GRÜNWALD LAB

A major focus in the lab lies on pancreatic ductal adenocarcinoma (PDAC), which remains one of the most challenging cancers to treat. PDAC is a notoriously heterogeneous cancer type, characterized by a complex tumor microenvironment (TME) which has complicated mechanistic and preclinical studies for decades. This heterogeneity was long thought to be the result of random cell changes representative of global tumor disorganization. Based on our own findings and a growing body of evidence in the literature, we are convinced that heterogeneity in solid tumors is not at all random but a critical foundation of malignant tissue function and adaptive behavior. In fact, solid tumors exhibit a considerable level of functional self-organization that we have barely appreciated. For instance, in PDAC, we find distinct spatial programs that are vastly distinct from each other, yet, highly conserved between different patients and disease sites. Their intratumoral co-existence instigates massive spatial heterogeneity yet, this heterogeneity is a well-definable function of few, fundamental tissue organizational mechanisms. In other words, despite their famous heterogeneity, PDAC tissues facto self-organize into relatively few states of functional relevance. Ongoing efforts in the lab are to understand whether other solid tumor types (lung, kidney, bladder) also utilize such spatial self-organizational programs, what their organ-specific tumor relevant functions are, and how we can diagnostically access this information to aid clinical decision making.

At the earliest stages of tumor initiation, neoplastic cells not only have to acquire the relevant driver mutations but also must successfully interact with an ever-evolving microenvironment. In this interaction, loss of tissue organization is a key permissive event in malignant transformation. Thorough understanding of the tumor ecosystem during transformation, beyond targeted analysis of the malignant epithelium alone, can thus provide major mechanistic insight and open much-needed diagnostic opportunities for accurate and longitudinal risk assessment.

In pursuit of earlier diagnosis and effective secondary prevention strategies as key unmet needs to improve patient outcomes, we are addressing the mechanisms of ecosystem co-evolution in pancreatic cancer initiation.

Tumors grow in people and every person is different. Why do some patients respond to a treatment while others don’t? The study of ultra-large cohorts (> 500.000 individuals) has outlined a considerable impact of confounding factors such as age, ethnic background, lifestyle, environmental exposures, and sex on the outcomes of genetic analyses and therapeutic targeting. Such ‘clinical heterogeneity’ has major implications for the design of mechanistic, experimental studies that are aimed at actual clinical progress. For instance, investigating effects of IL-6 in PDAC, we queried any potential confounders and found that the observed IL-6 driven immune phenotypes were consistent across transcriptional subtypes but sex-specific (https://pubmed.ncbi.nlm.nih.gov/37768107/). Beyond systematically testing such confounders in all our research questions, we are now specifically pursuing sexual dimorphisms in major pathways driving intratumoral immune heterogeneity. Furthermore, we are leveraging detailed epidemiological data to fully understand the impact of risk factors on the tumor biology of the resultant tumors.

We have assembled a solid collection of patient-derived tumor models as well as stromal cell cultures in our lab and are continuously growing this living biobank together with our collaborators. These three-dimensional organoid models allow us to mimic some of the complexities of tumors as well as different tumor subtypes in vitro and offer a unique platform for studying disease progression and therapeutic responses. We have previously established various Cancer Associated Fibroblast (CAFs) lines from primary patient tumors that recapitulate histomorphological phenotypes of their different originating tissue regions. In heterotypic cultures of tumor organoids, fibroblasts and immune cells, we model the complex, spatial interplay between tumor and TME cells in a controlled manner. Our new Cytation5 Live Cell Imager allows us to record longitudinal parallel morphometric analyses, drug/interference assays and cell type-specific imaging in high-throughput formats. We are developing these heterogeneity-informed platforms to learn about mechanisms of how the tumor-TME interaction shapes malignant behavior but also to understand differences in drug response in a patient specific manner.