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Multi-layer stratified oncology platform utilizing transcriptomics, prostate cancer organoids, and modeling of drug response

ABSTRACT: The high intra-patient heterogeneity in multifocal primary prostate cancer (PCa) has curtailed the efficacy of current treatment options. By employing twin biopsies from multiple lesions with matched Patient-derived organoids (PDO) models, the PCa molecular heterogeneity was investigated. We utilized genomics, transcriptomics and machine learning (ML) approaches to elucidate and predict the underlying mechanisms of pharmacological heterogeneity. Our data indicate a vulnerability of primary PCa organoids for small molecule inhibitors targeting receptor tyrosine kinases (MET, ALK, SRC). By exploring gene expression data from matched parental tissue in an unsupervised manner, we identified two distinct clusters of samples. Interestingly, the PDO drug responses were significantly different between the two clusters for 4/11 compounds tested. We developed a transcriptomics-based, cluster prediction model, which can accurately stratify samples into the two clusters. Notably, our prediction model is based on tissue profiles; therefore, it can be utilized to rapidly evaluate new cases and suggest promising drug candidates, even when PDO derivation is not feasible. Taken together, we propose a novel flexible stratified oncology approach that can swiftly and accurately highlight promising drug vulnerabilities of PCa patients.

ORGANISM(S): Homo sapiens

PROVIDER: GSE294532 | GEO | 2025/10/16

REPOSITORIES: GEO

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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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Multi-layer stratified oncology platform utilizing transcriptomics, prostate cancer organoids, and modeling of drug response

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