Roland Michael Schmid

This study shows that prolonged TGF-β signaling causes persistent NK cell dysfunction through epigenetic changes, while short-term signaling leads to reversible effects.

This study uses an in ovo model to show that the CAM platform supports tumor-stroma coevolution in pancreatic cancer, preserving patient-specific features and enabling functional analysis of stromal interactions.

This study identifies c-Rel as a driver of pancreatic cancer metastasis by promoting EMT, ECM remodeling, and resistance to isolation stress through fibronectin-integrin signaling.

This study shows that high-fat diets promote GEAC by altering the microbiota-Bile Acid axis and inhibiting FXR, with FXR agonists like OCA slowing disease progression.

This study identifies KRAS mutation as a driver of invasive gastro-esophageal adenocarcinoma in a mouse model, showing its synergistic role with Tp53 or Rb1 loss and potential as a therapeutic target.

The paper develops a machine learning model using radiomic features from MRI to predict survival and tumor subtype in pancreatic ductal adenocarcinoma with high accuracy.

This paper develops a machine learning model to predict molecular subtypes of PDAC from radiomic features, showing differential chemotherapy response based on subtype.