Culture media composition influences patient-derived organoids ability to predict therapeutic response in gastrointestinal cancers
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE212014 | GEO | 2022/10/12
REPOSITORIES: GEO
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Project description:Two molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) have been proposed: the “Classical” and “Basal-like” subtypes. However, the “molecular” classification has not been applied in real-world clinical practice. This study aimed to establish patient-derived organoids (PDOs) for PDAC and evaluate their application in subtype classification and clinical outcome prediction. We constructed a PDO library for morphologic and RNA-seq analyses and drug response assays in vitro. PDOs of PDAC were established at a high efficiency (> 70%) with at least 100,000 live cells. Morphologically, PDOs were classified as gland-like structures (GL type) or densely proliferating inside (DP type). RNA-seq analysis revealed that the “morphological” subtype (GL vs. DP) roughly corresponded to the “molecular” subtype (“Classical” vs. “Basal-like”). The proposed “morphological” classification predicted clinical treatment response and prognosis; the median overall survival of patients with GL type were significantly longer than that of those with DP type (P < 0.005). The GL type showed a better response to gemcitabine than the DP type in vitro, whereas the drug response of the DP type was improved by the combination of ERK and autophagy inhibition. PDAC PDOs facilitated subtype determination and clinical outcome prediction, thereby advancing precision medicine for PDAC.
2024-04-11 | GSE228801 | GEO
Project description:Patient-derived organoids after neoadjuvant FOLFIRINOX predict therapy resistance in pancreatic ductal adenocarcinoma
| PRJNA716264 | ENA
Project description:Precision oncology aims to improve clinical outcome of patients by offering personalized treatment through identifying druggable genomic aberrations within their tumors. This is particularly valid when it comes to offering alternative treatment options for patients with advanced tumors that are chemo-refractory. Patient-derived organoids (PDOs) are 3 dimensional tumoroids that can be expanded ex vivo and are both pheno- and genotypically identical to patients’ tumors. Observational studies have shown that PDO-based drug screens can predict treatment response with high sensitivity and specificity. Vlachogiannis G. reported a living biobank of patient-derived organoids (PDOs) from patients with advanced GI cancers enrolled in clinical trials. PDOs can recapitulate patients’ clinical response to chemotherapeutic agents. In 19 tumor organoids, the group performed molecular profiling and drug screens and then compared ex vivo organoid responses to anticancer drugs. Drug response to PDO based orthotopic mouse tumor xenografts correlated to the drug response of the patient in clinical trials. Further to the study, there were other retrospective validation studies utilizing PDOs from patients enrolled in clinical trials such as the TUMOROID, CinClare to predict clinical response. Ooft studied PDOs from patients with metastatic colorectal cancers enrolled in the TUMOROID study to predict response to irinotecan-based therapies. Yao generated a organoid biobank of 80 locally advanced rectal cancers. These patients were derived from a phase III study (CinClare) that compared neoadjuvant chemo-radiation using either capecitabine or CAPIRI. Response to chemoradiation in patients matched to that of rectal cancer organoids (sensitivity 78% and specificity 91.9%). In a systematic analysis of 17 studies (9 on advanced GI and pancreatic cancers, one on renal cell cancer and others on miscellaneous cancers), the pooled sensitivity and specificity for discriminating patients with a clinical response through PDO-based drug screen was 0.81 (95%CI 0.69-0.89) and 0.74 (95%CI 0.64-0.82) respectively. Within 4-6 weeks, PDO-based drug screen creates a true personalised platform by predicting patient-specific drug response with high accuracy. Recent technical advancements in growing these PDO ‘avatars’ from biopsies have made it possible to test suitable anticancer drugs in patients with advanced inoperable tumors, and explore the new possibilities for treatment options that otherwise would be missed by standard conventional therapies. In 2019, our group embarked on PDO research; investigators obtained tissues from patients with advanced/ inoperable solid tumors, and performing drug screens on these PDOs ex vivo. In several patients, investigators were able to identified drugs not otherwise used through sequencing data, and observed remarkable clinical response in patients with PDO responsive tumors. Investigators illustrate with cases that underwent PDO culture and drug screens. [ See appendix ] In the literature, the clinical utility of treatment based on PDO informed drug options has however not been fully established. Investigators therefore propose a phase 2 proof-of-concept clinical trial to evaluate efficacy of NGS/ PDO guided treatment in patients with inoperable or metastatic solid tumors..
| 109308 | ecrin-mdr-crc
Project description:Patient derived organoids (PDOs) closely resemble individual tumor biology. They are thus promising models for drug discovery and precision medicine. Here, we describe high-throughput imaging and automated image analysis of PDOs. We generated PDOs from colorectal cancer patients. Subsequently, we treated them with >500 substances to capture almost 6 million images by confocal microscopy. We developed a software framework to analyze how perturbations alter the organization of multicellular PDOs. Therewith, we observed a rich spectrum of reoccurring phenotypes. Targeting cellular processes, including signaling by MEK, GSK3 or CDKs, led to distinct architectural changes. Also, we detected compound-induced phenotypes only present in subsets of PDOs with specific molecular alterations. Finally, PDO response to anticancer drugs matched the clinical course of corresponding patients. The presented high-throughput imaging workflow and data allow compound profiling with complex multicellular organoid models for drug discovery and personalized medicine. We used microarrays to detail the global programme of gene expression underlying different lines of patient-derived colorectal cancer organoids.
2019-03-03 | GSE117548 | GEO
Project description:The transcriptional dynamics occurring at the self-organizing glandular epithelial during branching morphogenesis are pivotal for deciphering various processes ranging from normal tissue growth to cancer formation. For the past decade matrigel© has been widely used as extracellular matrix for the propagation of organoids, here we report that only in the presence of a higher than 70% collagen matrix symmetry breaking can be observed. Comparing the transcriptomic profile of collagen and matrigel grown-organoids we identified that matrigel organoids are more basal-like, have a higher EMT signature (GSEA) compared to the more classical collagen grown organoids. In this study we used single primary murine pancreatic ductal adenocarcinoma cells (PDAC) cells embedded in floating collagen gels and adapted the media supplementation, thus allowing organoids to self-organize into highly complex branched structures, replicating the in vivo tumour architecture. During organoid development we identified four distinct morphogenetic phases, each characterized by a unique pattern of cell proliferation, invasion, matrix deformation and protein expression. In our search for novel molecular drivers of branching morphogenesis we compared the transcriptome of two distinct phases, an early development (day 7) vs a late mature time point (day 13). We compared these two distinct developmental time points in using PCA, GSEA and respective heat maps of major processes illustrating the overexpression of genes associated with: proliferation, ECM interaction, signalling by Rho GTPases and EMT in day-7 organoids and genes associated with ion channel transport at day-13 organoids. An important aspect raised during our investigation was the effect of different genotypes (Ptf1aCre/+; KrasG12D/+, Pdx1Cre/+; KrasG12D/+; TP53fl/fl) on the branch formation of organoids. To this end we generated organoids derived from KC and KPC tumours, which interestingly gave rise to strikingly similar branching organoids. Although the morphology was not significantly altered the transcriptional profiling showed higher proliferation (Myc targets, E2F targets), EMT score for the KPC organoids. We propose that the spatiotemporal synchronized processes of cell proliferation, matrix remodeling, contraction and ion channel flux are key-events of the different morphogenic phases and lead to the formation of these complex structures. Importantly, these dynamic processes are accompanied by strong transcriptional profile changes, with the organoids undergoing de-differentiation during branch elongation and later on activating an epithelial gene expression program upon maturation. Taken together, these results illustrate the ability of tumour cells to self-organize in multicellular complex structures and provide with a novel system to study branching morphogenesis and tumour biology in vitro. In the updated submission we include new data sets from our recent publication. More specifically we focus on how we can capture inter- and intratumoral heterogeneity using our previously published organoid system (Randriamanantsoa, Papargyriou et al. 2022) of pancreatic cancer and how these morphologically diverse organoids respond to targeted therapy. We aim to understand the following four biological questions: First, we aim to address intertumoral heterogeneity by culturing classical and basal-like PDAC cells in 2D culture conditions and 3D floating collagen gels. Indeed, in both cases we observe a clear separation between mesenchymal and epithelial organoids and describe pivotal pathways (f.e. TGF pathway) that are differentially regulated between the two culture conditions (2D vs 3D). In detail, we culture 3 epithelial (ID: 8442, 9591, 53631) and 3 mesenchymal (ID: 8028, 9091, 16992) murine pancreatic cancer lines in established 2D conditions and in 3D floating collagen gels. Next, we focus on understanding the transcriptional background of distinct organoid morphologies derived from the same parental cell lines of either epithelial or mesenchymal origin. In more detail we transcriptionally analyze specific epithelial (line ID 9591) as a bulk population and their subclones: TEBBO, cystic branched, thick-branched and tree-like and mesenchymal pancreatic cancer line (line ID 16992) as a bulk population and their subclones: branched mesenchymal, firework and star-like. After performing a 102-drug screening on these clones we identified potent target therapy drugs acting in specific phenotypes. To validate the effects on the transcriptional level we treated all the epithelial organoid phenotypes with the combination of AZD5153 (BET/BRD4 inhibitor)+Poziotinib (pan-HER inhibitor) and the mesenchymal phenotypes with monotreatments of the following drugs: Birinapant (SMAC antagonist) Poziotinib (pan-HER inhibitor), Saracatinib (Src inhibitor) and RO5126766 (RAF/MEK inhibitor). Furthermore, to translate our findings in a human setting we developed a new media composition which enables the formation of branching organoids in pancreatic cancer patient-derived organoids (PDOs). We examined the effect of our newly developed media, the Basal Branching PDO Media on the transcriptome of 3 PDOs (PDO line ID: B211, B250, B320) compared to previously established media conditions such as the Full PDO Media.
2024-03-08 | GSE261159 | GEO
Project description:Bladder Cancer (BLCa) inter-patient heterogeneity is the primary cause of treatment failure, suggesting that patients could benefit from a more personalized treatment approach. Patient-derived organoids (PDOs) have been successfully used as a functional model for predicting drug response in different cancers. In our study, we established PDO cultures from different BLCa stages and grades. PDOs preserve the histological and molecular heterogeneity of the parental tumors (PTs), including their multiclonal genetic landscapes, and consistently share key genetic alterations, mirroring tumor evolution in longitudinal sampling. Our drug screening pipeline was implemented using PDOs, testing both standard-of-care and FDA-approved compounds for other tumors. Integrative analysis of drug response profiles with matched PDO genomic analysis was used to determine enrichment thresholds for candidate markers of therapy response and resistance. Finally, by assessing the clinical history of longitudinally sampled cases we were able to assess the disease clonal evolution matched with drug response.
2023-02-01 | GSE217956 | GEO
Project description:One of the emerging cancer vulnerabilities is altered metabolism, and several metabolic pathways have been shown to promote pancreatic ductal adenocarcinoma (PDAC). Here we use genetic targeting to delete SOAT1 from murine PDAC metastasis organoids, and use RNA-seq to identify genes differentially regulated in normal and cholesterol-supplemented media conditions in the presence or absence of SOAT1.
2020-06-16 | GSE141737 | GEO
Project description:To gain insight into the gene expression profile of breast patient derived organoids (PDOs) under endocrine therapy, and how cancer associated fibroblasts (CAFs) might influence gene expression and stimulate resistance, we performed RNA sequencing on three of the metastatic PDOs treated with control media and CAF-conditioned media, in the presence and absence of Fulvestrant (4-day treatment). These data revealed that Fulvestrant significantly suppressed the ER signature in the PDOs, suggesting that the ER-pathway is still active in these tumors although the patients had relapsed on ER-targeting agents (Tamoxifen, Letrozole).
2023-06-27 | GSE216540 | GEO
Project description:In this study, we applied Drop-seq, a high throughput single cell RNA-seq platform, to characterize the different cell types present in pancreatic cancer organoids. We sequenced the transcriptomes of 7675 single cells from organoids derived from a patient undergoing a Whipple procedure for pancreatic ductal adenocarcinoma (PDAC). We then developed a novel clustering approach based on a class of probabilistic generative models called topic models, leading to the identification of subpopulations of cells.
2020-06-01 | GSE114454 | GEO
Project description:We report a high degree of correlation between PDAC patient derived orgnanoid (PDO) drug sensitivity and clinical responses. This finding supports the utility of PDOs to tailor therapy for individual patients to improve clinical outcomes.
2021-11-10 | GSE187619 | GEO