Projects
1H-NMR and LCMS-based metabolomics on human plasma and peripheral blood mononuclear cells (PBMC) for early detection of colorectal cancer. University of Antwerp
Fluor-PSMA PET/CT for the early detection of recurrent prostate cancer after curative treatment Ghent University
The innovative value and objective of this study is to demonstrate that 18F-PSMA-11 PET / CT provides at least a non-inferior (or similar) diagnostic method in a prostate cancer patient population (with biochemical recurrence after local therapy with curative objective compared to 68Ga). -PSMA-11 PET / CT A second important objective is to investigate in a subpopulation whether 18F-PSMA-11 cannot be superior in the detection of ...
EV-TRACE: Extracellular Vesicle Tracking using surface proteins and Resonance Assays to detect breast Cancer in Early stage Ghent University
Extracellular Vesicle Tracking using surface proteins and Resonance Assays to detect breast Cancer in Early stage (EV-TRACE) A major challenge in cancer is to detect the disease early on and it locate organ of origin while stratifying patients to receive appropriate treatment to increase survival and quality of life. Most cancers that are detected early can only be cured by surgery; so without any systemic therapy. New, inexpensive and ...
Extracellular Vesicle Tracking using surface proteins and Resonance Assays to detect breast Cancer in Early stage (EV-TRACE) KU Leuven
Problem
Early detection reduces cancer-related deaths because time is a matter of life and death for a cancer victim. Diagnostic screening tests must be sensitive, specific, inexpensive, non-invasive and provide sufficient lead-time. Single markers typically lack sensitivity and specificity. Extracellular Vesicles (EV) in liquid biopsies hold promise in the non-invasive detection of cancer because their molecular content (proteins, ...
Targeting the leukemic cancer stam cell in early T-cell precursor Acute Lymphoblastic Leukemia (ETP-ALL) Ghent University
The abstract for "Targeting the leukemic cancer stam cell in early T-cell precursor Acute Lymphoblastic Leukemia (ETP-ALL) " is missing. Please contact the promotor for more information.
Exosomal miRNAs as a biomarker for early targeted therapy response in advanced triple negative breast cancer Ghent University
Triple negative breast cancer (TNBC) is a heterogeneous breast cancer subtype with limited
treatment options and poor prognosis following progression after neoadjuvant chemotherapy.
Transcriptional miRNA signatures of activation of MEK and PI3K pathways are highly prevalent in
TNBC and targeted therapies (TT) to modulate both pathways are in clinical trial. The current
challenge in clinical practice is learning to use the ...
cfDNA genome-wide methylation profiling for pre-symptomatic cancer detection and typing KU Leuven
Early diagnosis and promptness of intervention are crucial in cancer management. The current project aims to develop a reliable, sensitive, economic and non-invasive cancer monitoring and screening tool. For this purpose, liquid biopsy, which consists of a simple and minimally invasive blood sample, is appropriate. The plasma contains circulating free floating DNA (cfDNA), which consists of short DNA fragments derived from cell death. ...
Targeted detection of nucleic acid mutations for improved lung cancer diagnostics in liquid biopsies KU Leuven
In this project we aimed to improve the current molecular diagnostics approaches for lung cancer- related mutation detection in liquid biopsies. Liquid biopsy refers to sampling and analysis of biological fluids—typically blood—and has potential for screening, diagnosis, predicting and monitoring of treatment response. However, current assays based on circulating tumor DNA (DNA released by tumor cells in the blood) suffer from sensitivity ...
Deep-learning data fusion for patient screening and clustering from genomics liquid biopsies and its application for presymptomatic cancer detection and stratified medicine KU Leuven
My PhD research relates to the design of an Artificial Intelligence (AI) framework for learning complex relations between the DNA profile of a liquid biopsy (i.e., DNA extracted from a blood sample) and the diagnosis, prognosis, or relapse of a tumor. This AI framework will be able to continuously integrate information from DNA profiles from tens of thousands of liquid biopsies. In particular, it will allow building models for the early ...