Patient-derived organoids: a promising model for personalized cancer treatment

Yang, Huayu; Sun, Lejia; Liu, Meixi; Mao, Yilei

doi:10.1093/gastro/goy040

Cited by 62 publications

(60 citation statements)

References 23 publications

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“…Besides the phenotypic and genotyping profiling, the gene mutation spectrum of patient's tumours was also retained in patient-derived organoids [191,193,[198][199][200][201]. These organoids can be expanded long-term in culture without any loss of original characteristics of the derivative primary tissues and can be used for high-throughput drug screening [202]. In addition, few recent studies have shown that molecular profiling of patient-derived organoids is able to predict the accuracy on whether a patient would respond to specific drugs [191,203].…”

Section: Patient-derived Tumour Organoid Modellingmentioning

confidence: 99%

Ovarian Cancer, Cancer Stem Cells and Current Treatment Strategies: A Potential Role of Magmas in the Current Treatment Methods

Ahmed

Kadife²,

Raza

et al. 2020

Cells

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Epithelial ovarian cancer (EOC) constitutes 90% of ovarian cancers (OC) and is the eighth most common cause of cancer-related death in women. The cancer histologically and genetically is very complex having a high degree of tumour heterogeneity. The pathogenic variability in OC causes significant impediments in effectively treating patients, resulting in a dismal prognosis. Disease progression is predominantly influenced by the peritoneal tumour microenvironment rather than properties of the tumor and is the major contributor to prognosis. Standard treatment of OC patients consists of debulking surgery, followed by chemotherapy, which in most cases end in recurrent chemoresistant disease. This review discusses the different origins of high-grade serous ovarian cancer (HGSOC), the major sub-type of EOC. Tumour heterogeneity, genetic/epigenetic changes, and cancer stem cells (CSC) in facilitating HGSOC progression and their contribution in the circumvention of therapy treatments are included. Several new treatment strategies are discussed including our preliminary proof of concept study describing the role of mitochondria-associated granulocyte macrophage colony-stimulating factor signaling protein (Magmas) in HGSOC and its unique potential role in chemotherapy-resistant disease. of 35have been observed in OC patients but not in patients with benign and borderline tumours, and this hypomethylation correlates with advanced-stage disease and poor prognosis [48,49]. A genome-wide methylation profiling of blood cells from healthy controls and age-matched untreated OC patients identified CpG methylation of 2714 cancer-related genes, of which 56% were hypomethylated [50]. Ovarian Cancer Stem CellsCellular heterogeneity associated with genetic and epigenetic changes in tumours are linked with the initiation and expansion of CSCs, a population of cells within the tumour, which initiate tumour growth through self-renewal and differentiation processes [51,52]. These cells are more adaptive to the changing tumour microenvironment and tend to be more resistant to treatment. CSCs are highly plastic and a few numbers of isolated CSCs have been shown to be responsible for tumorgenesis and are more chemotherapy and radiation resistant due to their dormant state and a high expression of drug efflux pumps [53,54]. As a result, CSCs are able to adapt to different tumour microenvironments and survive due to their efficient DNA repair mechanisms and their capacity to evade host immune surveillance [55][56][57]. These inherent properties of CSCs suggest an active role in tumour relapse and emphasize the need to develop effective targeted therapies to improve clinical outcomes in patients [51][52][53][54][55][56][57].Stem cells have been identified in ovaries and fallopian tubes [58,59]. These cells express proteins including aldehyde dehydrogenase family 1 A2 (ALDH1A2), homeobox protein NANOG, LIM homeobox protein 9 (LHX9) and frizzled-related protein 1 (SRFP1) and have been observed in OSE, CIC and fimbria [2,[58][59][60][61][62]. In a...

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Section: Patient-derived Tumour Organoid Modellingmentioning

confidence: 99%

Ovarian Cancer, Cancer Stem Cells and Current Treatment Strategies: A Potential Role of Magmas in the Current Treatment Methods

Ahmed

Kadife²,

Raza

et al. 2020

Cells

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“…More recently, this technique was further developed to generate organoids from patient-derived cancer tissues. These include gastrointestinal, pancreatic, colorectal, hepatocellular carcinoma, cholangiocarcinoma, Barrett's esophagus, prostate, bladder, breast glioblastoma [42], and ovarian cancer [43], among others. In general, tumor histology was shown to be maintained in all tumor types and subtypes when compared with the parental tumor, including the expression of nuclear hormone receptors in breast and prostate cancer [44,45], although a slight decrease in ER was reported [44].…”

Section: Organoidsmentioning

confidence: 99%

Zebrafish Avatars towards Personalized Medicine—A Comparative Review between Avatar Models

Costa

Estrada

Mendes

et al. 2020

Cells

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Cancer frequency and prevalence have been increasing in the past decades, with devastating impacts on patients and their families. Despite the great advances in targeted approaches, there is still a lack of methods to predict individual patient responses, and therefore treatments are tailored according to average response rates. "Omics" approaches are used for patient stratification and choice of therapeutic options towards a more precise medicine. These methods, however, do not consider all genetic and non-genetic dynamic interactions that occur upon drug treatment. Therefore, the need to directly challenge patient cells in a personalized manner remains. The present review addresses the state of the art of patient-derived in vitro and in vivo models, from organoids to mouse and zebrafish Avatars. The predictive power of each model based on the retrospective correlation with the patient clinical outcome will be considered. Finally, the review is focused on the emerging zebrafish Avatars and their unique characteristics allowing a fast analysis of local and systemic effects of drug treatments at the single-cell level. We also address the technical challenges that the field has yet to overcome.The arrival of precision medicine and immunotherapy are giving hope to finally manage cancer treatment. Many advances were made possible due to the discovery of molecular pathways in tumor cells and on their interaction with the surrounding tumor microenvironment (TME) [1], leading to the development of many new therapies. The latest successes in HER2-targeted therapy and the discovery of immune checkpoint inhibitors are great examples of this [2]. However, not all patients respond and many are not eligible for these "new therapies". Thus, nowadays, the majority of patients are still treated with traditional chemo/radiotherapy and surgery according to clinical guidelines, which are developed and approved based on average efficacy rates.As a result of this "one-size-fits-all" approach, treatments may prove to be efficient for some patients but not for others. For example, in the international therapeutic guidelines (NCCN and ESMO) for advanced colorectal cancer (CRC) there are two main chemotherapeutic arms (FOLFOX and FOLFIRI), which show very similar response rates of~50% [3,4]. In other words,~50% of patients respond to treatment while~50% do not. Clinicians do not know in which group patients will fall, as there is no predictive screening test to provide this information. Thus, patients that start with FOLFOX and do not respond change to FOLFIRI, and vice-versa. This applies for CRC and many other cancers, being especially relevant in the metastatic scenario when oncology therapy guidelines reach branch

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“…43,44 PDXs involve propagating tumor tissue in mice, whereas PDOs are patient-derived tumor tissues embedded into a 3-dimensional matrix culture and then grown into tumor organoids that retain the structural and functional characteristics of the source tumor. 45 Recent studies found that PDXs and PDOs for various solid tumors had a high concordance with their native tumors, and thy identified effective drugs and novel combinations that were subsequently validated in cell lines and xenograft models of the corresponding tumor type. 46,47 These encouraging results highlight the potential of individualized dynamic models for guiding cancer treatment and next-generation clinical trial development.…”

Section: Cancer November 15 2020mentioning

confidence: 99%

Clinical trial design: Past, present, and future in the context of big data and precision medicine

Bergan

2020

Cancer

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Clinical trials are fundamental for advances in cancer treatment. The traditional framework of phase 1 to 3 trials is designed for incremental advances between regimens. However, our ability to understand and treat cancer has evolved with the increase in drugs targeting an expanding array of therapeutic targets, the development of progressively comprehensive data sets, and emerging computational analytics, all of which are reshaping our treatment strategies. A more robust linkage between drugs and underlying cancer biology is blurring historical lines that define trials on the basis of cancer type. The complexity of the molecular basis of cancer, coupled with manifold variations in clinical status, is driving the individually tailored use of combinations of precision targeted drugs. This approach is spawning a new era of clinical trial types. Although most care is delivered in a community setting, large centers support real-time multiomic analytics and their integrated interpretation by using machine learning in the context of real-world data sets. Coupling the analytic capabilities of large centers to the tailored delivery of therapy in the community is forging a paradigm that is optimizing service for patients. Understanding the importance of these evolving trends across the health care spectrum will affect our treatment of cancer in the future and is the focus of this review. Cancer 2020;126:4838-4846.

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Patient-derived organoids: a promising model for personalized cancer treatment

Cited by 62 publications

References 23 publications

Ovarian Cancer, Cancer Stem Cells and Current Treatment Strategies: A Potential Role of Magmas in the Current Treatment Methods

Ovarian Cancer, Cancer Stem Cells and Current Treatment Strategies: A Potential Role of Magmas in the Current Treatment Methods

Zebrafish Avatars towards Personalized Medicine—A Comparative Review between Avatar Models

Clinical trial design: Past, present, and future in the context of big data and precision medicine

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