Organoid sensitivity correlates with therapeutic resonsein patients with pancreatic cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE187619 | GEO | 2021/11/10
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:In this study, we have generated patient-derived organoids (PDOs) from primary and metastatic lesions of gastrointestinal cancers, including pancreatic ductal adenocarcinoma, colorectal adenocarcinoma, and cholangiocarcinoma and evaluated their ability to predict donor tumor drug response. Specifically, we examined individual PDO responses to therapeutic agents with the observed clinical responses of donor patients to the same treatments and demonstrated an approximately 80% concordance rate. Importantly, we found a profound influence of culture media in PDOs phenotypes, we observed a significant difference in response to common PDAC chemotherapies, distinct morphologies, and transcriptomes between media in the same PDOs. These studies demonstrate the important role of culture media when using PDOs to inform patient care and predict response across a spectrum of GI cancers. We compared transcriptome data from pancreatic ductal adenocarcinoma patient-derived organoids in two media (WNT and PaTOM).
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Project description:The interaction of neoplastic cells with their tumor microenvironment (TME) is required for cancer progression. However, in vitro cancer models, including recent in vitro 3-dimensional (3D) organoid cultures of primary human tumors, are typically comprised exclusively of neoplastic epithelium, with stromal and/or immune interactions requiring artificial reconstitution. As relevant to cancer immunotherapy, the unified co-culture of primary tumor epithelia with their endogenous, syngeneic tumor-infiltrating lymphocytes (TILs) as a cohesive unit has remained particularly elusive. Here, we used a single 3D air-liquid interface (ALI) methodology to successfully propagate 3D Patient-Derived Tumor Organoids (PDOs) as primary tumor epithelia together with native immune and myofibroblast stromal compartments without reconstitution. Derived from >100 diverse human surgically resected tumor samples or from murine tumors in syngeneic immunocompetent mice, PDOs preserved cancer histologic subtypes and mutational spectrum with endogenous T, B, NK cells and macrophages integrally embedded amidst the tumor epithelium. PDO-based TILs accurately recapitulated the T cell receptor (TCR) spectrum of the original tumors, as determined by a robust droplet-based immune profiling solution that links gene expression and immune repertoire in single cells. Anti-PD-1 or anti-PD-L1 treatment of organoids from murine tumors from syngeneic immunocompetent hosts induced activation and cytolytic activity of tumor antigen-specific TILs, indicating successful PDO modeling of immune checkpoint blockade (ICB) and anti-tumor immunity. Crucially, the anti-PD-1 antibody nivolumab activated TILs in PDOs from human lung, renal and melanoma clinical tumor resections. The organoid-based propagation of primary tumor epithelium en bloc with its endogenous immune stroma should facilitate mechanistic investigation of TME-specific local tumor immunity, with applications for functional testing of individualized patient immunotherapy responses.
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Project description:Acquired drug resistance is a major challenge for cancer therapy and the leading cause of cancer mortality. However, the mechanisms of drug resistance are diverse and the strategy to specifically target drug resistant cancer cells remains an unmet clinical issue. We establisheda32 colorectal cancer (CRC) PDO biobank and induced acquired drug resistance by repeated low-level exposures of chemo-agents. Chemosensitivity profiling and transcriptomic analysis studies34 revealed that chemo-resistant PDOs exhibited elevated expression of LGR4 and activationof the35 Wnt signaling pathway. Further, we performed antibody screening against LGR4 and selecteda36 monoclonal antibody (LGR4-mAb) that potently inhibited the LGR4/Wnt signaling. In drug resistant PDOs and xenograft models, treatment with LGR4-mAb significantly sensitizeddrug- 38 induced ferroptosis. Mechanistically, LGR4 dependent Wnt signaling transcriptionally up-regulated SLC7A11, a key inhibitor of ferroptosis, to confer acquired drug resistance. Targeting40 Wnt signaling by LGR4-mAb and by other modulators augments ferroptosis when co-administrated with chemotherapeutic agents. Finally, LGR4-mAb therapy was effective against other cancers that express high levels of LGR4. Collectively, our results demonstrate a new strategy to selectively activate ferroptosis and provide a new opportunity to fight refractoryand44 recurrent cancers.
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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: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..
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Project description:Understanding the phenotypic alterations that play a role in differential response to drugs will be pivotal in identifying predictive biomarkers and developing efficacious therapies for advanced CRC. The bulk of research to date has focused on the value of organoids as a predictive tool; some have characterized the transcriptomic profile in relation to drug sensitivity in an effort to identify predictive biomarkers, but only a limited number of studies have used quantitative proteomic analysis to characterize PDOs. Extensive literature indicates that transcriptomic and proteomic expression profiles lack correlation due to significant post-transcriptional regulation, which could explain why RNA signatures are rarely useful as drug response predictors in the clinic. In this study we generated PDO models from advanced CRC patients including heavily pre-treated patients and a model of microsatellite instable- (MSI) high CRC, for which pre- and post chemotherapy liver disease PDOs were established and characterized to ensure biological fidelity with the original tumors. Our main objective was to integrate functional drug assays on PDOs with proteotranscriptomic study to explore the mechanisms underlying drug response. To this end, we used SWATH-MS (sequential window acquisition of all theoretical mass spectrometry), a highly accurate proteomic quantification technique and a bulk RNA-seq analysis. This strategy could represent a useful tool to discover new therapeutic targets in advanced CRC and to guide personalized therapies.
2025-02-03 | PXD038149 | Pride
Project description:Purpose: Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest cancers, with a poor prognosis. Viro-immunotherapy using oncolytic viruses (OVs) represents a promising treatment for PDAC. However, PDACs from different patients respond differently to OV therapies, highlighting the need for predictive biomarkers to optimize outcomes. This study aimed to identify gene expression profiles (GEPs) that could serve as predictors for OV sensitivity. Experimental design: Patient-derived organoids (PDOs) from ten PDAC patients were assessed for sensitivity to various OVs: Newcastle Disease Virus, a Reovirus strain entering cells independently of JAM-A expression, the Edmonston vaccine strain of Measles Virus, and a gorilla-derived adenovirus. To identify GEPs with predictive value, OV sensitivity was correlated with the transcriptome of uninfected PDOs. These GEPs were analyzed in the Gene Ontology database to reveal biological processes associated with them. Results: PDOs showed heterogenic responses to OVs, with nine of ten being sensitive to at least one. Analysis of the generated GEPs using the Gene Ontology database identified intracellular aberrations as the primary determinant of OV sensitivity. Sensitivity to all OVs was associated with GEPs related to embryonic development, while varied sensitivity of the ten PDOs to four OVs was linked to cell cycle regulation, metabolism, and proliferation. Conclusions: This study revealed that OV sensitivity was associated with GEPs comprising genes involved in multiple biological processes. Further investigation into screening tumors for the identified GEPs may yield biomarkers for selecting the most effective OV for PDAC. This approach is a stepping stone toward personalized OV treatments.
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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.
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