutant meningiomas and validates a cross-species model for preclinical testing.

This study identifies high M2-TAM infiltration as an independent poor survival prognostic factor in meningiomas, overriding the beneficial effect of TILs.

This study integrates multi-omics and functional drug screening in patient-derived organoids to identify personalized therapeutic vulnerabilities in adult high-grade gliomas, finding distinct drug responses in IDH1 mutant and MYCN-amplified tumors.

This study identifies BRAT1 as a key driver of glioblastoma growth and invasion, showing that its inhibition with CurD reduces tumor migration and enhances radiation sensitivity.

This study uses cellular barcoding to analyze clonal dynamics in response to radiation, finding deterministic and stochastic selection processes contribute to radiation resistance in HNSCC cells.

This study integrates phospho-proteogenomic and single-cell transcriptomic data to subtype meningiomas and identify subtype-specific immune infiltration patterns.