DR-470 RADAR: Repurposing and Analysis of Drugable targets in Atypical Rare cancers
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DR-470 RADAR: Repurposing and Analysis of Drugable targets in Atypical Rare cancers
The RADAR study aims to improve outcomes for patients with rare cancers, which affect over 24,000 people annually in the …
DR-310 Clinical actionability for and heritable factors involved in glioblastoma
This project aims to use whole genome sequencing data to 1) describe the driver landscape of glioblastoma, 2) determine potential …
DR-405 Development of a Multi-Omic Test for Cancer of Unknown Primary
Cancer of unknown primary (CUP) is defined as a metastatic cancer where clinical investigations fail to identify the primary tissue …
DR-409 NoCoSMiCC: Non-coding somatic mutations in colorectal cancer
Colorectal cancer (CRC) is a significant malignancy and represents the third most common cancer and second most common cause of …
DR-428 Transcriptomic and Genome-wide machine learning model for predicting immunotherapy benefit in metastatic solid tumors
Immunotherapy has radically changed the treatment landscape across solid tumors. Regardless, biomarkers able to predict immunotherapy benefit are limited, and …
DR-436 Identification of metastatic drivers in breast cancer
Metastasis represents a significant clinical challenge in hormone receptor-positive (HR+) breast cancer. To investigate the genetic drivers of relapse and …
DR-439 Optimization of the Diagnostic and Therapeutic Management of Cancers of Unknown Primary (CUP) Using AI: Integration of Transcriptomic Data to Predict Tumor Origin
Identifying the original tissue of a metastatic cancer is key to choosing the best treatment. Cancers of Unknown Primary (CUP) …
DR-441 A transcriptomic-driven machine learning model to predict the efficacy of CDK4/6-inhibitors in metastatic hormone-receptors positive breast cancer
In metastatic hormone receptor-positive (HR+/HER2-) breast cancer (mBC), cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6-i) in combination with endocrine therapy …
DR-466 Verification of the presence of chimeric transfer RNAs in the cytosol of cancer patients
We have demonstrated that genes coding for transfer RNAs accumulate large amounts of somatic mutations in human tumors. Some of …
DR-463 HYDRA: Integrative Molecular Characterization of Pancreatic and Esophagogastric Cancer for Personalized Treatment Optimization
Esophagogastric and pancreatic cancers are among the deadliest cancers, characterized by poor prognoses and limited treatment efficacy. Despite intensive research, …
DR-457 NRF2 pathway activation in metastatic urothelial carcinoma
Patients with advanced bladder cancer have incredibly poor outcomes. Over half of patients die within 5 years, many of them …
DR-452 AI-Driven Tumor-Agnostic MSI-H Prediction and Immunotherapy Response Modeling
Microsatellite instability (MSI) is a key biomarker of sensitivity to immune checkpoint inhibitors (ICIs) across tumour types. Despite its clinical …
We willen het maximum aan informatie uit de tumor van de patiënt halen. Deze DNA-test is daarvoor het best beschikbare instrument. Er is maar één keer weefsel, een biopt, met voldoende tumorcellen nodig. Omdat het hele genoom wordt onderzocht, ook de gebieden in het DNA waarvan we nu nog niet weten of de gevonden afwijkingen belangrijk zijn, is deze DNA-test tumortype onafhankelijk en toekomstbestendig. Deze eigenschappen zijn de twee belangrijkste eigenschappen van WGS.