A5004723504- Bioinformatics and Genomic Networks
- Cancer Genomics and Diagnostics
- Gene expression and cancer classification
- Molecular Biology Techniques and Applications
- Colorectal Cancer Treatments and Studies
- RNA modifications and cancer
- Genomics and Chromatin Dynamics
- RNA Research and Splicing
- Cancer, Hypoxia, and Metabolism
- Metabolomics and Mass Spectrometry Studies
- Testicular diseases and treatments
- Nanoplatforms for cancer theranostics
- PARP inhibition in cancer therapy
- Melanoma and MAPK Pathways
- Machine Learning in Bioinformatics
- Multiple Myeloma Research and Treatments
- Metabolism, Diabetes, and Cancer
- Analytical Chemistry and Sensors
- Luminescence and Fluorescent Materials
- Cutaneous Melanoma Detection and Management
University Medical Center Groningen
2020-2021
University of Groningen
2020-2021
Leiden University
2017
Abstract Testicular cancer (TC) is the most common solid tumour in young men. While cisplatin-based chemotherapy highly effective TC patients, chemoresistance still accounts for 10% of disease-related deaths. Pre-clinical models that faithfully reflect patient tumours are needed to assist target discovery and drug development. Tumour pieces from eight patients were subcutaneously implanted NOD scid gamma (NSG) mice. Three patient-derived xenograft (PDX) TC, including one chemoresistant...
Light upconversion by triplet-triplet annihilation (TTA-UC) in nanoparticles has received considerable attention for bioimaging and light activation of prodrugs. However, the mechanism TTA-UC is inherently sensitive quenching molecular oxygen. A potential oxygen protection strategy coating with a layer oxygen-impermeable material. In this work, we explore if (organo)silica can fulfill protecting role. Three synthesis routes are described preparing water-dispersible (organo)silica-coated...
Abstract The interpretation of high throughput sequencing data is limited by our incomplete functional understanding coding and non-coding transcripts. Reliably predicting the function such transcripts can overcome this limitation. Here we report use a consensus independent component analysis guilt-by-association approach to predict over 23,000 groups comprised 55,000 using publicly available transcriptomic profiles. We show that, compared Principal Component Analysis, Independent...
Abstract Background Patient-derived bulk expression profiles of cancers can provide insight into the transcriptional changes that underlie reprogrammed metabolism in cancer. These represent average pattern all heterogeneous tumor and non-tumor cells present biopsies lesions. Hence, subtle footprints metabolic processes be concealed by other biological experimental artifacts. However, consensus independent component analyses (c-ICA) capture statistically both more pronounced processes....
ABSTRACT Patient-derived expression profiles of cancers can provide insight into transcriptional changes that underlie reprogrammed metabolism in cancer. These represent the average pattern all heterogeneous tumor and non-tumor cells present biopsies lesions. Therefore, subtle footprints metabolic processes be concealed by other biological experimental artifacts. We, therefore, performed consensus Independent Component Analyses (c-ICA) with 34,494 bulk patient-derived biopsies, non-cancer...
Patient-derived bulk expression profiles of cancers can provide insight into transcriptional changes that underlie reprogrammed metabolism in cancer. However, these represent the average pattern all heterogeneous tumor and non-tumor cells present biopsy. Therefore, subtle footprints metabolic processes be concealed by other biological experimental artifacts. We therefore performed consensus Independent Component Analyses (c-ICA) with 34,494 patient-derived biopsies, non-cancer tissues cell...
Abstract Background: Patient-derived bulk expression profiles of cancers can provide insight into transcriptional changes that underlie reprogrammed metabolism in cancer. These represent the average pattern all heterogeneous tumor and non-tumor cells present biopsies lesions. Hence, subtle footprints metabolic processes be concealed by other biological experimental artifacts. However, consensus Independent Component Analyses (c-ICA) capture statistically independent footprints, both more...