Rare cancers account for 1 in 4 of all diagnoses. Yet, while some are very well studied and characterized, many are not, to the point of lacking an established standard of care. Tumor organoids are a handy tool that allow us to investigate the biology of rare tumors, and help identifying susceptibilities that can be exploited therapeutically. We strive to develop strategies to model the good (benign tumors), the bad (slow growing, indolent cancers) and the ugly (aggressive, rapidly metastasizing cancers) of rare tumors.
Sarcomas are a family of over 100 rare cancers arising from bone, muscle and connective tissues. We develop organoid models of sarcoma to investigate the biology and evolution of drug resistance
cNFs are benign tumors that affect Neurofibromatosis type 1 (NF1) syndrome patients.While they never metastasize, cNFs can number in the thousands and significantly affect the quality of life of NF1 patients, with no existing systemic therapy. We develop cNF organoid models to understand genotype-phenotype correlations, heterogeneity and drug responses.
Paragangliomas and pheochromocytomas (PPGL) are rare neuroendocrine tumors, diagnosed in only a handful of individuals out of every million people. There is a lack of models, and no clear-cut way to determine who will progress to metastatic disease. We develop PPGL patient-derived organoids to investigate how unique genomic drivers contribute to drug responses, and identify biomarkers of progression.
Tumor organoids can reproduce a patient response to therapy ex vivo. We have pioneered methods to screen patient-derived organoids with high throughput (mini-ring platform) and identify effective therapies within a week from surgery. We continue to expand our screening platform to include different treatment modalities (chemoradiation, immuno-oncology drugs) and cell types (immune cells, vasculature, liver cells). We strive to improve our ability to model physiological responses to anti-cancer drugs and deploy personalized therapies for cancer leveraging tumor organoids.
We developed a high throughput screening platform that takes advantage of a unique geometry (“mini-rings”) to quickly and robustly establish tumor organoids in a format compatible with liquid handlers and automation. Drug sensitivity profiles are available within a week from surgery. We use this platform to investigate responses of rare tumors and find the most effective regimen in a personalized manner.
We have pioneered bioprinting approaches to couple our screening platform with high-speed live cell interferometry, an imaging modality that allows to determined cellular mass distribution in a label-free, non invasive manner and at a single organoid resolution. We plan to use this approach to personalize therapy and quickly determine treatment resistance patterns. We are also pursuing novel iterations of our foundational platform to perform screenings of chemoradiation combination therapies and immuno-oncology drugs. We develop co-culture methods to study the interaction of cancer cells with tumor microenvironment components and vasculature.
We are deploying our approaches to the clinic to advance organoid-based functional precision medicine. Our first trial is PREMOST: an organoid-based functional PREcision Medicine trial in OSTeosarcoma (NCT06064682). We are testing feasibility of using organoids for predicting drug response and guiding therapy in osteosarcoma.
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We investigate protein conformational changes in cancer cells, particularly protein misfolding and aggregation, and leverage these for cancer therapy. We investigate how protein aggregation affects cancer development, progression and resistance to stress to identify novel therapeutic targets. We aim to augment our anti-cancer drug repertoire by designing peptides that target aberrant protein-protein interactions.
p53 is a crucial tumor suppressor protein that prevents damaged cells from becoming cancerous. In order to proliferate uncontrollably, cancer cells often inactivate p53 by mutating it, as in the majority of ovarian cancer cases. Some mutations may loosen the structure of p53. In this process, a sticky segment of p53 is exposed to the surface and quickly clumps with other p53 proteins causing self-aggregation. p53 mutations are present in pre-neoplastic cells in the fallopian tube and in early ovarian cancer lesions. We test if self-aggregation of the mutated p53 promotes ovarian cancer progression from benign to a malignant state.
p53 is often mutated in many hard-to-treat sarcoma subtypes. We explore whether p53 misfolds in sarcoma and can be targeted for therapy.
p53 sequestration in aggregates drastically increases the fitness of cancer cells. We hypothesize that a similar phenomenon – transient changes in the conformation of other proteins – may help cancer cells survive. After all, many stressors including hypoxia, protein overexpression or oxidative damage are central to carcinogenesis and conducive to protein aggregation. We investigate which proteins undergo conformational changes and aggregation in sarcoma.