Martin Bornhäuser

Deep learning predicts IDH1 mutation status in acute myeloid leukemia from bone marrow smears

Abstract Acute myeloid leukemia (AML) with IDH1 mutations is amenable to targeted therapy, highlighting the need for reliable identification. We developed an attention-based multiple-instance learning model to predict IDH1 mutation status using bone marrow smear whole-slide image...

Durable treatment response to Trastuzumab deruxtecan in two patients with recurrent grade III anaplastic ependymoma

Abstract Background Anaplastic ependymoma is a rare and aggressive central nervous system malignancy for which effective systemic treatment options are limited. Trastuzumab deruxtecan (T-DXd), an antibody–drug conjugate targeting human epidermal growth factor receptor 2 (HER2), h...

A pancreatic cancer organoid-macrophage co-culture using starPEG-heparin hydrogel deciphers tumor-immune cell interactions

Abstract Macrophages are among the most abundant immune cells in the pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment (TME) and play a key role in regulating the immunosuppressive niche that facilitates tumor growth. Although recent three-dimensional (3D) culture sy...

Functional characterization of snoRNA-derived RNA (sdRNA) expression in healthy hematopoiesis and acute myeloid leukemia

Abstract SnoRNAs are highly expressed in AML and have implications in leukemogenesis and leukemic maintenance. SnoRNAs can be further processed into snoRNA-derived RNAs (sdRNAs). The role of sdRNAs in AML and healthy hematopoiesis remains largely elusive. We characterized sdRNA a...