Objective: Tumor hypoxia results in worse local control and patient survival. We performed a digital, single-cell-based analysis to compare two biomarkers for hypoxia (hypoxia-inducible factor 1-alpha [HIF-1α] and pimonidazole [PIMO]) and their effect on outcome in laryngeal cancer patients treated with accelerated radiotherapy with or without carbogen breathing and nicotinamide (AR versus ARCON).
Materials And Methods: Immunohistochemical staining was performed for HIF-1α and PIMO in consecutive sections of 44 laryngeal cancer patients randomized between AR and ARCON. HIF-1α expression and PIMO-binding were correlated using digital image analysis in QuPath. High-density areas for each biomarker were automatically annotated and staining overlap was analyzed. Kaplan-Meier survival analyses for local control, regional control and disease-free survival were performed to predict a response benefit of ARCON over AR alone for each biomarker.
Results: 106 Tissue fragments of 44 patients were analyzed. A weak, significant positive correlation was observed between HIF-1α and PIMO positivity on fragment level, but not on patient level. A moderate strength correlation (r = 0.705, p < 0.001) was observed between the number of high-density staining areas for both biomarkers. Staining overlap was poor. HIF-1α expression, PIMO-binding or a combination could not predict a response benefit of ARCON over AR.
Conclusion: Digital image analysis to compare positive cell fractions and staining overlap between two hypoxia biomarkers using open-source software is feasible. Our results highlight that there are distinct differences between HIF-1α and PIMO as hypoxia biomarkers and therefore suggest co-existence of different forms of hypoxia within a single tumor.
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http://dx.doi.org/10.1016/j.oraloncology.2022.105862 | DOI Listing |
J Biotechnol
January 2025
Technische Universität Berlin, Department of Biotechnology, Chair of Bioprocess Engineering, Berlin, Germany; Aalborg University, Department of Chemistry and Bioscience, Esbjerg, Denmark. Electronic address:
Digital holographic microscopy (DHM) is a label-free analytical technique for the determination of the cells' volume and their cytosolic refractive index. Here, we demonstrate the suitability of DHM for the quantification of total lipid accumulation in the oleaginous yeast Yarrowia lipolytica. Presently, microbial lipids are gaining increasing attention due to their nutritional value in feed and food applications.
View Article and Find Full Text PDFNeurosci Bull
July 2024
State Key Laboratory of Digital Medical Engineering, Department of Otolaryngology Head and Neck Surgery, Zhongda Hospital, School of Life Sciences and Technology, Advanced Institute for Life and Health, Jiangsu Province High-Tech Key Laboratory for Bio-Medical Research, Southeast University, Nanjing, 210096, China.
Hearing loss and deafness, as a worldwide disability disease, have been troubling human beings. However, the auditory organ of the inner ear is highly heterogeneous and has a very limited number of cells, which are largely uncharacterized in depth. Recently, with the development and utilization of single-cell RNA sequencing (scRNA-seq), researchers have been able to unveil the complex and sophisticated biological mechanisms of various types of cells in the auditory organ at the single-cell level and address the challenges of cellular heterogeneity that are not resolved through by conventional bulk RNA sequencing (bulk RNA-seq).
View Article and Find Full Text PDFCell Rep Methods
October 2023
Department of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, USA. Electronic address:
Imaging mass cytometry (IMC) is a powerful technique capable of detecting over 30 markers on a single slide. It has been increasingly used for single-cell-based spatial phenotyping in a wide range of samples. However, it only acquires a rectangle field of view (FOV) with a relatively small size and low image resolution, which hinders downstream analysis.
View Article and Find Full Text PDFPLOS Digit Health
March 2023
Institute of AI for Health, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
Explainable AI is deemed essential for clinical applications as it allows rationalizing model predictions, helping to build trust between clinicians and automated decision support tools. We developed an inherently explainable AI model for the classification of acute myeloid leukemia subtypes from blood smears and found that high-attention cells identified by the model coincide with those labeled as diagnostically relevant by human experts. Based on over 80,000 single white blood cell images from digitized blood smears of 129 patients diagnosed with one of four WHO-defined genetic AML subtypes and 60 healthy controls, we trained SCEMILA, a single-cell based explainable multiple instance learning algorithm.
View Article and Find Full Text PDFSemin Diagn Pathol
March 2023
Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, 10833 Le Conte Avenue, Los Angeles, CA, 90095, United States of America. Electronic address:
Cytology plays an important role in diagnosing and managing human diseases, especially cancer, as it is often a simple, low cost yet effective, and non-invasive or minimally invasive diagnostic tool. However, traditional morphology-based cytology practice has limitations, especially in the era of precision diagnosis. Recently there have been tremendous efforts devoted to apply computational tools and to perform molecular analysis on cytological samples for a variety of clinical purposes.
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