Publications by authors named "Ron Ma Heeren"
Article Synopsis
- Aberrant glycosylation is significant in cancer, but its role in breast cancer metastasis was under-researched; this study aimed to fill that gap by examining N-glycosylation in metastatic breast cancer (BC) patients.
- The research involved analyzing tissue samples from 17 metastatic BC patients using mass spectrometry imaging (MSI) to assess changes in N-glycosylation patterns across different metastatic sites.
- Findings revealed a generalized increase in N-glycan abundance during metastasis, with specific alterations in glycan types; this suggests potential diagnostic and therapeutic applications targeting glycosylation in metastatic breast cancer.
Background: Barrett's esophagus (BE) is a precursor lesion of esophageal adenocarcinoma and may progress from non-dysplastic through low-grade dysplasia (LGD) to high-grade dysplasia (HGD) and cancer. Grading BE is of crucial prognostic value and is currently based on the subjective evaluation of biopsies. This study aims to investigate the potential of machine learning (ML) using spatially resolved molecular data from mass spectrometry imaging (MSI) and histological data from microscopic hematoxylin and eosin (H&E)-stained imaging for computer-aided diagnosis and prognosis of BE.
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