Publications by authors named "K Bankov"

Aims: Anti-claudin-18.2 (CLDN18.2) therapy was recently approved for the treatment of gastric or gastro-oesophageal junction adenocarcinoma.

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A vast multitude of tasks in histopathology could potentially benefit from the support of artificial intelligence (AI). Many examples have been shown in the literature and first commercial products with FDA or CE-IVDR clearance are available. However, two key challenges remain: (1) a scarcity of thoroughly annotated images, respectively the laboriousness of this task, and (2) the creation of robust models that can cope with the data heterogeneity in the field (domain generalization).

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Article Synopsis
  • Fibrinolysis plays a crucial role in the release of hematopoietic stem cells from bone marrow, affecting the development of B-cell acute lymphoblastic leukemia (B-ALL).
  • Activation of plasmin, driven by annexin A2, alters the extracellular matrix (ECM), which impacts cancer cell growth by trapping the growth factor IGF1 and hindering signaling pathways.
  • Inhibiting plasmin activation with ε-aminocaproic acid (EACA) shows promise in reducing tumor size and extending survival in B-ALL models, suggesting that targeting fibrinolysis could be a helpful addition to cancer treatment.
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Salivary gland cancer (SGC) is a rare cancer that can present a diagnostic challenge to pathologists, with emerging, but still limited options for the treatment of recurrent/metastatic disease. We aimed to characterize the cohort of salivary gland cancers in our institute and generate a tissue microarray (TMA) with clinical data available for immunohistochemical analysis. We extracted the cases of salivary gland cancers in our institute and generated a TMA with 72 patients between 2002 and 2017 with sufficient paraffin block material.

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Purpose: Dedicated gene signatures in small (SD-iCCA) and large (LD-iCCA) duct type intrahepatic cholangiocarcinoma remain unknown. We performed immune profiling in SD- and LD-iCCA to identify novel biomarker candidates for personalized medicine.

Methods: Retrospectively, 19 iCCA patients with either SD-iCCA (n = 10, median age, 63.

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