Title Promoter Affiliations Abstract "Exploring the heterogeneity of rare ovarian cancerDefining (epi)genomic transition from precursor lesion to invasive rare ovarian cancer" "Els Van Nieuwenhuysen, Ignace Vergote" "Laboratory of Translational Genetics (VIB-KU Leuven), Translational Cell & Tissue Research, Gynaecological Oncology" "My research project continues on the work of my co-promotor, Dr. Els Van Nieuwenhuysen. She has already characterized rare ovarian tumors on DNA-level. Little is known today on these types of tumors. The approach is to deepdive into these groups of tumors (of which the bio-bank has already been established during my co-promoter's previous research) on RNA-level, methylation and histone modification. Furthermore, we try to look further into the rare tumor workgroup of ENGOT (European Network for Gynaecological Oncological Trial) in order to answer clinical questions about and treatment modalities for these types of tumors." "Searching for new leads in the diagnosis of ovarian cancer" "An Coosemans" "Laboratory for Tumor Immunology and Immunotherapy, Gynaecological Oncology, Woman and Child" "Ovarian cancer is a silent killer, metastasizing troughout the abdomen before causing symptoms. A total of 80% of patients will die of the disease. Survival can be ameliorated by screening, improving diagnosis or improving treatment. research so far has invested in optimizing treatment resulting in an increase in overall survival from 18 to 44 months over the last 20 years. Screening has been proven no to be beneficial. optimizing the diagnosis has always been the lowes priority in literature, which is of course wrong because good treatment starts with a correct diagnosis. The IOTA (International Ovarian Tumor Analysis) terms, definitions and models, developed by an international consortium coordinated by Dirk Temmerman (UZ Leuven), have tremendously increased the diagnosis of ovarian pathology, discriminating benign from borderline and malignant ovarian cyst by the use of ultrasound variables. However, the models are not impeccable. A substanial number of masses are still hard to calssify.In this research project, called TRANS-IOTA (translational IOTA) we want to search for new biomarkers in ovarian cancer patients that in the end then can serve as new diagnostic tool on itself or can be integrated in the IOTA models, improving their accuracy. As biomarkers, we will focus on three pillars: proteins (thusfar the only toroughly studied liquid biopsy in ovarian cancer), ctDNA (cellfree DNA resulting from apoptotic cells, a fastly emerging approach in the field of cancer, though for ovarian cancer only limited studies) and the ratios of immune cells (no studies as a possible liquid biopsy in ovarian cancer). The teams involved in this TRANS-IOTA research have substantial knowledge in these diverse fields, which makes this a unique approach of studying three types of biomarkers at the same time possible.An amelioration of the diagnosis will lead to a more correct and earlier diagnosis. On the one hand, this will result (if the cyst turns out to be malignant) in a correct oncologic treatment from the beginning on and in the diagnosis at an earlier stage, leading to an increase in patient survival. On the other hand, it will result (if the cyst turns out to be benign) in a more conservative follow up and therefore reduced morbidity of unnecessary surgery." "Efficacy of abemaciclib and letrozole in estrogen receptor-positive rare ovarian cancer and unravelling mechanisms of response and resistance" "Els Van Nieuwenhuysen" "Gynaecological Oncology" "Ovarian cancer (OC) is the 5th leading cause of cancer death in women, accounting for more deaths than any other cancer of the female reproductive system. There are several different subtypes of ovarian carcinoma, which indicates its heterogeneous character. Epithelial ovarian cancer represents 90% of the ovarian tumors, of which high-grade serous ovarian cancer (HGSOC) is the most common subtype. Less common types of epithelial ovarian cancer include low-grade serous ovarian tumors (LGSOC), endometrioid (EMOC), mucinous (MucOC) and clear cell carcinoma (OCCC). The other 10% are non-epithelial ovarian cancers including germ cell tumors and sex cord-stromal tumors. Until recently, treatment of rare subtypes of OC was mainly based on the treatment of HGSOC, as no distinction was made between different subtypes in clinical trials. This leaded to a uniform treatment strategy. Up till now, clinical trials in rare OC are extremely scarce. This PhD project will focus on rare subtypes of OC, namely low-grade serous/endometrioid ovarian cancers (LGSOC/LGEM) and adult granulosa cell tumors (aGCT). Both LGSOC and LGEM have good prognosis in early disease, but treating advanced and recurrent disease is a challenge given their resistance to chemotherapy. They are typically diagnosed at a younger age, have an indolent character and follow a protracted clinical course, compared with HGSOC. The adult-type granulosa cell tumors are in general diagnosed at an early stage with an indolent growth pattern and also have a relatively good prognosis. Despite their good prognosis, recurrences may occur many years after the initial diagnosis. In case of these late recurrences, the majority of patients will succumb of their disease. This emphasizes the inefficacy of current treatment and the need for more effective therapies as treatment options are limited in these types of rare OC. Since the estrogen receptor (ER) is highly expressed in these types of tumors, they are considered to be potentially responsive to hormonal therapies. Although several reports suggest that endocrine therapy may be effective, there is no consensus on the therapeutic approach nor on the criteria needed to define which population of patients would benefit from a specific anti-ER treatment. The results of large randomized phase 3 trials of the combination of an aromatase inhibitor combined with a CDK4/6 inhibitor in hormone sensitive, HER2 negative breast cancer can form the basis for a trial with this drug combination in hormone sensitive rare OC. Letrozole is an anti-ER drug (aromatase inhibitor) and abemaciclib a cell cycle inhibitor (cyclin kinase 4/6 inhibitor) both characterized by a low toxicity and high tolerability profile. Since LGSOC/LGEM and aGCT carry a high ER expression, we hypothesize that the combination of letrozole and abemaciclib might represent a valuable alternative therapeutic strategy for these patients. Therefore, we will set up a clinical trial to define the efficacy of letrozole and abemaciclib in ER-positive LGSOC/LGEM and aGCT. In addition, we aim to better define which patients to select for endocrine therapy and unravel the mechanisms of endocrine resistance in these tumors. Therefore, we will collect blood and tumor biopsies for translational research aimed at identifying biomarkers of resistance and to characterize the adaptive genetic mechanisms of response to endocrine treatment." "Tumor heterogeneity in relapsed or metastatic breast, ovarian and colorectal cancer" "Diether Lambrechts" "Laboratory of Translational Genetics (VIB-KU Leuven)" "Cancer is a genetic disease. Genetic changes or mutations that alter the function of genes, can provide a cell with a selective growth advantage compared to its surrounding cells. Next-generation sequencing is revolutionizing the characterization of these (epi)genetic alterations and is gaining influence on therapy choice and prediction of prognosis. This manuscript describes the results and interpretations derived of genetic characterizations on three different cancer cohorts:A first part investigates genetic heterogeneity after first-line chemotherapy in high-grade serous ovarian cancer. Most high-grade serous ovarian cancer patients benefit from platinum therapy, yet progressively develop resistance through subsequent relapses. The aim of this study was to investigate which aberrations are involved in acquired platinum resistance byprofiling 31 high-grade serous ovarian tumors before and after first-line platinum therapy. Subsequently, a pair-wise analysis was performed to map the changes occurring during disease progression and to identify possible mechanisms of therapy resistance. Already after a single line of platinum, there is huge variability between primary and recurrent tumors, advocating that in high-grade serous ovarian cancerbiopsies need to be collected at relapse to tailor treatment options to the underlying genetic profile. Nevertheless, all primary platinum-sensitive high-grade serous ovarian tumorsremained homologous recombination-deficient, irrespective of whether they became resistant to second-line platinum, further suggesting these tumors qualify for second-line PARP inhibitor treatment. Finally, chromosomal instability contributes to acquired resistance after a single line of platinum therapy.On a second cohort, phylogenetic analysis of metastatic progression in breast cancer using somatic mutations and copy number alterations was performed.Distant metastatic disease is the main cause of breast cancer mortality. The aim of this study was to investigate the contribution of tumor heterogeneity to metastasis by profiling and comparing the primary tumor site with multiple matched metastases collected during autopsy of 10 breast cancer patients. Combining the allelic frequencies of somatic mutations with copy number information allowed to infer tumor clonality and reconstruct the phylogenetic evolution. We found that the major route of metastatic progression seems to be a cascading dissemination starting from the primary tumor and then from metastasis to metastasis but we also observed multiple seeding events and horizontal re-seeding in de novo metastatic patients.A third cohort was characterized to determine the genomic landscape of metastatic colorectal cancer treated with bevacizumab. Since its approval, bevacizumab (Avastin® - Roche) has been widely administered to metastatic colorectal cancer patients (both those with or without K-ras/Braf mutations) as a first line treatment in combination with chemotherapy. However, several clinical investigations over the past years showed clear evidence for a very heterogeneous response amongst patients. The aim of this study was to profile 200 patients, treated with bevacizumab, in order to determine the genomic landscape and to investigate possible predictive biomarkers that help to select patients with the greatest treatment benefit. We identified 3 copy number subtypes differing in copy number burden due to copy number instability. Tumors belonging to intermediate-to-high instability subtypes (CNA subtypes 2 and 3) had improved outcome following chemotherapy and bevacizumab versuschemotherapy alone compared to CNA subtype 1 tumors with a very low copy number burden. These copy number subtypes overlapped with the consensus molecular subtypes (CMS) in colorectal cancer and experiments with CMS2 and CMS4 xenografts, clustered in CNA subtypes 2 and 3 showed an increase response to BVZ." "Taking ovarian cancer diagnosis to the next level: differential diagnosis of malignancy type, and added value of advanced data sources such as MRI, proteomics, circulating tumour DNA and circulating tumour cells" "Ben Van Calster" "Woman and Child" "Excellent tools to predict whether a detected ovarian tumour is benign or malignant prior to surgery are pivotal for several reasons: (1) currently a minority of ovarian cancers is treated by experienced gynaecological oncologists, (2) the value of screening for ovarian cancer has not been established, and (3) ovarian cancer is largely asymptomatic in its early stages such that accurate diagnosis is paramount to optimize survival. The International Ovarian Tumour Analysis (IOTA) consortium has developed tools based on clinical and ultrasound information. However, it is time to take ovarian cancer diagnosis to the next level by fine-tuning existing tools on several grounds. Firstly, differential diagnosis of different classes of malignancy is clinically important for selecting the optimal treatment. Hence this project will focus on tools that predict whether a tumour is benign, borderline malignant, stage I cancer, advanced stage cancer, or secondary metastatic cancer. Secondly, this project will investigate the value of magnetic resonance imaging (MRI) as a second stage test, the added value of proteomics to differential diagnosis, and the role of circulating tumour DNA and circulating tumour cells for diagnosis. The ultimate potential of DNA and cell information may be to establish a procedure for a golden standard diagnosis for malignancy or malignancy type without the need for surgery." "beurs EVDS Sofie Van Dorpe: Extracellular vesicles as blood-based biomarker for early stage ovarian cancer" "Hannelore Denys" "Department of Internal Medicine and Pediatrics" "Ovarian cancer is a silent killer. Early stage ovarian cancer is difficult to diagnose because most symptoms are subtle and thus of little use in diagnosis. As a result, the diagnosis is rarely made until the cancer spreads and advances to later stages. If diagnosed and treated in an early stage, ovarian cancer is often curable. However, when diagnosed in a late clinical stage, ovarian cancer is associated with a 5-year survival of only 35%. Early detection is key to reducing ovarian cancer-associated deaths.  Tumor-derived extracellular vesicles (EV), nanometer-sized membrane vesicles which contain proteins, lipids, and nucleic acids, enter the circulation and as such their quantification and characterization may enable the diagnosis of cancer. The molecular content of EV is a fingerprint of the releasing cells and they are enriched for highly selected biomarkers which otherwise would consitute only a very small proportion of the total molecular blood content. The feasibility of blood-based EV protein biomarkers to diagnose early lesions of cancer is recently demonstrated for pancreatic cancer." "IOTA-AI: AI-assisted automated detection of ovarian cancer on ultrasound imaging" "Wouter Froyman" "Woman and Child, Dynamical Systems, Signal Processing and Data Analytics (STADIUS)" "Ovarian cancer is the seventh most common cancer in women and constitutes the most lethal gynecological malignancy. Timely diagnosis and appropriate referral to gynecological oncology expert centers is pivotal to improve patient outcomes. Ultrasonography (US) is a readily available, cheap and harmless technique, and is widely accepted as first-line imaging modality for assessment of ovarian masses. Currently, the ADNEX model is the best available ultrasound-based mathematical model to differentiate between benign and several types of malignant ovarian tumors. However, it relies on the ability of the US operator to reliably (manually) locate, delineate and measure the tumor area and its associated features. Previously, we developed automated feature detection methods in collaboration with ESAT-STADIUS and General Electric, where we demonstrated the effectiveness of a deep convolutional neural network (DCNN) approach. The objective of this C3 project is to further develop and validate a fully automated classification model for triaging patients with ovarian masses. Implementation of such a model in centers where specialized ultrasound operators are not available, would facilitate the early detection of ovarian cancer and positively impact patients’ survival." "Deciphering the dendritic cell compartment in ovarian cancer to assess their potential as tumor vaccines." "Damya Laoui" "Department of Bio-engineering Sciences" "Advanced stage ovarian cancer (OC) patients only have an overall 5- year survival of 20%. While targeted therapies such as PARP inhibitors have improved progression free survival, immunotherapy has so far not resulted in clear patient benefit. Importantly, the role of tumor-dendritic cells (DCs) as a key player in mounting an adaptive immune response has not been investigated yet in OC. Indeed, our lab has uncovered that vaccination with tumor-cDCs can elicit a therapeutically relevant immune response. Therefore, in this project, we will evaluate the cDC heterogeneity in OC and the potential to use tumor-cDCs as vaccine to treat OC. More specifically, we will identify and characterize different cDC populations at the transcriptomic, proteomic and functional level in both a murine OC model and patient samples using state-of-the-art technologies. As in OC, BRCA1/2 mutations are present in 20% of the patients and determine patient outcome, their role in defining cDC function will also be studied. On top, we will investigate the impact of chemotherapy and PARP inhibitors on tumor-cDC function and assess the role of immunosuppressive cells thereon. As last, in the murine OC model, the effectiveness of the different cDC populations as OC vaccine will be assessed. The results of this project will provide new insights into the role of cDCs in OC and will propose a novel therapeutic approach for OC that overcomes the currently witnessed barriers to effective therapeutic responses." "Development of tumor-derived dendritic cell therapies to prevent ovarian cancer metastasis" "An Coosemans" "Laboratory for Tumor Immunology and Immunotherapy" "Of the patients diagnosed with high-grade sero-tubal ovarian cancer (HGSTOC), 80% ultimately relapse and die of the cancer. Immunotherapy has so far not resulted in clear patient benefit, likely due to the high infiltration of immunosupressive cells. Our lab has recently shown that cell therapy using tumor-derived conventional dendritic cells (cDCs) is able to overcome this obstacle and elicit an anti-tumor response in a metastatic lung cancer model. Therefore, in this project, I will evaluate if tumor-derived cDC-based therapies could serve as novel treatment strategy for HGSTOC. First, we will determine the impact of DC empowering therapies alone or in combination with standard-of-care chemotherapy on cDCs in the primary tumor and ascitic fluid of the intrabursally injected ID8-fLuc ovarian cancer model. Consequently, using the optimized DC enhancing strategy, the efficacy of tumor-derived cDC therapy using different cDC subsets will be evaluated. A combination of CITE-seq analysis and cell depletion strategies will then allow us to determine the mode of action of the therapy and evaluate the cellular interactome of the effector cells during treatment. Combining tumor-derived cDC therapy with therapies targeting cellular interactions detrimental for effector cell function will then allow to further improve therapy response. Overall, this project will therefore uncover novel treatment strategies for HGSTOC to enhance patient survival." "The natural K, Fe, and Cu isotopic response to Pt-based chemotherapeutic drug resistance in ovarian cancer" "Frank Vanhaecke" "Department of Chemistry" "Cancer is the second leading cause of death globally and in the EU, and was responsible for an estimated one in six deaths in 2018. Early diagnosis plays an important role in determining cancer treatment outcomes, but the diagnosis of ovarian cancer poses significant challenges; the routine screening of asymptomatic average-risk women is not recommended by any professional society. Chemotherapy using Pt-based compounds (e.g. carboplatin, cisplatin) is a standard treatment, but tumours that are initially responsive may develop chemoresistance, resulting in treatment failure. The ability to predict patient response towards postoperative treatments would allow for ineffective treatments and harmful side effects to be avoided and alternative treatments to be commenced at earlier stages. Several mechanisms underlying tumour cell resistance have been identified so far, including the altered expression of ion channels (Na, Mg, K, and Ca) and Fe-, Cu-, and Zn-binding proteins, but these remain poorly understood and it is unclear whether they can be exploited as markers of resistance. To that end, I will apply high-precision isotopic analysis by multicollector-inductively coupled plasma-mass spectrometry to Fe, K, and Cu to understand processes and determine whether changes in the natural abundances of these isotopes are associated with the development of resistance to Pt-based chemotherapeutic drugs in high-grade serous ovarian cancer (HGSOC), the deadliest gynaecological cancer, which accounts for ~70% of ovarian malignancies. Deviations in natural isotopic abundances signal biochemical changes (affecting the extent of isotopic fractionation accompanying some biochemical processes) occurring as a result of a disease in a systematic and reliable way. Through ovarian cancer cell line, tumour spheroid, and HGSOC patient plasma experiments, I aim to develop a revolutionary, minimallyinvasive prognostic marker of Pt-based chemotherapeutic drug resistance."