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Author Le Compte, M.; Cardenas De La Hoz, E.; Peeters, S.; Smits, E.; Lardon, F.; Roeyen, G.; Vanlanduit, S.; Prenen, H.; Peeters, M.; Lin, A.; Deben, C.
Title Multiparametric tumor organoid drug screening using widefield live-cell imaging for bulk and single-organoid analysis Type A1 Journal article
Year 2022 Publication Jove-Journal Of Visualized Experiments Abbreviated Journal Jove-J Vis Exp
Volume Issue 190 Pages 1-18
Keywords A1 Journal article; Engineering sciences. Technology; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT); Antwerp Surgical Training, Anatomy and Research Centre (ASTARC); Center for Oncological Research (CORE)
Abstract Patient-derived tumor organoids (PDTOs) hold great promise for preclinical and translational research and predicting the patient therapy response from ex vivo drug screenings. However, current adenosine triphosphate (ATP)-based drug screening assays do not capture the complexity of a drug response (cytostatic or cytotoxic) and intratumor heterogeneity that has been shown to be retained in PDTOs due to a bulk readout. Live-cell imaging is a powerful tool to overcome this issue and visualize drug responses more in-depth. However, image analysis software is often not adapted to the three-dimensionality of PDTOs, requires fluorescent viability dyes, or is not compatible with a 384-well microplate format. This paper describes a semi-automated methodology to seed, treat, and image PDTOs in a high-throughput, 384-well format using conventional, widefield, live-cell imaging systems. In addition, we developed viability marker-free image analysis software to quantify growth rate-based drug response metrics that improve reproducibility and correct growth rate variations between different PDTO lines. Using the normalized drug response metric, which scores drug response based on the growth rate normalized to a positive and negative control condition, and a fluorescent cell death dye, cytotoxic and cytostatic drug responses can be easily distinguished, profoundly improving the classification of responders and non-responders. In addition, drug-response heterogeneity can by quantified from single-organoid drug response analysis to identify potential, resistant clones. Ultimately, this method aims to improve the prediction of clinical therapy response by capturing a multiparametric drug response signature, which includes kinetic growth arrest and cell death quantification. ,
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Wos 000928020400010 Publication Date 2022-12-24
Series Editor Series Title (up) Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1940-087x ISBN Additional Links UA library record; WoS full record; WoS citing articles
Impact Factor 1.2 Times cited Open Access OpenAccess
Notes Approved Most recent IF: 1.2
Call Number UA @ admin @ c:irua:193168 Serial 7271
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Author Le Compte, M.; Cardenas De La Hoz, E.; Peeters, S.; Rodrigues Fortes, F.; Hermans, C.; Domen, A.; Smits, E.; Lardon, F.; Vandamme, T.; Lin, A.; Vanlanduit, S.; Roeyen, G.; van Laere, S.; Prenen, H.; Peeters, M.; Deben, C.
Title Single-organoid analysis reveals clinically relevant treatment-resistant and invasive subclones in pancreatic cancer Type A1 Journal article
Year 2023 Publication npj Precision Oncology Abbreviated Journal
Volume 7 Issue 1 Pages 128-14
Keywords A1 Journal article; Center for Oncological Research (CORE); Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT); Antwerp Surgical Training, Anatomy and Research Centre (ASTARC)
Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal diseases, characterized by a treatment-resistant and invasive nature. In line with these inherent aggressive characteristics, only a subset of patients shows a clinical response to the standard of care therapies, thereby highlighting the need for a more personalized treatment approach. In this study, we comprehensively unraveled the intra-patient response heterogeneity and intrinsic aggressive nature of PDAC on bulk and single-organoid resolution. We leveraged a fully characterized PDAC organoid panel ( N  = 8) and matched our artificial intelligence-driven, live-cell organoid image analysis with retrospective clinical patient response. In line with the clinical outcomes, we identified patient-specific sensitivities to the standard of care therapies (gemcitabine-paclitaxel and FOLFIRINOX) using a growth rate-based and normalized drug response metric. Moreover, the single-organoid analysis was able to detect resistant as well as invasive PDAC organoid clones, which was orchestrates on a patient, therapy, drug, concentration and time-specific level. Furthermore, our in vitro organoid analysis indicated a correlation with the matched patient progression-free survival (PFS) compared to the current, conventional drug response readouts. This work not only provides valuable insights on the response complexity in PDAC, but it also highlights the potential applications (extendable to other tumor types) and clinical translatability of our approach in drug discovery and the emerging era of personalized medicine.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Wos 001118015800001 Publication Date 2023-12-08
Series Editor Series Title (up) Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2397-768x ISBN Additional Links UA library record; WoS full record; WoS citing articles
Impact Factor Times cited Open Access
Notes Approved Most recent IF: NA
Call Number UA @ admin @ c:irua:201455 Serial 9091
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Author Deben, C.; Freire Boullosa, L.; Rodrigues Fortes, F.; Cardenas De La Hoz, E.; Le Compte, M.; Seghers, S.; Peeters, M.; Vanlanduit, S.; Lin, A.; Dijkstra, K.K.; Van Schil, P.; Hendriks, J.M.H.; Prenen, H.; Roeyen, G.; Lardon, F.; Smits, E.
Title Auranofin repurposing for lung and pancreatic cancer : low CA12 expression as a marker of sensitivity in patient-derived organoids, with potentiated efficacy by AKT inhibition Type A1 Journal article
Year 2024 Publication Journal of Experimental and Clinical Cancer Research Abbreviated Journal
Volume 43 Issue 1 Pages 88-15
Keywords A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT); Antwerp Surgical Training, Anatomy and Research Centre (ASTARC); Center for Oncological Research (CORE)
Abstract Background This study explores the repurposing of Auranofin (AF), an anti-rheumatic drug, for treating non-small cell lung cancer (NSCLC) adenocarcinoma and pancreatic ductal adenocarcinoma (PDAC). Drug repurposing in oncology offers a cost-effective and time-efficient approach to developing new cancer therapies. Our research focuses on evaluating AF's selective cytotoxicity against cancer cells, identifying RNAseq-based biomarkers to predict AF response, and finding the most effective co-therapeutic agents for combination with AF. Methods Our investigation employed a comprehensive drug screening of AF in combination with eleven anticancer agents in cancerous PDAC and NSCLC patient-derived organoids (n = 7), and non-cancerous pulmonary organoids (n = 2). Additionally, we conducted RNA sequencing to identify potential biomarkers for AF sensitivity and experimented with various drug combinations to optimize AF's therapeutic efficacy. Results The results revealed that AF demonstrates a preferential cytotoxic effect on NSCLC and PDAC cancer cells at clinically relevant concentrations below 1 µM, sparing normal epithelial cells. We identified Carbonic Anhydrase 12 (CA12) as a significant RNAseq-based biomarker, closely associated with the NF-κB survival signaling pathway, which is crucial in cancer cell response to oxidative stress. Our findings suggest that cancer cells with low CA12 expression are more susceptible to AF treatment. Furthermore, the combination of AF with the AKT inhibitor MK2206 was found to be particularly effective, exhibiting potent and selective cytotoxic synergy, especially in tumor organoid models classified as intermediate responders to AF, without adverse effects on healthy organoids. Conclusion Our research offers valuable insights into the use of AF for treating NSCLC and PDAC. It highlights AF's cancer cell selectivity, establishes CA12 as a predictive biomarker for AF sensitivity, and underscores the enhanced efficacy of AF when combined with MK2206 and other therapeutics. These findings pave the way for further exploration of AF in cancer treatment, particularly in identifying patient populations most likely to benefit from its use and in optimizing combination therapies for improved patient outcomes.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Wos 001190581500001 Publication Date 2024-03-22
Series Editor Series Title (up) Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1756-9966 ISBN Additional Links UA library record; WoS full record
Impact Factor Times cited Open Access
Notes Approved no
Call Number UA @ admin @ c:irua:204924 Serial 9136
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