Het verkennen van de heterogeniteit van zeldzame eierstokkanker

Knowledge about molecular mechanisms driving tumorigenesis in non epithelial ovarian cancer NEOC and rare epithelial OC remains limited. Our research group has previously undertaken comprehensive whole-genome sequencing to characterise the genomic landscape of these heterogeneous malignancies10. However, the field of rare ovarian cancer remains largely unexplored, highlighting a critical need for further in-depth investigation. To address this gap, we seek to deepen our understanding of these rare ovarian cancers through a multi-omics approach, incorporating bulk RNA sequencing, DNA methylation profiling, and single-cell RNA sequencing (scRNA-seq). Expanding research efforts in these rare subtypes holds the potential to yield significant insights into their distinct biological features. Our objective is to investigate this diverse group of rare ovarian cancers from multiple perspectives, aiming to construct a comprehensive and detailed molecular profile. This tailored strategy is imperative for elucidating the unique characteristics of each ovarian cancer subtype, ultimately facilitating the development of more precise and effective therapeutic interventions. Single cell map on rare ovarian cancer Unravelling the immune landscape of non-epithelial ovarian cancer. Ovarian carcinomas exhibit substantial inter- and intratumorally heterogeneity, forming intricate ecosystems composed of diverse cell types, including immune cells, mesenchymal stromal cells, fibroblasts, and extracellular matrix components. Collectively, these cellular components constitute the tumour microenvironment (TME), which plays a pivotal role in tumour initiation, proliferation, and therapeutic response in cancer. Various methodologies are employed to investigate the genetic complexity of the TME. The conventional approach, bulk RNA sequencing, provides an averaged gene expression profile across a population of cells within a sample. However, this method may obscure critical information, such as structural diversity and functional heterogeneity. To overcome these limitations, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool. In contrast to bulk RNA-seq, scRNA-seq enables gene expression analysis at the resolution of individual cells, uncovering novel cellular features that may be masked by conventional sequencing techniques. This approach facilitates the identification of potential therapeutic targets through the characterisation of distinct cellular subpopulations, offering opportunities for personalised therapeutic strategies and insights into mechanisms of treatment resistance. To enhance our understanding of the landscape of rare ovarian cancers, we constructed a comprehensive blueprint of immune and fibroblast heterogeneity in non-epithelial ovarian malignancies. Multi-Omics analysis of Endometriosis-Related Ovarian Tumours and Precursors Women with endometriosis appear to have a more than threefold risk for endometriosis-related ovarian cancer (EROC)42. Even though, the exact mechanism of conversion from endometriosis to invasive cancer has not been clarified just yet, mutation in ARID1A gene seems to play a key role. This mutation is the most frequent alternation in OCCC (40-67%) and is also noted in endometriosis. Given that ARID1A-mutated OCCC are typically characterised by a lack of genomic instability, this suggests a critical role of epigenetic mechanisms in this disease. Despite the high prevalence of ARID1A mutation, a well-defined diagnostic approach for identifying patients at an increased risk of developing EROC has not yet been established. In this thesis we address the following questions: What is the (epi)genetic relationship between endometriosis and invasive EROC? How do they relate and what are the mechanisms of transition? To address these questions, we need to extent our knowledge about the molecular genetic profiles of the rare ovarian cancers through next-generation sequencing. Our intention is to further reveal the transcriptome and epigenome of EROC to integrate DNA, RNA, and methylation alterations. Identifying transformation markers can help us to recognise subsets of women with increased risk of ovarian cancer and a better insight into the tumorigenesis. Revised Radiological Criteria: A Retrospective Analysis of MRI Imaging in Low-Grade Serous Ovarian Cancer Low-grade serous ovarian cancers (LGSOC) constitute approximately 5% of all serous ovarian cancers. LGSOC typically follows a more indolent course, leading to an extended overall survival when compared to their high-grade counterparts. Despite this, they exhibit heightened resistance to chemotherapy, with a response rate of 4-23%109. Consequently, the prognosis significantly benefits from optimal surgery. At UZ Leuven, operability is defined using whole-body diffuse-weighted (WB-DW) MRI imaging, which provides a comprehensive visualization of the (extra-)peritoneal spread. While MRI is effective in detecting surgically critical areas, it tends to underestimate the extent of disease spread. Consequently, our objective is to conduct a retrospective analysis of operability predictions in LGSOC patients who underwent preoperative WB-DW MRI in our hospital. The focus is on correlating preoperative radiological features with intra-operative findings and pathology reports. More specifically, we try to find correlation between radiological features versus response to first line treatment (PFS and OS) and between genetic features and outcome data.