Biology subjects

Herter, S.

Publications and source records attributed to Herter, S..

3 recordsLinked to original sources

bioRxiv2025

Dynamic BH3 profiling predicts clinical outcomes in acute myeloid leukemia

Predictive biomarkers can potentially meet the need for improved drug assignment in acute myeloid leukemia (AML). Fewer than half of AML patients have actionable mutations: consequently, targeted therapy achieves remission in only a fraction of those who have them. Dynamic BH3 Profiling (DBP), a functional assay, can measure changes in ex vivo drug-induced apoptotic priming in multiple cancers. To assess the feasibility and predictive capacity of DBP in AML, we prospectively tested DBP using a fixed-drug panel in myeloblasts from 92 patients. We generated a database combining genetic and functional annotation. Established AML clinical and genetic prognostic characteristics were associated with drug-induced apoptotic priming. We observed distinct interpatient sensitivities to single drugs or combinations with the BCL2-inhibitor venetoclax, and intrapatient apoptotic priming differences based on CD123-expression within distinct cell subpopulations. DBP further predicted the likelihood of remission to chemotherapy and targeted agents, supporting its use to identify optimal personalized therapy. Statement of significanceDynamic BH3 profiling provides patient-specific drug vulnerability data in real-time to inform prognosis and therapy selection. Key takeawaysO_LIDynamic BH3 profiling can be performed on bone marrow and leukemic blood from AML patients in 48 hours. C_LIO_LIKnown clinical prognostic factors associate with drug-induced apoptotic priming in AML. C_LIO_LIDrug-induced apoptotic priming identifies drug vulnerabilities in individual patients and predicts clinical response to chemotherapy and small molecule inhibitors. C_LI

cancer biology↗

bioRxiv2022

scifAI: Explainable machine learning for profiling the immunological synapse and functional characterization of therapeutic antibodies

Therapeutic antibodies are widely used to treat severe diseases. Most of them alter immune cells and act within the immunological synapse; an essential cell-to-cell interaction to direct the humoral immune response. Although many antibody designs are generated and evaluated, a high-throughput tool for systematic antibody characterization and prediction of function is lacking. Here, we introduce the first comprehensive open-source framework, scifAI (single-cell imaging flow cytometry AI), for preprocessing, feature engineering and explainable, predictive machine learning on imaging flow cytometry (IFC) data. Additionally, we generate the largest publicly available IFC data set of the human immunological synapse containing over 2.8 million images. Using scifAI, we analyze class frequency- and morphological changes under different immune stimulation. T cell cytokine production across multiple donors and therapeutic antibodies is quantitatively predicted in vitro, linking morphological features with function and demonstrating the potential to significantly impact antibody design. scifAI is universally applicable to IFC data. Given its modular architecture it is straightforward to incorporate into existing workflows and analysis pipelines, e.g. for rapid antibody screening and functional characterization.

bioinformatics↗

bioRxiv2022

Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation

Glioblastoma (GBM) harbors a highly immunosuppressive tumor microenvironment (TME) which influences glioma growth. Major efforts have been undertaken to describe the TME on a single-cell level. However, human data on regional differences within the TME remain scarce. Here, we performed high-depth single-cell RNA sequencing (scRNAseq) on paired biopsies from the tumor center, peripheral infiltration zone and blood of five primary GBM patients. Through analysis of > 45000 cells, we revealed a regionally distinct transcription profile of microglia (MG) and monocyte-derived macrophages (MdMs) and an impaired activation signature in the tumor-peripheral cytotoxic-cell compartment. Comparing tumor-infiltrating CD8+ T cells with circulating cells identified CX3CR1high and CX3CR1int CD8+ T cells with effector and memory phenotype, respectively, enriched in blood but absent in the TME. Tumor CD8+ T cells displayed a tissue-resident memory phenotype with dysfunctional features. Our analysis provides a regionally resolved mapping of transcriptional states in GBM-associated leukocytes, serving as an additional asset in the effort towards novel therapeutic strategies to combat this fatal disease.

cancer biology↗