Publications by authors named "Cor J Ravensbergen"

Background: Approximately 1% of all breast cancers occur in men. With an annual incidence of 130 cases in the Netherlands, the occurrence of male breast cancer is rare.

Case Description: We report the case of a 72-year-old male who was referred to a breast outpatient clinic for the evaluation of a multinodular skin lesion of the nipple.

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Background: Oncological sigmoid and rectal resections are accompanied with substantial risk of anastomotic leakage. Preoperative risk assessment and patient selection remain difficult, highlighting the importance of finding easy-to-use parameters. This study evaluates the prognostic value of contrast-enhanced (CE) computed tomography (CT)-based muscle measurements for predicting anastomotic leakage.

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In the pursuit of personalized diagnostics and tailored treatments, quantitative protein tests contribute to a more precise definition of health and disease. The development of new quantitative protein tests should be driven by an unmet clinical need and performed in a collaborative effort that involves all stakeholders. With regard to the analytical part, mass spectrometry (MS)-based platforms are an excellent tool for quantification of specific proteins in body fluids, for example focused on cancer.

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A 71-year-old female visited the gynaecology outpatient clinic with an inguinal lump and lower abdominal pain. Radiologic imaging of the abdomen demonstrated a pelvic mass with a diameter of 11 centimeters. Subsequent histopathologic analysis of the inguinal lump revealed a metastatic lesion of a gastrointestinal stromal tumour.

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Liquid biopsy has emerged as a novel approach to tumor characterization, offering advantages in sample accessibility and tissue heterogeneity. However, as mutational analysis predominates, the tumor microenvironment has largely remained unacknowledged in liquid biopsy research. The current work provides an explorative transcriptomic characterization of the Stroma Liquid Biopsy (SLB) proteomics panel in colon carcinoma by integrating single-cell and bulk transcriptomics data from publicly available repositories.

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The best current biomarker strategies for predicting response to immune checkpoint inhibitor (ICI) therapy fail to account for interpatient variability in response rates. The histologic tumor-stroma ratio (TSR) quantifies intratumoral stromal content and was recently found to be predictive of response to neoadjuvant therapy in multiple cancer types. In the current work, we predicted the likelihood of ICI therapy responsivity of 335 therapy-naive colon adenocarcinoma tumors from The Cancer Genome Atlas, using bioinformatics approaches.

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