Research focus

Our laboratory represents a technology-driven translational research group. We aspire to tackle important questions in oncology by translating multi-omics data into clinically applicable knowledge. The objectives of our research are to leverage the profiling of patient samples to improve cancer prevention, diagnosis, prognosis, and therapy. Our investigations leverage cutting-edge single-cell and spatial technologies, along with advanced bioinformatics, to seamlessly integrate omics datasets with clinical and fundamental biological information. This approach generates novel insights and useful biomarkers for the field of oncology.

Strategically situated within the University Hospital (UZ) Campus in Leuven, Belgium, our laboratory benefits from longstanding collaborations with esteemed oncologists at UZ Leuven. These partnerships position us at the forefront of translational cancer research in Leuven, facilitating the seamless translation of research findings into clinical practice.

Our work is currently focused on three main research topics in the field of cancer biology and immunlogy:

• Single-cell multi-omics profiling of the tumor microenvironment (TME) during cancer immunotherapy

Cancer immunotherapy, particularly ICB, has transformed cancer treatment, but its effectiveness is limited, with durable responses seen in only a minority of patients. Collaborating with UZ Leuven oncologists, we utilize advanced single-cell technologies to profile tumor biopsies from patients enrolled in clinical trials. This enables us to generate rich, fine-grained data of the TME during immunotherapy. Our goal is to achieve unparalleled resolution in monitoring therapeutic response, shedding light on why certain patients or cancer types exhibit resistance. Through this, we aim to identify robust predictive biomarkers of immune checkpoint blockade (ICB) response, mitigating unnecessary toxicity in non-responders. Furthermore, we anticipate that these insights will unveil novel treatment combinations capable of eliciting durable therapeutic responses in refractory patients.

We found surprising TME heterogeneity across different cancers. Analyzing 233,591 single cells from lung, colorectal, ovary, and breast cancer patients, we created a pan-cancer blueprint of stromal cell heterogeneity (Qian et al., Cell Research 2021). This revealed 68 stromal cell populations, 46 shared between cancer types and 22 unique. We characterized each population, highlighting marker genes, transcription factors, metabolic activities, and tissue-specific expression differences. Applying this blueprint to melanoma tumors undergoing ICB, we identified a predictive naïve CD4+ T-cell phenotype for therapy response.

Our recent research, including two window-of-opportunity studies, analyzed pre- and on-treatment biopsies to uncover how TME heterogeneity influences ICB response. In 54 triple-negative breast cancer (TNBC) patients from the BioKey study, we observed how T-cells after 1 dose of anti-PD1 markedly proliferated and expanded in ~30% of patients (Bassez et al., Nat Med 2021). Gene expression analysis allowed us to define two contrasting immune contexts that were either positively or negatively associated with T-cell expansion upon ICB. In head and neck squamous cell carcinoma (HNSCC), we explored the contribution of anti-CTLA4 therapy in combination with anti-PD-L1 monotherapy (Franken et al., Immunity 2024). Interestingly, while anti-PD-L1 alone induced CD8+ T-cell expansion, combining it with anti-CTLA4 allowed CD4+ T-cells to also expand towards activated Thelper-1 (TH1) cells. Spatial analysis confirmed co-localization of expanding CD4+ and CD8+ T-cells surrounded by dendritic cells expressing T-cell homing factors. T-cell receptor tracing suggested that anti-CTLA4 triggered trafficking of CD4+ naïve/central memory (TN/CM) cells from tumor-draining lymph nodes to activated TH1-cells in tumors.

• Single-cell characterization of the bronchoalveolar lavage immune cell composition

Our lab specializes in single-cell sequencing of bronchoalveolar lavage fluid to address various clinical questions.

In a recent study, we investigated the pathophysiology of immune checkpoint inhibitor (ICI) related pneumonitis. By conducting single-cell RNA and T-cell receptor sequencing on bronchoalveolar lavage fluid from patients with ICI-related pneumonitis we identified an accumulation of pathogenic T-helper 17.1 cells. This sheds light on potential therapeutic targets, such as repurposing anti-IL-23.

Additionally, we studied COVID-19, encompassing research on critical versus mild cases (Wauters, Van Mol et al., Cell Research 2021), as well as COVID-19-associated pulmonary aspergillosis (CAPA), a severe superinfection with the fungus Aspergillus affecting critically ill COVID-19 patients (Feys et al., The Lancet Microbe 2024). Through our investigations, we endeavor to provide crucial insights into the mechanisms underlying these conditions, paving the way for improved diagnostic and therapeutic strategies.

• The use of plasma cell-free DNA (cfDNA) as a diagnostic test to characterize and monitor tumors non-invasively 

Plasma cell-free DNA (cfDNA) offers a non-invasive means to characterize and monitor tumors, providing real-time insights into tumor dynamics. While cfDNA in healthy individuals primarily originates from leukocytes, cancer patients have a significant portion of tumor-derived DNA (ctDNA) circulating in their blood. Detecting ctDNA is crucial, especially when tumor re-biopsy isn't feasible, as the molecular profile of the tumor may have changed over time. Leveraging advances from non-invasive prenatal testing (NIPT), cfDNA-based tests are emerging as potential cancer screening tools.

Our work has shown the efficacy of plasma-derived cfDNA low-coverage whole-genome sequencing (LC-WGS) in ovarian cancer, using chromosomal instability as a biomarker (Vanderstichele et al., Clin Cancer Res. 2017). However, this method is limited to tumors with a certain degree of chromosomal instability, missing those without it. To address this, we've explored characterizing the tissue-of-origin of ctDNA by analyzing nucleosome position patterns in cfDNA, revealing differences between cancer patients and healthy controls.

Our approach provides two independent diagnostic readouts from a single test. Additionally, we've developed a protocol for targeted bisulfite sequencing to assess DNA methylation status in low concentrations of fragmented cfDNA. This method shows promise as a biomarker for detecting tumor DNA in plasma from various cancers.

Preliminary data suggests that combining metrics like chromosomal instability, nucleosome footprinting, and DNA methylation improves ctDNA detection, especially in ovarian cancer. We're optimizing these methods for broader application across different cancer types, considering that ctDNA levels vary depending on cancer type.

• Tumor antigen discovery for personalized immunotherapy

While T-cell expansion indicates a response to ICB, predicting which T-cells will expand based on their TCR sequences remains a challenge. Identifying these T-cells and the corresponding tumor antigens could explain why some patients do not respond to ICB. Moreover, it could lead to the discovery of potent antitumor TCRs or specific tumor antigens for engineered TCR-based therapies or personalized vaccination studies.

Our approach involves analyzing the tumor antigen landscape of treatment-naïve and on-treatment tumor biopsies from cancer patients who have undergone ICB therapy. Through single-cell and spatial RNA and TCR profiling, we aim to identify T-cells likely to be tumor-reactive based on their spatial localization, expansion status, and gene expression. We will then use our unique TWISTAR platform to characterize these potential tumor antigens, reconstructing the landscape of relevant tumor antigens during ICB response in cancer patients.