Patient-derived organoids for precision oncology: a platform to facilitate clinical decision making

Abstract

Background Despite recent advances in research, there are still critical lacunae in our basic understanding of the cause, pathogenesis, and natural history of many cancers, especially heterogeneity in patient response to drugs and mediators in the transition from malignant to invasive phenotypes. The explication of the pathogenesis of cancer has been constrained by limited access to patient samples, tumor heterogeneity and lack of reliable biological models. Amelioration in cancer treatment depends on further understanding of the etiologic, genetic, biological, and clinical heterogeneity of tumor microenvironment. Patient-derived organoids recapitulate the basic features of primary tumors, including histological complexity and genetic heterogeneity, which is instrumental in predicting patient response to drugs. Methods Human iPSCs from healthy donors, breast and ovarian cancer patients were successfully differentiated towards isogenic hepatic, cardiac, neural and endothelial lineages. Multicellular organoids were established using Primary cells isolated from tumor tissues, histologically normal tissues adjacent to the tumors (NATs) and adipose tissues (source of Mesenchymal Stem Cells) from ovarian and breast cancer patients. Further these organoids were propagated and used for drug resistance/sensitivity studies. Results Ovarian and breast cancer patients’ organoids showed heterogeneity in drug resistance and sensitivity. iPSCs-derived cardiomyocytes, hepatocytes and neurons showed donor–to-donor variability of chemotherapeutic drug sensitivity in ovarian cancer patients, breast cancer patients and healthy donors. Conclusion We report development of a novel integrated platform to facilitate clinical decision-making using the patient's primary cells, iPSCs and derivatives, to clinically relevant models for oncology research.

The future of cancer therapy: exploring the potential of patient-derived organoids in drug development

“…A single PDO model may not fully capture the complexity of an entire tumor because intra-tumor heterogeneity can lead to varying growth patterns and drug responses, making clinical applications more complicated ( Ramon et al, 2020 ; Bose et al, 2021 ). Another crucial aspect is long-term viability and functionality, which require a deep understanding of the tumor microenvironment, including stromal interactions and nutrient signaling ( Gjorevski et al, 2016 ; Chitrangi et al, 2023 ).…”

Organoids: An Emerging Precision Medicine Model for Prostate Cancer Research

“…Herein, we summarized recent clinical studies that utilized PCa organoids and model systems for evaluating the novel therapies for PCa diseases (Table 2). These studies included the clinical trials conducted at Centre Antoine Lacassagne in France (NCT03952793) [121], The Christie NHS Foundation Trust in the UK (NCT04723316) [122], the Netherlands Cancer Institute in the Netherlands (NCT02695459), Fudan University in China (NCT04927611) [123], SpeciCare, Georgia, USA (NCT03896958) [124], and the Rutgers Cancer Institute in New Jersey (NCT02458716) [36] (Table 2). Recently, a PDO-based model was employed in a Phase II trial (NCT01799278) for investigating the efficacy of the aurora kinase inhibitor Alisertib (MLN8237) for mCRPC and NEPC.…”

Navigating the Immune Maze: Pioneering Strategies for Unshackling Cancer Immunotherapy Resistance

“…For instance, PDX research has led to the discovery of alternative immune checkpoints and changes in antigen presentation, shaping the development of combination therapies and influencing clinical treatment modifications. Such studies have also identified biomarkers predictive of treatment response, allowing for the adaptation of clinical protocols [155].…”

“…Insights gained from PDX studies have informed the enrollment of patients in trials for new targeted agents, leading to improved outcomes. These translational models are thus integral to the evolution of personalized medicine, enhancing the specificity and adaptability of cancer therapies [155].…”