Project description:We introduce OncoLoop, a highly-generalizable, precision medicine framework to triangulate between available mouse models, human tumors, and large-scale drug perturbational assays with in vivo validation to predict personalized treatment
Project description:Purpose: Advanced high-grade gastroenteropancreatic neuroendocrine neoplasm (GEP-NEN) are highly aggressive and heterogeneous epithelial malignancies with poor clinical outcomes. No therapeutic predictive biomarkers exist and representative preclinical models to study their biology are missing. Patient-derived (PD) tumoroids may enable fast ex vivo pharmacotyping and provide subsidiary biological information for more personalized therapy strategies in individual patients. Experimental Design: PD tumoroids were established from rare biobanked surgical resections of advanced high-grade GEP-NEN patients. Using targeted in vitro pharmacotyping and next-generation sequencing of patient samples and matching PD tumoroids, we profiled individual patients and compared treatment-induced molecular stress response and in vitro drug sensitivity to the clinical therapy response. Results: We demonstrate high success rates in culturing PD tumoroids of high-grade GEP-NENs within clinically meaningful timespans. PD tumoroids recapitulate biological key features of high-grade GEP-NEN and mimic clinical response to cisplatin and temozolomide in vitro. Moreover, investigating treatment-induced molecular stress responses in PD tumoroids in silico, we discovered and functionally validated Lysine demethylase 5A (KDM5A) and interferon-beta (IFNB1) as two vulnerabilities that act synergistically in combination with cisplatin and may present novel therapeutic options in high-grade GEP-NENs. Conclusion: Patient-derived tumoroids from high-grade GEP-NENs represent a relevant model to screen drug sensitivities of individual patients within clinically relevant timespans and provide novel functional insights into drug-induced stress responses. Clinical patient response to standard-of-care chemotherapeutics matches with drug sensitivities of PD tumoroids. Together, our findings provide a functional precision oncology approach for gathering patient-centered subsidiary treatment information that will potentially increase therapeutic opportunities in the framework of personalized medicine.
Project description:Personalized treatment for patients with advanced solid tumors critically depends on the deep characterization of tumor cells. These patients frequently develop malignant serous effusions (MSE). The value of MSE-based tumor cell characterization for guiding precision oncology is, however, currently unclear. Here, we present a comprehensive characterization of a pan-cancer cohort of 150 MSE samples at the cellular, molecular, and functional level. Our integrative analysis reveals dynamic cellular heterogeneity in MSE, and uncovers links between tumor driver mutations and ex vivo growth patterns. Strong concordance between genomic and transcriptional profiles of MSE and their corresponding solid tumors validates their use as a model system for solid tumor biology. We link baseline gene expression patterns to global ex vivo drug sensitivity, and demonstrate that drug-induced transcriptional changes in MSE are highly indicative of compound mode of action. Two case studies exemplify the utility of our approach in investigating acquired resistance to targeted therapy and identifying treatment options for relapsed solid tumors. In summary, our study provides a functional multi-omics view on a pan-cancer MSE cohort and underlines the utility of MSE-based precision oncology.
Project description:Personalized treatment for patients with advanced solid tumors critically depends on the deep characterization of tumor cells. These patients frequently develop malignant serous effusions (MSE). The value of MSE-based tumor cell characterization for guiding precision oncology is, however, currently unclear. Here, we present a comprehensive characterization of a pan-cancer cohort of 150 MSE samples at the cellular, molecular, and functional level. Our integrative analysis reveals dynamic cellular heterogeneity in MSE, and uncovers links between tumor driver mutations and ex vivo growth patterns. Strong concordance between genomic and transcriptional profiles of MSE and their corresponding solid tumors validates their use as a model system for solid tumor biology. We link baseline gene expression patterns to global ex vivo drug sensitivity, and demonstrate that drug-induced transcriptional changes in MSE are highly indicative of compound mode of action. Two case studies exemplify the utility of our approach in investigating acquired resistance to targeted therapy and identifying treatment options for relapsed solid tumors. In summary, our study provides a functional multi-omics view on a pan-cancer MSE cohort and underlines the utility of MSE-based precision oncology.
Project description:Personalized therapy of rheumatoid arthritis (RA) based on traditional Chinese medicine cold and hot syndromes is selection of the best treatment for an individual patient. Wutou Decoction (WTD) is one of the classic Chinese herbal formulae which achieve favorable therapeutic response in treating RA-cold syndrome. Microarray analysis based on the adjuvant induced arthritis model combined with characteristics of RA and cold/hot syndromes was performed to screen RA-cold and RA-hot-syndrome-related genes, as well as WTD effect genes.
Project description:The potential of eccrine sweat as a bio-fluid of interest for diagnosis and personalized therapy has not yet been fully evaluated, due to the lack of in-depth sweat characterization studies. Thanks to recent developments in the field of omics together with the availability of accredited eccrine sweat collection methods, the analysis of human sweat may now be envisioned as a standardized, non-invasive test for individualized monitoring and personalized medicine. Here, we characterized individual sweat samples, collected from 28 healthy adult volunteers under the most standardized sampling methodology, by applying an optimized Shotgun proteomic analysis. This deep characterization of the sweat proteome allowed the identification of about 1000 unique proteins from which 347 were identified across all samples. Annotation-wise, the study of the sweat proteome unveiled the over-representation of newly addressed Actin dynamics, oxidative stress and proteasome-related functions, in addition to well-described proteolysis and anti-microbial immunity. The sweat proteome composition appeared to be correlated to the inter-individual variability of sweat secretion parameters (water and solute losses). Besides, both gender-exclusive proteins and gender-specific protein abundances were highlighted in spite of the high similarity between human female and male sweat proteomes. In conclusion, standardized sample collection coupled to optimized shotgun proteomics significantly improved the depth of sweat proteome coverage, far beyond previous similar studies. The identified proteins were involved in many diverse biological processes and molecular functions indicating the potential of this bio-fluid as a valuable biological matrix for further studies. Addressing sweat variability, our results prove the proteomic profiling of sweat to be a promising bio-fluid for individualized, non-invasive monitoring and personalized medicine.
Project description:Acute myeloid leukemia (AML) is characterized by malignant myeloid precursors that span a cellular hierarchy from dedifferentiated leukemic stem cells to mature blasts. While the diagnostic and prognostic importance of AML blast maturation is increasingly recognized, personalized therapies are currently not tailored to a patient’s individual makeup of this cellular hierarchy. In this study, we use multiplexed image-based ex vivo drug screening (pharmacoscopy) to systematically quantify the drug sensitivity across the cellular hierarchy of AML patients. We analyzed 174 prospective and longitudinal patient samples from 44 newly diagnosed AML patients, which indicated that differences in the AML hierarchy significantly identified poor responses to first-line therapy, outperforming European LeukemiaNet (ELN) criteria. Critically, drug response profiling across the AML hierarchy of each patient improved the accuracy of predicting patient response to first-line therapy (AUC 0.91), and revealed alternative individualized treatment options targeting the complete AML hierarchy of non-responding patients. We confirmed these findings in an independent cohort of 26 relapsed/refractory AML patients, for whom pan-hierarchy response profiling improved response predictions post hoc. Overall, our results quantify the clinical importance of therapeutically targeting the complete cellular hierarchy of newly diagnosed AML, and identify multiplexed image-based ex vivo drug screening to enable quantification and targeting of the AML maturation hierarchy for improved personalized treatment.